Rule Based Approach for Stock Selection: An Expert System
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This document summarizes a research paper that proposes a rule-based expert system for stock selection. The system would use artificial intelligence techniques to solve problems in the specialized domain of the stock market. It highlights the need for an expert system in stock markets to help show a country's economic growth. The paper presents a rule-based approach for the expert system to select particular stocks.
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This document provides an introduction to a book on innovation systems in Southeast Asia. It discusses the concept of national innovation systems and how it has influenced policymakers in the region. While the concept was initially developed by European researchers, it has since caught on in Asia. The document then summarizes some of the key findings from chapters in the book that analyze innovation systems in six Southeast Asian countries. Some common themes identified are that governments continue to play a leading role in developing innovation systems, policies still focus on linear models of innovation driven by public research, and efforts are being made to strengthen linkages between actors but with limited success so far. The introduction sets the stage for comparative analyses of national innovation systems in Southeast Asia.
A study on improvement activities for indian
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
Se toolkit v.1.2.6
This document introduces a systems engineering toolkit for infrastructure developed by the Centre for Systems Engineering and Innovation at Imperial College London. The toolkit provides an overview of systems engineering fundamentals and pointers to existing resources to aid in developing knowledge about systems engineering for infrastructure. It describes the origins and definitions of systems engineering, motivations for its application to infrastructure, and highlights some key tools and methods including process models, dependence modeling, modeling languages, flow representations, and mathematical analysis.
Similar to Rule Based Approach for Stock Selection: An Expert System (20)
Applications of Artificial Neural Network in Forecasting of Stock Market Index
Applications of Artificial Neural Network in Forecasting of Stock Market Index
Analysis and Comparative Study of the Development of Technology with Artifici...
Analysis and Comparative Study of the Development of Technology with Artifici...
Applications of Artificial Intelligence in Human Life
Applications of Artificial Intelligence in Human Life
A study on improvement activities for indian manufacturing industries
A study on improvement activities for indian manufacturing industries
Ranking of indian institutions contributing to computer
Ranking of indian institutions contributing to computer
SOCIAL MEDIA ANALYSIS ON SUPPLY CHAIN MANAGEMENT IN FOOD INDUSTRY
SOCIAL MEDIA ANALYSIS ON SUPPLY CHAIN MANAGEMENT IN FOOD INDUSTRY
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SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
OBJECTIVES: To determine how SPSS can be a useful tool to evaluate Course Learning Outcomes and analyze student's performance with the help of KS test, histogram and skewness of the tool. It is also contributing to facilitate Deep learning amongst students with the help of achievement of normal distribution of grades. METHODS: Comparative analysis is done using course specification, syllabus, assessment method(Final Exam Question paper is taken as tool) and result statistics for the course of STATISTICAL PROGRAMMING (217 CSM), 3rd year (level 5 course) that is part of BCS curriculum in department of Computer Science, College of computer Science in King Khalid University. Teaching strategies are compared for two years. i.e; 2013 and 2014. Moreover the research inferences the relevance of application of NCAAA standards in meeting Learning outcomes of any module for department of Computer Science, CCS, KKU. RESULTS: Comparison of question papers depict that now students are motivated to have deep learning in terms of understanding, solving, reasoning based questions as contrast to shallow learning (memorized questions) in the past. It is indeed improving Learning domains too (Knowledge, Cognitive, Interpersonal and Communication skills) more effectively than in the past. Also grade distribution is Normal with well-defined curve for 2014 as compared to 2013 having variation in Standard deviation too. Teacher centered learning lead to surface learning. After NCAA standards implementation, there is more focus on learned centered teaching. Design of learning assessments is in such a way that it should meet learning outcomes successfully. CONCLUSIONS: The research is contributing in flourishing the personality of the students to produce qualified graduates with excellence in communication, logically and technically capable enough to share their knowledge nationally and internationally with much more confidence at any platform. Also it is opening door for researchers to evaluate their performance with the help of SPSS in academics or anywhere where we want to gather.
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
Detection of software bugs and its occurrences, repudiation and its root cause is a very difficult process in large multi threaded applications. It is a must for a software developer or software organization to identify bugs in their applications and to remove or overcome them. The application should be protected from malfunctioning. Many of the compilers and Integrated Development Environments are effectively identifying errors and bugs in applications while running or compiling, but they fail in detecting actual cause for the bugs in the running applications. The developer has to reframe or recreate the package with the new one without bugs. It is time consuming and effort is wasted in Software Development Life Cycle. There is a possibility to use graph mining techniques in detecting software bugs. But there are many problems in using graph mining techniques. Managing large graph data, processing nodes with links and processing subgraphs are the problems to be faced in graph mining approach. This paper presents a novel algorithm named BugLoc which is capable of detecting bugs from the multi threaded software application. The BugLoc uses object template to store graph data which reduces graph management complexities. It also uses substring analysis method in detecting frequent subgraphs. The BugLoc then analyses frequent subgraphs to detect exact location of the software bugs. The experimental results show that the algorithm is very efficient, accurate and scalable for large graph dataset.
Motion Object Detection Using BGS Technique
The detection of moving object is an important in many applications such as a vehicle identification in a traffic monitoring system,human detection in a crime branch.In this paper we identify a vehicle in a video sequence.This paper briefly explain the detection of moving vehicle in a video.We introduce a new algorithm BGS for idntifying vehicle in a video sequence. First, we differentiate the foreground from background in frames by learning the background. Then, the image is divided into many small nonoverlapped frames. The candidates of the vehicle part can be found from the frames if there is some change in gray level between the current image and the background. The extracted background subtraction method is used in subsequent analysis to detect a vehicle and classify moving vehicle.
Analysis of Women Harassment in Villages Using CETD Matrix Modal
It is commonly understood that misbehavior intends to upset .Law says , the repeated intentional misbehavior towards women is an offensive. The main concept of this paper can find something interesting that will make us reflect on what is done by women’s rights and gender equality. To solve such problem, in this paper we are interested to adopt CETD matrix.
Solving Assignment Problem Using L-R Fuzzy Numbers
In this paper we determine a new method to solving assignment problem using L-R fuzzy parameters. This method requires finding out the minimal cost reach optimality compared to the existing methods available in the literature. Numerical examples show that the fuzzy assignment ranking method offers an effective way for handling the fuzzy assignment problem.
Fuzzy Chroamtic Number of Line Graph using α-Cuts
In this paper, we introduce chromatic number of line graph using α-cuts. The concept of chromatic number of fuzzy graphs was introduced by Munoz et.al, later Eslahchi and onagh. They are defined by the fuzzy chromatic number of complete graphs (kn), cycle graph (cn), star graph (sn), wheel graph (wn), and line graph are found and results are summarized.
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
In this paper, using a new Fuzzy bimodal called Induced Neutrosophic Cognitive Relational Maps (INCRM) we analyse the Socio-Economic problem faced by Rag-Pickers. Based on the study, conclusions and some remedial measures are stated.
Dual Trapezoidal Fuzzy Number and its Applications
In this Paper, we introduce Convergence of α-Cut. We define at Which point the α-Cut converges to the fuzzy numbers and it will be illustrated by example using dual trapezoidal fuzzy number and some mensuration problems are illustrated with approximated values.
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
This paper presents an implementation of one dimensional Burgers equation using implicit method with Intel Xeon Phi Coprocessor. In particular, we used MAGMA MIC library which is an open source high performance library for solving a systems of non-linear equations. Further for high performance computation we consider offload mode as the primary mode of operation for Intel Xeon phi coprocessor. The result obtained from implicit scheme is then compared with the exact values and it’s seen that the results obtained are approximate and reliable. The result table showed that the proposed scheme achieved higher performance on Intel MIC platform.
Saturation Index of π(D(r,s))
Adin and Roichman [1] introduced the concept of permutation graphs and Peter Keevash, Po-Shen Loh and Benny Sudakov [2] identified some permutation graphs with maximum number of edges. Ryuhei Uehara, Gabriel Valiente, discussed on Linear structure of Bipartite Permutation Graphs and the Longest Path Problem [3]. If i, j belongs to a permutation on p symbols {1, 2, …, p} and i is less than j then there is an edge between i and j in the permutation graph if i appears after j in the sequence of permutation. So the line of i crosses the line of j in the permutation. Hence there is a one to one correspondence between crossing of lines in the permutation and the edges of the corresponding permutation graph. In this paper we found the conditions for a permutation to realize a double star and comprehend the algorithm to determine the satuation index of the permutation. AMS Subject Classification (2010): 05C35, 05C69, 20B30.
Classification and Prediction of Heart Disease from Diabetes Patients using H...
The multi-factorial chronicle, severe disease among human is diabetes. As a result of abnormal level of glucose in body leads to heart attack, kidney disease, renal failure, Hyperglycemia and also cancer in organs like liver and pancreas. Many studies have been proved that several types of heart diseases are possible in diabetic patients having a high blood sugar. Many approaches were proposed to diagnose both Diabetes and heart diseases. Most of the diabetes people can also have heart diseases called as Diabetic Cardiomyopathy. The earliest manifestation of diabetic cardiomyopathy is needed certain processes. The objective of the study is to examine the association of heart disease and diabetes. The relationship between diabetes and cardiovascular diseases are examined by taking into account of age, sex and associated diabetic and cardiovascular risk factors. The data are collected from patients with diabetes. From these data, features are selected by ant colony optimization and those selected features are given to hybrid PSO-LIBSVM to classify abnormal and normal data. This performance is evaluated using performance metrics and proved this classifiers efficiency for detection of Diabetic Cardiomyopathy.
Format Preserving Encryption for Small Domain
Cryptography is important in communicating secured information that is vulnerable to distortion. The main goal of this paper is encrypting the small arbitrary length data without any changes in the length and data type. We propose a flexible arbitrary length small domain block cipher (FPESD). FPESD is based on AES Algorithm. The resulting cipher text is the same as input plaintext. Here, we use Galois finite field GF (28) and format preserving key to implement FPE. For decryption format preserving key is used along with cipher text and secret key.
Intuitionistic Double Layered Fuzzy Graph and its Cartesian Product Vertex De...
The intuitionistic double layered fuzzy graph gives a 3-D structural view to a fuzzy graph. To find the cartesian product of two intuitionistic double layered fuzzy graphsis a challenging one. In this paper under some condition,a simple method to find the vertex degree of cartesian product of two IDLFG without the cartesianproduct structure is given.
Clustering and Classification in Support of Climatology to mine Weather Data ...
Knowledge of climate data of region is essential for business, society, agriculture, pollution and energy applications. Climate is not fixed, the fluctuation in the climate can be seen from year to year.The data mining application help meteorological scientists to predictaccurate weather forecast and decisions and also provide more performance and reliability than any other methods. The data mining techniques applied on weather data are efficient when compare to the mathematical models used. Various techniques of data mining are applied on climate data to support weather forecasting, climate scientists, agriculture, vegetation, water resources and tourism. The aim of this paper is to provide a review report on various data mining techniques applied on weather data set in support of weather prediction and climate analysis.
Test Suite Reduction Based on Fault Detection with Cost Optimization
Test Suite Reduction is an optimization technique to identify the minimally sized subset of test cases with enforced constraints involved. The main purpose of test suite reduction is to deduce increased number of test cases that in turn increase the time and cost involved in execution. Fault Detection is the method of identifying the faults that affect the outcome of the system either logically or syntactically. This paper focuses on the reduction of the test suite that has high fault identification rates and also incurs low cost of execution of test cases. The proposed approach includes a new parameter Fault Detection Effectiveness to identify fault rates of test suite; an algorithm for test suite reduction based on priority of requirements; a low cost framework to identify the execution of test cases with minimum budget. Thus, the proposed work defines a test suite that has high fault detection effectiveness providing maximum coverage to requirements at minimum cost of execution.
Artifact Facet Ranking and It’s Applications
As the e-commerce is gaining popularity various customer surveys of objects are currently accessible on the Internet. These surveys are frequently disordered, prompting challenges in knowledge discovery and object assessment. This article proposes an object feature positioning skeleton, which consequently recognizes the critical features of an object from online customer surveys. The critical object features are recognized focused around two perceptions: 1) they are normally commented extensively by customers and 2) customer suppositions on the critical feature significantly impact their general assessments on the object. Specifically, given the customer surveys of an item, we first extract the object feature by a shallow reliance parser and focus customer suppositions on these features through an opinion characterizer. We then create a probabilistic object feature positioning calculation to identify the criticalness of perspectives by at the same time considering feature recurrence and the impact of customer opinion given to every feature over their general opinion. The experimental results on 3 popular products demonstrate the effectiveness of our approach.
Effectual Data Integrity Checking Technique Based on Number Theory
Cloud Computing makes data really mobile and a client can simply access a chosen cloud with any internet accessible device. The espousal and dispersion of Cloud computing are threatened by unresolved security issues that affect both the cloud provider and the cloud user. The integrity of data stored in the cloud is one of the challenges to be addressed before the novel storage model is applied widely. This paper analyses the efficiency issues and security dodge of an existing scheme and proposes an amended data integrity scheme using improved RSA and number theory based concept for cloud archive. This scheme of protecting the integrity of guest virtual machines can be agreed upon by both the cloud and the customer and can be incorporated in the service level agreement (SLA).Based onhypothetical analysis, we demonstrate that the proposedscheme has a provably safe and highly adroit dataintegrity inspection measure.
Micro-Neuro-Sensor Recording of STN Neurons of the Human Brain
What cause to the neurons of the human brain cells when they are damaged. They become inactive. So damage to subthalamiuc nucleus (STN) neurons of the human brain causing larger involuntary movements and thereby attacking the Parkinson’s disease (PD). Deep brain stimulation (DBS) of bilateral sub thalamic nuclei (STN) is an efficient method of rehabilitation technique in subjects with advanced idiopathic Parkinson’s (or Parkinson) disease. Accurate targeting of STN neurons and placement of microelectrodes/ (neurosensors) are paramount importance for optimal results after STN-DBS method.In this paper, microminiaturized electrode recordings (MER) of STN neurons were detected in a mean of 3.5 ±1.1 channels on right hemisphere and 3.6 ±1.04 on left hemisphere.Final channel selected were most commonly central seen in 42.3% followed by anterior in 33.7%. When a high current is delivered to STN or GPi neurons of basal ganglia (a component of human brain), causing their inhibition and improved indication of symptoms. It is now known that there is a significant change in the firing pattern and a reorganization of the entire basal ganglia circuit with DBS. The MER of STN neurons has identified a specific high frequency irregular larger amplitude firing patterns seen only in disease states and hence used to detect the neurons of ST nucleus during functional surgery. Microelectrode recording is so useful to confirm the right path but has to be taken in consideration with effects on macro stimulation.
EDM: Finding Answers to Reduce Dropout Rates in Schools
The focus of this paper is to get a bird's eye view of the various factors that could be analyzed to present schools and governments timely indicators of school dropouts. With the help of EDM, one could have access to enormous amounts of data. The crux of the matter would be to identify the data in line with plans and ideas that would eventually lead to the formulation of policies that enhance the teaching and learning process.
Analysis of Effort Estimation Model in Traditional and Agile (USING METRICS ...
Agile software development has been gaining popularity and replacing the traditional methods of developing software. However, estimating the size and effort in Agile software development still remains a challenge. Measurement practices in agile methods are more important than traditional methods, because lack of appropriate an effective measurement practices will increase the risk of project. This paper discuss about traditional and agile effort estimation model, and analysis done on how the metrics are used in estimation process. The paper also suggeststo use object point and use case point to improve accuracy of effort in agile software development.
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SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
Analysis of Women Harassment in Villages Using CETD Matrix Modal
Analysis of Women Harassment in Villages Using CETD Matrix Modal
Solving Assignment Problem Using L-R Fuzzy Numbers
Solving Assignment Problem Using L-R Fuzzy Numbers
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
Dual Trapezoidal Fuzzy Number and its Applications
Dual Trapezoidal Fuzzy Number and its Applications
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
Classification and Prediction of Heart Disease from Diabetes Patients using H...
Classification and Prediction of Heart Disease from Diabetes Patients using H...
Intuitionistic Double Layered Fuzzy Graph and its Cartesian Product Vertex De...
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Clustering and Classification in Support of Climatology to mine Weather Data ...
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Micro-Neuro-Sensor Recording of STN Neurons of the Human Brain
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EDM: Finding Answers to Reduce Dropout Rates in Schools
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Analysis of Effort Estimation Model in Traditional and Agile (USING METRICS ...
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Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
Authoring a personal GPT for your research and practice: How we created the Q...
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
Randomised Optimisation Algorithms in DAPHNE
Slides from talk:
Aleš Zamuda: Randomised Optimisation Algorithms in DAPHNE .
Austrian-Slovenian HPC Meeting 2024 – ASHPC24, Seeblickhotel Grundlsee in Austria, 10–13 June 2024
https://ashpc.eu/
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
原版纸张【微信：741003700 】【(uvic毕业证书)维多利亚大学毕业证】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
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留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
The binding of cosmological structures by massless topological defects
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
学校原件一模一样【微信：741003700 】《(salfor毕业证书)索尔福德大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
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留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/20240520 Planning a Circuit Simulator in JavaScript.pptx
Evaporation step counter work. I have done a physical experiment.
(Work in progress.)
Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityUniversity of Rennes, INSA Rennes, Inria/IRISA, CNRS
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Applied Science: Thermodynamics, Laws & Methodology.pdf
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Phenomics assisted breeding in crop improvement
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Compexometric titration/Chelatorphy titration/chelating titration
Classification
Metal ion ion indicators
Masking and demasking reagents
Estimation of Magnisium sulphate
Calcium gluconate
Complexometric Titration/ chelatometry titration/chelating titration, introduction, Types-
1.Direct Titration
2.Back Titration
3.Replacement Titration
4.Indirect Titration
Masking agent, Demasking agents
formation of complex
comparition between masking and demasking agents,
Indicators/Metal ion indicators/ Metallochromic indicators/pM indicators,
Visual Technique,PM indicators (metallochromic), Indicators of pH, Redox Indicators
Instrumental Techniques-Photometry
Potentiometry
Miscellaneous methods.
Complex titration with EDTA.
3D Hybrid PIC simulation of the plasma expansion (ISSS-14)
3D Particle-In-Cell (PIC) algorithm,
Plasma expansion in the dipole magnetic field.
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Applied Science: Thermodynamics, Laws & Methodology.pdf
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Rule Based Approach for Stock Selection: An Expert System
- 1. International Journal of Computing Algorithm, Vol 4(1), June 2015 ISSN(Print):2278-2397 Website: www.ijcoa.com Rule Based Approach for Stock Selection: An Expert System Sachin Kamley1 , R.S. Thakur2 , Shailesh Jaloree3 1 Deptt. of Comp. App.,S.A.T.I.,Vidisha (M.P.), India 2 Deptt. of Comp. App.,M.A.N.I.T.,Bhopal (M.P.), India 3 Deptt. of App.Math’s,S.A.T.I., Vidisha (M.P.) India Abstract Artificial Intelligence (AI) is one of most emerging field in the research field and has given boost to the most growing technology known as Expert System (ES). An ES is a computer based program that is built to solve the problems in specialized domain. There are various expert systems in diversified areas like medical, engineering, agriculture, science etc. have been developed over the last five decades. Stock market is also one of the most important growing areas which shows the country’s economic growth and also shows the need of expert system. This paper mainly highlights the need of expert system in stock market as well as rule based expert system approach for particular stock selection.