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Decision Aid Sciences and Application (DASA), International Conference on

作者： Haider K. Hoomod Mohammad Alaa Al-Hamami Aqeel Kamil Kadhim Qutaiba Humadi Mohammed Jolan Rokan Niaf College of Education Mustansiriyah University Baghdad Iraq Department of Management Information Systems Applied Science University Manama Kingdom of Bahrain Computer Techniques Engineering Department Imam Al-Kadhim College Baghdad Iraq College of Nursing University of Baghdad Baghdad Iraq Informatics Institute for Postgraduate Studies University of Information Technology and Communications Baghdad Iraq

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

With the advent of the Internet of Things, a world was born in which everything could be uniquely identified and monitored, tracked, and managed by computer programs. Items can self-configure using a predefined communication protocol. Other software programs can be linked to operate together using Message Queue Telemetry Transport Protocol (MQTT) or MQSeries components. Business integration software and middleware are common terms for this category of applications. With its suggested lightweight, easy-to-implement, and lowbandwidth system for billions of smart items, the MQTT protocol offers a wide range of potential applications, including home automation. In order to enhance the power savings in MQservice routing, we presented an intelligent assistant for optimizing routing model. For Internet of Things (IoT) purposes, it introduces an optimal routing model based on optimized hybrid machine learning-based anomaly detection (OHMLA). In order to extend the reach of a network, the offered approach allows Internet of Things devices to make efficient use of energy. To further enhance Intrusion Detection identification and get optimum network selection routes, the moth Salp Swarm technique (SSA) technique is used for the optimized hyperparameters. The model is capable of accurately detecting attacks that result in network congestion, causing delays in connection response and data transfer in IoT network.

关键词： Transport protocols Network intrusion detection Machine learning Routing Data transfer Data models Delays Classification algorithms Internet of Things Intelligent sensors

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AlGaAs soliton microcombs at room temperature

AlGaAs soliton microcombs at room temperature

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Conference on Lasers and Electro-Optics (CLEO)

作者： Lue Wu Weiqiang Xie Chao Xiang Lin Chang Yan Yu Hao-Jing Chen Yoshihisa Yamamoto John E. Bowers Kerry J. Vahala Myoung-Gyun Suh T. J. Watson Laboratory of Applied Physics California Institute of Technology Pasadena CA USA Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA USA Physics & Informatics Laboratories NTT Research Inc. Sunnyvale CA USA

Soliton generation in AlGaAs microresonators at room temperation is reported for the first time. The destabilizing thermo-optic effect is shown to instead provide stability for high soliton repetition rates. The optic... 详细信息

ISBN: (纸本)9781957171258

关键词： Dielectric microcavities Frequency combs Microresonators Mode locking Q factor Thermo optic effects

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Design and Fabrication Challenges of Integrated Optical Circuits for Quantum Computing Applications

Design and Fabrication Challenges of Integrated Optical Circ...

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International Conference on Transparent Optical Networks

作者： Simeon I. Tsintzos Konstantinos Tsimvrakidis Alexandra Sinani Adonis Bogris James C. Gates Peter G.R. Smith Ali W. Elshaari Val Zwiller Christos Riziotis National Hellenic Research Foundation Theoretical & Physical Chemistry Institute Athens Greece Department of Informatics and Computer Engineering University of West Attica Egaleo Greece Optoelectronics Research Centre University of Southampton Southampton United Kingdom Department of Applied Physics Royal Institute of Technology (KTH) Stockholm Sweden Institute for Advanced Modelling and Simulation University of Nicosia Nicosia Cyprus

The paper presents current design issues, limitations, and fabrication challenges towards the development of hybrid integrated optical circuits with embedded single photon sources, which are critical components for future quantum computing, sensing, and communication systems. Optical nanowires with embedded quantum dots (NWQD) are very promising single photon sources, with several reported results of integration in high index platforms like silicon or silicon nitride. Silica on silicon is a favorable platform for optical computing, providing the high degree of customization when combined with direct laser writing techniques for definition of optical structures with refractive index modification. However, the low ~10 -3 achievable refractive index contrast imposes strict limitations on the compatibility with NWQD resulting in general in low coupling efficiency as shown in this work. Consideration of several design and fabrication issues demonstrates the potential for NQWD integration in laser written silica based optical circuits with adequate efficiency for practical applications.

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Digital Twin Definition for Detecting Abnormal Perspiration Patterns in High-Stress Professions

Digital Twin Definition for Detecting Abnormal Perspiration ...

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Roedunet International Conference (RoEduNet)

作者： Cristian Vizitiu Ioan Turcin Kevin Alexander Dominey Selver Softic Adrian-Cătălin Dinculescu Vlad I. Bocăneţ Cosmin Dugan Sorin-Aurel Moraru The Space Applications and Technologies Laboratory Institute of Space Science -Subsidiary of INFLPR Magurele Romania Department of Automatics and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania Department Automation Technology CAMPUS 02 University of Applied Sciences Graz Austria Department IT & Business Informatics CAMPUS 02 University of Applied Sciences Graz Austria Department of Manufacturing Engineering Faculty of Industrial Engineering Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (数字)9798331540388

ISBN: (纸本)9798331540395

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based Systems engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation.

关键词： Adaptation models Generative AI Psychology Human factors Machine learning Predictive models Physiology Digital twins Modeling Biomedical monitoring

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Sasirangan Cloth Recognition and Shopping Experience Simulation Based on Virtual Reality Game with Non-Player Character Integration

Sasirangan Cloth Recognition and Shopping Experience Simulat...

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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Subandi Subandi Aulia Akhrian Syahidi Siti Zakiah Kiyoshi Kiyokawa Ahmad Riyadi M. Helmy Noor Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia Informatics Engineering Undergraduate Program Faculty of Computer Science Universitas Brawijaya Malang Indonesia Cybernetics and Reality Engineering Laboratory Nara Institute of Science and Technology Ikoma Japan Informatics Engineering Diploma Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia

ISBN: (纸本)9781665476652

Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is also one of the potentials that can attract local and foreign tourists to visit South Kalimantan. However, in recent years, tourist visits to South Kalimantan have decreased due to the impact of the COVID-19 pandemic. Then it also has an impact on the delay in the implementation of the Banjarmasin Sasirangan Festival which is usually held annually. The next impact is a decrease in turnover and interest in shopping for Sasirangan cloth, so that employees who work for Sasirangan cloth craftsmen are dismissed and reduce people's income. So the purpose of this study is to report the results of the development of a Virtual Reality Game application called VR-SasiranganKu by integrating the interaction of Non-Player Character (NPC) behavior with the type of narrative in the simulation genre game. VR-SasiranganKu is recommended to introduce and at the same time promote Sasirangan cloth to users, then justify the reaction to knowledge and shopping experience, and evaluate user experience using the UX Honeycomb method. Respondents involved as many as 100 people who are local and national tourists. The results show that the interaction of NPC behavior can provide good direction to users regarding the introduction of Sasirangan cloth by presenting an appropriate interaction design based on the narrative and the theme of the NPC that has been adopted, the results of justification using VR-SasiranganKu can provide knowledge reaction and very good shopping experience, and based on user experience evaluation that VR-SasiranganKu has adopted a very good UX with an average score of 4.91.

关键词： Human computer interaction COVID-19 Solid modeling Pandemics Games Virtual reality User experience

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Morphosyntactic Probing of Multilingual BERT Models

arXiv

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arXiv 2023年

作者： Acs, Judit Hamerlik, Endre Schwartz, Roy Smith, Noah A. Kornai, Andras Budapest Hungary Budapest University of Technology and Economics Budapest Hungary Department of Applied Informatics Comenius University in Bratislava Faculty of Mathematics Physics and Informatics Bratislava Slovakia Hebrew University of Jerusalem Jerusalem Israel Paul G. Allen School of Computer Science and Engineering University of Washington SeattleWA United States Allen Institute for Artificial Intelligence SeattleWA United States

We introduce an extensive dataset for multilingual probing of morphological information in language models (247 tasks across 42 languages from 10 families), each consisting of a sentence with a target word and a morphological tag as the desired label, derived from the Universal Dependencies treebanks. We find that pre-trained Transformer models (mBERT and XLM-RoBERTa) learn features that attain strong performance across these tasks. We then apply two methods to locate, for each probing task, where the disambiguating information resides in the input. The first is a new perturbation method that "masks" various parts of context;the second is the classical method of Shapley values. The most intriguing finding that emerges is a strong tendency for the preceding context to hold more information relevant to the prediction than the following context. © 2023, CC BY.

关键词： Perturbation techniques

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Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments 6

Deep Reinforcement Learning-based Obstacle Avoidance for Rob...

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6th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Li, Keqin Chen, Jiajing Yu, Dezhi Dajun, Tao Qiu, Xinyu Lian, Jieting Ji, Ryan Zhang, Shengyuan Wan, Zhenyu Sun, Baiwei Hong, Bo Ni, Fanghao Han, Jiaqi Ama University Department of Computer Science Quezon Philippines Courant Institute New York University 251 Mercer St New YorkNY10012 United States University of California Berkeley University Avenue and Oxford St School of Information BerkeleyCA94720 United States Carnegie Mellon University Master of Science in Mechanical Engineering School of Engineering 5000 Forbes Avenue PittsburghPA United States Northeastern University College of Engineering Seattle United States School of Professional Studies New York University Master of Science in Database Technology 50 West 4th Street New YorkNY United States Cornell University College of Engineering 616 Thurston Ave IthacaNY14853 United States Cornell University Master of Professional Science in Applied Statistics-Data Science College of Computing and Information Science 616 Thurston Ave IthacaNY United States Independent Researcher Beijing China University of California Irvine Master of Computer Science Donald Bren School of Information and Computer Sciences 510 Aldrich Hall IrvineCA United States Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350389418

This paper proposes a deep reinforcement learning based on the warehouse environment, the mobile robot obstacle avoidance Algorithm. Firstly, the value function network is improved based on the pedestrian interaction. We can learn to obtain the relative importance of the current state and the historical trajectory state as well as the joint impact on the robot's obstacle avoidance strategy. Secondly, the reward function of reinforcement learning is designed based on the spatial behaviour of pedestrians, and the robot is punished for the state where the angle changes too much, so as to achieve the requirement of comfortable obstacle avoidance. Finally, the feasibility and effectiveness of the deep reinforcement learning-based mobile robot obstacle avoidance algorithm in the warehouse environment in the complex environment of the warehouse are verified through simulation experiments. © 2024 IEEE.

关键词： Deep reinforcement learning

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Correction to: Concept Design Evaluation of Sustainable Product–Service Systems: A QFD–TOPSIS Integrated Framework with Basic Uncertain Linguistic Information

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Group Decision and Negotiation 2024年第3期33卷 513-514页

作者： Yang, Qiang Chen, Zhen-Song Zhu, Jiang-Hong Martínez, Luis Pedrycz, Witold Skibniewski, Mirosław J. School of Economics and Management Chongqing Jiaotong University Chongqing China Research Center of Integrated Customs-Port Logistics & Shipping Development Chongqing China School of Civil Engineering Wuhan University Wuhan China College of Traffic and Transportation Chongqing Jiaotong University Chongqing China Department of Computer Science University of Jaén Jaén Spain Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Department of Civil and Environmental Engineering University of Maryland College Park USA Chaoyang University of Technology Taichung Taiwan Institute for Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland

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Simon’s Period Finding on a Quantum Annealer

arXiv

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arXiv 2025年

作者： Robertson, Reece Doucet, Emery Mzaouali, Zakaria Domino, Krzysztof Gardas, Bartlomiej Deffner, Sebastian Department of Computer Science & Electrical Engineering Department of Physics Quantum Science Institute UMBC Baltimore United States Department of Physics Quantum Science Institute UMBC Baltimore United States Institut für Theoretische Physik Universität Tübingen Auf der Morgenstelle 14 Tübingen72076 Germany Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland National Quantum Laboratory College Park United States

Dating to 1994, Simon’s period-finding algorithm is among the earliest and most fragile of quantum algorithms. The algorithm’s fragility arises from the requirement that, to solve an n qubit problem, one must fault-tolerantly sample O(n) linearly independent values from a solution space. In this paper, we study an adiabatic implementation of Simon’s algorithm that requires a constant number of successful samples regardless of problem size. We implement this algorithm on D-Wave hardware and solve problems with up to 298 qubits. We compare the runtime of classical algorithms to the D-Wave solution to analyze any potential advantage. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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Automatic detection of lung nodule in CT scan slices using CNN segmentation schemes: A study

Automatic detection of lung nodule in CT scan slices using C...

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2022 International Conference on Machine Learning and Data engineering, ICMLDE 2022

作者： Kadry, Seifedine Herrera-Viedma, Enrique Crespo, Rubén González Krishnamoorthy, Sujatha Rajinikanth, Venkatesan Faculty of Applied Computing and Technology Noroff University College Kristiansand94612 Norway Research Institute in Data Science and Computational Intelligence University of Granada Andalusian Granada Spain Computer Science Department School of Engineering and Technology Universidad Internacional de la Rioja 26006 Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Tamil Nadu Chennai600119 India

The lung is one of the prime respiratory organs in human physiology, and its abnormality will severely disrupt the respiratory system. Lung Nodule (LN) is one of the abnormalities, and early screening and treatment are necessary to reduce its harshness. The proposed work aims to implement the Convolutional-Neural-Network (CNN) segmentation methodology to extract the LN in various lung CT slices, such as axial, coronal, and sagittal planes. This work consists of the following phases;(i) Image collection and pre-processing, (ii) Ground-truth generation, (iii) CNN-supported segmentation, and (iv) Performance evaluation and validation. In this work, the merit of pre-trained CNN segmentation schemes is verified using (i) One-fold training and (ii) Two-fold training methods. The test images for this study are collected from The Cancer Imaging Archive (TCIA) database. The experimental investigation is executed using Python®, and the outcome of this study confirms that the VGG-SegNet helps to get better values of Jaccard (>88%), Dice (>93%), and Accuracy (>96%) compared to other CNN methods. © 2023 The Authors. Published by Elsevier B.V.

关键词： computerized tomography

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