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Keyword: MACA Support Vector Machine Based Technique for Fault Detection in A Power Distribution Integrated System with Renewable Energy Distributed Generation
The integration of renewable energy distributed generation (REDG) into the energized distribution power grid has become more popular in recent years. This has been escalated by the general global energy shortages. The REDG has proven to be effective for energy sustainability and reliability. However, there are technical challenges which arise from integrating REDG into the…
Read MoreOptimization of the Procedures for Checking the Functionality of the Greek Railways: Data Mining and Machine Learning Approach to Predict Passenger Train Immobilization
Information is the driving force of businesses because it can ensure the ability of knowledge and prediction. The railway industry produces a huge volume of data, with the proper processing of them and the use of innovative technology, there is the possibility of beneficial information to be provided which constitute the deciding factor for the…
Read MoreFraud Detection Call Detail Record Using Machine Learning in Telecommunications Company
Fraud calls have a serious impact on telecommunications operator revenues. Fraud detection is very important because service providers can feel a significant loss of income. We conducted a fraud research case study on one of the operators that experienced fraud in 2009 and 2018. Call Detail Record (CDR) containing records of customer conversations such as…
Read MoreEfficient Discretization Approaches for Machine Learning Techniques to Improve Disease Classification on Gut Microbiome Composition Data
The human gut environment can contain hundreds to thousands bacterial species which are proven that they are associated with various diseases. Although Machine learning has been supporting and developing metagenomic researches to obtain great achievements in personalized medicine approaches to improve human health, we still face overfitting issues in Bioinformatics tasks related to metagenomic data…
Read MoreMachine Learning Model to Identify the Optimum Database Query Execution Platform on GPU Assisted Database
With the current amount of data nowadays, the need for processing power has vastly grown. By relying on CPU processing power, current processing power is depending on the frequency and parallelism of the current CPU device. This means this method will lead to increased power consumption. Current research has shown that by utilize the power…
Read MoreIntrusion Detection in Cyber Security: Role of Machine Learning and Data Mining in Cyber Security
In recent years, cyber security has been received interest from several research communities with respect to Intrusion Detection System (IDS). Cyber security is “a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc.” An IDS is a software…
Read MoreClassification Model of Contact Center Customers Emails Using Machine Learning
E-mail is one of the media services used at the contact center. The challenge faced by e-mail services is how to handle e-mails that enter large quantities every day efficiently to provide fast and appropriate service to customers. The purpose of this study is to find which method has the best accuracy in classifying emails…
Read MoreSensor Based on-the-go Detection of Macro Nutrients for Agricultural Crops
Agriculture, being the vital sector, contributes to India’s GDP by 18%. It is necessary to enhance the production in this sector with minimal need of resources to get the good yield of crops. It in turn boosts up the necessity of automation in the field of agriculture. This paper discusses about the experimental study which…
Read MoreOptimization of the Electrical Discharge Machining of Powdered Metallurgical High-Speed Steel Alloy using Genetic Algorithms
Through the Electrical Discharge Machining, the temperature is very high, which can lead to the material phase’s transformation and affects material properties, which can lead to failure of the products in the industry. This study aims to investigate the effect of a new input parameter (pulse cycle time Tc), with other parameters on the EDM…
Read MoreQuranic Reciter Recognition: A Machine Learning Approach
Recitation and listening of the Holy Quran with Tajweed is an essential activity as a Muslim and is a part of the faith. In this article, we use a machine learning approach for the Quran Reciter recognition. We use the database of Twelve Qari who recites the last Ten Surah of Quran. The twelve Qari…
Read MoreEstimating Academic results from Trainees’ Activities in Programming Exercises Using Four Types of Machine Learning
Predicting trainees’ final academic results in the early stage of programming class is a significant mission in the field of learning analytics. Performing exercises in programming class is hard and it takes a lot of time for trainees. For this reason, careful support with trainees are offered in many classes through classroom assistants (CAs). Even…
Read MoreAn Investigative Study on Technology Impact on the Quality of Working Life in a University Healthcare and Pharmacy
The purpose of this study was to investigate the impact of the implementation of the Online Appointment Scheduling system and Pharm Partner system technologies on the quality of working life for users in a small healthcare environment at the University of Technology, Jamaica. Both qualitative and quantitative methods were employed. Two data collection instruments were:…
Read MoreEffects of Using Fuzzy Material Handling Inputs in the Genetic Algorithm for Machine Layout
This study introduces the implementation of fuzzy set theory to solve machine layout design issues, in order to handle vague information, using a genetic algorithm with tournament selection as the selection operator. The material handling inputs, including frequency and volume of materials that move between machines, were the parameters regarded as fuzzy numbers. The experimental…
Read MoreA Support Vector Machine Cost Function in Simulated Annealing for Network Intrusion Detection
This paper proposes a computationally intelligent algorithm for extracting relevant features from a training set. An optimal subset of features is extracted from training examples of network intrusion datasets. The Support Vector Machine (SVM) algorithm is used as the cost function within the thermal equilibrium loop of the Simulated Annealing (SA) algorithm. The proposed fusion…
Read MoreAssessment of Coordinated Multipoint Transmission Modes for Indoor and Outdoor Users at 28 GHz in Urban Macrocellular Environment
The aim of this article is to analyze and evaluate the performance of Coordinated Multipoint (CoMP) transmission approach at a frequency of 28 GHz using three dimensional ray tracing simulations in an urban macrocellular environment. The new performance metric introduced in this article is the relative power usage. Other performance metrics examined in this article…
Read MoreAnalysis of Garri Frying Machine Manufacturing in Nigeria: Design Innovation
Production of garri (edible processed and granulated form of cassava) and sustaining the production process has become so laborious, time consuming, and predisposes one to some form of danger, especially as it concerns the hot fire that one is disposed to during the process. In west African tradition, where this garri serves as one of…
Read MoreMachine Learning Applied to GRBAS Voice Quality Assessment
Voice problems are routinely assessed in hospital voice clinics by speech and language therapists (SLTs) who are highly skilled in making audio-perceptual evaluations of voice quality. The evaluations are often presented numerically in the form of five-dimensional ‘GRBAS’ scores. Computerised voice quality assessment may be carried out using digital signal processing (DSP) techniques which process…
Read MoreA Comparative Study of a Hybrid Ant Colony Algorithm MMACS for the Strongly Correlated Knapsack Problem
Metaheuristic hybridization has recently been widely studied and discussed in many research works as it allows benefiting from the strengths of metaheuristics by combining adequately the different algorithms. MMACS is a new hybrid ant colony optimization algorithm based on the foraging behavior of ants. This algorithm presents two hybridization levels. The first hybridization consists in…
Read MoreEmotional Impact of Suicide on Active Witnesses: Predicting with Machine Learning
Predicting the impact of suicide on incidental witnesses at an early stage helps to avert the possible side effect. When suicide is committed in public, incidental observers are left to grapple with it. In many cases, these incidental witnesses tend to experience the emotional side effect with time. In this study, we employed a Machine…
Read MoreAn Electroencephalogram Analysis Method to Detect Preference Patterns Using Gray Association Degrees and Support Vector Machines
This paper introduces an electroencephalogram (EEG) analysis method to detect preferences for particular sounds. Our study aims to create novel brain–computer interfaces (BMIs) to control human mental (NBMICM), which are used to detect human mental conditions i.e., preferences, thinking, and consciousness, choose stimuli to control these mental conditions, and evaluate these choices. It is important…
Read MoreA Machine Learning Framework Using Distinctive Feature Extraction for Hand Gesture Recognition
There are more than 7billion people in the world where there are around 500 million people in the world who are denied from normal lifestyle due to physical and mental issue. It is completely fair to say that every person deserves to enjoy a normal lifestyle. While physically and mentally challenged people find suitable way…
Read MoreDirect Torque Control of Multiphase Doubly Converter-fed Asynchronous Machines Incorporating the Harmonic Torques
Doubly fed asynchronous machines have an outstanding property: they can be operated up to twice rated speed delivering full rated torque. This paper presents, for the first time in the literature, a control system for multiphase asynchronous machines fed by Voltage Source Inverters (VSIs) both in stator and rotor that incorporates the harmonic torques. The…
Read MorePredicting Smoking Status Using Machine Learning Algorithms and Statistical Analysis
Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting…
Read MoreHardware Acceleration on Cloud Services: The use of Restricted Boltzmann Machines on Handwritten Digits Recognition
Cloud computing allows users and enterprises to process their data in high performance servers, thus reducing the need for advanced hardware at the client side. Although local processing is viable in many cases, collecting data from multiple clients and processing them in a server gives the best possible performance in terms of processing rate. In…
Read MoreImproving System Reliability Assessment of Safety-Critical Systems using Machine Learning Optimization Techniques
Quality assurance of modern-day safety-critical systems is continually facing new challenges with the increase in both the level of functionality they provide and their degree of interaction with their environment. We propose a novel selection method for black-box regression testing on the basis of machine learning techniques for increasing testing efficiency. Risk-aware selection decisions are…
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