Computer Research Articles

A System for the Analysis of Historical Electoral Results of the National Electoral Institute of Mexico

This paper presents a computer system capable of analyzing the databases of the results of the elections in Mexico, using genetic algorithms to achieve efficient analyses that will serve for the creation of reports with the information generated, in a shorter time than it can take to perform a manual analysis. The developed system implements the Windows Forms environment with the C# programming language and the SQL Server relational database system. In this research, the variables related to the execution time in the generation of reports will be measured, with respect to the traditional method, in addition to collecting relevant information that the system shows through experimentation.

Numerical Investigation of Turbulent Convection Flow in a Rectangular Closed Cavity

Natural turbulent convection in closed cavities has many practical applications in the field of engineeringsuch as the design of electronic computer chips, atomic installation and industrial cooling among others. Inparticular, it enables in achieving a desired micro-climate and efficient ventilation in a building. Recent studiesshow that turbulent flow is affected by variations in Rayleigh numbers, aspect ratio, and heater positionamong others. Temperature is kept constant in all these studies hence inadequate literature on the effectsof temperature on a turbulent flow. In this study, aspect ratio and Rayleigh numbers are kept constant at2 and 1012 respectively and natural turbulent convection flow in a closed rectangular cavity is investigatednumerically as the operating temperature is varied from 285.5K to 293K. The rectangular cavity’s lower wallwas heated and cooling done at the top face wall while the rest of the vertical walls were kept in adiabaticcondition. Material properties such as density of the fluid kept on changing at any given temperature. Thethermal profile data generated influenced the nature of the turbulent flow. The non-linear averaged continuity,momentum, and energy equation terms were modeled by the SST k − ω model to generate streamlines,isotherms, and velocity magnitude for a different operating temperature and presented graphically. The finitedifference method and FLUENT were used to solve two SST k − ω model equations, vortices, and energy withboundary conditions. It was discovered that, as the operating temperature increased turbulence decreaseddue to a decrease in the velocity of the elements and vortices became more parallel and smaller.

Use of Artificial Intelligence Technologies in Visual Design

Artificial intelligence (AI) refers to computer systems crafted to replicate human cognitive functions such as learning, perception, and problem-solving. Recently, AI technologies have gained widespread popularity across various domains including healthcare and finance. They have also significantly impacted visual design. This study investigates the burgeoning influence and utilization of AI technologies in visual design, delving into their effects and applications. It scrutinizes how AI innovations transform visual design processes, influence creativity, and shape design practices. The research emphasizes the emergence of AI-powered design tools, their impact on designer creativity, and the potential advantages and drawbacks they pose to creative processes. Furthermore, it examines the ethical and practical dimensions inherent in integrating AI into design practices. By thoroughly assessing AI's impact on visual design, the study aims to prognosticate future technological advancements in this realm.

Preface

In 2024, the highly anticipated 4th International Conference on Electronic Communication, Computer Science and Technology (ECCST 2024) was held in Shanghai, China during September 20th to 22nd. The conference aimed to provide a high-end platform for experts, scholars, researchers, and enterprise representatives in the fields of electronic communication and computer science and technology from all over the world to present their research results, exchange academic views, and discuss future development trends. The conference invited many famous experts and scholars from home and abroad, who together discussed the latest research progress, technical breakthroughs and application practices in the fields of electronic communication and computer science and technology. The keynote speech session was a highlight of the conference, during which keynote speakers shared their latest achievements and experiences in their respective research fields, bringing an academic feast to the participants. In addition, ECCST 2024 also set up a number of oral and poster presentation sessions. Attendees had an in-depth discussion on the topics they are interested in, exchanged ideas and shared experiences with their peers, and jointly promoted the development in the fields of electronic communication and computer science and technology. The conference proceedings, as one of the important outcomes of the conference, gathers the wisdom and insights of the participants and provides valuable academic resources for the development of related fields. It covers a wide range of research directions of electronic communication and computer science and technology, including Digital Circuits, Low Power Design and VLSI Physical Design, Signal and Information Processing, Communication Network and Systems, Computer Programming, and many other aspects. The content of the proceedings includes both research on fundamental theories and exploration of application technologies, fully demonstrating the diversity and richness of the fields. ECCST 2024 has a far-reaching impact. Firstly, it provided an international communication platform for experts and scholars in the fields of electronic communication and computer science and technology, facilitated academic exchanges and cooperation between different countries and regions, promoted the development and application of electronic communication and computer technologies in universities and enterprises, and injected new vitality into the innovation and development of related disciplines industries. Secondly, the papers included in the conference proceedings are published in the Journal of Physics: Conference Series after a strict review process, and will be submitted to international famous databases, such as EI Compendex and Scopus, for indexing, which provides a strong guarantee for the promotion and dissemination of these academic achievements. Here, we would like to thank all the people involved in ECCST 2024 for their dedication and efforts. Acknowledgement goes to the organizing committee members for their careful planning and organization, which provided a strong guarantee for the smooth convening of the conference; to the keynote speakers for their wonderful speeches, which brought valuable academic insights to the participants; to the authors for their active participation, which contributed to the richness of the conference proceedings; and to all the attendees for their enthusiastic participation and support, which made ECCST 2024 a complete success. The Committee of ECCST 2024 List of Committee Member is available in this Pdf.

Host Based-Intrusion Detection System (Anomaly Detection System)

The objective of our statistical anomaly detection project is to develop an IDS that notices behavior which is based on observed action, detects abnormalities or possible intrusions. The system utilizes statistical analysis techniques, specifically features to discover anomalous patterns of activity, and receives input data in the form of stats.txt and event.txt files. The project's goal is to offer a dependable and efficient IDS that can assist in identifying and averting cyberattacks on networks and computer systems

Trustworthy and Scalable Federated Edge Learning for Future Integrated Positioning, Communication, and Computing System: Attacks and Defenses

Trustworthy and Scalable Federated Edge Learning for Future Integrated Positioning, Communication, and Computing System: Attacks and Defenses

Designing a Novel Network Anomaly Detection Framework using Multi-Serial Stacked Network with Optimal Feature Selection Procedures over DDOS Attacks

- Distributed denial-of-service (DDoS) attacks are the major threat that disrupts the services in the computer system and networks using traffic and targeted sources. So, real-world attack detection techniques are considered an important element in executing cybersecurity tasks. The present DDoS techniques are prone to False Positive Rates (FPR) and also it didn’t acquire the complicated patterns presented in the attack traffic. Internet of Things (IoT) is a complicated network with resource-constrained devices and networks that are prone to different security threats like DDoS attacks. Later, the Software Defined Networking (SDN) with IoT models is used to enhance the access control techniques and security models. DDoS attacks are considered as an important threat in the IoT networks. Hence, it is important to construct a novel network anomaly detection model with a deep learning mechanism to resolve the limitations of the existing techniques. Initially, essential data required for the validation are gathered from the IDS ISCX 2012 dataset. The optimal features are selected from input data using the Predefined-Mud Ring Algorithm (P-MRA). The optimally selected features are provided to the Multi-Serial Stacked Networks (Multi-SSN), which is the fusion of Convolutional Autoencoder (CAE), Gated Recurrent Unit (GRU), and Bayesian Learning (BL) networks. Here, the essential features for the validation are acquired from the CAE and GRU. Then, these features are stacked and given to the BL mechanism for detecting the anomalies in the network. Further, several experimental validations are performed in the developed framework over traditional network anomaly detection mechanism.

Multi-type feature fusion visual navigation for asteroid landing

In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features, such as significant recognition and extraction errors, low computational efficiency, and limited navigation accuracy, a novel approach for multi-type fusion visual navigation is proposed. This method aims to overcome the limitations of single-type features and enhance navigation accuracy. Analytical criteria for selecting multi-type features are introduced, which simultaneously improve computational efficiency and system navigation accuracy. Concerning pose estimation, both absolute and relative pose estimation methods based on multi-type feature fusion are proposed, and multi-type feature normalization is established, which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation. The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.

A Framework for a Master’s in Applied Artificial Intelligence Program in Computer and Information Systems Discipline

A Framework for a Master’s in Applied Artificial Intelligence Program in Computer and Information Systems Discipline

Linear and nonlinear coupling of light in twin-resonators with Kerr nonlinearity

Nonlinear effects in microresonators are efficient building blocks for all-optical computing and telecom systems. With the latest advances in microfabrication, coupled microresonators are used in a rapidly growing number of applications. In this work, we investigate the coupling between twin-resonators in the presence of Kerr nonlinearity. We use an experimental setup with controllable coupling between two high-Q resonators and discuss the effects caused by the simultaneous presence of linear and nonlinear coupling between the optical fields. Linear-coupling-induced mode splitting is observed at low input powers, with the controllable coupling leading to a tunable mode splitting. At high input powers, the hybridized resonances show spontaneous symmetry breaking (SSB) effects, in which the optical power is unevenly distributed between the resonators. Our experimental results are supported by a detailed theoretical model of nonlinear twin-resonators. With the recent interest in coupled resonator systems for neuromorphic computing, quantum systems, and optical frequency comb generation, our work provides important insights into the behavior of these systems at high circulating powers.

TD3-based trajectory optimization for energy consumption minimization in UAV-assisted MEC system

Unmanned Aerial Vehicle (UAV) assisted Mobile Edge Computing (MEC) systems provide substantial benefits for task offloading and communication services, especially in situations where traditional communication infrastructure is unavailable. Current research emphasizes maintaining communication quality while minimizing total energy consumption and optimizing UAV flight trajectories. However, several issues remain: First, the energy consumption objective function lacks comprehensiveness, neglecting the impact of UAV flight energy consumption; second, an effective Deep Reinforcement Learning (DRL) algorithm has not been employed to address the non-convexity of the objective function; third, there is insufficient discussion regarding the practical significance of the proposed approach. To address these issues, this paper formulates an objective function aimed at minimizing MEC energy consumption by considering task offloading decisions, communication delays, computational energy consumption, and UAV flight energy consumption. We propose a Population Diversity-based Particle Swarm Optimization-Double Delay Deep Deterministic Policy Gradient (PDPSO-TD3) algorithm to find the optimal solution, enhance UAV flight trajectories through optimized offloading decisions, ensure efficient communication, and minimize the total energy consumption of the MEC system. Furthermore, we discuss the practical applicability of PDPSO-TD3 in detail and present the proposed scheme. Experimental results demonstrate that compared to the Deep Deterministic Policy Gradient (DDPG) algorithm, for transmission delay, MEC energy consumption, UAV flight energy consumption, and User Equipments (UEs) access rate metrics. The proposed PDPSO-TD3 algorithm can improvement the performance by about 14.3%, 10.1%, 6.1%, and 3.3%, respectively.

Integrated photonic modular arithmetic processor

Integrated photonic computing has emerged as a promising approach to overcome the limitations of electronic processors in the post-Moore era. However, present integrated photonic computing systems face challenges in achieving high-precision calculations, consequently limiting their potential applications, and their heavy reliance on analog-to-digital (AD) and digital-to-analog (DA) conversion interfaces undermines their performance. Here we propose an innovative photonic computing architecture featuring scalable calculation precision and, to our knowledge, a novel photonic conversion interface. By leveraging the residue number system (RNS) theory, the high-precision calculation is decomposed into multiple low-precision modular arithmetic operations executed through optical phase manipulation. Those operations directly interact with the digital system via our proposed optical digital-to-phase converter (ODPC) and phase-to-digital converter (OPDC). Through experimental demonstrations, we showcase a calculation precision of 9 bits and verify the feasibility of the ODPC/OPDC photonic interface. This approach paves the path towards liberating photonic computing from the constraints imposed by limited precision and AD/DA converters.

Research on on-site real-time detection technology of transmission line pulling force based on sensors

During the transmission process, the stay wire tower plays an important role in supporting and stabilizing. By monitoring the tension of the stay wire, the deformation and abnormal force of the stay wire tower structure can be detected in a timely manner, and measures can be taken to adjust and repair it. In terms of wire tension monitoring, the main methods currently used include various monitoring technologies such as electronic, mechanical, and optical. However, traditional cable force monitoring methods have problems such as low monitoring accuracy and poor real-time performance, so it is necessary to develop a real-time detection technology based on sensors. This article uses computer technology to achieve real-time detection of transmission line pulling force based on sensors. Firstly, select a suitable sensor for measuring the pulling force. Then, the sensor data is transmitted to the computer system for real-time processing and analysis. Finally, the results are displayed through the interface, facilitating real-time monitoring and control by monitoring personnel. After experimental verification, the real-time detection technology based on sensors proposed in this article can accurately monitor the pulling force of transmission lines. The monitoring results show that this technology has high accuracy and good real-time performance, and can timely detect and handle abnormal wire force situations.

Coded Computing for Half-Duplex Wireless Distributed Computing Systems via Interference Alignment

Coded Computing for Half-Duplex Wireless Distributed Computing Systems via Interference Alignment

Big Data (R)evolution in Geography: Complexity Modelling in the Last Two Decades

ABSTRACTThe use of data and statistics along with computational systems heralded the beginning of a quantitative revolution in Geography. Use of simulation models (Cellular Automata and Agent‐Based Models) followed in the late 1990s, with ontology and epistemology of complexity theory and modelling being defined a little less than two decades ago. We are, however, entering a new era where sensors regularly collect and update large amounts of spatio‐temporal data. We define this ‘Big Data’ as geolocated data collected in sufficiently high volume (exceeding storage capacities of the largest personal hard drives currently available), that is updated at least daily, from a variety of sources in different formats, often without recourse to verification of its accuracy. We then identify the exponential growth in the use of complexity simulation models in the past two decades via an extensive literature review (broken down by application area), but also notice a recent slowdown. Further, a gap in the utilisation of Big Data by modellers to calibrate and validate their models is noted, which we attribute to data availability issues. We contend that Big Data can significantly boost simulation modelling, if certain constraints and issues are managed properly.

Examining the Cyclical Nature of Crimes: A Looped Crime Script of Data Theft from Organizational Networks

Most prior research on network attacks is predominantly technical, yet little is known about behavioral patterns of attackers inside computer systems. This study adopts a criminological perspective to examine these patterns, with a particular focus on data thieves targeting organizational networks. By conducting interviews with cybersecurity experts and applying crime script analysis, we developed a comprehensive script that describes the typical progression of attackers through organizational systems and networks in order to eventually steal data. This script integrates phases identified in previous academic literature and expert-defined phases that resemble phases from industry threat models. However, in contrast to prior cybercrime scripts and industry threat models, we did not only identify sequential phases, but also illustrate the circular nature of network attacks. This finding challenges traditional perceptions of crime as a linear process. In addition, our findings underscore the importance of considering both successful and failed attacks in cybercrime research to develop more effective cybersecurity strategies.

Novel Wafer-Level Ta-Ta Direct Thermocompression Bonding for 3D Integration of Superconducting Interconnects for Scalable Quantum Computing System

Novel Wafer-Level Ta-Ta Direct Thermocompression Bonding for 3D Integration of Superconducting Interconnects for Scalable Quantum Computing System

INFORMATION TECHNOLOGIES IN THE DEVELOPMENT OF WEB RESOURCES

The article focuses on an overview, analysis and examples of the use of information technology in the development of web resources. Information technology is a field of knowledge and practical applications related to the collection, processing, storage, transmission and use of information using computer systems. Information technology is used in various industries, such as business, medicine, education, science, entertainment, and many others. Information technology covers a wide range of technologies, including software, hardware, networks, and other tools that help in managing information. They are used at every stage of web resource development, from design to deployment and support. The article describes the key aspects of IT: programming languages and frameworks; databases that can be used to store information on a web server, as well as to provide access to data through web applications using programming languages and frameworks; web servers and hosting; version control systems that help developers effectively manage code and work together on projects of any complexity; security (ensuring the security of web resources includes the use of encryption methods, data validation, protection against Testing and debugging are iterative processes that are repeated throughout the development cycle to ensure the quality and reliability of a web application). They can be used to automate business processes, increase productivity, ensure data security, simplify communication, and provide access to information.

A Review of Expert Systems Integration in Signal Plan Optimisation

In urban networks, periodic peak traffic congestion often occurs during the day, namely in the morning and afternoon hours. Due to spatial constraints and the inability to increase capacity through physical road expansion, modern traffic management increasingly relies on Intelligent Transport Systems (ITS) solutions. One such solution is the integration of automatic licence plate recognition, an expert system and microsimulation tools aimed at optimising the network performance of signalised intersections within a network. Based on real-time and historical data on individual vehicle trajectories, the system predicts the route of each vehicle through the observed segment of the traffic network, determines the network load and proposes optimal signal plans. This paper provides an overview of conducted research related to the optimisation of signal plans utilising expert systems. Mathematical models for capacity and load determination, as well as computational intelligence-based systems used for signalised intersection management strategies, are described. Finally, the paper proposes a basic framework and guidelines related to the suggested system, highlighting open questions and potential challenges in its development.

GPS Tracking and Indoor Navigation System

This project is an idea of developing an application based on a navigation system formed by Graph Data Structure. An indoor positioning system (IPS) can be thought of as a global positioning system (GPS) for indoor venues. While GPS is used outdoors, IPS can detect real-time locations to accurately determine the coordinates of people or assets inside a building. These coordinates are typically represented visually by a blue dot on a digital indoor map to provide additional context to users and features such as wayfinding. The project aims to have certain objectives such as a tracking system, navigation system that is inside a small area of a building. This idea aims to track the location of any particular device within a building and show a navigation to that device in an efficient manner. Not only tracking of devices but also solving a problem of finding a particular room in the building through data of different paths that is stored. This project comes under the intelligent system design and development domain and falls under the sector of analysing and designing hardware, software and operating systems for computers. The main objective of this system design is to navigate through the area and find places to reach with ease and as fast as possible, it is helpful for people who are new at that place and even finding a user in that particular vicinity by live tracking technique.