The final cost of public school building projects, like other construction projects, is unknown
to the owner till the account closure. Artificial Neural Networks (ANN) is used in an attempt to
predict the final cost of two story (12 classes) school projects under lowest bid system of award
before work starts. A database of (65) school projects records completed in (2007-2012) are used to
develop and verify the ANN model. Based on expert opinions, nine out of eleven parameters are
considered to have the most significant impact on the magnitude of final cost. Hence they are used as
model inputs while the output of the model is going to be the final cost (FC). These parameters are;
accepted bid price, average bid price, estimated cost, contractor rank, supervising engineer
experience, project location, number of bidders, year of contracting, and contractual duration. It was
found that ANN has the ability to predict the final cost for school projects with very good degree of
accuracy having a coefficient of correlation (R) of (91%), and an average accuracy percentage of
(99.98%).
Funding agencies such as the U.S. National Science Foundation (NSF), U.S. National Institutes of Health (NIH), and the Transportation Research Board (TRB) of The National Academies make their online grant databases publicly available which document a variety of information on grants that have been funded over the past few decades. In this paper, based on a quantitative analysis of the TRB’s Research In Progress (RIP) online database, we explore the feasibility of automatically estimating the appropriate funding level, given the textual description of a transportation research project. We use statistical Text Mining (TM) and Machine Learning (ML) technologies to build this model using the 14,000 or more records of the TRB’s RIP research grants big data. Several Natural Language Processing (NLP) based text representation models such as the Latent Dirichlet Allocation (LDA), Latent Semantic Indexing (LSI) and the Doc2Vec Machine Learning (ML) approach are used to vectorize the project descriptions and generate semantic vectors. Each of these representations is then used to train supervised regression models such as Random Forest (RF) regression. Out of the three latent feature generation models, we found LDA gives the least Mean Absolute Error (MAE) using 300 feature dimensions and RF regression model. However, based on the correlation coefficients, it was found that it is not very feasible to accurately predict the funding level directly from the unstructured project abstract, given the large variations in source agencies, subject areas, and funding levels. By using separate prediction models for different types of funding agencies, funding levels were better correlated with the project abstract.
Construction Management (CM) has to deal with a variety of uncertainties related to Time, Cost, Quality, and Safety, to name a few. Such uncertainties make the entire construction process highly unpredictable. It, therefore, falls under the purview of artificial neural networks (ANNs) in which the given hazy information can be effectively interpreted in order to arrive at meaningful conclusions. This paper reviews the application of ANNs in construction activities related to the prediction of costs, risk, and safety, tender bids, as well as labor and equipment productivity. The review suggests that the ANN’s had been highly beneficial in correctly interpreting inadequate input information. It was seen that most of the investigators used the feed forward back propagation type of the network; however, if a single ANN architecture was found to be insufficient, then hybrid modeling in association with other machine learning tools such as genetic programming and support vector machines were much useful. It was however clear that the authenticity of data and experience of the modeler are important in obtaining good results.
Comparison of Cost Estimation Methods using Hybrid Artificial Intelligence on...IJERA Editor
Cost estimating at schematic design stage as the basis of project evaluation, engineering design, and cost
management, plays an important role in project decision under a limited definition of scope and constraints in
available information and time, and the presence of uncertainties. The purpose of this study is to compare the
performance of cost estimation models of two different hybrid artificial intelligence approaches: regression
analysis-adaptive neuro fuzzy inference system (RANFIS) and case based reasoning-genetic algorithm (CBRGA)
techniques. The models were developed based on the same 50 low-cost apartment project datasets in
Indonesia. Tested on another five testing data, the models were proven to perform very well in term of accuracy.
A CBR-GA model was found to be the best performer but suffered from disadvantage of needing 15 cost drivers
if compared to only 4 cost drivers required by RANFIS for on-par performance.
Development Principles of Knowledge Database of Intelligent System for Estima...ITIIIndustries
In the paper, a principles underlying the construction of an intelligent information system estimated results of the dynamic interaction of orbital systems with space debris is presented. It describes the knowledge database model based on these principles which is the synthesis of theoretical and practical information in the field of estimating the high-speed interaction of objects.
Developing Competitive Strategies in Higher Education through Visual Data Miningertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/visual-data-mining-for-developing-competitive-strategies-in-higher-education/
Information visualization is the growing field of computer science that aims at visually mining data for knowledge discovery. In this paper, a data mining framework and a novel information visualization scheme is developed and applied to the domain of higher education. The presented framework consists of three main types of visual data analysis: Discovering general insights, carrying out competitive benchmarking, and planning for High School Relationship Management (HSRM). In this paper the framework and the square tiles visualization scheme are described and an application at a private university in Turkey with the goal of attracting bright-est students is demonstrated.
Funding agencies such as the U.S. National Science Foundation (NSF), U.S. National Institutes of Health (NIH), and the Transportation Research Board (TRB) of The National Academies make their online grant databases publicly available which document a variety of information on grants that have been funded over the past few decades. In this paper, based on a quantitative analysis of the TRB’s Research In Progress (RIP) online database, we explore the feasibility of automatically estimating the appropriate funding level, given the textual description of a transportation research project. We use statistical Text Mining (TM) and Machine Learning (ML) technologies to build this model using the 14,000 or more records of the TRB’s RIP research grants big data. Several Natural Language Processing (NLP) based text representation models such as the Latent Dirichlet Allocation (LDA), Latent Semantic Indexing (LSI) and the Doc2Vec Machine Learning (ML) approach are used to vectorize the project descriptions and generate semantic vectors. Each of these representations is then used to train supervised regression models such as Random Forest (RF) regression. Out of the three latent feature generation models, we found LDA gives the least Mean Absolute Error (MAE) using 300 feature dimensions and RF regression model. However, based on the correlation coefficients, it was found that it is not very feasible to accurately predict the funding level directly from the unstructured project abstract, given the large variations in source agencies, subject areas, and funding levels. By using separate prediction models for different types of funding agencies, funding levels were better correlated with the project abstract.
Construction Management (CM) has to deal with a variety of uncertainties related to Time, Cost, Quality, and Safety, to name a few. Such uncertainties make the entire construction process highly unpredictable. It, therefore, falls under the purview of artificial neural networks (ANNs) in which the given hazy information can be effectively interpreted in order to arrive at meaningful conclusions. This paper reviews the application of ANNs in construction activities related to the prediction of costs, risk, and safety, tender bids, as well as labor and equipment productivity. The review suggests that the ANN’s had been highly beneficial in correctly interpreting inadequate input information. It was seen that most of the investigators used the feed forward back propagation type of the network; however, if a single ANN architecture was found to be insufficient, then hybrid modeling in association with other machine learning tools such as genetic programming and support vector machines were much useful. It was however clear that the authenticity of data and experience of the modeler are important in obtaining good results.
Comparison of Cost Estimation Methods using Hybrid Artificial Intelligence on...IJERA Editor
Cost estimating at schematic design stage as the basis of project evaluation, engineering design, and cost
management, plays an important role in project decision under a limited definition of scope and constraints in
available information and time, and the presence of uncertainties. The purpose of this study is to compare the
performance of cost estimation models of two different hybrid artificial intelligence approaches: regression
analysis-adaptive neuro fuzzy inference system (RANFIS) and case based reasoning-genetic algorithm (CBRGA)
techniques. The models were developed based on the same 50 low-cost apartment project datasets in
Indonesia. Tested on another five testing data, the models were proven to perform very well in term of accuracy.
A CBR-GA model was found to be the best performer but suffered from disadvantage of needing 15 cost drivers
if compared to only 4 cost drivers required by RANFIS for on-par performance.
Development Principles of Knowledge Database of Intelligent System for Estima...ITIIIndustries
In the paper, a principles underlying the construction of an intelligent information system estimated results of the dynamic interaction of orbital systems with space debris is presented. It describes the knowledge database model based on these principles which is the synthesis of theoretical and practical information in the field of estimating the high-speed interaction of objects.
Developing Competitive Strategies in Higher Education through Visual Data Miningertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/visual-data-mining-for-developing-competitive-strategies-in-higher-education/
Information visualization is the growing field of computer science that aims at visually mining data for knowledge discovery. In this paper, a data mining framework and a novel information visualization scheme is developed and applied to the domain of higher education. The presented framework consists of three main types of visual data analysis: Discovering general insights, carrying out competitive benchmarking, and planning for High School Relationship Management (HSRM). In this paper the framework and the square tiles visualization scheme are described and an application at a private university in Turkey with the goal of attracting bright-est students is demonstrated.
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.
Enhancement of student performance prediction using modified K-nearest neighborTELKOMNIKA JOURNAL
The traditional K-nearest neighbor (KNN) algorithm uses an exhaustive search for a complete training set to predict a single test sample. This procedure can slow down the system to consume more time for huge datasets. The selection of classes for a new sample depends on a simple majority voting system that does not reflect the various significance of different samples (i.e. ignoring the similarities among samples). It also leads to a misclassification problem due to the occurrence of a double majority class. In reference to the above-mentioned issues, this work adopts a combination of moment descriptor and KNN to optimize the sample selection. This is done based on the fact that classifying the training samples before the searching actually takes place can speed up and improve the predictive performance of the nearest neighbor. The proposed method can be called as fast KNN (FKNN). The experimental results show that the proposed FKNN method decreases original KNN consuming time within a range of (75.4%) to (90.25%), and improve the classification accuracy percentage in the range from (20%) to (36.3%) utilizing three types of student datasets to predict whether the student can pass or fail the exam automatically.
A fuzzy approach to evaluate suitability of infrastructure projects with safetyeSAT Journals
Abstract
The current project deals with safety management in highways and infrastructure (Buildings and Roads).The research is partly doctrinal and partly empirical in natural. Research tools used is fuzzy logic. The scope research has been to mainly cover highways and infrastructure (Buildings and Roads).The topic of construction includes the process of Highways, Building and society roads, construction and maintenance, including the design of respective construction, contracting, accomplishing, supervision, and maintenance of Highways, Building, society roads and related structures. Our study of project will fulfil the safety requirements by using Fuzzy logic that should be consider before starting highways and infrastructure (Buildings and Roads) and this study will be very helpful in construction industry. as this study will decrease the chances of accidents as well as to save lives. Today so many people lose their lives when traffic has to move through maintenance works and road construction every year also during the construction of Buildings. The cases of construction section injuries and accidental death are predicted to go even higher than now. Construction in highways and infrastructure (Building and Roads) covers various activities, techniques, materials and source of danger therefore because of this conditions the probability of accidents increases every time. The fact is construction industry has the most disappointing record of safety compare to all industrial sectors, with a risk of casualty 5 times higher than several other industry in the world. The higher rate of accidents and deaths in the construction industry compare to all other industries are may be due to the process of the construction work. The factors due to which the rate of accidents are high in construction industry are such as poor planning, lack of safety training, lack of supervision, lack of safety equipment , and lack of incident investigation helps to create more problems in future. Hence, by using Multi criteria decision making by Fuzzy logic will reduce the risk of accidents while construction of highways and infrastructure (Building and Roads).
Keywords: Highway and Infrastructure Safety, Defuzzification, Fuzzy Multi Criteria Decision Making, Expert Opinion, Linguistic Terms and Safety Potential Index
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Calculation of Reusability Matrices for Object Oriented applicationsIJMERJOURNAL
ABSTRACT: Reusability is one of the major concerns of object oriented applications. Object oriented paradigm is having its own various advantages including reusability. There are a lots of Metrics available for quantitative measure of readabilities of any of the application which is developed using object oriented paradigm. The goals of software metrics are to identify and control essential parameters that affect the parameters related to software development. There are various types of measurements which are required in software development including size of the project, complexities involved, measurement of cohesion and coupling among modules, testability, reusability, effort and resources required etc. This paper presents a practical calculation on some of the reusability metrics which can be used for object oriented applications
Performance evaluation of the explicit approximations of the implict colebroo...eSAT Journals
Abstract
The implicit Colebrook equation has been the standard for estimating pipe friction factor in a fully developed turbulent regime. Several artificial intelligence (AI)-based and non AI-based explicit models have been developed as viable replacement for the implicit Colebrook equation. However, it is not obvious which of the models and/or approaches is the best. In this paper, the performances of the available non AI-based explicit models were compared with those of the AI-based models. The results show that genetic algorithm has been successfully utilized in optimizing the explicit model parameters with the best improvements being from 0.12% to 0.0026% based on maximum relative error index. Although genetic programming and gene expression programming techniques offer the advantage of producing explicit analytical formulas for determination of output parameters, they are found to be grossly inaccurate with errors up to 7% for most accurate model developed. Artificial neural network, a prominent AI-based method has been used to significantly improve friction factor predictions with a high accuracy of 0.004% equivalent to that obtainable with the non-AI based models. The most accurate models are among those developed using the non AI -based techniques with errors up to 1.04 ×10-1 0 %. There is still possibility of improving on the gains made using the artificial intelligence techniques.
Modeling Delay Percentage of Construction Projects in Egypt Using Statistical...IOSR Journals
This paper presents two models for predicting the delay percentage in construction projects in Egypt.
The first model based on regression analysis. 74 causes that lead to delay in construction projects gathered
from literature. A questionnaire survey was made on construction contractors of construction projects in Egypt
to evaluate the relative importance of these causes. 14 causes were obtained as the most significant causes that
affect the delay percentage (DP) and these are the independent variables of the proposed model. Data for the
occurrence of the previous causes on a yes/no basis and the corresponding DP (dependent variable) for 20
construction projects was collected. The data was divided into two sets, the first set contains projects for the
purpose of model building. The results revealed that there was a strong linear relationship between DP and 9
causes from 14 causes that significantly affect DP of projects. These causes are: difficulties in obtaining work
permits from authorities concerned, original contract duration too short, inflation, difficulties in financing the
project by the contractor, effect of subsurface conditions, changes in the scope of the project, economic
conditions, excessive bureaucracy in the owner administration, and inefficient coordination by the owner in the
early planning &design stages. The second set contains 8 projects for the validation purposes and comparison
with the second model. The second model is a statistical fuzzy approach which is a hybrid approach from fuzzy
logic and regression analysis. A regression equation between each cause and DP using projects of first set was
extracted. The relative weight of each cause is determined by its coefficient of determination (R2
) value. The
degree of severity each cause had received from questionnaire analysis was used to fuzzify this cause. A
trapezoidal membership function was used to represent the delay percentages in construction projects in
general depending on 18 out of 30 the previous 20 projects. Two projects were excluded from this function due
to their divergence values from other projects. Thus, the expected delay percentage of a project is then
determined using fuzzy rules. Validation of the two models using projects of the second set revealed that
regression model has prediction capabilities higher than that of statistical fuzzy model. The average percentage
error for regression model was 30.3, against 38.5 for statistical fuzzy model.
The electrical power system in offshore oil & gas installation, consists of a large
distribution network, generally operating in island mode i.e., without grid support. For a compact
utility plate form design, multiple gas turbine-generators without generator transformers, feed
directly to 11kV switchgear. Such a configuration however, introduces high capacitive charging
current (Ico), which is more than the preferred high resistance grounding of generator neutral
through 10A, 10sec resistor, to safeguard the generator core from damage during an earth fault.
Therefore, some utility prefers to select low resistance grounding to limit the fault current above
Ico; however this can cause severe damage to generator core. Generally, oil & gas installation is a
customized design. So, earthing scheme of 11kV generating utility system should be selected
judiciously at basic engineering stage to avoid equipment damage and protection mal-operation
during operation. Different methods of earthing scheme are available to mitigate the same. One of
the method is presented here in which generator neutral is connected to high resistance grounding
and 11kV switchgear connected to low resistance grounding though zig-zag transformer, subject to
single grounding operation at a time. Prior to synchronization or under complete load throw
scenario, generator circuit breaker is opened. So, an earth fault in generator or evacuation system,
create over-voltage or ferro-resonance conditions, stressing insulation of generator and associated
system. This is mitigated by putting neutral earthing resistor into service at generator neutral. This
paper presents the experience learned in designing neutral earthing scheme for off-shore utility
plant in view of high capacitive charging current at 11kV voltage level, outlines impact on stator
core damage, mitigation and conclusion
Despite of many advances in design of complex software development there remains the
problem of highly inadequately specifying the requirements form the stakeholders for any real time
application
In this study an attempt is made to develop SCC mixes of different Strengths by using
various ranges of cement, Metakaolin and Fly ash with appropriate quantity of Super
plasticizer. A total of 11 (eleven) mixes has been prepared by this research. This chapter is mainly
focused on the cost analysis of the designed SCC mixes and Normal Vibrating Concrete (NVC)
mixes. The number of skilled labour, vibrator operators and the number of defects can drastically be
reduced, owing to user-friendly characteristics of SCC. The time, cost and quality are the three
important factors which assume significance in construction due to their impact on the industry as a
whole. Any development which has a positive impact on these factors is always in the interest of
civil engineering. As SCC requires a higher volume of fines replacement of cement content by
mineral admixtures like fly ash which increases the viscosity and workability of fresh concrete and
reduces the cost of SCC
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.
Enhancement of student performance prediction using modified K-nearest neighborTELKOMNIKA JOURNAL
The traditional K-nearest neighbor (KNN) algorithm uses an exhaustive search for a complete training set to predict a single test sample. This procedure can slow down the system to consume more time for huge datasets. The selection of classes for a new sample depends on a simple majority voting system that does not reflect the various significance of different samples (i.e. ignoring the similarities among samples). It also leads to a misclassification problem due to the occurrence of a double majority class. In reference to the above-mentioned issues, this work adopts a combination of moment descriptor and KNN to optimize the sample selection. This is done based on the fact that classifying the training samples before the searching actually takes place can speed up and improve the predictive performance of the nearest neighbor. The proposed method can be called as fast KNN (FKNN). The experimental results show that the proposed FKNN method decreases original KNN consuming time within a range of (75.4%) to (90.25%), and improve the classification accuracy percentage in the range from (20%) to (36.3%) utilizing three types of student datasets to predict whether the student can pass or fail the exam automatically.
A fuzzy approach to evaluate suitability of infrastructure projects with safetyeSAT Journals
Abstract
The current project deals with safety management in highways and infrastructure (Buildings and Roads).The research is partly doctrinal and partly empirical in natural. Research tools used is fuzzy logic. The scope research has been to mainly cover highways and infrastructure (Buildings and Roads).The topic of construction includes the process of Highways, Building and society roads, construction and maintenance, including the design of respective construction, contracting, accomplishing, supervision, and maintenance of Highways, Building, society roads and related structures. Our study of project will fulfil the safety requirements by using Fuzzy logic that should be consider before starting highways and infrastructure (Buildings and Roads) and this study will be very helpful in construction industry. as this study will decrease the chances of accidents as well as to save lives. Today so many people lose their lives when traffic has to move through maintenance works and road construction every year also during the construction of Buildings. The cases of construction section injuries and accidental death are predicted to go even higher than now. Construction in highways and infrastructure (Building and Roads) covers various activities, techniques, materials and source of danger therefore because of this conditions the probability of accidents increases every time. The fact is construction industry has the most disappointing record of safety compare to all industrial sectors, with a risk of casualty 5 times higher than several other industry in the world. The higher rate of accidents and deaths in the construction industry compare to all other industries are may be due to the process of the construction work. The factors due to which the rate of accidents are high in construction industry are such as poor planning, lack of safety training, lack of supervision, lack of safety equipment , and lack of incident investigation helps to create more problems in future. Hence, by using Multi criteria decision making by Fuzzy logic will reduce the risk of accidents while construction of highways and infrastructure (Building and Roads).
Keywords: Highway and Infrastructure Safety, Defuzzification, Fuzzy Multi Criteria Decision Making, Expert Opinion, Linguistic Terms and Safety Potential Index
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Calculation of Reusability Matrices for Object Oriented applicationsIJMERJOURNAL
ABSTRACT: Reusability is one of the major concerns of object oriented applications. Object oriented paradigm is having its own various advantages including reusability. There are a lots of Metrics available for quantitative measure of readabilities of any of the application which is developed using object oriented paradigm. The goals of software metrics are to identify and control essential parameters that affect the parameters related to software development. There are various types of measurements which are required in software development including size of the project, complexities involved, measurement of cohesion and coupling among modules, testability, reusability, effort and resources required etc. This paper presents a practical calculation on some of the reusability metrics which can be used for object oriented applications
Performance evaluation of the explicit approximations of the implict colebroo...eSAT Journals
Abstract
The implicit Colebrook equation has been the standard for estimating pipe friction factor in a fully developed turbulent regime. Several artificial intelligence (AI)-based and non AI-based explicit models have been developed as viable replacement for the implicit Colebrook equation. However, it is not obvious which of the models and/or approaches is the best. In this paper, the performances of the available non AI-based explicit models were compared with those of the AI-based models. The results show that genetic algorithm has been successfully utilized in optimizing the explicit model parameters with the best improvements being from 0.12% to 0.0026% based on maximum relative error index. Although genetic programming and gene expression programming techniques offer the advantage of producing explicit analytical formulas for determination of output parameters, they are found to be grossly inaccurate with errors up to 7% for most accurate model developed. Artificial neural network, a prominent AI-based method has been used to significantly improve friction factor predictions with a high accuracy of 0.004% equivalent to that obtainable with the non-AI based models. The most accurate models are among those developed using the non AI -based techniques with errors up to 1.04 ×10-1 0 %. There is still possibility of improving on the gains made using the artificial intelligence techniques.
Modeling Delay Percentage of Construction Projects in Egypt Using Statistical...IOSR Journals
This paper presents two models for predicting the delay percentage in construction projects in Egypt.
The first model based on regression analysis. 74 causes that lead to delay in construction projects gathered
from literature. A questionnaire survey was made on construction contractors of construction projects in Egypt
to evaluate the relative importance of these causes. 14 causes were obtained as the most significant causes that
affect the delay percentage (DP) and these are the independent variables of the proposed model. Data for the
occurrence of the previous causes on a yes/no basis and the corresponding DP (dependent variable) for 20
construction projects was collected. The data was divided into two sets, the first set contains projects for the
purpose of model building. The results revealed that there was a strong linear relationship between DP and 9
causes from 14 causes that significantly affect DP of projects. These causes are: difficulties in obtaining work
permits from authorities concerned, original contract duration too short, inflation, difficulties in financing the
project by the contractor, effect of subsurface conditions, changes in the scope of the project, economic
conditions, excessive bureaucracy in the owner administration, and inefficient coordination by the owner in the
early planning &design stages. The second set contains 8 projects for the validation purposes and comparison
with the second model. The second model is a statistical fuzzy approach which is a hybrid approach from fuzzy
logic and regression analysis. A regression equation between each cause and DP using projects of first set was
extracted. The relative weight of each cause is determined by its coefficient of determination (R2
) value. The
degree of severity each cause had received from questionnaire analysis was used to fuzzify this cause. A
trapezoidal membership function was used to represent the delay percentages in construction projects in
general depending on 18 out of 30 the previous 20 projects. Two projects were excluded from this function due
to their divergence values from other projects. Thus, the expected delay percentage of a project is then
determined using fuzzy rules. Validation of the two models using projects of the second set revealed that
regression model has prediction capabilities higher than that of statistical fuzzy model. The average percentage
error for regression model was 30.3, against 38.5 for statistical fuzzy model.
The electrical power system in offshore oil & gas installation, consists of a large
distribution network, generally operating in island mode i.e., without grid support. For a compact
utility plate form design, multiple gas turbine-generators without generator transformers, feed
directly to 11kV switchgear. Such a configuration however, introduces high capacitive charging
current (Ico), which is more than the preferred high resistance grounding of generator neutral
through 10A, 10sec resistor, to safeguard the generator core from damage during an earth fault.
Therefore, some utility prefers to select low resistance grounding to limit the fault current above
Ico; however this can cause severe damage to generator core. Generally, oil & gas installation is a
customized design. So, earthing scheme of 11kV generating utility system should be selected
judiciously at basic engineering stage to avoid equipment damage and protection mal-operation
during operation. Different methods of earthing scheme are available to mitigate the same. One of
the method is presented here in which generator neutral is connected to high resistance grounding
and 11kV switchgear connected to low resistance grounding though zig-zag transformer, subject to
single grounding operation at a time. Prior to synchronization or under complete load throw
scenario, generator circuit breaker is opened. So, an earth fault in generator or evacuation system,
create over-voltage or ferro-resonance conditions, stressing insulation of generator and associated
system. This is mitigated by putting neutral earthing resistor into service at generator neutral. This
paper presents the experience learned in designing neutral earthing scheme for off-shore utility
plant in view of high capacitive charging current at 11kV voltage level, outlines impact on stator
core damage, mitigation and conclusion
Despite of many advances in design of complex software development there remains the
problem of highly inadequately specifying the requirements form the stakeholders for any real time
application
In this study an attempt is made to develop SCC mixes of different Strengths by using
various ranges of cement, Metakaolin and Fly ash with appropriate quantity of Super
plasticizer. A total of 11 (eleven) mixes has been prepared by this research. This chapter is mainly
focused on the cost analysis of the designed SCC mixes and Normal Vibrating Concrete (NVC)
mixes. The number of skilled labour, vibrator operators and the number of defects can drastically be
reduced, owing to user-friendly characteristics of SCC. The time, cost and quality are the three
important factors which assume significance in construction due to their impact on the industry as a
whole. Any development which has a positive impact on these factors is always in the interest of
civil engineering. As SCC requires a higher volume of fines replacement of cement content by
mineral admixtures like fly ash which increases the viscosity and workability of fresh concrete and
reduces the cost of SCC
Articulated Wheeled Vehicles (AWVs) are a class of wheeled locomotion systems where the
chassis is connected to a set of ground-contact wheels via actively- or passively-controlled
articulations, which can regulate wheel placement with respect to chassis during locomotion. In this
paper the design, development and integration of vibration isolated mobile trailer platform,
customized to meet the user’s requirements in general and optical requirements in particular is
discussed. The study also focusses on performance requirements, system requirements and technical
details of the articulated vehicle system
As water can neither be created nor destroyed, more than 80% of quantity of water used for
domestic purposes appear as wastewater. Increasing water demand due to growing population
coupled with human related activities against the constant water resources solicits attention of the
water managers to think of wastewater as a source of water across the world. Wastewater deserves
recognition as a source of irrigation water in different countries around the world. India becomes
water stress with the per capita available water dropping down below 2000 cubic metre per head per
year. Uneven distribution of water resources from north to south makes water crisis severe in the
states like Tamil Nadu. Available water is shared by different sectors and stiff competition between
sector viz: drinking and irrigation prevails. In India, the total wastewater generation from the urban
towns has been assessed as 38474 MLD. It indicates its potential for reuse in water management.
Wastewater reuse has been in practice at selected locations around the world including India.
Guidelines, clearly explaining the health associated factors, have been developed and prescribed by
the EPA, US and WHO. Sewage treatment plants are installed to treat the sewage by the government
and effluent may be used for indirect and direct reuse purposes. The forecast of the wastewater
generation from Madurai City Corporation indicates the quantity of 162.8 MLD at 2014 and is likely
to be 338.7 MLD in the year 2044. The irrigation potential of wastewater reuse is assessed as 3000
ha with crops like groundnut, maize, millet etc during 2014 and about 6000 ha during 2044. Scope
for utilizing the existing minor irrigation tanks/ponds may be used for storage. Such tanks may also
be useful in polishing the water quality as a result of natural purification. Scope for groundwater
recharge through soil-aquifer treatment is also more.
In a symmetric cipher, both parties must use the same key for encryption and decryption.
This means that the encryption key must be shared between the two parties before any messages can
be decrypted. Symmetric systems are also known as shared secret systems or private key systems.
Symmetric ciphers are significantly faster than asymmetric ciphers, but the requirements for key
exchange make them difficult to use. In an asymmetric cipher, the encryption key and the decryption
keys are separate. In an asymmetric system, each person has two keys. One key, the public key, is
shared publicly. The second key, the private key, should never be shared with anyone.When you
send a message using asymmetric cryptography, you encrypt the message using the recipients public
key. The recipient then decrypts the message using his private key. That is why the system is called
asymmetric. Because asymmetric ciphers tend to be significantly more computationally intensive,
they are usually used in combination with symmetric ciphers to implement effect public key
cryptography. The asymmetric cipher is used to encrypt a session key and the encrypted session key
is then used to encrypt the actual message. This gives the key-exchange benefits of asymmetric
ciphers with the speed of symmetric ciphers.
AN ARTIFICIAL NEURAL NETWORK-BASED APPROACH COUPLED WITH TAGUCHI'S METHOD FOR...IAEME Publication
Nowadays, project duration prediction has become of crucial importance for managers since it points out the expectancy-life of project realization. To this end, the Neural Network-based approach coupled with the Taguchi method is used to predict the necessary time, which allows the fulfillment of the targeted project within the prescribed span without delay. Accordingly, the whole process for modeling the targeted problem is described, in which the modeling and simulation of the activities network are introduced for calculating the total average time of project. Then, the neural network approach is adopted to predict the total time for finishing the considered project within the deadlines, where the neural network’s input variables are composed of success probability, improvement and learning factors. While, the output variable is the total average project duration, which is the critical data during design phase. After that, the well-known Taguchi method is purposefully used to optimize the already obtained target by neural network. Finally, Simulation analysis through MATLAB are used to show the efficiency of the proposed approach regarding the workability of the approach when it comes to estimating the deadline of the targeted project.
A systematic mapping study of performance analysis and modelling of cloud sys...IJECEIAES
Cloud computing is a paradigm that uses utility-driven models in providing dynamic services to clients at all levels. Performance analysis and modelling is essential because of service level agreement guarantees. Studies on performance analysis and modelling are increasing in a productive manner on the cloud landscape on issues like virtual machines and data storage. The objective of this study is to conduct a systematic mapping study of performance analysis and modelling of cloud systems and applications. A systematic mapping study is useful in visualization and summarizing the research carried in an area of interest. The systematic study provided an overview of studies on this subject by using a structure, based on categorization. The results are presented in terms of research such as evaluation and solution, and contribution such as tools and method utilized. The results showed that there were more discussions on optimization in relation to tool, method and process with 6.42%, 14.29% and 7.62% respectively. In addition, analysis based on designs in terms of model had 14.29% and publication relating to optimization in terms of evaluation research had 9.77%, validation 7.52%, experience 3.01%, and solution 10.51%. Research gaps were identified and should motivate researchers in pursuing further research directions.
Time-Cost Trade-Off Analysis in a Construction Project Problem: Case Studyijceronline
In construction project, cost and time reduction is crucial in today’s competitive market respect. Cost and time along with quality of the project play vital role in construction project’s decision. Reduction in cost and time of projects has increased the demand of construction project in the recent years. Trade-off between different conflicting aspects of projects is one of the challenging problems often faced by construction companies. Time, cost and quality of project delivery are the important aspects of each project which lead researchers in developing time-cost trade-off model. These models are serving as important management tool for overcoming the limitation of critical path methods frequently used by company. The objective of time-cost trade-off analysis is to reduce the original project duration with possible least total cost. In this paper critical path method with a heuristic method is used to find out the crash durations and crash costs. A regression analysis is performed to identify the relationship between the times and costs in order to formulize an optimization problem model. The problem is then solved by Matlab program which yields a least cost of $60937 with duration 129.50 ≈130 days. Applying this approach, the result obtained is satisfactory, which is an indication of usefulness of this approach in construction project problems.
PREDICTION OF AVERAGE TOTAL PROJECT DURATION USING ARTIFICIAL NEURAL NETWORKS...IAEME Publication
The prediction of project‘s expectancy life is an important issue for entrepreneurs since it helps them to avoid the expiration time of projects. To properly address this issue, Neural Network-based approach, fuzzy logic and regression methods are used to predict the necessary time that can be consumed to put an end to the targeted project. Before applying the three aforementioned approaches, the modeling and simulation of the activities network are introduced for calculating the total average time of project. Then, comparatively speaking, the neural network, fuzzy logic and regression method approach are compared in terms prediction’s accuracy. The generated error from the three methods is compared, namely different types of errors are calculated. Basically, the input variables consist of the probability of success (PS), the coefficient of improvement (Coef_PS) and the coefficient of learning (CofA), while the output variable is the average total duration of the project (DTTm). The Predicted mean square error (MSE) values are purposefully used to compare the three models. Interestingly, the results show that the optimum prediction model is the fuzzy logic model with accurate results. It is noteworthy to say that the application in this paper can be applied on a real case study.
In the present paper, applicability and
capability of A.I techniques for effort estimation prediction has
been investigated. It is seen that neuro fuzzy models are very
robust, characterized by fast computation, capable of handling
the distorted data. Due to the presence of data non-linearity, it is
an efficient quantitative tool to predict effort estimation. The one
hidden layer network has been developed named as OHLANFIS
using MATLAB simulation environment.
Here the initial parameters of the OHLANFIS are
identified using the subtractive clustering method. Parameters of
the Gaussian membership function are optimally determined
using the hybrid learning algorithm. From the analysis it is seen
that the Effort Estimation prediction model developed using
OHLANFIS technique has been able to perform well over normal
ANFIS Model.
Conceptual Cost Estimate of Libyan Highway Projects Using Artificial Neural N...IJERA Editor
It is well known that decisions at early stages of a construction project have great impact on subsequent project performance. Conceptual cost estimate is a challenging task that is done with limited information at the early stages of a project life where many factors affecting the project costs are still unknown. The objective of this paper is to support decision makers in predicting the conceptual cost of highway construction projects in Libya. Initially, the factors that significantly influence highway construction are identified. Then, an artificial neural network model is developed for predicting the cost. The network is trained and tested with a total of 67 projects historical data. Training of the model is administered via back-propagation algorithm. The model is coded ad implemented using MATLAB® to facilitate its use. An optimization module is also added to the Neural Network model with the objective of minimizing the error of the predicted cost. The model is then validated and the results show better predictions of conceptual cost of highway projects in Libya.
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.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
11. Where: A = actual value, E = estimated or predicted value, n = total number of cases (6 for
validation).
2. Root Mean Squared Error:
!$
#
3. Mean Absolute Percentage Error:
%
#
$
4. Average accuracy percentage (AA %) [9]:
AA% = 100% -MAPE
5. The Coefficient of Determination (R2)
6. The Coefficient of Correlation (R).
The results of these statistical parameters are shown in table (6).
Table (6): Statistical Measures Results
Description Statistical parameters
MPE 0.23%
RMSE 0.12
MAPE 0.014%
AA% 99.98%
R2 83 %
R 91%
To assess the validity of the derived equation of the ANN model in predicting the final cost
of a school project (FC), the natural logarithm (Ln) of predicted values of (FC) are plotted against the
natural logarithm (Ln) of measured (observed) values for validation data set as shown in fig. (4). It is
clear from this figure that the resulted ANN has a generalization capability for any data set used
within the range of data used in the training phase. It is a proven fact that neural nets have a strong