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Keyword: ATCAnalysis of Economic Load Dispatch with a lot of Constraints Using Vortex Search Algorithm
In modern powers systems, one of the most considerable topics is economic load dispatch (ELD). ELD is non-linear problem and it became non-convex and non-smooth problem with some constraints such as valve point loading effect. ELD is very crucial for energy generation and distribution in power systems. For solving ELD problem, a lot of methods…
Read MoreA Modified Patch Antenna with Square-Open Loop Resonator Slot for Improved Bandwidth Performance in WiFi Applications
A novel, modified square patch antenna with square open loop resonator slot, operating at 5.5 GHz, for improved bandwidth performance is proposed in this article. A complementary square open loop resonator is introduced on the patch to enhance the bandwidth more than twice that of the conventional square patch antenna operating at the same frequency.…
Read MoreAn Application of ANN Model with Bayesian Regularization Learning Algorithm for Computing the Operating Frequency of C-Shaped Patch Antennas
In this paper, an application of artificial neural network (ANN) using bayesian regularization (BR) learning algorithm based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped patch antennas (CPAs) in UHF band. Firstly, the operating frequencies of 144 CPAs having varied dimensions and electrical parameters were simulated by the XFDTD…
Read MoreCooperative Game Theory for Grid Service Pricing: A Utility-Centric Approach
This study presents a novel alternative to traditional Net Energy Metering (NEM) by proposing a set of innovative pricing schemes for solar customers participating in utility-led grid service programs through the aggregation of Distributed Energy Resources (DERs). Grounded in cooperative game theory, the proposed framework facilitates equitable and efficient value allocation among key stakeholders, namely…
Read MoreAI-Based Photography Assessment System using Convolutional Neural Networks
Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…
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 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 MoreEnhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…
Read MoreOptimizing the Performance of Network Anomaly Detection Using Bidirectional Long Short-Term Memory (Bi-LSTM) and Over-sampling for Imbalance Network Traffic Data
Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…
Read MoreMRI Semantic Segmentation based on Optimize V-net with 2D Attention
Over the past ten years, deep learning models have considerably advanced research in artificial intelligence, particularly in the segmentation of medical images. One of the key benefits of medical picture segmentation is that it allows for a more accurate analysis of anatomical data by separating only pertinent areas. Numerous studies revealed that these models could…
Read MoreOmni-directional Multi-view Image Measurement System in the Co-sphere Framework
This study presents an “Omnidirectional multi-view image measurement system”, which can be used to provide multi-camera 3D reconstruction and multi-view image information. Its characteristic is that four cameras take images from multiple perspectives in the co-sphere framework. The C0 is the middle camera fixed as the geometric center point of measurement, and provides a front…
Read MoreHybrid Intrusion Detection Using the AEN Graph Model
The Activity and Event Network (AEN) is a new dynamic knowledge graph that models different network entities and the relationships between them. The graph is generated by processing various network security logs, such as network packets, system logs, and intrusion detection alerts, which allows the graph to capture security-relevant activity and events in the network.…
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 MoreBirds Images Prediction with Watson Visual Recognition Services from IBM-Cloud and Conventional Neural Network
Bird watchers and people obsessed with raising and taming birds make a kind of motivation about our subject. It consists of the creation of an Android application called ”Birds Images Predictor” which helps users to recognize nearly 210 endemic bird species in the world. The proposed solution compares the performance of the python script, which…
Read MoreSensitive Analysis in Holding and Penalty Costs for the Stochastic Sequencing Problem in Agile Manufacturing
In agile manufacturing, due to the desire to meet customer’s requirements, processing times are stochastic because operations could be done by robots or humans. This can cause several problems in scheduling the jobs, and it is necessary to select the dispatch rule with the least change in costs and times, to respond quickly to different…
Read MoreA Proposal of Code Modification Problem for Self-study of Web Client Programming Using JavaScript
In current societies, web application systems take central roles in computer systems. Thus, web client programming using JavaScript has increased values to add dynamic features and functions in web pages by well working with HTML and CSS. In this paper, as a new type of exercise problem for its self-study, we propose a code modification…
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 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 MoreValue Trace Problems for Code Reading Study in C Programming
C programming is taught in a lot of universities across the world as the first computer programming language. Then, for novice students, it is important to read many simple C source codes and understand their behaviors to be familiar to the programming paradigm. Unfortunately, effective tools to support independent code reading study at home have…
Read MoreProblems of Increasing the Intelligence of Algorithms for Optimal Distribution of the Current Load on the Combined Heat and Power Plant and Ways to Solve Them
The problem of optimal distribution of the current load of a combined heat and power plant with a complex composition of equipment is considered. A multi-criteria approach is proposed for parts of graphs with a constant load in time, considering the factors of economy, reliability and ecology. For sections of the graph with a time-variable…
Read MoreImpact Assessment of the Renewable Energy Sources Implementation in Bulgarian Single-Family Houses on the Greenhouse Gas by HOMER Pro Software
It is widely known that cities now house more than half of the world’s population. Within this framework, this study presents the possibilities for real-world application of renewable energy sources (RES) in urban areas, as well as their contribution to the urban deployment of the new energy paradigm. A comparison is made between hybrid power…
Read MoreA Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern
The ocean surface temperatures or sea surface temperatures have a significant influence on local and global weather. The change in sea surface temperatures will lead to the change in rainfall patterns. In this paper, the long-term rainfall forecasting is developed for planning and decision making in water resource management. The similarity of sea surface temperature…
Read MoreAn Efficient Combinatorial Input Output-Based Using Adaptive Firefly Algorithm with Elitism Relations Testing
Combinatorial software testing is regarded as a crucial part when it comes to the software development life cycle. However, it would be impractical to exhaustive test highly configurable software due to limited time as well as resources. Moreover, a combinatorial testing strategy would be to employ input-output-based relations (IORs) due to its benefits versus other…
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