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Keyword: SinAnalytical Study on the Effect of Rotor Slot Skewing on the Parasitic Torques of the Squirrel Cage Induction Machine
Skewing of the rotor slot of a squirrel-cage induction machine has been commonly used since the beginning. However, little guidance is given regarding the principle of the working effect of the method, but even in such rare cases, the explanation does not cover the true physical reality. Consequently no formula exists for calculation of the…
Read MoreImpact of Integrating Chatbots into Digital Universities Platforms on the Interactions between the Learner and the Educational Content
The rapid expansion of digital universities across Africa addresses the need for scalable higher education solutions, but challenges such as limited physical infrastructure and high dropout rates persist. In digital learning environments, effective interaction with educational content is crucial for student success. This article explores the transformative role of chatbots integrated into digital university platforms,…
Read MoreEvaluation of Physicochemical Stability in Extemporaneous Omeprazole-Based Preparations
Extemporaneous omeprazole-based preparations are commonly used in hospitals; however, there are no validated studies about physicochemical stability. This study aimed to determine if temperature, luminosity, and the type of diluent affect the stability of omeprazole in the extemporaneous preparation. For stability, the methodology validated previously by our group was used. The 2k experimental design included…
Read MoreTrue Random Number Generator Implemented in ReRAM Crossbar Based on Static Stochasticity of ReRAMs
True Random Number Generators (TRNG) find applications in various fields, especially hardware security. We suggest a TRNG that exploits the intrinsic static stochasticity of Resistive Switching Random Access Memories (ReRAMs) to generate random bits. Other suggested designs use stochasticity in the switching mechanism, which requires high precision over input voltage and time. In the proposed…
Read MoreOn Adversarial Robustness of Quantized Neural Networks Against Direct Attacks
Deep Neural Networks (DNNs) prove to be susceptible to synthetically generated samples, so-called adversarial examples. Such adversarial examples aim at generating misclassifications by specifically optimizing input data for a matching perturbation. With the increasing use of deep learning on embedded devices and the resulting use of quantization techniques to compress deep neural networks, it is…
Read MoreDevelopment and Application of Value Karuta to Understand Value in Lean Management: Initial Small-group Trial in Japan and the UK
This study proposes the Value Karuta (VK), an application of the traditional Japanese card game karuta. Its goal is to contribute to the understanding of value, which is the first principle of lean management. After stating the problems of lean management and the specifications of VK, this paper confirms the validity of the proposal by…
Read MoreWeb Application Interface Data Collector for Issue Reporting
Insufficient information is often pointed out as one of the main problems with bug reports as most bugs are reported manually, they lack detailed information describing steps to reproduce the unexpected behavior, leading to increased time and effort for developers to reproduce and fix bugs. Current bug reporting systems lack support for self-hosted systems that…
Read MoreEnergy Management Policy and Strategies in ASEAN
This research analyses the challenges faced by ASEAN countries in managing its energy efficiencies and resources due to rapid economic growth, increasing energy demand, and diverse energy infrastructures across member states. This paper explores the energy management policies and strategies within the ASEAN region, focusing on the integration of energy efficiency measures, renewable energy initiatives,…
Read MoreEffectiveness of a voice analysis technique in the assessment of depression status of individuals from Ho Chi Minh City, Viet Nam: A cross-sectional study
The Mind Monitoring System (MIMOSYS) is a novel voice analysis technique for mental health assessment that has been validated in some languages; however, no research has been conducted on the Vietnamese yet. This study aimed to examine the ability of the Vitality score extracted from the MIMOSYS system to assess depression status based on the…
Read MoreGPT-Enhanced Hierarchical Deep Learning Model for Automated ICD Coding
In healthcare, accurate communication is critical, and medical coding, especially coding using the ICD (International Classification of Diseases) standards, plays a vital role in achieving this accuracy. Traditionally, ICD coding has been a time-consuming manual process performed by trained professionals, involving the assignment of codes to patient records, such as doctor’s notes. In this paper,…
Read MoreAutomated Performance analysis E-services by AES-Based Hybrid Cryptosystems with RSA, ElGamal, and ECC
Recently Network safety has become an important or hot topic in the security society (i.e. Encryption and Decryption) developed as a solution of problem that have an important role in the security of information systems (IS). So protected/secure the shared data and information by many methods that require in all internet faciality, data health and…
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 MoreLeveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
Polyfluoroalkyl substances (PFAS) are persistent chemicals that accumulate in the body and environment. Although recent studies have indicated that PFAS may disrupt kidney function, the underlying mechanisms and overall effects on the organ remain unclear. Therefore, this study aims to elucidate the impact of PFAS on kidney health using machine learning techniques. Utilizing a dataset…
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 MoreMalaysia’s Renewable Energy Policy and its Impact on ASEAN Countries
As the global community increasingly shifts its focus towards sustainable development and combating climate change, renewable energy policies have become pivotal in shaping national and regional energy landscapes. Malaysia, as a developing nation with a rapidly growing economy, has recognized the importance of renewable energy sources in achieving its socio-economic goals while addressing environmental concerns.…
Read MoreRevolutionizing Robo-Advisors: Unveiling Global Financial Markets, AI-Driven Innovations, and Technological Landscapes for Enhanced Investment Decisions
Robo-advisors, fundamental to the financial services sector, have undergone substantial technological metamorphosis. Innovations in artificial intelligence, blockchain, cloud technology, augmented reality, and virtual reality have reshaped the financial industry’s landscape. As automated investment solutions, robo-advisors are on the brink of further technological evolution. This comprehensive research amalgamates historical data, behavioral insights, and emerging market trends…
Read MoreExploring Current Challenges on Security and Privacy in an Operational eHealth Information System
Bearing in mind that patient data is extremely sensitive, it is crucial to establish strong protection when the security and privacy of healthcare data are concerned. Prioritizing data security and privacy is essential for the overall healthcare industry in order to maintain the reliability of electronic healthcare (eHealth) information systems. This study explores the gathered…
Read MoreSpatial Distribution Patterns of the Royal Development Projects Initiated by King Rama 9th of Thailand
The study aimed to create a chronological overview of the royal development projects initiated by King Rama IX and to analyze their spatial distribution patterns. The research used a mixed-methods approach, combining quantitative and qualitative data collection methods such as obtaining data from relevant offices, internet research, and field observations. Data analysis involved descriptive statistics…
Read MoreOptimal Engagement of Residential Battery Storage to Alleviate Grid Upgrades Caused by EVs and Solar Systems
The integration of distributed energy resources has ushered in a host of complex challenges, significantly impacting power quality in distribution networks. This work studies these challenges, exploring issues such as voltage fluctuations and escalating power losses caused by the integration of solar systems and electric vehicle (EV) chargers. We present a robust methodology focused on…
Read MoreMathematical Model of Wind Turbine Simulator Based Five-Phase Permanent Magnet Synchronous Generator with Nonlinear Loads and Harmonic Analysis
This paper presents mathematical model of a wind turbine simulator based five-phase permanent magnet generator supplying nonlinear load. The mathematical model of wind turbine characteristics together with available tool blocks of the five-phase permanent generator and semiconductor devices of an AC-DC converter formed as a nonlinear load is implemented on MATLAB /Simulink to investigate the…
Read MoreDevelopment of a GSM-RC Automated Device for Measuring Mobile Communication Signal Strength and Meteorological Parameters
The automated Global System for Mobile Communication Signal Strength and Radio Climatological (GSM-RC) measuring device is an integration of different electronic sensors in a box for an in-situ measuring system. The sensor, data logging, and communication subsystems are integrated for transmitting information on meteorological parameters (MPs) and GSM signal strength level (SSL). The goal is…
Read MoreInvestigating Heart Rate Variability Index Classification in Macaca fascicularis and Humans: Exploring Applications for Personal Identification and Anonymization Studies
In this paper, we determine the feasibility of differentiating between the heart rate patterns of Macaca fascicularis and human infants by comparing pertinent hyperparameters. This verification process was undertaken to ascertain the suitability of Macaca fascicularis heart rate data as a testbed for evaluating heart rate parameter privacy safeguarding methodologies. The biological characteristics of Macaca…
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 MoreComparing Kalman Filter and Diffuse Kalman Filter on a GPS Signal with Noise
The navigation control of an autonomous vehicle can be determined by the coordinates of a GPS (Global Positioning System) positioning system, angular velocity, and acceleration with an INS (Inertial Navigation System). However, the errors associated with these devices do not allow it to be the only measurement system used in an autonomous vehicle. The need…
Read MoreSmart Agent-Based Direct Load Control of Air Conditioner Populations in Demand Side Management
The integration of fluctuating renewable resources such as wind and solar into existing power systems poses challenges to grid reliability and the seamless incorporation of these resources. To address the inherent variability in renewable generation, direct load control emerges as a promising method for demand-side management. Thermostatically controlled appliances, like air conditioners, hold a significant…
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