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Keyword: AlgorithmsA Review on Autonomous Mobile Robot Path Planning Algorithms
The emerging trend of modern industry automation requires intelligence to be embedded into mobile robot for ensuring optimal or near-optimal solutions to execute certain task. This yield to a lot of improvement and suggestions in many areas related to mobile robot such as path planning. The purpose of this paper is to review the mobile…
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 MoreEye Feature Extraction with Calibration Model using Viola-Jones and Neural Network Algorithms
This paper presents the setup of eye tracking calibration methodology and the preliminary test results of the training model from the eye tracking data. Eye tracking requires good accuracy from the calibration process of the human eyes feature extraction from facial region. Viola-Jones algorithm is applied for this purpose by using Haar Basic feature filters…
Read MoreMulti Biometric Thermal Face Recognition Using FWT and LDA Feature Extraction Methods with RBM DBN and FFNN Classifier Algorithms
Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…
Read MoreImprove the Accuracy of Short-Term Forecasting Algorithms by Standardized Load Profile and Support Regression Vector: Case study Vietnam
Short-term load forecasting (STLF) plays an important role in building business strategies, ensuring reliability and safe operation for any electrical system. There are many different methods, including: regression models, time series, neural networks, expert systems, fuzzy logic, machine learning and statistical algorithms used for short-term forecasts. However, the practical requirement is how to minimize the…
Read MoreApplication of Fractal Algorithms to Identify Cardiovascular Diseases in ECG Signals
The aim of this article was the identification of cardiovascular diseases, after applying Katz and Higuchi fractal algorithms on 4 databases of ECG signals downloaded from the Physionet website: heart failure (HF), hypertension (H), ischemic heart disease (IHD) and normal sinus rhythm (NSR). For this purpose, initially the ECG signals passed through a filtering stage…
Read MoreSimulation-Optimisation of a Granularity Controlled Consumer Supply Network Using Genetic Algorithms
The decision support systems regarding the Supply Chains (SCs) management services can be significantly improved if an effective viable method is utilised. This paper presents a robust simulation optimisation approach (SOA) for the design and analysis of a granularity controlled and complex system known as Consumer Supply Network (CSN) incorporating uncertain demand and capacity. Minimising…
Read MoreAn enhanced Biometric-based Face Recognition System using Genetic and CRO Algorithms
Face recognition is one of the most well-known biometric methods. It is a technique used for identifying individual from his face. The recognition process takes the face and compares it with the one stored in the database for recognizing it. Many methods were proposed to achieve that. In this paper, a new technique is proposed…
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 MoreAlgorithms for Technical Integration of Virtual Power Plants into German System Operation
This paper critically evaluates the operational perspective of Virtual Power Plants (VPP) in Germany by analyzing key factors to replace conventional power plants in the future power system. Therefore, its necessity for the secure operation as well as the technical and economic benefits for the German power system are pointed out. The single sections describe…
Read MoreComparison of K-Means and Fuzzy C-Means Algorithms on Simplification of 3D Point Cloud Based on Entropy Estimation
In this article we will present a method simplifying 3D point clouds. This method is based on the Shannon entropy. This technique of simplification is a hybrid technique where we use the notion of clustering and iterative computation. In this paper, our main objective is to apply our method on different clouds of 3D points.…
Read MoreAdapting Model Predictive Control for a PV Station and Evaluating two different MPPT Algorithms P&O and FLC
In this paper first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for…
Read MoreCIRB-Edge for Secure, Energy-Efficient, and Real-Time Edge Computing
In this work, we present CIRB-Edge, a novel integer compression method designed specifically to overcome the limitations of traditional techniques such as Huffman coding, Delta encoding, and dictionary-based algorithms. These legacy methods often fall short in meeting the stringent requirements of secure, energy-efficient, and real-time edge computing due to their high computational overhead, memory demands,…
Read MoreHardware and Secure Implementation of Enhanced ZUC Steam Cipher Based on Chaotic Dynamic S-Box
Despite the development of the Internet and wired networks such as fiber optics, mobile networks remain the most used thanks to the mobility they offer to the user. However, data protection in these networks is more complex because of the radio channels they use for transmission. Hence,there is a need to find more sophisticated data…
Read MoreAdvancements in Explainable Artificial Intelligence for Enhanced Transparency and Interpretability across Business Applications
This manuscript offers an in-depth analysis of Explainable Artificial Intelligence (XAI), em- phasizing its crucial role in developing transparent and ethically compliant AI systems. It traces AI’s evolution from basic algorithms to complex systems capable of autonomous de- cisions with self-explanation. The paper distinguishes between explainability—making AI decision processes understandable to humans—and interpretability, which provides…
Read MoreOn Mining Most Popular Packages
In this paper, we will discuss two algorithms to solve the so-called package design problem, by which a set of queries (referred to as a query log) is represented by a collection of bit strings with each indicating the favourite activities or items of customers. For such a query log, we are required to design…
Read MoreDeploying Trusted and Immutable Predictive Models on a Public Blockchain Network
Machine learning-based predictive models often face challenges, particularly biases and a lack of trust in their predictions when deployed by individual agents. Establishing a robust deployment methodology that supports validating the accuracy and fairness of these models is a critical endeavor. In this paper, we introduce a novel approach to deploying predictive models, such as…
Read MoreAn Adaptive Heterogeneous Ensemble Learning Model for Credit Card Fraud Detection
The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…
Read MoreA Novel Metric for Evaluating the Stability of XAI Explanations
Automated systems are increasingly exerting influence on our lives, evident in scenarios like AI-driven candidate screening for jobs or loan applications. These scenarios often rely on eXplainable Artificial Intelligence (XAI) algorithms to meet legal requirements and provide understandable insights into critical processes. However, a significant challenge arises when some XAI methods lack determinism, resulting in…
Read MoreDevelopment and Usability Evaluation of Mobile Augmented Reality Contents for Railway Vehicle Maintenance Training: Air Compressor Case
The air compressor of a railroad vehicle is an important equipment that produces compressed air used in braking systems. New visual interaction techniques were proposed and evaluated to develop effective augmented reality content for maintenance support and training of this device. To this end, modeling techniques capable of fast animation, storyboard production to support light…
Read MoreAnalysis of Emotions and Movements of Asian and European Facial Expressions
The aim of this study is to develop an advanced framework that not only recognize the dominant facial emotion, but also contains modules for gesture recognition and text-to-speech recognition. Each module is meticulously designed and integrated into unified system. The implemented models have been revised, with the results presented through graphical representations, providing prevalent emotions…
Read MoreComparative Study of J48 Decision Tree and CART Algorithm for Liver Cancer Symptom Analysis Using Data from Carnegie Mellon University
Liver cancer is a major contributor to cancer-related mortality both in the United States and worldwide. A range of liver diseases, such as chronic liver disease, liver cirrhosis, hepatitis, and liver cancer, play a role in this statistic. Hepatitis, in particular, is the main culprit behind liver cancer. As a consequence, it is decisive to…
Read MoreMulti-Layered Machine Learning Model For Mining Learners Academic Performance
Different colleges and universities have different approaches to dealing with low-performance learners. However, in most cases, analgesics do not deal with root problems. This research suggests a model of three layers of variables sequentially adaptable to a deep-root issue. The suggested model can identify early pupils who could be at risk because of inaccurate or…
Read MoreMetaheuristic Optimization Algorithm Performance Comparison for Optimal Allocation of Static Synchronous Compensator
The relevance of static synchronous compensator (STATCOM) controllers in controlling power network parameters is causing them to be included in contemporary networks. But for the intended objectives to be attained, the best device positioning and parameter settings are essential. This work compares the performance of the particle swarm optimization (PSO) and firefly algorithm (FA) in…
Read MoreDesign, Optimization and Simulation of a New Decoder for Reed Solomon and BCH Codes using the New Syndromes Block
In this paper, a new syndrome block for Reed Solomon RS and BCH codes used respectively in digital Video broadcasting DVB-S and DVB-S2 has been presented in order to reduce the number of iterations compared to the existed block, which can be found in the literature, the new method is based on a factorization of…
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