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2nd Workshop on Cross-Cultural Considerations in NLP, C3NLP 2024

作者： Baltaji, Razan Hemmatian, Babak Varshney, Lav R. Department of Electrical and Computer Engineering United States Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign United States

ISBN: (纸本)9798891761469

This study explores the sources of instability in maintaining cultural personas and opinions within multi-agent LLM systems. Drawing on simulations of inter-cultural collaboration and debate, we analyze agents’ pre- and post-discussion private responses alongside chat transcripts to assess the stability of cultural personas and the impact of opinion diversity on group outcomes. Our findings suggest that multi-agent discussions can encourage collective decisions that reflect diverse perspectives, yet this benefit is tempered by the agents’ susceptibility to conformity due to perceived peer pressure and challenges in maintaining consistent personas and opinions. Counterintuitively, instructions that encourage debate in support of one’s opinions increase the rate of inconstancy. Without addressing the factors we identify, the full potential of multi-agent frameworks for producing more culturally diverse AI outputs will remain untapped. © 2024 Association for Computational Linguistics.

关键词： Chatbots

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A Hyperbolic Micromagnet for Multiple Spin Qubits with Fast Rabi Oscillations and High Addressability

IEEE Electron Device Letters

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IEEE Electron Device Letters 2024年第4期45卷 526-529页

作者： Chang, Che-Hao Li, Yu-Cheng Wu, Yu-Jui Liao, Chen-Yao Lin, Min-Jui Tsao, Hung-Yu Li, Jiun-Yun Graduate Institute of Electronics Engineering National Taiwan University Taipei10617 Taiwan Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA02139 United States National Taiwan University Department of Electrical Engineering Graduate Institute of Electronics Engineering Graduate School of Advanced Technology Taipei10617 Taiwan Taiwan Semiconductor Research Institute Hsinchu30078 Taiwan

We demonstrate a hyperbolic micromagnet to increase the manipulation speed of electron spins in silicon quantum dots using electric dipole spin resonance (EDSR). For single qubits, the hyperbolic magnet provides a large gradient of transverse magnetic fields of 4.9 mT/nm with the corresponding Rabi frequency ( 69 MHz). We then demonstrate that this hyperbolic micromagnet can drive a linear array of qubits with Rabi frequencies of 19 69 MHz and a high addressability (minimum difference of Larmor frequencies) up to 590 MHz to suppress the crosstalk between different qubits. We show that 15 qubits can be effectively addressed for high fidelity by this hyperbolic micromagnet. © 1980-2012 IEEE.

关键词： Magnetic fields

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Lightweight, High-Entropy TRNG Using Quad Cross-Coupled Feedback Architecture

Lightweight, High-Entropy TRNG Using Quad Cross-Coupled Feed...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Williams, Shelby Kirtonia, Prosen Akter, Sonia Khalil, Kasem Bayoumi, Magdy Univ. of Mississippi Department of Electrical and Computer Engineering OxfordMS38677 United States Univ. of Louisiana at Lafayette Center for Advanced Computer Studies LafayetteLA70504 United States Univ. of Louisiana at Lafayette Dept. of Electrical and Computer Engineering LafayetteLA70504 United States

ISBN: (纸本)9798331504847

This paper presents a lightweight, high-entropy true random number generator architecture featuring an innovative quad cross-coupled feedback mechanism to enhance randomness. The primary goal is to develop an efficient and secure true random number generator that addresses the growing demand for reliable random number generation in cryptographic and security-critical applications. The motivation stems from the need to improve entropy, reduce resource utilization, and ensure robustness across varying technologies. With the intention of achieving near-perfect randomness, the Quad-Input Oscillating Circuit module integrates self-coupled, jitter-inducing ring oscillators with cross-coupled feedback loops to induce metastability. Comprehensive evaluations confirm a Shannon entropy of 0.999818, a minimum entropy of 0.977257, and a collision entropy of 0.999636. The design was synthesized using Synopsys Design Compiler at 45 nm, 32 nm, and 14 nm, achieving a maximum frequency of 6.7 GHz, power consumption as low as 72 μW, and area utilization of 24 μ m2 at 14 nm. Rigorous validation through multiple statistical test suites, including the AIS-31, Autocorrelation, Deviation, Diehard, the National institute of Standards and Technologies SP800-22 and SP800-90B, and TestU01, confirms its efficiency and reliability. Real random bits were implemented as oscilloscope-viewable signals on the Cyclone V Field Programmable Gate Array developed by Altera, representing a significant advancement in secure random number generation technologies. © 2025 IEEE.

关键词： Field programmable gate arrays (FPGA)

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IOT Design and Water Monitoring of an Aquaponic System 3

IOT Design and Water Monitoring of an Aquaponic System

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3rd IEEE International Conference on Signal, Control and Communication, SCC 2023

作者： Asma, Takrouni Hedfi Mohamed, Houmia Kaouther, Laabidi Omri Higher Institute of Technological Studies Electrical Engineering Department Tozeur Tunisia Network and Engineering University of Jeddah Department of Electrical and Computer Saudi Arabia

ISBN: (纸本)9798350326390

The concept of smart agriculture involves integrating fish and plants in the same environment. This paper showcases an aquaponics system that utilizes an Arduino board, sensors, and hardware devices for its design and monitoring. The system is a closed-loop ecosystem that combines fish farming (aquaculture) and soilless plant growing (hydroponics). This innovative approach is beneficial for both the aquaculture and horticultural sectors as it enables the permanent reuse of water for breeding and reduces the use of chemical inputs in crop production management. The aquaponic system is self-regulating and can adjust itself when the pH, temperature, and water level sensors indicate that they are out of range. This is accomplished by combining the concept of embedded systems with the IOT (Internet of Things). © 2023 IEEE.

关键词： Hydroponics

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Quantum-Enhanced Zero Trust Security: Evolution, Implementation, and Application 1

Quantum-Enhanced Zero Trust Security: Evolution, Implementat...

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1st International Conference on Quantum Communications, Networking, and Computing, QCNC 2024

作者： Lin, Jun Jiang, Qiu Zhang, Weiyong Lin, Zihao Du, Xiaojiang Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States

ISBN: (纸本)9798350366778

In today's fast-paced digital economy, the widespread adoption of new technologies brings about significant challenges in network security. This paper delves into the evolution of Zero Trust network architecture, marking a significant shift from traditional perimeter-centric security methods. It embraces the 'never trust, always verify' philosophy, moving away from conventional approaches. Subsequently, the paper explores the strategic implementation of Zero Trust, focusing on essential components such as Policy Enforcement Points (PEP) and Identity and Access Management (IAM). It also addresses the challenges in deploying Zero Trust architectures, including the high demands for real-time detection, and suggests viable solutions to these challenges. An important aspect of this study is the emerging role of quantum technology in enhancing network security. The integration of quantum technology with Zero Trust principles is poised to offer more robust network protection, particularly with the advancements in quantum key research. Current research in quantum keys opens new avenues for applying the Zero Trust philosophy in practical scenarios. This fusion is instrumental in laying the foundation for a more secure and innovative network security framework, aiming to effectively counter the evolving digital threats and strengthen the infrastructure of the digital economy against potential vulnerabilities. © 2024 IEEE.

关键词： Network Security Quantum Technology Zero Trust

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Market-Based Environmental Policies in the Power Sector: State of the Art and Future Research Needs

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Current Sustainable/Renewable Energy Reports 2023年第3期10卷 59-74页

作者： Siddiqui, Afzal S. Tanaka, Makoto Chen, Yihsu Department of Computer and Systems Sciences Stockholm University Kista Sweden Department of Mathematics and Systems Analysis Aalto University Espoo Finland National Graduate Institute for Policy Studies Tokyo Japan Department of Electrical and Computer Engineering and Environmental Studies Department University of California Santa CruzCA United States

Purpose of Review: So-called Green New Deals aim to decarbonise the power sector via market-based instruments. Consequently, engineering-economic models for analysing the sustainable-energy transition have proliferated. This review categorises existing approaches and identifies areas for extending the state of the art. Recent Findings: We cluster the extant literature into two groups: engineering/operational research (M1) and environmental economics (M2). While M1 focuses on the power sector’s technical and spatio-temporal aspects, M2’s emphasis is on incentives and externalities. Depending on the nature of the research question, either perspective (or both) may be suitable. Summary: Since the envisaged electrification of the wider economy implies tighter coupling between formerly distinct sectors, e.g., power and heat, both M1 and M2 will have to adapt to the new paradigm in terms of methodology and application areas. Here, eliciting coordinating mechanisms, enhancing algorithms for solving hierarchical models, soft linking bottom-up and top-down models, and crafting robust environmental policy in face of uncertainty over externalities are some of the vistas for future research. © 2023, The Author(s).

关键词： Game theory

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Signal Conducting System with Effective Optimization Using Deep Learning for Schizophrenia Classification

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computer Systems Science & engineering 2023年第5期45卷 1869-1886页

作者： V.Divya S.Sendil Kumar V.Gokula Krishnan Manoj Kumar School of Electrical and Electronics Engineering Sathyabama Institute of Science and TechnologyChennaiTamilnaduIndia Department of Electrical and Electronics Engineering S A Engineering CollegeChennaiTamilnaduIndia Department of Computer Science and Information Technology CVR College of EngineeringMangalpallyHyderabadTelanganaIndia School of Computer Science University of Petroleum and Energy StudiesDehradunIndia

Signal processing based research was adopted with Electroencephalogram(EEG)for predicting the abnormality and cerebral *** proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or *** detection and intervention are vital for better ***,the diagnosis of schizophrenia still depends on clinical observation to *** reliable biomarkers,schizophrenia is difficult to detect in its early phase and hence we have proposed this *** this work,the EEG signal series are divided into non-linear feature mining,classification and validation,and t-test integrated feature selection *** this work,19-channel EEG signals are utilized from schizophrenia class and normal ***,the datasets initially execute the splitting process based on raw 19-channel EEG into 6250 sample point’s *** this process,1142 features of normal and schizophrenia class patterns can be *** other hand,157 features from each EEG patterns are utilized based on Non-linear feature extraction process where 14 principal features can be identified in terms of considering the essential *** last,the Deep Learning(DL)technique incorporated with an effective optimization technique is adopted for classification process called a Deep Convolutional Neural Network(DCNN)with mayfly optimization *** proposed technique is implemented into the platform of MATLAB in order to obtain better results and is analyzed based on the performance analysis framework such as accuracy,Signal to Noise Ratio(SNR),Mean Square Error,Normalized Mean Square Error(NMSE)and *** comparison,the proposed technique is proved to a better technique than other existing techniques.

关键词： Deep learning optimization algorithm signal conducting system schizophrenia convolutional neural network mayfly optimization algorithm

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Backpropagation Shuffled Leaping Neural Network Implementation in Classification of DDoS Packet Flow Traffic in Data Mining

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SN computer Science 2024年第8期5卷 1131页

作者： Umamaheswari, N. Kumutha, K. Kalaivani, M.S. Ramya, R. Tagore College of Arts and Science Tamilnadu Chennai India Department of Computer Application- PG Vels Institute of Science Technology and Advanced Studies Tamilnadu Chennai India Department of Computer science and Engineering Bannari Amman Institute of Technology Tamil Nadu Erode India

All web applications remember the ultimate goal of storage services, Distributed Denial of Service (DDoS), to achieve high security from various attacks. The client-server application reduces fees and runs the elite registration gadget, while the notable part assumes that it is manufactured using a grant application. Analysis of the traceback data is difficult in the previous system, and then it containsa common DDoS attack *** DDoS attacks involving different network layers such as (SIDDoS (SQL (Structured Query Language) injection), HTTP (HyperText Transfer Protocol) flood, TCP (Transmission Control Protocol) are recommended here as there are signs that new datasets of common datasets are not being collected in the proposed system. The DDoS attack classification consists of three main steps: preprocessing, trace out the source IP address, Backpropagation Shuffled Leaping Neural Network (BSLNN) based on maintaining the specifications’ integrity. The preprocessing is the first step based on the Gabor Filter used to remove the data’s noise and the second Adaboost Random Optimal Selection method to analyzethe packet flow’s relative frequency. The third step is the Backpropagation Shuffled Leaping Neural Network (BSLNN) classification of traceback data maintaining the specifications analysis’s integrity. The proposed system achieves good periodic study of packet flow accuracy and time complexity. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adaboost random optimal selection Backpropagation Shuffled Leaping Neural Network (BSLNN) Gabor filter Preprocessing Trace out the source IP address

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Energy-aware resource management in fog computing for IoT applications: A review, taxonomy, and future directions

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Software - Practice and Experience 2024年第2期54卷 109-148页

作者： Hashemi, Sayed Mohsen Sahafi, Amir Rahmani, Amir Masoud Bohlouli, Mahdi Department of Computer Engineering Qeshm Branch Islamic Azad university Qeshm Iran Department of Computer Engineering South Tehran Branch Islamic Azad University Tehran Iran Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou Taiwan Department of Computer Science and Information Technology Institute for Advanced Studies in Basic Sciences Zanjan Iran Research and Innovation Department Petanux GmbH Bonn Germany Zanjan Iran

The energy demand for Internet of Things (IoT) applications is increasing with a rise in IoT devices. Rising costs and energy demands can cause serious problems. Fog computing (FC) has recently emerged as a model for location-aware tasks, data processing, fast computing, and energy consumption reduction. The Fog computing model assists cloud computing in fast processing at the network's edge, which also exerts a vital role in cloud computing. Due to the fast computing in fog servers, different quality of service (QoS) approaches have been proposed in various sections of the fog system, and several quality factors have been considered in this regard. Despite the significance of QoS in Fog computing, no extensive study has focused on QoS and energy consumption methods in this area. Therefore, this article investigates previous research on the use and guarantee of Fog computing. This article reviews six general approaches that discuss the published articles between 2015 and late May 2023. The focal point of this paper is evaluating Fog computing and the energy consumption strategy. This article further shows the advantages, disadvantages, tools, types of evaluation, and quality factors according to the selected approaches. Based on the reviewed studies, some open issues and challenges in Fog computing energy consumption management are suggested for further study. © 2023 John Wiley & Sons Ltd.

关键词： Quality of service

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A Comprehensive Review on the Prediction of Video Frame and Motion Contents

A Comprehensive Review on the Prediction of Video Frame and ...

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2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Mohana Priya, P. Ulagapriya, K. Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331541170

ISBN: (纸本)9798331541187

The capability of predicting, or analyzing the future outcomes of motion pictures using intelligent systems is the video frame prediction process. Video frame prediction is a significant and challenging aspect of computer Vision (CV) applications. Video prediction plays a vital role in terms of robotics and Artificial Intelligence (AI) applications in detecting the future frames of a video, depending on which, the decision-making process can be carried out. The existing video frame prediction processes include pixel law based and motion-based predictions, which have been proven to be ambiguous. This leads to inaccurate predictions and indirectly deteriorates the performance of the real time applications. This paper performs a detailed review of the existing methodologies, their merits, pitfalls and challenges that create havoc in the video frame prediction process. In addition, this paper performs a detailed analysis on the existing datasets that assist in the video prediction process. This review summarizes various methodologies and datasets along with their performance analysis, which will open research possibilities in the field of video frame prediction. © 2024 IEEE.

关键词： Artificial Intelligence computer Vision Datasets Robotics Video frame prediction

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