The document discusses using genetic algorithms for financial forecasting. It begins with an abstract that notes genetic algorithms have been used extensively in various domains including finance to generate profitable trading rules. The document then provides background on genetic algorithms and their basic functions like selection, crossover and mutation. It explains how genetic algorithms can be used to develop a model for financial forecasting by evaluating trading rules based on historical data to determine which rules would have yielded the highest returns.
Improvement of genetic algorithm using artificial bee colonyjournalBEEI
This document proposes using an artificial bee colony algorithm to improve a genetic algorithm. It does this by generating the initial population for the genetic algorithm rather than using random generation. The proposed method is tested on random number generation and the travelling salesman problem. For random number generation, five statistical tests are used to evaluate fitness, with the goal of generating random numbers that pass all tests. For the travelling salesman problem, fitness is based on minimizing the total distance travelled. The results show the proposed method performs better than the traditional genetic algorithm in terms of mean iterations, execution time, error rate, and finding the shortest route.
Feature selection using modified particle swarm optimisation for face recogni...eSAT Journals
Abstract
One of the major influential factors which affects the accuracy of classification rate is the selection of right features. Not all features have vital role in classification. Many of the features in the dataset may be redundant and irrelevant, which increase the computational cost and may reduce classification rate. In this paper, we used DCT(Discrete cosine transform) coefficients as features for face recognition application. The coefficients are optimally selected based on a modified PSO algorithm. In this, the choice of coefficients is done by incorporating the average of the mean normalized standard deviations of various classes and giving more weightage to the lower indexed DCT coefficients. The algorithm is tested on ORL database. A recognition rate of 97% is obtained. Average number of features selected is about 40 percent for a 10 × 10 input. The modified PSO took about 50 iterations for convergence. These performance figures are found to be better than some of the work reported in literature.
Keywords: Particle swarm optimization, Discrete cosine transform, feature extraction, feature selection, face recognition, classification rate.
ENTROPY-COST RATIO MAXIMIZATION MODEL FOR EFFICIENT STOCK PORTFOLIO SELECTION...cscpconf
This paper introduces a new stock portfolio selection model in non-stochastic environment.Following the principle of maximum entropy, a new entropy-cost ratio function is introduced as
the objective function. The uncertain returns, risks and ividends of the securities are considered as interval numbers. Along with the objective function, eight different types of constraints are used in the model to convert it into a pragmatic one. Three different models have been proposed by defining the future inancial market optimistically, pessimistically and in hecombined form to model the portfolio selection problem. To illustrate the effectiveness and tractability of the proposed models, these are tested on a set of data from Bombay Stock Exchange (BSE). The solution has been done by genetic algorithm.
Resolving Multi Objective Stock Portfolio Optimization Problem Using Genetic ...Hok Lie
This document summarizes a research paper that proposes using a genetic algorithm to solve a multi-objective stock portfolio optimization problem. It aims to generate a portfolio with the highest expected return and lowest risk. The document first discusses modern portfolio theory and defines the optimization problem. It then describes using a genetic algorithm with real number encoding to evolve portfolio weight solutions. The algorithm is verified using historical stock data, where expected returns and risk are estimated and a fitness function is developed to maximize return and minimize risk. The results show the genetic algorithm converges to better solutions than random search.
The document describes an Operations Research course. It includes 8 units covering topics like linear programming, transportation problems, queuing theory, PERT-CPM techniques, game theory, and integer programming. It provides details of each unit including the number of lecture hours and the topics to be covered. It also lists the textbooks and reference books for the course. The course aims to introduce students to various operations research techniques and their applications in decision making.
Fuzzy Logic Based Parameter Adaptation of Interior Search Algorithmijtsrd
This paper proposes a detailed switching model for the medium voltage cascaded H bridge multi level inverter drive and induction motor system using fuzzy logic controller which is suitable for power system dynamic studies. The model includes the We describe in this book recent advances in the fuzzy logic based augmentation of neural networks and in optimization algorithms and their application in areas fuzzy logic can help design robust individual behaviours units. Fuzzy logic controllers incorporate heuristic control knowledge. It is convenient choice when a precise linear model of the system to be controlled cannot be easily found. Another advantage of fuzzy logic control is to use fuzzy logic for representing uncertainties, such as vagueness or imprecision which cannot be solved by probability theory. Also fuzzy logic offers greater flexibility to user, among which we can choose the one that best, fits the type of combination to be performed. M. Bhuvaneswari | P. Daniel Samson | V. Anish ""Fuzzy Logic"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30186.pdf
Paper Url : https://www.ijtsrd.com/other-scientific-research-area/other/30186/fuzzy-logic/m-bhuvaneswari
Comparison of Cell formation techniques in Cellular manufacturing using three...IJERA Editor
This document compares three cell formation techniques for cellular manufacturing: Rank Order Clustering 2 (ROC-2), Direct Clustering Analysis (DCA), and Adaptive Resonance Theory (ART). It evaluates the performance of each using grouping efficiency and the number of exceptional elements. The key findings are that ART outperforms the other two techniques, providing faster computation and the ability to handle large industrial problems. ART is an artificial neural network approach that can dynamically adapt machine-part cells. The document concludes ART is an effective method for machine-part cell formation in cellular manufacturing.
Improvement of genetic algorithm using artificial bee colonyjournalBEEI
This document proposes using an artificial bee colony algorithm to improve a genetic algorithm. It does this by generating the initial population for the genetic algorithm rather than using random generation. The proposed method is tested on random number generation and the travelling salesman problem. For random number generation, five statistical tests are used to evaluate fitness, with the goal of generating random numbers that pass all tests. For the travelling salesman problem, fitness is based on minimizing the total distance travelled. The results show the proposed method performs better than the traditional genetic algorithm in terms of mean iterations, execution time, error rate, and finding the shortest route.
Feature selection using modified particle swarm optimisation for face recogni...eSAT Journals
Abstract
One of the major influential factors which affects the accuracy of classification rate is the selection of right features. Not all features have vital role in classification. Many of the features in the dataset may be redundant and irrelevant, which increase the computational cost and may reduce classification rate. In this paper, we used DCT(Discrete cosine transform) coefficients as features for face recognition application. The coefficients are optimally selected based on a modified PSO algorithm. In this, the choice of coefficients is done by incorporating the average of the mean normalized standard deviations of various classes and giving more weightage to the lower indexed DCT coefficients. The algorithm is tested on ORL database. A recognition rate of 97% is obtained. Average number of features selected is about 40 percent for a 10 × 10 input. The modified PSO took about 50 iterations for convergence. These performance figures are found to be better than some of the work reported in literature.
Keywords: Particle swarm optimization, Discrete cosine transform, feature extraction, feature selection, face recognition, classification rate.
ENTROPY-COST RATIO MAXIMIZATION MODEL FOR EFFICIENT STOCK PORTFOLIO SELECTION...cscpconf
This paper introduces a new stock portfolio selection model in non-stochastic environment.Following the principle of maximum entropy, a new entropy-cost ratio function is introduced as
the objective function. The uncertain returns, risks and ividends of the securities are considered as interval numbers. Along with the objective function, eight different types of constraints are used in the model to convert it into a pragmatic one. Three different models have been proposed by defining the future inancial market optimistically, pessimistically and in hecombined form to model the portfolio selection problem. To illustrate the effectiveness and tractability of the proposed models, these are tested on a set of data from Bombay Stock Exchange (BSE). The solution has been done by genetic algorithm.
Resolving Multi Objective Stock Portfolio Optimization Problem Using Genetic ...Hok Lie
This document summarizes a research paper that proposes using a genetic algorithm to solve a multi-objective stock portfolio optimization problem. It aims to generate a portfolio with the highest expected return and lowest risk. The document first discusses modern portfolio theory and defines the optimization problem. It then describes using a genetic algorithm with real number encoding to evolve portfolio weight solutions. The algorithm is verified using historical stock data, where expected returns and risk are estimated and a fitness function is developed to maximize return and minimize risk. The results show the genetic algorithm converges to better solutions than random search.
The document describes an Operations Research course. It includes 8 units covering topics like linear programming, transportation problems, queuing theory, PERT-CPM techniques, game theory, and integer programming. It provides details of each unit including the number of lecture hours and the topics to be covered. It also lists the textbooks and reference books for the course. The course aims to introduce students to various operations research techniques and their applications in decision making.
Fuzzy Logic Based Parameter Adaptation of Interior Search Algorithmijtsrd
This paper proposes a detailed switching model for the medium voltage cascaded H bridge multi level inverter drive and induction motor system using fuzzy logic controller which is suitable for power system dynamic studies. The model includes the We describe in this book recent advances in the fuzzy logic based augmentation of neural networks and in optimization algorithms and their application in areas fuzzy logic can help design robust individual behaviours units. Fuzzy logic controllers incorporate heuristic control knowledge. It is convenient choice when a precise linear model of the system to be controlled cannot be easily found. Another advantage of fuzzy logic control is to use fuzzy logic for representing uncertainties, such as vagueness or imprecision which cannot be solved by probability theory. Also fuzzy logic offers greater flexibility to user, among which we can choose the one that best, fits the type of combination to be performed. M. Bhuvaneswari | P. Daniel Samson | V. Anish ""Fuzzy Logic"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30186.pdf
Paper Url : https://www.ijtsrd.com/other-scientific-research-area/other/30186/fuzzy-logic/m-bhuvaneswari
Comparison of Cell formation techniques in Cellular manufacturing using three...IJERA Editor
This document compares three cell formation techniques for cellular manufacturing: Rank Order Clustering 2 (ROC-2), Direct Clustering Analysis (DCA), and Adaptive Resonance Theory (ART). It evaluates the performance of each using grouping efficiency and the number of exceptional elements. The key findings are that ART outperforms the other two techniques, providing faster computation and the ability to handle large industrial problems. ART is an artificial neural network approach that can dynamically adapt machine-part cells. The document concludes ART is an effective method for machine-part cell formation in cellular manufacturing.
The document provides an overview of the history and applications of operations research (OR). It discusses:
- OR originated in the UK during World War II when scientists were called upon to apply a scientific approach to military operations and allocate scarce resources effectively.
- The success of OR in the military spread its use to other government departments and industries.
- Today, OR uses quantitative techniques like mathematical modeling, computer analysis and simulation to help organizations like the military, businesses, transportation and more make optimal decisions. It breaks problems down and finds the best solutions.
Fuzzy Inventory Model for Constantly Deteriorating Items with Power Demand an...iosrjce
IOSR Journal of Mathematics(IOSR-JM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
AnAccurate and Dynamic Predictive Mathematical Model for Classification and P...inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Hybrid Genetic Algorithms and Simulated Annealing for Multi-trip Vehicle Rout...IJECEIAES
Vehicle routing problem with time windows (VRPTW) is one of NP-hard problem. Multi-trip is approach to solve the VRPTW that looking trip scheduling for gets best result. Even though there are various algorithms for the problem, there is opportunity to improve the existing algorithms in order gaining a better result. In this research, genetic algoritm is hybridized with simulated annealing algoritm to solve the problem. Genetic algoritm is employed to explore global search area and simulated annealing is employed to exploit local search area. Four combination types of genetic algorithm and simulated annealing (GA-SA) are tested to get the best solution. The computational experiment shows that GA-SA1 and GA-SA4 can produced the most optimal fitness average values with each value was 1.0888 and 1.0887. However GA-SA4 can found the best fitness chromosome faster than GA-SA1.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Novel approach for predicting the rise and fall of stock index for a specific...IAEME Publication
The document summarizes a proposed approach to predict the rise and fall of a stock index using subtractive clustering, neuro-fuzzy inference systems, and a novel contribution factor algorithm. The approach involves obtaining historical stock market data, performing subtractive clustering on graphs of the data, generating initial rules from the clusters, predicting outcomes using ANFIS modeling, applying the contribution factor algorithm, and making a stock index rise or fall prediction. The goal is to help intraday traders efficiently analyze stock market movements.
An Application of Genetic Algorithm for Non-restricted Space and Pre-determin...drboon
The use of a genetic algorithm is presented to solve a facility layout problem in the situation where there is non-restricted space but the ratio of plant length and width is pre-determined. A two-leveled chromosome is constructed. Six rules are established to translate the chromosome to facility design. An approach of solving a facility layout problem is proposed. A numerical example is employed to illustrate the approach.
Biology-Derived Algorithms in Engineering OptimizationXin-She Yang
The document discusses biology-derived algorithms and their applications in engineering optimization. It describes several biology-inspired algorithms including genetic algorithms, photosynthetic algorithms, neural networks, and cellular automata. Genetic algorithms and photosynthetic algorithms are discussed in more detail. The document also provides examples of how these algorithms can be applied to problems in engineering optimization, such as parameter estimation and inverse analysis.
This document discusses an evolutionary fragment mining approach to analyze stock market behavior for investment purposes. It begins by providing background on data mining and association rule mining techniques. It then proposes a fragment-based approach to reduce the time and space complexity of processing large stock market data sets. This approach works by grouping similar attributes into fragments before applying association rule mining algorithms. Experimental results found relationships between the share values of large and small IT companies, showing how the approach could generate useful rules for predicting stock market trading.
Study of effectiveness of time series modeling (arima) in forecasting stock p...IJCSEA Journal
Stock price prediction has always attracted interest because of the direct financial benefit and the
associated complexity. From our literature review, we felt the need of a study having sector specific
analysis with a broad range of stocks. In this paper, we have conducted a study on the effectiveness of
Autoregressive Integrated Moving Average (ARIMA)model, on fifty six Indian stocks from different sectors.
We have chosen ARIMA model, because of its simplicity and wide acceptability of the model. We also have
studied the effect on prediction accuracy based on various possible previous period data taken. The
comparison and parameterization of the ARIMA model have been done using Akaike information criterion
(AIC). The contribution of the paper , are a) coverage of a good number of Indian stocks b) Analysis of the
models based on sectors c) Analysis of prediction accuracy based on the varying span of previous period
data.
Optimization of Mechanical Design Problems Using Improved Differential Evolut...IDES Editor
Differential Evolution (DE) is a novel evolutionary
approach capable of handling non-differentiable, non-linear
and multi-modal objective functions. DE has been consistently
ranked as one of the best search algorithm for solving global
optimization problems in several case studies. This paper
presents an Improved Constraint Differential Evolution
(ICDE) algorithm for solving constrained optimization
problems. The proposed ICDE algorithm differs from
unconstrained DE algorithm only in the place of initialization,
selection of particles to the next generation and sorting the
final results. Also we implemented the new idea to five versions
of DE algorithm. The performance of ICDE algorithm is
validated on four mechanical engineering problems. The
experimental results show that the performance of ICDE
algorithm in terms of final objective function value, number
of function evaluations and convergence time.
The document summarizes research on machine learning techniques for stock market prediction. It classifies techniques into three categories: time series analysis, neural networks, and hybrid techniques. Neural networks are identified as generally performing best, especially when combined with data preprocessing methods. The document implements and compares techniques including layered recurrent neural networks (LRNN), which performed better than feedforward neural networks and wavelet neural network (Wsmpca-NN) at predicting stock prices of companies.
Design and Implementation of a Multi-Agent System for the Job Shop Scheduling...CSCJournals
This document proposes an agent-based parallel genetic algorithm for solving the job shop scheduling problem. The approach divides the genetic algorithm population into multiple subpopulations that are evolved independently in parallel on different hosts. Agents are used to create the initial populations in parallel and execute the genetic algorithm operations. The genetic algorithm runs in execution phases where subpopulations evolve independently, and migration phases where the subpopulations exchange solutions. Experimental results showed this parallel approach improves the performance over a non-parallel genetic algorithm.
The document summarizes several improved algorithms that aim to address the drawbacks of the Apriori algorithm for association rule mining. It discusses six different approaches: 1) An intersection and record filter approach that counts candidate support only in transactions of sufficient length and uses set intersection; 2) An approach using set size and frequency to prune insignificant candidates; 3) An approach that reduces the candidate set and memory usage by only searching frequent itemsets once to delete candidates; 4) A partitioning approach that divides the database; 5) An approach using vertical data format to reduce database scans; and 6) A distributed approach to parallelize the algorithm across machines.
Hybrid Methods of Some Evolutionary Computations AndKalman Filter on Option P...IJMERJOURNAL
ABSTRACT: The search for a better option price continues within the financial institution. In pricing a put option, holders of the underlying stock always want to make the best decision by maximizing profit. We present an optimal hybrid model among the following combinations: Kalman Filter-Genetic Programming(KF-GP), Kalman Filter-Evolutionary Strategy(KF-ES) and Evolutionary Strategy -Genetic Programming(ES- GP). Our results indicate that the hybrid method involving Kalman Filter-Evolutionary Strategy(KF-ES) is the best model for any investor. Sensitivity analysis was conducted on the model parameters to ascertain the rigidity of the model.
ON AVERAGE CASE ANALYSIS THROUGH STATISTICAL BOUNDS : LINKING THEORY TO PRACTICEcscpconf
Theoretical analysis of algorithms involves counting of operations and a separate bound is provided for a specific operation type . Such a methodology is plagued with its inherent
limitations. In this paper we argue as to why we should prefer weight based statistical bounds,which permit mixing of operations, instead as a robust approach. Empirical analysis is an important idea and should be used to supplement and compliment its existing theoretical counterpart as empirically we can work on weights (e.g. time of an operation can be taken as its weight). Not surprisingly, it should not only be taken as an opportunity so as to amend the mistakes already committed knowingly or unknowingly but also to tell a new story.
On average case analysis through statistical bounds linking theory to practicecsandit
This summary provides the key points from the document in 3 sentences:
The document discusses the limitations of theoretical analysis of algorithms and argues that empirical analysis through statistical bounds can provide a more robust approach for average case analysis. It explains that statistical bounds allow for mixing of different operations rather than analyzing each separately, and do not require pre-assuming a specific input distribution like uniform. The use of statistical bounds for empirical analysis is proposed as a way to supplement theoretical analysis and provide more insight into how algorithms may perform in practice.
This document summarizes a study that compared a single chamber microbial fuel cell (SC-MFC) to a double chamber microbial fuel cell (DC-MFC) using different electron acceptors. The SC-MFC used oxygen from the air as the cathode, while the DC-MFC used diluted hydrogen peroxide. Testing found the DC-MFC produced a higher open circuit voltage of 448mV compared to 200mV for the SC-MFC. The DC-MFC also generated more power, with a maximum power of 7.57mW and coulombic efficiency of 9.2%, versus 0.46mW and 1.88% respectively for the SC-MFC. This suggests hydrogen per
The document summarizes a study on stress among nurses working in hospitals in India. It discusses sources of stress for nurses such as heavy workloads, long hours, lack of support, and issues with hospital administration and policies. The study found high levels of dissatisfaction among nurses regarding opportunities for career development, participation in professional activities, and recognition for their work. It concluded that hospital structure and policies contributed significantly to nurse stress.
This document summarizes a research study on the medical records department of a hospital in India. The study aimed to analyze the existing procedures of the medical records department to identify areas for improvement. Key findings included:
1) The department was found to be computerized and using ICD coding systems, though electronic health records could still be implemented.
2) Issues identified were insufficient staffing and limited space for storage and work.
3) Recommendations included increasing staff and storage space to address problems faced by the department.
This document summarizes a research article that proposes a new evolutionary algorithm method for designing multilayer thin-film coatings. The method adapts the crossover and mutation processes to directly depend on the value of the merit function, which represents the difference between the target and computed reflectance/transmittance values. The proposed method is compared to other evolutionary algorithm methods and is shown to obtain acceptable coating design solutions. Specifically, the method is applied to design a 15-layer antireflection coating and 16-layer 50% beam splitter coating, achieving low merit function values and reflectance/transmittance curves close to the targets.
The document is an academic journal article that discusses:
- Generating control signals for switching components of a DC/AC converter using wavelets to regulate the frequency of the output signal.
- Measuring the frequency of an input AC voltage signal by detecting zero crossings using a microcontroller and generating output signals with a controllable frequency based on the input.
- Simulations showing the generation of pulses using Haar wavelets for various numbers of pulses within a half period, with timing information and waveform plots.
The document provides an overview of the history and applications of operations research (OR). It discusses:
- OR originated in the UK during World War II when scientists were called upon to apply a scientific approach to military operations and allocate scarce resources effectively.
- The success of OR in the military spread its use to other government departments and industries.
- Today, OR uses quantitative techniques like mathematical modeling, computer analysis and simulation to help organizations like the military, businesses, transportation and more make optimal decisions. It breaks problems down and finds the best solutions.
Fuzzy Inventory Model for Constantly Deteriorating Items with Power Demand an...iosrjce
IOSR Journal of Mathematics(IOSR-JM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
AnAccurate and Dynamic Predictive Mathematical Model for Classification and P...inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Hybrid Genetic Algorithms and Simulated Annealing for Multi-trip Vehicle Rout...IJECEIAES
Vehicle routing problem with time windows (VRPTW) is one of NP-hard problem. Multi-trip is approach to solve the VRPTW that looking trip scheduling for gets best result. Even though there are various algorithms for the problem, there is opportunity to improve the existing algorithms in order gaining a better result. In this research, genetic algoritm is hybridized with simulated annealing algoritm to solve the problem. Genetic algoritm is employed to explore global search area and simulated annealing is employed to exploit local search area. Four combination types of genetic algorithm and simulated annealing (GA-SA) are tested to get the best solution. The computational experiment shows that GA-SA1 and GA-SA4 can produced the most optimal fitness average values with each value was 1.0888 and 1.0887. However GA-SA4 can found the best fitness chromosome faster than GA-SA1.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Novel approach for predicting the rise and fall of stock index for a specific...IAEME Publication
The document summarizes a proposed approach to predict the rise and fall of a stock index using subtractive clustering, neuro-fuzzy inference systems, and a novel contribution factor algorithm. The approach involves obtaining historical stock market data, performing subtractive clustering on graphs of the data, generating initial rules from the clusters, predicting outcomes using ANFIS modeling, applying the contribution factor algorithm, and making a stock index rise or fall prediction. The goal is to help intraday traders efficiently analyze stock market movements.
An Application of Genetic Algorithm for Non-restricted Space and Pre-determin...drboon
The use of a genetic algorithm is presented to solve a facility layout problem in the situation where there is non-restricted space but the ratio of plant length and width is pre-determined. A two-leveled chromosome is constructed. Six rules are established to translate the chromosome to facility design. An approach of solving a facility layout problem is proposed. A numerical example is employed to illustrate the approach.
Biology-Derived Algorithms in Engineering OptimizationXin-She Yang
The document discusses biology-derived algorithms and their applications in engineering optimization. It describes several biology-inspired algorithms including genetic algorithms, photosynthetic algorithms, neural networks, and cellular automata. Genetic algorithms and photosynthetic algorithms are discussed in more detail. The document also provides examples of how these algorithms can be applied to problems in engineering optimization, such as parameter estimation and inverse analysis.
This document discusses an evolutionary fragment mining approach to analyze stock market behavior for investment purposes. It begins by providing background on data mining and association rule mining techniques. It then proposes a fragment-based approach to reduce the time and space complexity of processing large stock market data sets. This approach works by grouping similar attributes into fragments before applying association rule mining algorithms. Experimental results found relationships between the share values of large and small IT companies, showing how the approach could generate useful rules for predicting stock market trading.
Study of effectiveness of time series modeling (arima) in forecasting stock p...IJCSEA Journal
Stock price prediction has always attracted interest because of the direct financial benefit and the
associated complexity. From our literature review, we felt the need of a study having sector specific
analysis with a broad range of stocks. In this paper, we have conducted a study on the effectiveness of
Autoregressive Integrated Moving Average (ARIMA)model, on fifty six Indian stocks from different sectors.
We have chosen ARIMA model, because of its simplicity and wide acceptability of the model. We also have
studied the effect on prediction accuracy based on various possible previous period data taken. The
comparison and parameterization of the ARIMA model have been done using Akaike information criterion
(AIC). The contribution of the paper , are a) coverage of a good number of Indian stocks b) Analysis of the
models based on sectors c) Analysis of prediction accuracy based on the varying span of previous period
data.
Optimization of Mechanical Design Problems Using Improved Differential Evolut...IDES Editor
Differential Evolution (DE) is a novel evolutionary
approach capable of handling non-differentiable, non-linear
and multi-modal objective functions. DE has been consistently
ranked as one of the best search algorithm for solving global
optimization problems in several case studies. This paper
presents an Improved Constraint Differential Evolution
(ICDE) algorithm for solving constrained optimization
problems. The proposed ICDE algorithm differs from
unconstrained DE algorithm only in the place of initialization,
selection of particles to the next generation and sorting the
final results. Also we implemented the new idea to five versions
of DE algorithm. The performance of ICDE algorithm is
validated on four mechanical engineering problems. The
experimental results show that the performance of ICDE
algorithm in terms of final objective function value, number
of function evaluations and convergence time.
The document summarizes research on machine learning techniques for stock market prediction. It classifies techniques into three categories: time series analysis, neural networks, and hybrid techniques. Neural networks are identified as generally performing best, especially when combined with data preprocessing methods. The document implements and compares techniques including layered recurrent neural networks (LRNN), which performed better than feedforward neural networks and wavelet neural network (Wsmpca-NN) at predicting stock prices of companies.
Design and Implementation of a Multi-Agent System for the Job Shop Scheduling...CSCJournals
This document proposes an agent-based parallel genetic algorithm for solving the job shop scheduling problem. The approach divides the genetic algorithm population into multiple subpopulations that are evolved independently in parallel on different hosts. Agents are used to create the initial populations in parallel and execute the genetic algorithm operations. The genetic algorithm runs in execution phases where subpopulations evolve independently, and migration phases where the subpopulations exchange solutions. Experimental results showed this parallel approach improves the performance over a non-parallel genetic algorithm.
The document summarizes several improved algorithms that aim to address the drawbacks of the Apriori algorithm for association rule mining. It discusses six different approaches: 1) An intersection and record filter approach that counts candidate support only in transactions of sufficient length and uses set intersection; 2) An approach using set size and frequency to prune insignificant candidates; 3) An approach that reduces the candidate set and memory usage by only searching frequent itemsets once to delete candidates; 4) A partitioning approach that divides the database; 5) An approach using vertical data format to reduce database scans; and 6) A distributed approach to parallelize the algorithm across machines.
Hybrid Methods of Some Evolutionary Computations AndKalman Filter on Option P...IJMERJOURNAL
ABSTRACT: The search for a better option price continues within the financial institution. In pricing a put option, holders of the underlying stock always want to make the best decision by maximizing profit. We present an optimal hybrid model among the following combinations: Kalman Filter-Genetic Programming(KF-GP), Kalman Filter-Evolutionary Strategy(KF-ES) and Evolutionary Strategy -Genetic Programming(ES- GP). Our results indicate that the hybrid method involving Kalman Filter-Evolutionary Strategy(KF-ES) is the best model for any investor. Sensitivity analysis was conducted on the model parameters to ascertain the rigidity of the model.
ON AVERAGE CASE ANALYSIS THROUGH STATISTICAL BOUNDS : LINKING THEORY TO PRACTICEcscpconf
Theoretical analysis of algorithms involves counting of operations and a separate bound is provided for a specific operation type . Such a methodology is plagued with its inherent
limitations. In this paper we argue as to why we should prefer weight based statistical bounds,which permit mixing of operations, instead as a robust approach. Empirical analysis is an important idea and should be used to supplement and compliment its existing theoretical counterpart as empirically we can work on weights (e.g. time of an operation can be taken as its weight). Not surprisingly, it should not only be taken as an opportunity so as to amend the mistakes already committed knowingly or unknowingly but also to tell a new story.
On average case analysis through statistical bounds linking theory to practicecsandit
This summary provides the key points from the document in 3 sentences:
The document discusses the limitations of theoretical analysis of algorithms and argues that empirical analysis through statistical bounds can provide a more robust approach for average case analysis. It explains that statistical bounds allow for mixing of different operations rather than analyzing each separately, and do not require pre-assuming a specific input distribution like uniform. The use of statistical bounds for empirical analysis is proposed as a way to supplement theoretical analysis and provide more insight into how algorithms may perform in practice.
This document summarizes a study that compared a single chamber microbial fuel cell (SC-MFC) to a double chamber microbial fuel cell (DC-MFC) using different electron acceptors. The SC-MFC used oxygen from the air as the cathode, while the DC-MFC used diluted hydrogen peroxide. Testing found the DC-MFC produced a higher open circuit voltage of 448mV compared to 200mV for the SC-MFC. The DC-MFC also generated more power, with a maximum power of 7.57mW and coulombic efficiency of 9.2%, versus 0.46mW and 1.88% respectively for the SC-MFC. This suggests hydrogen per
The document summarizes a study on stress among nurses working in hospitals in India. It discusses sources of stress for nurses such as heavy workloads, long hours, lack of support, and issues with hospital administration and policies. The study found high levels of dissatisfaction among nurses regarding opportunities for career development, participation in professional activities, and recognition for their work. It concluded that hospital structure and policies contributed significantly to nurse stress.
This document summarizes a research study on the medical records department of a hospital in India. The study aimed to analyze the existing procedures of the medical records department to identify areas for improvement. Key findings included:
1) The department was found to be computerized and using ICD coding systems, though electronic health records could still be implemented.
2) Issues identified were insufficient staffing and limited space for storage and work.
3) Recommendations included increasing staff and storage space to address problems faced by the department.
This document summarizes a research article that proposes a new evolutionary algorithm method for designing multilayer thin-film coatings. The method adapts the crossover and mutation processes to directly depend on the value of the merit function, which represents the difference between the target and computed reflectance/transmittance values. The proposed method is compared to other evolutionary algorithm methods and is shown to obtain acceptable coating design solutions. Specifically, the method is applied to design a 15-layer antireflection coating and 16-layer 50% beam splitter coating, achieving low merit function values and reflectance/transmittance curves close to the targets.
The document is an academic journal article that discusses:
- Generating control signals for switching components of a DC/AC converter using wavelets to regulate the frequency of the output signal.
- Measuring the frequency of an input AC voltage signal by detecting zero crossings using a microcontroller and generating output signals with a controllable frequency based on the input.
- Simulations showing the generation of pulses using Haar wavelets for various numbers of pulses within a half period, with timing information and waveform plots.
This document discusses the challenges of digital preservation including technological obsolescence, organizational issues, and resource requirements. It outlines the key components of a digital preservation program including organizational infrastructure, technological infrastructure, and sustainable resources. Digital preservation aims to maintain digital assets in a readable format over time and ensure their continued accessibility and understandability despite changing technologies. Standards and migration strategies are important for long-term digital preservation.
This document summarizes the reform of the U.S. patent system through the Leahy-Smith American Invents Act of 2011. It overhauled the previous "first to invent" system, replacing it with a "first inventor to file" system to harmonize U.S. patent law with other countries. Key changes include prioritizing the inventor who first files a patent application over those who may have invented first. The act aimed to reduce the backlog of patent applications and lawsuits by simplifying the patent process.
The document summarizes a research paper that proposes a new mechanism to detect and prevent selfish nodes exhibiting packet dropping attacks in mobile ad hoc networks (MANETs). The mechanism works by calculating the Local Forward Percentage (LFP) of nodes based on the Principle of Flow Conservation, and identifying paths with LFP below a threshold as malicious. It modifies the Ad Hoc On-Demand Distance Vector (AODV) routing protocol to suppress route replies for detected malicious paths, preventing those paths from being used for future data transmission. The mechanism aims to address limitations in existing acknowledgement-based schemes for detecting misbehaving nodes in MANETs.
1) The document describes a wavelet-based technique for denoising underwater signals affected by wind-driven ambient noise. It uses discrete wavelet transform to decompose the noisy signal into coefficients. 2) Thresholding is then applied to the coefficients, where threshold values are calculated separately for each level of decomposition using universal thresholding. 3) The signal is then reconstructed from the modified coefficients after thresholding to reduce noise. The technique aims to improve the signal-to-noise ratio of underwater signals corrupted by wind noise.
Quanto fica meu seguro auto com condutor adicional?Bidu Corretora
Você sabia que ter um condutor adicional pode aumentar o valor do seu seguro auto? Veja uma simulação de quanto ficaria o seguro de um casal que tem carro compartilhado - e lembre-se de sempre falar a verdade na hora da cotação do seu seguro de carro!
Protestos ocorreram em várias capitais brasileiras com pessoas pedindo mudanças políticas e sociais. Imagens mostram manifestantes nas ruas do Rio de Janeiro, com cartazes e gritos de ordem. As manifestações pediram por mais democracia, direitos e qualidade de vida para a população brasileira.
El documento trata sobre los derechos humanos, su origen y evolución histórica. Explica que los derechos humanos se recogieron formalmente en la Declaración de los Derechos del Hombre y del Ciudadano en 1789 y en la Declaración Universal de los Derechos Humanos en 1948. Además, define los derechos humanos como aquellas libertades y garantías inherentes a todo ser humano, sin distinción, que permiten una vida digna. Finalmente, discute que aunque los derechos humanos tienen sus raíces en la cultura
Kelly is a leading scientific staffing provider that places scientific professionals in various fields including biotechnology, clinical research, pharmaceuticals, and more. They placed nearly 11,000 scientific employees for over 1,800 client locations last year, helping clients meet their staffing needs and development goals. Kelly has extensive experience in scientific staffing, having placed professionals in scientific roles since 1995.
Este documento presenta un libro de lectura para niños de nivel B titulado "Cerca y lejos". El libro utiliza fotos de animales como leones, búhos, lobos y ciervos para enseñar a los niños los conceptos de cerca y lejos. Cada página contiene dos fotos de un animal, una etiquetada como "cerca" y la otra como "lejos", para ayudar a los niños a distinguir la distancia. El libro también proporciona créditos de las fotos utilizadas.
Parabéns pelos trabalhos conduzidos!!!!
Consultoria de Estratégia, Processos e Projetos Multidisciplinares
Case de sucesso...
Com mais de 10 anos de história e dezenas de trabalhos entregues com sucesso por todo Brasil, credenciam a IE Consulting como uma das empresas referência no segmento de consultorias empresariais.
A IE Consulting tem o diferencial da mobilidade de atuação, conforme os cenários que se apresentam no dia-a-dia dos trabalhos. A estratégia e capacidade da empresa em formar consultores multifuncionais esta diretamente ligada às inúmeras variações que ocorrem no mercado, economia, política e comportamento do consumidor.
A importância e o respeito que a empresa tem pelos seus clientes resultam em parcerias duradouras e de confiança mútua.
Os serviços de consultoria IE Consulting estão divididos em três áreas de atuação:
:: Consultoria Estratégica
• Mapa e plano estratégico;
• Elaboração do plano de ações (metodologia 5W 2H);
• Implantação dos indicadores de desempenho (KPI’s – Key Performance Indicators);
• Construção do Balanced Scorecard.
:: Apoio à identificação dos Processos-Chave
• Mapeamento de Processos, desenho e implantação de fluxos e procedimentos;
• Ferramentas de Controle das Não Conformidades;
• Estabelecer uma padronização das comunicações;
• Revisão das práticas e aperfeiçoamento do controle de documentos e registros.
:: Gestão de Projetos Multidisciplinares
• Business Plan;
• Planejamento de cada etapa (Project Charter);
• Cronograma para gestão dos entregáveis;
• Validação do conteúdo desenvolvido;
• Implantação e capacitação das equipes;
• Monitoramento dos resultados.
“Nossa proposta de trabalho não é reinventar as empresas, mas sim extrair o potencial de todos os recursos já existentes”, diz um dos sócios-fundadores da IE Consulting.
Interessante, não acham??? Sua empresa precisa saber mais sobre estes temas??? Deixe seu contato nesta publicação.
Atenciosamente
IE Consulting
Este documento describe dos tipos de cimentaciones. Las zapatas aisladas transmiten cargas de pilares al terreno a través de superficies de apoyo más grandes que su canto, usualmente en forma de paralelepípedos. Las zapatas corridas reciben cargas lineales a través de muros u otros elementos estructurales y son de gran longitud comparada con su sección transversal.
Este documento descreve uma aula de Geografia para alunos do 5o ano sobre localização e rotas dentro da cidade onde vivem. Os objetivos são ensinar os alunos a usar mapas online para estudar e se divertir, apresentar um conceito de mapa interativo e expandir seu conhecimento. Na aula, os alunos usarão mapas online em duplas para localizar lugares e traçar rotas, e depois debaterão suas experiências.
This document summarizes a research paper that analyzes the performance and convergence of a novel genetic algorithm model towards finding global minima. The paper introduces genetic algorithms, which are probabilistic search algorithms inspired by natural evolution. It describes the components of genetic algorithms, including chromosomes, fitness functions, reproduction, crossover, and mutation operators. It also discusses encoding solutions as chromosomes and two common genetic algorithm models: Holland's original model and the common model. The paper aims to present an analysis of applying genetic algorithms to optimize test functions and finding their global minima.
This document summarizes a research article from the International Journal of Electronics and Communication Engineering & Technology. The article compares the performance of three genetic algorithm crossover operators - PMX, OX, and CX - for solving the Traveling Salesman Problem (TSP). It finds that the PMX operator enables achieving a better solution than the other two operators tested. The document provides background on genetic algorithms and describes the TSP optimization problem, literature on using genetic algorithms for TSP, and proposes a new PMX crossover scheme to resolve TSP more efficiently.
This document proposes a stock market forecasting system that uses both a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model and a decision tree algorithm. The GARCH model is used to predict stock prices and their volatility over time. A decision tree algorithm is then applied to optimize the GARCH model by reducing errors and false predictions. The decision tree assigns weights to parameters like earnings per share, sales revenue, and trading volume to classify the quality of the input data. This combined GARCH and decision tree approach aims to more accurately forecast stock market movements and prices.
Scalable Rough C-Means clustering using Firefly algorithm..................................................................1
Abhilash Namdev and B.K. Tripathy
Significance of Embedded Systems to IoT................................................................................................. 15
P. R. S. M. Lakshmi, P. Lakshmi Narayanamma and K. Santhi Sri
Cognitive Abilities, Information Literacy Knowledge and Retrieval Skills of Undergraduates: A
Comparison of Public and Private Universities in Nigeria ........................................................................ 24
Janet O. Adekannbi and Testimony Morenike Oluwayinka
Risk Assessment in Constructing Horseshoe Vault Tunnels using Fuzzy Technique................................ 48
Erfan Shafaghat and Mostafa Yousefi Rad
Evaluating the Adoption of Deductive Database Technology in Augmenting Criminal Intelligence in
Zimbabwe: Case of Zimbabwe Republic Police......................................................................................... 68
Mahlangu Gilbert, Furusa Samuel Simbarashe, Chikonye Musafare and Mugoniwa Beauty
Analysis of Petrol Pumps Reachability in Anand District of Gujarat ....................................................... 77
Nidhi Arora
The document discusses using a NSGA-III-based meta decision tree to classify real estate data. NSGA-III is a metaheuristic optimization technique that can find optimal solutions. It is used to iteratively optimize the parameters of a meta-J48 decision tree model to improve classification accuracy of real estate data. Experimental results found the proposed NSGA-III technique outperformed other methods in terms of accuracy, true positive rate, true negative rate, precision, and F-measure. Therefore, the technique is applicable for real-time real estate users.
Analysis of selection schemes for solving job shop scheduling problem using g...eSAT Journals
Abstract Scheduling problems have the standard consideration in the field of manufacturing. Among the various types of scheduling problems, the job shop scheduling problem is one of the most interesting NP-hard problems. As the job shop scheduling is an optimization problem, Genetic algorithm was selected to solve it In this study. Selection scheme is one of the important operators of Genetic algorithm. The choice of selection method to be applied for solving problems has a wide role in the Genetic algorithm process. The speed of convergence towards the optimum solution for the chosen problem is largely determined by the selection mechanism used in the Genetic algorithm. Depending upon the selection scheme applied, the population fitness over the successive generations could be improved. There are various type of selection schemes in genetic algorithm are available, where each selection scheme has its own feasibility for solving a particular problem. In this study, the selection schemes namely Stochastic Universal Sampling (SUS), Roulette Wheel Selection (RWS), Rank Based Roulette Wheel Selection (RRWS) and Binary Tournament Selection (BTS) were chosen for implementation. The characteristics of chosen selection mechanisms of Genetic algorithm for solving the job shop scheduling problem were analyzed. The Genetic algorithm with four different selection schemes is tested on instances of 7 benchmark problems of different size. The result shows that the each of the four selection schemes of Genetic algorithm have been successfully applied to the job shop scheduling problems efficiently and the performance of Stochastic Universal Sampling selection method is better than all other four selection schemes. Keywords: Genetic Algorithm, Makespan, Selection schemes
STOCK PRICE PREDICTION USING TIME SERIESIRJET Journal
This document discusses using time series analysis and ARIMA modeling to predict stock prices. It begins with an introduction that explains why accurately predicting stock prices is challenging but important for investors. It then provides an overview of time series analysis and some common time series forecasting techniques like ARIMA, exponential smoothing, and naive methods. The document reviews related work applying machine learning to securities market prediction. It outlines the methodology, which involves gathering stock market data and analyzing it with ARIMA and other time series models to forecast future stock prices. Finally, it discusses the existing methodology and limitations of solely using ARIMA modeling for time series forecasting.
STOCK PRICE PREDICTION USING TIME SERIESIRJET Journal
This document discusses using time series analysis and machine learning algorithms to predict stock prices. Specifically, it analyzes using the ARIMA (Autoregressive Integrated Moving Average) model and other techniques like exponential smoothing, naive forecasting, seasonal naive forecasting and neural networks. The document outlines the existing methodology for stock price prediction, which involves collecting historical data, cleaning it, and using it to train and test models. It then evaluates the performance of ARIMA and exponential smoothing models on stock price data from Yahoo Finance, finding they achieved 97.6% accuracy, outperforming other algorithms. The conclusion is that time series methods like ARIMA and exponential smoothing produced reliable models when the training data exhibited strong trends, but
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a research paper that uses an artificial neural network approach to forecast stock market prices in India. The paper trains a feedforward neural network using a backpropagation algorithm on data from 5 Indian companies between 2004 and 2013. The network is tested in MATLAB to predict stock prices and calculate an error rate for accuracy. The neural network model is found to provide a computational method for predicting stock market movements based on historical price and volume data.
Prediction of Euro 50 Using Back Propagation Neural Network (BPNN) and Geneti...AI Publications
Modeling time series is often associated with the process forecasts certain characteristics in the next period. One of the methods forecasts that developed nowadays is using artificial neural network or more popularly known as a neural network. Use neural network in forecasts time series can be a good solution, but the problem is network architecture and the training method in the right direction. One of the choices that might be using a genetic algorithm. A genetic algorithm is a search algorithm stochastic resonance based on how it works by the mechanisms of natural selection and genetic variation that aims to find a solution to a problem. This algorithm can be used as teaching methods in train models are sent back propagation neural network. The application genetic algorithm and neural network for divination time series aim to get the weight optimum. From the training and testing on the data index share price euro 50 obtained by the RMSE testing 27.8744 and 39.2852 RMSE training. The weight or parameters that produced by has reached an optimum level in second-generation 1000 with the best fitness and the average 0.027771 the fitness of 0.0027847.Model is good to be used to give a prediction that is quite accurate information that is shown by the close target with the output.
The document proposes a hybrid algorithm combining genetic algorithm and cuckoo search optimization to solve job shop scheduling problems. It aims to minimize makespan (completion time of all jobs) by scheduling jobs on machines. The genetic algorithm is used to explore the search space but can get trapped in local optima. Cuckoo search optimization performs local search faster than genetic algorithm and helps avoid local optima. Experimental results on benchmark problems show the hybrid algorithm yields better solutions in terms of makespan and runtime compared to genetic algorithm and ant colony optimization algorithms.
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...paperpublications3
Abstract: Engineering design problems are complex by nature because of their critical objective functions involving many variables and Constraints. Engineers have to ensure the compatibility with the imposed specifications keeping the manufacturing costs low. Moreover, the methodology may vary according to the design problem.
The main issue is to choose the proper tool for optimization. In the earlier days, a design problem was optimized by some of the conventional optimization techniques like gradient Search, evolutionary optimization, random search etc. These are known as classical methods.
The method is to be properly Chosen depending on the nature of the problem- an incorrect choice may sometimes fail to give the optimal solution. So the methods are less robust.
Now-a-days soft-computing techniques are being widely used for optimizing a function. These are more robust. Genetic algorithm is one such method. It is an effective tool in the realm of stochastic optimization (non-classical). The algorithm produces many strings and generation to reach the optimal point.
The main objective of the paper is to optimize engineering design problems using Genetic Algorithm and to analyze how the algorithm reaches the optima effectively and closely. We choose a mathematical expression for the objective function in terms of the design variables and optimize the same under given constraints using GA.
A NOVEL APPROACH TO MINE FREQUENT PATTERNS FROM LARGE VOLUME OF DATASET USING...IAEME Publication
In this paper, MDL based reduction in frequent pattern is presented. The ideal outcome of any pattern mining process is to explore the data in new insights. And also, we need to eliminate the non-interesting patterns that describe noise. The major problem in frequent pattern mining is to identify the interesting patterns. Instead of performing association rule mining on all the frequent item sets, it is feasible to select a sub set of frequent item sets and perform the mining task. Selecting a small set of frequent item sets from large amount of interesting ones is a difficult task. In our approach, MDL based algorithm is used for reducing the number of frequent item sets to be used for association rule mining is presented.
COMPARISON BETWEEN THE GENETIC ALGORITHMS OPTIMIZATION AND PARTICLE SWARM OPT...IAEME Publication
Close range photogrammetry network design is referred to the process of placing a set of
cameras in order to achieve photogrammetric tasks. The main objective of this paper is tried to find
the best location of two/three camera stations. The genetic algorithm optimization and Particle
Swarm Optimization are developed to determine the optimal camera stations for computing the three
dimensional coordinates. In this research, a mathematical model representing the genetic algorithm
optimization and Particle Swarm Optimization for the close range photogrammetry network is
developed. This paper gives also the sequence of the field operations and computational steps for this
task. A test field is included to reinforce the theoretical aspects.
Comparison between the genetic algorithms optimization and particle swarm opt...IAEME Publication
The document compares the genetic algorithms optimization and particle swarm optimization methods for designing close range photogrammetry networks. It presents the genetic algorithm and particle swarm optimization as two popular meta-heuristic algorithms inspired by natural evolution and collective animal behavior, respectively. The document develops mathematical models representing the genetic algorithm and particle swarm optimization for close range photogrammetry network design and evaluates them in a test field to reinforce the theoretical aspects.
This document discusses using particle swarm optimization based on variable neighborhood search (PSO-VNS) to attack classical cryptography ciphers. PSO is a population-based optimization algorithm inspired by bird flocking behavior. VNS is a metaheuristic algorithm that explores neighborhoods of solutions to escape local optima. The paper proposes improving PSO with VNS to find better solutions. It evaluates PSO-VNS on substitution and transposition ciphers, finding it recovers keys better than standard PSO and other variants.
A model for profit pattern mining based on genetic algorithmeSAT Journals
Abstract
Mining profit oriented patterns is a novel technique of association rule mining in data mining, which basically focuses on important issues related with business. As it is well known that every business aims to generate the profit and find the ways to improve the same. In earlier days association rule mining was used for market basket analysis and targeted only some of the business and commercial aspects. Afterwards the researchers started to aim the most prominent element of any business i.e. Profit, and determined the innovative way to generate the association rules based on profit. Profit oriented patterns mining approach combines the statistic based pattern mining with value-based decision making to generate those patterns with the maximum profit and some ways to generate recommenders for future strategy. To achieve the desired goal the traditional association rule mining alone is not effectual, so we combine the strength of genetic algorithm with association rule mining to enhance its capability. The study shows that Genetic Algorithm improves the effectiveness and efficiency of association rule mining outcome, since genetic algorithms are competent to handle the problems related with the uncertainty, multi-dimensional, non-differential, non-continuous, and non-parametrical, non-linearity constraint and multi-objective optimization problems. In this paper we apply the concept of profit pattern mining with genetic algorithm to generate profit oriented pattern which help out in future business expansion and fulfill the business objective.
Keywords: Data Mining, Association Rule Mining, Profit Pattern Mining, Genetic Algorithm
A model for profit pattern mining based on genetic algorithmeSAT Journals
Abstract
Mining profit oriented patterns is a novel technique of association rule mining in data mining, which basically focuses on important issues related with business. As it is well known that every business aims to generate the profit and find the ways to improve the same. In earlier days association rule mining was used for market basket analysis and targeted only some of the business and commercial aspects. Afterwards the researchers started to aim the most prominent element of any business i.e. Profit, and determined the innovative way to generate the association rules based on profit. Profit oriented patterns mining approach combines the statistic based pattern mining with value-based decision making to generate those patterns with the maximum profit and some ways to generate recommenders for future strategy. To achieve the desired goal the traditional association rule mining alone is not effectual, so we combine the strength of genetic algorithm with association rule mining to enhance its capability. The study shows that Genetic Algorithm improves the effectiveness and efficiency of association rule mining outcome, since genetic algorithms are competent to handle the problems related with the uncertainty, multi-dimensional, non-differential, non-continuous, and non-parametrical, non-linearity constraint and multi-objective optimization problems. In this paper we apply the concept of profit pattern mining with genetic algorithm to generate profit oriented pattern which help out in future business expansion and fulfill the business objective.
Keywords: Data Mining, Association Rule Mining, Profit Pattern Mining, Genetic Algorithm
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
The majority of the population in India lives in villages. The village is the back bone of the country. Village or rural industries play an important role in the national economy, particularly in the rural development. Developing the rural economy is one of the key indicators towards a country’s success. Whether it be the need to look after the welfare of the farmers or invest in rural infrastructure, Governments have to ensure that rural development isn’t compromised. The economic development of our country largely depends on the progress of rural areas and the standard of living of rural masses. Village or rural industries play an important role in the national economy, particularly in the rural development. Rural entrepreneurship is based on stimulating local entrepreneurial talent and the subsequent growth of indigenous enterprises. It recognizes opportunity in the rural areas and accelerates a unique blend of resources either inside or outside of agriculture. Rural entrepreneurship brings an economic value to the rural sector by creating new methods of production, new markets, new products and generate employment opportunities thereby ensuring continuous rural development. Social Entrepreneurship has the direct and primary objective of serving the society along with the earning profits. So, social entrepreneurship is different from the economic entrepreneurship as its basic objective is not to earn profits but for providing innovative solutions to meet the society needs which are not taken care by majority of the entrepreneurs as they are in the business for profit making as a sole objective. So, the Social Entrepreneurs have the huge growth potential particularly in the developing countries like India where we have huge societal disparities in terms of the financial positions of the population. Still 22 percent of the Indian population is below the poverty line and also there is disparity among the rural & urban population in terms of families living under BPL. 25.7 percent of the rural population & 13.7 percent of the urban population is under BPL which clearly shows the disparity of the poor people in the rural and urban areas. The need to develop social entrepreneurship in agriculture is dictated by a large number of social problems. Such problems include low living standards, unemployment, and social tension. The reasons that led to the emergence of the practice of social entrepreneurship are the above factors. The research problem lays upon disclosing the importance of role of social entrepreneurship in rural development of India. The paper the tendencies of social entrepreneurship in India, to present successful examples of such business for providing recommendations how to improve situation in rural areas in terms of social entrepreneurship development. Indian government has made some steps towards development of social enterprises, social entrepreneurship, and social in- novation, but a lot remains to be improved.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
Manufacturing industries have witnessed an outburst in productivity. For productivity improvement manufacturing industries are taking various initiatives by using lean tools and techniques. However, in different manufacturing industries, frugal approach is applied in product design and services as a tool for improvement. Frugal approach contributed to prove less is more and seems indirectly contributing to improve productivity. Hence, there is need to understand status of frugal approach application in manufacturing industries. All manufacturing industries are trying hard and putting continuous efforts for competitive existence. For productivity improvements, manufacturing industries are coming up with different effective and efficient solutions in manufacturing processes and operations. To overcome current challenges, manufacturing industries have started using frugal approach in product design and services. For this study, methodology adopted with both primary and secondary sources of data. For primary source interview and observation technique is used and for secondary source review has done based on available literatures in website, printed magazines, manual etc. An attempt has made for understanding application of frugal approach with the study of manufacturing industry project. Manufacturing industry selected for this project study is Mahindra and Mahindra Ltd. This paper will help researcher to find the connections between the two concepts productivity improvement and frugal approach. This paper will help to understand significance of frugal approach for productivity improvement in manufacturing industry. This will also help to understand current scenario of frugal approach in manufacturing industry. In manufacturing industries various process are involved to deliver the final product. In the process of converting input in to output through manufacturing process productivity plays very critical role. Hence this study will help to evolve status of frugal approach in productivity improvement programme. The notion of frugal can be viewed as an approach towards productivity improvement in manufacturing industries.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.