International Journal of Advanced Communication Technology (IJACT)

Efficient Hexagonal Gridding Method for DNA Microarray Image

Maziidah Mukhtar Ahmad — 2024-11-19

In genetics, a deoxyribonucleic acid (DNA) microarray is a useful instrument that is frequently used to track thousands of genes' expression levels simultaneously. For DNA microarray, gene expression is done through microarray spot gridding, segmentation and intensity extraction. The gridding processes identify each microarray spot location and supply their coordinates for the spot. Many microarray technologies arrange their microarray spots in in rectangular fashion. However, a hexagonal grid arrangement is also being used to increase the density of the spot per unit area. While gridding microarray arranged in rectangular fashion is straightforward, gridding microarray arranged in hexagonal fashion posed its own challenge due to the irregular structure of the spot location. To solve this problem, this paper discusses two proposed methods to perform gridding for microarrays arranged in a hexagonal fashion, namely alternate-column and diamond-shape methods. These methods have been evaluated in nine different benchmark images that represent best, typical and worst-case images. Based on our experiments, the proposed diamond-shape and alternate-column methods achieved an average accuracy of 93.6% and 92.1%, respectively. In terms of computational load, the diamond shape consumes three times less computational loads as compared to the alternate-column.

A Comparative Study of Binary and Fibonacci Decomposition Watermarking for Medical Images

Norsabihah Adnan — 2024-11-19

This study addresses the critical challenge of embedding additional information into medical images, specifically focusing on the trade-off between watermark capacity and visual quality. The importance of this challenge lies in maintaining the diagnostic value of medical images while securely embedding auxiliary data such as patient identifiers or copyright information. The study conducts a comparative analysis of two watermarking schemes: binary decomposition and Fibonacci decomposition. The binary and Fibonacci decompositions were specifically applied by utilizing modified binary watermarks and leveraging the specific domain properties of the host medical images to minimize disruptions during the embedding process. The evaluation was performed on a dataset of brain magnetic resonance imaging (MRI) images. The watermark capacity was varied to assess its impact on visual quality, which was quantified using Peak Signal-to-Noise Ratio (PSNR). The results demonstrated that the Fibonacci decomposition method achieved a higher watermark capacity of up to 3.5 bpp while maintaining high visual quality, with an average PSNR value of 76.5 dB. These results indicate that the Fibonacci decomposition approach offers significant advantages in achieving a balance between high capacity and minimal image distortion, making it a promising solution for medical image watermarking applications.

Bibliometric Analysis Of Travelling Salesman Problem With Drones (TSP-D)

Yugeswary Kanesen — 2024-12-30

The growing need for efficient package delivery systems in Last Mile Delivery (LMD) has attracted significant attention, bringing the Travelling Salesman Problem with Drones (TSP-D) to the forefront of scholarly research. The research under consideration generated a surge in scientific output across various domains, including economics, industry, and logistics, owing to the potential benefits it presents. The primary objective of this study is to compile, organize, and analyze the literature on TSP-D in the context of LMD. A comprehensive bibliometric analysis scrutinized the progress made in this field during the period spanning 2017 to 2024. The study encompassed an extensive analysis of a corpus of 2,397 scholarly publications, yielding numerous intriguing conclusions derived from a meticulously constructed framework. This review addresses inquiries about the most prevalent research categories on resolving TSP-D, focusing on exact and metaheuristic approaches.

Performance Evaluation of Fault Tolerance in 6G Software Defined Network (SDN)

Lim Jia Chyin — 2024-12-30

Traditional Operations and Maintenance (O&M) have made real-time fault location of devices challenging due to the rapid growth of network devices. Therefore, Intelligent O&M in 6G networks leveraged using Software Defined Network (SDN) are expected to optimise network operations through fault tolerance mechanisms. SDN is an emerging paradigm that offers dynamic and efficient solutions to the complex network environment. This paper provides a comprehensive overview of fault tolerance as a critical algorithm for SDN under Intelligent O&M, evaluating the performance of fault tolerance mechanisms and investigating the effectiveness of fault tolerance mechanisms towards TCP, UDP and ICMPv4 with two different scenarios. Simulation results demonstrate that the proposed fault tolerance mechanisms under Intelligent O&M within a 6G network can reduce the delay by 98.79%, ensuring more reliable network infrastructure.

Optimizing Drone-Based Delivery Using the Pity Beetle Algorithm A Novel Approach.

Yugeswary Kanesen — 2024-12-31

The Travelling Salesman Problem with Drones (TSP-D) has emerged as a significant optimization challenge in last-mile delivery systems. Addressing scalability issues with datasets exceeding 250 nodes, this study introduces the Pity Beetle Algorithm (PBA), a novel metaheuristic. The PBA demonstrates superior performance in balancing exploration and exploitation to optimize delivery routes effectively. Results from new simulations conducted for this journal show delivery time reductions in a broader range of scenarios, with improvements up to 60% over standard benchmarks. Statistical analyses confirm the algorithm’s capability to enhance computational efficiency and scalability. Additionally, the PBA’s dynamic tuning mechanisms enable it to adapt effectively to varying dataset sizes and configurations. Beyond its computational benefits, this study underscores the real-world applicability of the PBA in logistics, providing industries with a robust tool to optimize delivery times and reduce operational costs. This research opens avenues for integrating PBA with hybrid models and real-time optimization techniques, further enhancing its potential to tackle complex logistical challenges.