In recent times, unmanned aerial vehicles (UAVs) are constructed in the vehicular network. Through this technology the communication becomes more flexible and efficient but still it consists of certain drawbacks in terms of device deployment and data collection. For that purpose, in this article an efficient data collection system and effective relaying model (DCERM-UAV) is constructed in the aerial vehicles to improve the network stability. The core concentrations of these models are providing effective data aggregation, relaying among the vehicles and improving deployment of it. Through this process the stability of the vehicles is increased and that leads to high quality communication among them. The parameters which are used to analyses the performance of the network model are energy efficiency, energy consumption, network throughput, routing overhead and data delivery ratio. From the final results it gets proven that the DCERM-UAV achieves maximum efficiency when compared with the earlier research works.
Rectangular patch antennas are important components in modern wireless communication systems, including 5 G and emerging 6 G technologies. These antennas support highfrequency, high-capacity, and energy-efficient wireless communication. For beamforming, the dimensions of these antennas significantly influence their radiation patterns, and antenna gain. Beamforming technology is essential for 5G and 6G networks, enhancing coverage, capacity, and energy efficiency. Effective beamforming relies on array configurations of rectangular patch antennas, with precise control over antenna patterns to improve signal quality and minimize interference. This article explores the impact of the size of rectangular patch array antenna in the mmWave frequency band. The primary goal is to maximize channel capacity between transmitters and receivers. Our study involves simulations using discretized antenna patterns for various patch array antenna sizes, based on realistic room models and a ray-tracing approach. The results demonstrate that larger antenna arrays can significantly increase network capacity. However, selecting the optimal steering vectors for all antennas becomes more complex with increasing antenna size, but is essential for achieving the best configuration.
The challenge of optimal optical signal transmission in optical fiber networks is crucial for enhancing the network’s reliability, performance, and service quality. Traditional pathfinding methods, such as Dijkstra’s algorithm, focus on finding the shortest path but fail to account for critical factors like optical signal loss and wavelength continuity. This paper proposes a novel algorithm that integrates traditional pathfinding methods with multi-constraint checks to effectively overcome these challenges. Inspired by the similarity between multi-constrained pathfinding in optical networks and vehicle charging path planning model, our approach aims to identify the optimal path in large-scale optical networks quickly. The simulation results demonstrate that our approach successfully addresses the complex requirements of optical signal routing and relay under multiple constraints, achieving promising outcomes.
The response time of Artificial Neural Network (ANN)-inference is of utmost importance in embedded applications, particularly continual stream-processing. Predictive maintenance applications require timely predictions of state changes. This study serves to enable the reader to estimate the response time of a given model based on the underlying platform, and emphasizes the relevance of benchmarking generic ANN applications on edge devices. We analyze the influence of net parameters, activation functions as well as single-and multithreading on execution times. Potential side effects such as tact rate variances or other hardware-related influences are being outlined and accounted for. The results underline the complexity of task-partitioning and scheduling strategies while emphasizing the necessity of precise concertation of the parameters to achieve optimal performance on any platform. This study shows that cutting-edge frameworks don’t necessarily perform the required concertations automatically for all configurations, which may negatively impact performance.
Health risks associated with milk contamination can take many forms. There is currently little data on the trends in microbial contamination and the mapping of its distribution. This study aims to map the spread of microbial contamination in cattle milk throughout ASEAN and assess trends in this area. A database originating from Scopus is collected using Boolean operators. This research used 19,967 papers as references with topics or themes of bacteria, milk, microbes, and antibiotics with loci in the ASEAN region. The analysis results show that 2021 is the peak of article production with 49 articles, followed by 2022 with 40 articles. The most productive institution is Khon Kaen University. Key research topics include antimicrobial resistance, lactic acid bacteria, bovine health issues, and fermentation in milk production. Research on antimicrobial resistance, the use of lactic acid bacteria in dairy products, cow health, and the milk fermentation process needs to be explored further. Collaboration between countries, especially Thailand and Malaysia, must also be improved to produce higher-quality research.
Ultra-light block cipher (ULBC) is a SPN-based block cipher, operates 64 bit state and use 128 bits key. Here, we present meet-in-the-middle (MITM) attack on ULBC. MITM attack strategy proposed by Demirci and Selcuk. In this paper, we partition cipher ULBC in two halves and separate key space by two independent set and observe matching between encryption of first half with decryption of second half. By this method, called MITM attack, we can reduce the key space for exhaustive search. Basic fault analysis of ULBC requires 192 faulty ciphertext to detect full key register. Also, we provide another fault analysis method of ULBC, which requires only average 57 faulty ciphertext to retrieve master key. Here we assume that we can induce nibble fault in after or before substitution layer to any rounds. MITM and differential fault attack particularly exploits weakness like dependency, linearity of designing key schedule.
This work studies performance comparison on radio frequency ($\mathbf{R F}$) energy harvesting ($\mathbf{E H}$) in power splitting (PS) and time-switching (TS) modes in reconfigurable intelligent surfaces (RIS)-aided cooperative spectrum sensing (CSS). CSS model considers multiple primary user (PU) nodes and a single PU emulation attacker (PUEA) node. A distant dependent model of reflected channel gain in RIS antenna is developed for calculating the harvested residual energy (RE). The primary objective is to maximize the total RE while meeting a predefined detection and false alarm probabilities of PU along with the individual secondary user’s (SU’s) energy causality constraint. Simulation results show the efficacy of the proposed work due to the involvement of RIS antenna on total RE, as gain of about 45% and 38.97% for PS and TS modes compared to the existing works while maintaining the above mentioned constraints. Performance of RE with the change in the placement of RIS antenna near/far to PU is analyzed for both PS and TS modes.
Radiofrequency identification (RFID) technology has revolutionized various industries, including transportation systems. This paper explores the implementation of RFID technology in highway toll systems in Malaysia. It focuses on the technical aspects, benefits, challenges, and future prospects of RFID highway sensing. The deployment by PLUS Malaysia Berhad, which integrates automated number plate recognition (ANPR) and aims to achieve a barrier-less, multilane free flow (MLFF) system, is highlighted. This initiative is part of a broader strategy to enhance traffic management and reduce congestion on Malaysian highways.
This research explores the utilization of mobile applications in a leading transportation service company in Indonesia. The study aims to understand how the company drives innovation through its mobile application to meet the demands of an evolving market. Drawing on James March’s innovation theory, which suggests that organizations can innovate through events that create momentum, the research was conducted qualitatively. Interviews were conducted with key personnel responsible for development within the company, as well as 15 customers. The findings indicate that March’s theory and the concept of digital mastery are applicable within the transportation sector, serving as key factors in the company’s shift from a conventional to a technology-focused approach. The study concludes that the organization’s ability to navigate technological disruption was evidenced by its strategic decisions, aligning with March’s concept of innovation through reach events.
This paper focuses on dynamic analysis for malware detection on Android. Initially, a literature review was conducted to understand both static and dynamic analysis approaches and their limitations, particularly highlighting the shortcomings of static analysis. The study demonstrates techniques for extracting various traces, such as system calls and network traffic, using dynamic analysis. The core of the study is the design of an automated system for the dynamic analysis of Android malware. This system automates the capture and analysis of APK traces using modules that monitor system calls, debug logs, and network traffic. It was found that relying on a single dynamic analysis module is insufficient, leading to false negatives, whereas combining data from all three modules enhances detection accuracy. Future directions include developing an intermediary using MQTT to reduce database load and improving the learning process for the three modules.
Firewalls are network security systems positioned between internal and external networks to isolate them. Their fundamental functions include zone isolation, access control, attack protection, and redundancy design. However, firewalls also face numerous security challenges, with Distributed Denial of Service (DDoS) attacks being a major concern, particularly the Denial of Firewalling (DoF) attacks targeting firewalls. Despite extensive research on DDoS attacks against traditional networks, relatively fewer studies focus on DoF attacks. To comprehensively understand the latest research progress and inspire the development of new solutions to counter DoF attacks, this paper conducts an extensive survey of existing research progress and forms a review. Firstly, we analyze the principles of DDoS attacks against firewalls, as well as the security risks of new firewall technologies, and classify them based on attack rates and target components of firewalls. Secondly, we analyze and evaluate the existing DoF attack detection technologies. Next, we summarize the existing DoF attack mitigation techniques. Finally, we discuss current challenges and open issues. We hoped that this research work will assist relevant researchers in effectively addressing DoF attacks.
This study examines the dynamic transformations occurring within public relations ($\mathbf{P R}$) and journalism in Indonesia in response to the advancement of artificial intelligence (AI) technology. The primary aim is to explore how the integration of AI necessitates the continued adherence to ethical codes in PR and journalism practices. The research is anchored in the theoretical frameworks of media ecology and professional ethics. The methodology includes in-depth interviews with 15 participants, comprising PR professionals, journalists, and media experts, to gather primary data. The analysis reveals key themes related to system dynamics, ethical dilemmas, and perceptions of technology use. The findings indicate that while PR practitioners and journalists in Indonesia are increasingly utilizing AI tools in their work, challenges remain due to previous work habits. However, there is a general acceptance of AI as a tool that enhances efficiency. This supports the applicability of media ecology and professional ethics theories to these professions. The study underscores the need for ongoing adaptation to technological advancements while maintaining professional ethical standards.
