The Effects of Chemical Hazards in Sustainable Development of Agriculture Using Fuzzy Associative Memories (FAM)
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The effect of innovative methods of teaching in education are needed today’s education system where the system is unfair in many ways like providing knowledge, judging the student and formation of a student. Little changes and effort will bring effective change in the life of the students and will not only learn the subject but also will learn some special skills needed for life. In this paper we analyze the effects of innovative methods of teaching in education using Fuzzy Associative Memories (FAM). We arrive at the conclusions by this study how the new methods will help in development of the education system. This paper has four sections. In section one we recall the notion of Fuzzy Associative Memories (FAM) and its properties. In section two we describe the problem. In Section three we adopt FAM to this problem and analyze the problem. Section four gives the conclusions based on our study.
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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.
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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.
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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.
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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.
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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.
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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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https://ashpc.eu/
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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。
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The cost of acquiring information by natural selection
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It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
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- 1. International Journal of Computing Algorithm, Vol 3(2), June 2014 ISSN(Print):2278-2397 Website: www.ijcoa.com The Effects of Chemical Hazards in Sustainable Development of Agriculture Using Fuzzy Associative Memories (FAM) J. Maria Roy Felix, V. Jerald Vivian Department of Mathematics, Loyola College, Chennai E-mail: vivian.jerald@gmail.com Abstract The effect of innovative methods of teaching in education are needed today’s education system where the system is unfair in many ways like providing knowledge, judging the student and formation of a student. Little changes and effort will bring effective change in the life of the students and will not only learn the subject but also will learn some special skills needed for life. In this paper we analyze the effects of innovative methods of teaching in education using Fuzzy Associative Memories (FAM). We arrive at the conclusions by this study how the new methods will help in development of the education system. This paper has four sections. In section one we recall the notion of Fuzzy Associative Memories (FAM) and its properties. In section two we describe the problem. In Section three we adopt FAM to this problem and analyze the problem. Section four gives the conclusions based on our study.