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Dahlan Abdullah
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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
Core Subject : Science, Education, Social, Engineering,
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation
The journal covers all aspects of applied engineering, applied Science and information technology, that is: Engineering: Energy Mechanical Engineering Computing and Artificial Intelligence Applied Biosciences and Bioengineering Environmental and Sustainable Science and Technology Quantum Science and Technology Applied Physics Earth Sciences and Geography Civil Engineering Electrical, Electronics and Communications Engineering Robotics and Automation Marine Engineering Aerospace Science and Engineering Architecture Chemical & Process Structural, Geological & Mining Engineering Industrial Mechanical & Materials Science: Bioscience & Biotechnology Chemistry Food Technology Applied Biosciences and Bioengineering Environmental Health Science Mathematics Statistics Applied Physics Biology Pharmaceutical Science Information Technology: Artificial Intelligence Computer Science Computer Network Data Mining Web Language Programming E-Learning & Multimedia Information System Internet & Mobile Computing Database Data Warehouse Big Data Machine Learning Operating System Algorithm Computer Architecture Computer Security Embedded system Coud Computing Internet of Thing Robotics Computer Hardware Information System Geographical Information System Virtual Reality, Augmented Reality Multimedia Computer Vision Computer Graphics Pattern & Speech Recognition Image processing ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT in education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 79 Documents
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Search results for , issue "Vol 5, No 2 (2025)" : 79 Documents clear
Sustainable Supply Chain Practices in Engineering-Based Manufacturing Firms Nuritdinovich, Muhidinov Ayubbek; Vij, Priya
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1494

Abstract

Sustainable Supply Chain Management (SSCM) assesses the environmental implications associated with all conventional supply chain (SC)activities to mitigate their adverse effects. This study presents a fuzzy-based methodology for examining obstacles in SSCM within the environment. Seven manufacturing companies from the electronics industry are participating. The study's findings reveal three primary challenges in engineering-based manufacturing firms. The barriers include knowledge-related factors (insufficient understanding of the adverse effects on business, absence of training programs for industry-specific training, monitoring, and mentoring, lack of technical expertise, and challenges in recognizing environmental possibilities), commitment-related issues (deficiency in corporate social accountability), and design-related challenges (complexities in designing for the reusing/recycling of used goods).The suggested research is among the first investigations undertaken within the environment regarding identifying SSCM barriers in the electrical and electronics industry. Secondly, the obstacles are examined via causation and prominent relationships, which assist decision-makers, policy developers, and organizational managers tackle the essential factors necessary to achieve SSCM activities.
Blockchain-Enabled Secure Data Sharing Framework for Healthcare IoT Devices Jing, Qi
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1520

Abstract

Medical data security challenges have increased dramatically because healthcare institutions continue to integrate more Internet of Things devices to deliver data-driven clinical services. Access control systems based on RBAC, ABAC and MAC do not meet the requirements of flexible protection and scalable and context-aware security which are needed for dynamic healthcare environments. The research objective focuses on creating a resilient decentralized access control solution which delivers secure time-sensitive access permissions in healthcare IoT systems. A blockchain-based hybrid access control framework with RBAC and ABAC provides the solution to meet this requirement. A dual mechanism of smart contracts and IPFS storage runs the model while variables and user-facing elements shift based on environmental characteristics and individual circumstances. Results from experimental evaluation show that this proposed framework delivers 96.5% access precision together with policy evaluation times below 3.2 ms and 120 ms response times while handling 74 transactions per second while remaining affordable at $2.1 and demanding 45 to 52 MB from critical system memory. The obtained results demonstrate better scalability together with enhanced performance and adaptability when compared to using ABAC, RBAC and MAC singularly. Healthcare IoT systems should implement a blockchain-based hybrid access control system as an optimal method to secure data sharing in real-time resource-constrained scenarios.
Real-time Image Processing in Embedded Vision Systems for Autonomous Vehicles Venugopal, Vedanarayanan; Mohanty, Monalisa; Boregowda, Vinay Kumar Sadolalu; Singh, Suraj; Singh, Manpreet; Deepthi, Pochampalli; Deepak, Shashikant
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1495

Abstract

The most recent studies show that the benefits of the IT improvements associated to ads were substantial. These days, there is a lot of controversy over the optimal way to store, retrieve, and access personal and other data.Since systems are developing so quickly and clients may now access information virtually from anywhere, delivering personal or official information on a physical device has become outdated. This is how distributed computing has emerged and expanded to meet the needs of efficiency, security, unwavering quality, and laziness. The widespread use of Internet of Things devices promises to alter some aspects of our lifestyle. The delivery of human services services is being transformed by other individual Internet of Things devices, such as wearable wellness, wellness monitoring devices, and system-powered restorative devices. This invention promises to benefit the elderly and others with disabilities, enabling higher degrees of independence and personal fulfilment at an affordable price. According to the legally enforceable claim, the Internet of Things connects everything to the Internet, conducts data exchange, and transmits information via data-detecting devices including sensors, RFID, and global positioning systems. The Web of Things must be designed to detect, guide, and filter objects in order to provide clients with a variety of innovative data management services. The effects on transportation planning of autonomous cars, often known as self-driving, driverless, or robotic vehicles. Based on past vehicle technology experience, it examines the likelihood of such vehicles developing and being used quickly, their potential costs and benefits, how they will impact travel behaviour, and how they will influence planning choices like the best parking, roads, and public transportation options.
Study on Seismic Performance of Rebar Sleeve Grouting Connection in Prefabricated Concrete Buildings Syamsunur, Deprizon; Naiyuan, Cui; Surol, Salihah; Hisyam Jusoh, Muhammad Noor; Md Noh, Nur Ilya Farhana; Ardana, Putu Doddy Heka
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1530

Abstract

This research aims at assessing the reliability of rebar sleeve grouting connections used in P.C building under cyclic lateral loadings. Such connections are necessary for structural stability at the time of an earthquake. It is essential to determine their performance for improving the safety in prefabricated structures. For the research, three full scale column to foundation samples that used standardized construction materials and methods were used in testing. Rebar sleeve grouting connections were each confined and encased in high strength grout and had ribbed steel sleeves to enhance the mechanical interlocking. Specific performance factors like load transfer efficiency, deformability and energy absorption were recorded as lateral cyclic loads were progressively applied to simulate actual seismic actions. Measurements were made using load cells, displacement transducers, and strain gauges while videotaping of the experiment was done with normal and high-speed cameras. The analysis also showed that of all the factors, sleeve geometry, grout quality and bond strength means have larger impact on seismic performance. Energy dissipation and deformation capacity was captured by displaying that ductile failure modes included rebar yielding and controlled grout cracking. All these findings are relevant to understanding the learnings available for the prefabricated structure design in improving the construction practices and defining the standard tests required to enhance the Seismic performance of the structures.
AI-Powered Adaptive Metamaterials for Reconfigurable Optoelectronics Soy, Aakansha; Nayak, Ashu; Joshi, Praveen Kumar
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1491

Abstract

Coming from the breakthrough of AI-powered adaptive metamaterials (AI-AM), as reconfigurable optoelectronics, these represent a technology that allows real-time, autonomous optical and electronic control. This work presents an AI-AM framework based on machine learning, reinforcement learning, and neuromorphic computing, which aims to develop a new artificial intelligence that optimally dynamically modifies metamaterial behavior. In contrast to traditional metamaterials, the proposed system implements self-adjusting of the wavelength selectivity, polarization, and beam steering at the nanoscale using AI-driven control focused on environmental stimuli. It uses generative AI models to come up with the most optimal material configurations, reinforcement learning to adapt the tuning process, and edge AI processors for running optimised decisions in nanoseconds. For the evaluation and simulation, it is shown that active and passive integrated circuits are capable of significant improvements for response time, energy efficiency, and functional adaptability, compared to conventional approaches. Some key applications of smart lenses for augmented reality, beam steering for 5G/6G networks in AI mode, quantum-enhanced sensor and hardware configuration for neuromorphic photonic processors, etc. This work proposes a paradigm shift in the optoelectronic technology and bridges the gap between artificial intelligence and material science. Based on this study, the potential of using AI augmented metamaterials for revolutionizing photonics, communications, and quantum computing, and next-generation AI intelligent optoelectronic devices with highly reconfigurable, highly efficient, and highly multifunctional properties is demonstrated. The other two areas that future research will address will be scalability, advanced AI training models, and broader real-world applications.
Machine Learning-guided Synthesis of Quantum Entangled Materials Vij, Priya; Nandy, Manish; Pandey, Mamta
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1496

Abstract

The synthesis of materials into quantum entangled materials is a complicated challenge to an accurate and computational prediction of those materials. In this proposed work, it develops an AI-guided framework based on the combination between machine learning (ML) and reinforcement learning (RL), and quantum simulations to push the designing and validating of quantum materials at a much faster pace. In the first, graph neural networks (GNNs) are used to extract the atomic level quantum features, and in the second, generative models (VAE/GAN) are utilized to discover some novel entangled structures. In addition, fabrication with the synthesis parameters as parameters in the reinforcement learning results in an improvement of the experiment synthesis and a decrease of experiment failures as well as significant improvement of reproducibility. It demonstrates that the proposed hybrid ML-quantum simulation is validated on entanglement fidelity in real-world quantum computing platforms using IBM Qiskit and Google Cirq. As the proposed method is way beyond traditional ones, it has higher quantum coherence time, synthesis efficiency as well as higher prediction accuracy. In addition to enabling scaling-up of cryptography, quantum computing, and next generation nanomaterials, it is a cost and scalable framework for creating next generation quantum technologies applications as it is. And the model is further researched for the generalization in regards to real-time experimental feedback and for the expansion of the framework to a more general quantum materials program. The results show that AI approaches can truly accelerate the quantum material innovation even when syntheses are not at all possible.
Artificial Intelligence in Film and Television Production: Idea Generation and Post-Production Li, Kang
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1531

Abstract

This paper takes the impact of artificial intelligence on film and television art creation as the topic, from the creative generation of film and television art creation and post-production, two aspects of the impact of artificial intelligence on film and television production. The impact of artificial intelligence on film and television production for a more in-depth discussion and research, combined with examples of research and analysis, the use of science and technology point of view theory of film and television art creation in the new era of the artistic impact of the presentation of a specific description. Through the study, artificial intelligence plays a pivotal role in the process of film and television production, from pre-planning to script writing to later video editing and special effects production. The successful use of artificial intelligence in the field of film and television art creation has a great impact on the overall value chain involving the film and television industry, which is of great social significance.
AI-Assisted Animation Storyboard Design and Automated Storyboard Generation Ou, Han
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1534

Abstract

This paper develops an Artificial Intelligence assisted animation storyboard design framework that uses Stable Diffusion 1.5 (SD-1.5) together with Visual Geometry Group 1-Convolutional Neural Network (VGG-1CNN) and Generative Pre-trained Transformer 3.5 (GPT-3.5) to produce automated game character images and narrative-focused storyboards. The proposed system utilizes combined text and sketch prompts for generating storyboard frames which preserve visual coherence together with stylistic continuity. The three main elements that power improved image generation through advanced diffusion control techniques include Contrastive Language-Image Pretraining (CLIP) neural networks and VGG-1CNN and Variational Autoencoder (VAE). The sequence starts by translating textual descriptions into numerical latent space codes using a neural network before the computer generates images based on these guidelines. The basic sketch receives edge detection through Canny edge maps to give better results in image refinement. By applying the VGGNet architecture to vector representations of generated images the system improves visual precision together with prompt compliance. The image quality receives additional enhancement through an iterative scheduler-based removal of noise which refines vector representations during multiple successive stages. The deployment of GPT-3.5 gives the system ability to create written narratives suited for each story frame while preserving narrational continuity. A decoder-based upscaling technique applies to the final output to generate high-resolution visually appealing storyboard frames that properly highlight the visual elements alongside textual content. The automated solution established through this model delivers an efficient pre-production animation pipeline automation that minimizes work efforts and conserves artistic and narrative quality.
Digital Detox and Mindfulness: Psychological Effects of Reducing Mobile App Usage Among University Students Norquziyeva, Zebo; Davlatova, Zebo; Kholnazarov, Umid; Edilboyev, Unarbek; Sattorova, Zilola; Xamrakulova, Kamola; Nurullayeva, Nodira; Shabbazova, Dilfuza
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.1493

Abstract

In the contemporary digital era, college students are among the most frequent users of mobile applications and social media systems, raising substantial worries around addiction to technology. Although online resources provide many benefits, their improper usage and excessive reliance present significant risks. This research examines the impacts of a one-day Digital Detox (DD) program on undergraduates in Uzbekistan, concentrating on the consequences of refraining from smartphone use. The detox camp, modeled after similar programs, sought to assess the effects of a total DD. The research used qualitative approaches, conducting comprehensive conversations with respondents to evaluate improvements in self-awareness, connections with others, and general well-being. The results showed that people were more aware of themselves, had better connections, and felt much more relaxed. There were problems like Nomophobia (the fear of being without a mobile device) and FOMO (the fear of missing out).The findings demonstrate that DD programs significantly reduce digital reliance and promote conscious technology use among students. This study improves what we already know about the benefits of DD approaches and points out areas that need further research and application.

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