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All Journal Indonesian Journal of Electrical Engineering and Computer Science Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Habib Hamam
Université de Moncton
Computer Science & IT Engineering Mechanical Engineering Transportation

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Exploring the intricacies of human memory and its analogous representation in ChatGPT Habib Hamam
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1760-1769

Abstract

Human memory and ChatGPT both rely on associations and patterns to generate contextually relevant responses. We explore how they work in tandem. Both use associations to activate related information when prompted. Memory forms generic representations that become precise with added details, similar to ChatGPT's responses with specific prompts. Activation Through Cues: Memory and ChatGPT recall based on cues or prompts, influenced by input. Level of Detail: Memory constructs mental images based on information, just as ChatGPT responds to input details. Dynamic Nature: Both adapt to memorize repeated segments with diverse continuations. By understanding the dynamics of memory and its parallels with ChatGPT's response generation, researchers can further enhance the model's capabilities. Fine-tuning the model's ability to activate relevant information, generate specific responses, and adapt to varying levels of detail and specificity in the input can contribute to its overall performance and relevance in various language tasks.
Topology Optimization of Passive UHF RFID Systems for Constrained Environments Rahma ZAYOUD; Habib Hamam
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 3 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Radio Frequency Identification (RFID), a remote identification and localization technology, utilizes electromagnetic and magnetic field properties and signal processing. However, this technology suffers from sensitivity issues such as the presence of liquid and metal, object movement, and collision, that negatively affect its reading rate. To address this complex problem, we first demonstrate the strong relationship between the physical RFID topology configuration and its reading rate, based on fundamental principles. Subsequently, we developed an application that determines the best possible reading rate in a hostile environment—where all RFID constraints are present—by optimizing the physical topology configuration. For this purpose, we used the simulated annealing algorithm as an optimization technique. These algorithms are structured methods implemented in programming languages to solve complex problems by maximizing or minimizing an objective function under specific constraints. The results are promising: the algorithm converged three times to the same optimal solution within a single run; it required 48.5% of total iterations to find this configuration, which achieved a reading rate of 42.5% in a hostile environment. This optimal rate is considered satisfactory, especially when compared to the initial configuration's reading rate of approximately 7.5% under the same conditions.
Co-Authors Rahma ZAYOUD