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Keyword: RODesign of an Off-Grid Hybrid Energy System for Electrification of a Remote Region: a Case Study of Upper Blink Water Community, South Africa
Electrifying or connecting remote and isolated communities to the national grid is very difficult and expensive. This challenge is due to the geographic locations of these isolated communities and terrain that needs navigation when installing transmission lines to transmit power to the communities. This article presents a case study of the design of a hybrid…
Read MoreDeep Learning in Monitoring the Behavior of Complex Technical Systems
The article is devoted to the methods of monitoring and control of vibration processes occurring in the structure and units of complex and unique electromechanical equipment. The monitoring object is considered as a dynamic multidimensional information object, for the study of which analytical and numerical methods of modeling and simulation of multidimensional chaotic systems are…
Read MoreBER Performance Evaluation Using Deep Learning Algorithm for Joint Source Channel Coding in Wireless Networks
In the time past, virtually all the contemporary communication systems depend on distinct source and channel encoding schemes for data transmission. Irrespective of the recorded success of the distinct schemes, the new developed scheme known as joint source channel coding technique has proven to have technically outperformed the conventional schemes. The aim of the study…
Read MoreRegularity of Radon Transform on a Convex Shape
Radon transform is a mathematical tool widely applied in various domains, including biophysics and computer tomography. Previously, it was discovered that applying the Radon transform to a binary image comprising circle forms resulted in discontinuity. As a result, the line detection approach based on it became discontinued. The d-Radon transform is a modified version of…
Read MoreEstimating a Minimum Embedding Dimension by False Nearest Neighbors Method without an Arbitrary Threshold
The false nearest neighbors (FNN) method estimates the variables of a system by sequentially embedding a time series into a higher-dimensional delay coordinate system and finding an embedding dimension in which the neighborhood of the delay coordinate vector in the lower dimension does not extend into the higher, that is, a dimension in which no…
Read MorePerformance Adjustment Factor for Fixed Solar PV Module
There are different factors which contribute to the amount of output power which can be delivered by solar photovoltaic (PV) module at any time of the year. The factors include but not limited to solar irradiation, ambient temperature, relative humidity, wind velocity, position of sun in the sky, geographical position of installed solar PV module…
Read MoreMetamaterial-Inspired Compact Single and Multiband Filters
In this paper, Compact bandpass filters have been designed. A single bandpass filter was designed using novel triple concentric complementary split-ring resonators placed along the microstrip line in the ground plane. Gaps and via were placed on the microstrip line to control electromagnetic characteristics, resulting in a single bandpass filter. In turn, spiral resonators were…
Read MoreOn the Prediction of One-Year Ahead Energy Demand in Turkey using Metaheuristic Algorithms
Estimation of energy demand has important implications for economic and social stability leading to a more secure energy future. One-year-ahead energy demand estimation for Turkey has been proposed in this paper, using the metaheuristics method with GDP, the total population, and the quantities of imports and exports, as inputs variables. The records obtained from historical…
Read MoreA Machine Learning Model Selection Considering Tradeoffs between Accuracy and Interpretability
Applying black-box ML models in high-stakes fields like criminology, healthcare and real-time operating systems might create issues because of poor interpretability and complexity. Also, model building methods that include interpretability is now one of the growing research topics due to the absence of interpretability metrics that are both model-agnostic and quantitative. This paper introduces model…
Read MoreµPMU Hardware and Software Design Consideration and Implementation for Distribution Grid Applications
This article presents a roadmap for distribution grid µPMU hardware and software design consideration and implantation to ensure high performance within limited computational time of sampling frequency 512 samples/cycle. A proposed 12 channels, multi-voltage level µPMU hardware and rules of voltage and current transducer, analog filter, analog-to-digital converter, sampling rate definition, and PCB design and…
Read MoreARAIG and Minecraft: A Modified Simulation Tool
Various interruptions to the daily lives of researchers have necessitated the usage of simulations in projects which may not have initially relied on anything other than physical inquiry and experiments. The programs and algorithms introduced in this paper, which is an extended version of research initially published in ARAIG And Minecraft: A COVID-19 Workaround, create…
Read MoreComputer Vision Radar for Autonomous Driving using Histogram Method
Mobility is a fundamental human desire. All societies aspire to safe and efficient mobility at low ecological and economic costs. ADAS systems (Advanced Driver Assistance Systems) are safety systems designed to eliminate human error in driving vehicles of all types. ADAS systems such as Radars use advanced technologies to assist the driver while driving and…
Read MoreLow-cost Smart Basket Based on ARM System on Chip Architecture: Design and Implementation
This paper presents the design and implementation of a low-cost basket based on an ARM system on chip architecture using Raspberry Pi single board computer. The inspiration of this research is how to support the traditional low-income retail store in Thailand driving the local micro-business deal with the economic impacts of survival business from the…
Read MoreA Supervised Building Detection Based on Shadow using Segmentation and Texture in High-Resolution Images
Building detection in aerial or satellite imagery is one of the most challenging tasks due to the variety of shapes, sizes, colors, and textures of man-made objects. To this end, in this paper, we propose a novel approach to extracting buildings in high-resolution images based on prior knowledge of the shadow position. Firstly, the image…
Read MoreDeep Learning Affective Computing to Elicit Sentiment Towards Information Security Policies
Information security behaviour is an integral part of modern business and has become a central theme in many research studies. One of the essential tools available that can be used to influence information security behaviour is information security policies (ISPs). These types of policies, which is mandatory in most organisations, are formalised rules and regulations…
Read MoreIndoor Position and Movement Direction Estimation System Using DNN on BLE Beacon RSSI Fingerprints
In this paper, we propose a highly accurate indoor position and direction estimation system using a simple fully connected deep neural network (DNN) model on Bluetooth Low Energy (BLE) Received Signal Strength Indicators (RSSIs). Since the system’s ultimate goal is to function as an indoor navigation system, the system estimates the indoor position simultaneously as…
Read MoreAntenna System Design To Increase Power Transfer Efficiency with NFC Wireless Charging Technology
The NFC wireless charging feature is an extension of the NFC technology that can be implanted on wearables. The purpose of this paper is to show how to increase power transfer efficiency on both transmitter and receiver antenna systems. To demonstrate this problematic, firstly this paper gives an overview of how this NFC feature is…
Read MoreSecured Multi-Layer Blockchain Framework for IoT Aggregate Verification
Technologies designed for digital provenance, especially the Internet of Things (IoT) and blockchain, may allow for security, transparency, and traceability in the global supply chain. However, upstream nodes in the supply chain that work for large-scale production suppliers are not considered. In addition, most IoT blockchain systems adopt an ID-based signature scheme that may affect…
Read MoreA CMOS On-Chip High-Precision PVTL Detector
A novel PVTL (Process, Voltage, Temperature, Leakage) detection circuit consisting of four individual detectors is proposed in the investigation. Voltage Variation Detector is composed of a feedback control block comprising multi-stage delay cells using high Vth devices such that 0.5% of VDD variation can be detected. Temperature Detector based on a current to pulse converter…
Read MoreHole-Confined Polar Optical Phonon Interaction in \(\mathrm{Al_{0.35}Ga_{0.65}As/GaAs/Al_{0.25}Ga_{0.75}As}\) Quantum Wells
In Al0.35Ga0.65As/GaAs/Al0.25Ga0.75As quantum wells, the hole-confined polar optical phonon interaction is investigated. To calculate the valence band structure, we use the Luttinger-Kohn Hamiltonian with the k.p method. Within the dielectric continuum model, the hole-confined phonon scattering rates of intrasubband heavy holes in quantum well are calculated. It is found that the scattering rates are governed…
Read MoreHigh Performance SqueezeNext: Real time deployment on Bluebox 2.0 by NXP
DNN implementation and deployment is quite a challenge within a resource constrained environment on real-time embedded platforms. To attain the goal of DNN tailor made architecture deployment on a real-time embedded platform with limited hardware resources (low computational and memory resources) in comparison to a CPU or GPU based system, High Performance SqueezeNext (HPS) architecture…
Read MoreGeneralized Linear Model for Predicting the Credit Card Default Payment Risk
Predicting the credit card default is important to the bank and other lenders. The credit default risk directly affects the interest charged to the borrower and the business decision of the lenders. However, very little research about this problem used the Generalized Linear Model (GLM). In this paper, we apply the GLM to predict the…
Read MoreEncompassing Chaos in Brain-inspired Neural Network Models for Substance Identification and Breast Cancer Detection
The main purpose in this work is to explore the fact that chaos, as a biological characteristic in the brain, should be used in an Artificial Neural Network (ANN) system. In fact, as long as chaos is present in brain functionalities, its properties need empirical investigations to show their potential to enhance accuracies in artificial…
Read MoreTowards a Model-based and Variant-oriented Development of a System of Systems
The development of an aggregated system consisting of autonomously developed components is usually implemented as a self-contained unit. If such an aggregation is understood as a system of systems (SoS) that communicates via interfaces with its autonomous subsystems and components, the interfaces and communication exchange should play a central role in the architectural design. In…
Read MoreHeuristic Analysis of Overall Performance Measurement Perception and Management in Automotive Industry
Overall Performance (OP) measurement is an essential instrument in sustainable manufacturing implementation and management. The effective use of key performance indicators (KPIs) can potentially contribute to identify the firm’s overall performance, provide the crucial gaps between desired results and current actions, and thus facilitate the implementation and execution of improvement strategies. This study attempts to…
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