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1st International Conference on Data, Computation and Communication, ICDCC 2024

作者： Palarimath, Suresh Maran, Pyingkodi Valsalan, Prajoona Wilfred Blessing, N.R. Kavitha, S.J. Steffi, S. College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Kongu Engineering College Department of Computer Applications Erode India College of Engineering Dhofar Univesity Electrical and Computer Engineering Department Salalah Oman College of Computing and Information Sciences Univesity of Technology and Applied Sciences Ibri Oman Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798331532956

Due to the ongoing advancements in science and technology, it seems that artificial intelligence and computers have encountered a limitation in their progress. Contemporary scientific research requires more sophisticated interconnection technology to ensure the continued progress of science and technology. Amidst this setting, the technology of Internet of Things (IoT) has progressively been visible to individuals. This technology will significantly impact human lifestyle and quality of life, and the Internet of Things has seen substantial progress. Information technology is intricately intertwined with the lives of citizens. The integration of information technology with the IoT is aimed at maximizing the technological advancement of the Internet of Things, with Internet technology serving as the central component. The use of artificial intelligence and computer intelligence in Internet technology is versatile, and issues pertaining to artificial intelligence and computing intelligence are progressively emerging. Artificial intelligence and computational intelligence play a significant role in the Internet of Things. However, their application process is challenging and lacks creativity, necessitating ongoing improvements at the application level. This study examines the use of artificial intelligence and computational intelligence in the Internet of Things. © 2024 IEEE.

关键词： Artificial intelligence computational intelligence Internet of things

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Simulate the Machine Learning Algorithm to Organize the CRAHN Network System

Simulate the Machine Learning Algorithm to Organize the CRAH...

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Advancement in Electronics & Communication Engineering (AECE), International Conference on

作者： P Prabakaran L. Chandra Sekhar Reddy LVD Ravikumar Manish Kumar Verma Department Of Computer Applications School of computing sciences Vels Institute of Science Technology and Advanced Studies Chennai India Department of CSE(Data Science) CMR College of Engineering & Technology Medchal Hyderabad India Department of Information Technology Shri Vishnu Engineering College For Women Bhimavaram India Department of Psychology Lovely Professional University Phagwara India

Using available channels in a wireless spectrum, cognitive radio (CR) may automatically adjust transmission settings to optimize radio operational behaviour. To function properly, a CR ad hoc network (CRAHN) has to be dynamically capable construct autonomous and decentralized networks without negatively impacting licensed main user (PU) systems. For this reason, an effective spectrum necessitates a system structure based on artificial intelligence. This research provides a model for network planning, learning, and dynamic configuration that is based on a distributed autonomous CRAHN network system that uses reinforcement learning. The proposed optimization techniques for spectrum sensing, ad hoc network design, and context-aware signal categorization are all derived from the system model and are based on machine learning. The cognitive and detection engines may be used to examine the spectrum utilization and neighbour network status in the immediate area. To adapt to the ever-changing nature of the wireless environment, the suggested policy engine may generate network operating policies, identify policy conflicts, and infer the best course of action. Together with the erudition engine, whereby apply the recommended machine-learning methods, the decision engine arrives at the best possible settings for the CRAHN. In addition, guarantee peaceful cohabitation with surrounding systems to have excellent signal context recognition ability.

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Assessing the value of advanced computing infrastructure for supporting research: new tools to inform research policy

arXiv

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arXiv 2025年

作者： Snapp-Childs, Winona G. Hancock, David Y. Smith, Preston M. Towns, John Stewart, Craig A. Pervasive Technology Institute Office of the VP for IT Indiana University BloomingtonIN47408 United States Research Technologies Office of the VP for IT Indiana University BloomingtonIN47408 United States Rosen Center for Advanced Computing Purdue University West LafayetteIN47906 United States National Center for Supercomputing Applications University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Computer Science Indiana University BloomingtonIN47408 United States

Purpose: How much to invest in research facilities has long been a question in research policy and practice in higher education. This matter is time-sensitive due to critical financial challenges at institutions in the USA, with signs of significant problems in Europe. The purpose of this report is to present new techniques for assessment of one particular type of research infrastructure - computing facilities and staff that support research. These new approaches are timely because of the ongoing financial crises which may make it essential for institutions of higher education to make difficult decisions regarding research infrastructure. Principal results: We present recently developed methods for assessment of the economic and scientific value of investment in advanced computing facilities and services. Existing examples of these tools in use show that investment in advanced computing facilities and services contributes importantly to positive financial and academic outcomes for institutions of higher education. We present a format based on the Balanced Scorecard concept for summarizing such information. Conclusion: The methods presented here enable quantitative assessment of the relationship between investment in computing facilities and research and education outcomes. These methods should be of interest to research policy investigators and practitioners. The analysis methods described may be applied retroactively, making this report of potentially immediate value in setting research policies. © 2025, CC BY.

关键词： Decentralized finance

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Exploring the Synergy of Artificial and Computational Intelligence for Technological Advancements

Exploring the Synergy of Artificial and Computational Intell...

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Data, Computation and Communication (ICDCC), International Conference on

作者： Suresh Palarimath Pyingkodi Maran Prajoona Valsalan Wilfred Blessing N. R S. J. Kavitha Steffi S College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Sultanate of Oman Department of Computer Applications Kongu Engineering College Erode India Electrical and Computer Engineering Department College of Engineering Dhofar Univesity Salalah Sultanate of Oman College of Computing and Information Sciences Univesity of Technology and Applied Sciences Ibri Sultanate of Oman Department of Computer Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (数字)9798331532956

ISBN: (纸本)9798331532963

关键词： Computers Planets Internet of Things Artificial intelligence Information technology Computational intelligence Creativity

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Multi-Modal Emotion and Gesture Recognition System for Humans and Animals Using Computer Vision and Deep Learning

Multi-Modal Emotion and Gesture Recognition System for Human...

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IoT Based Control Networks and Intelligent Systems (ICICNIS), International Conference on

作者： Rekha R Nair Tina Babu Kishore S Smitha Shivaswamy Aruna S Manchikalapudi Bhargavi Department of Computer Science and Engineering Alliance School of Advanced Computing Alliance University Bengaluru India Department of Computer Application Nitte Institute of Professional Education Nitte(Deemed to be University) Mangaluru Karnataka India Department of Computer Applications Acharya Institute of Technology Bengaluru India School of Science and Computer studies CMR University Bangalore India Department of Computer Science and Engineering(AIML) Malla Reddy College of Engineering and Technology Hyderabad India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

Emotion recognition through facial expressions and gesture analysis has emerged as a key area of research in computer vision and human-computer interaction. The ability to automatically detect and classify human emotions has wide-ranging applications, from enhancing user experiences to improving mental health monitoring and surveillance systems. This project builds on this background to develop a comprehensive system for recognizing emotions and gestures in both humans and animals. The system integrates facial emotion recognition, hand gesture interpretation, and animal emotion detection into a single platform. Using advanced deep learning models and computer vision libraries, the system classifies facial expressions into categories such as happiness, sadness, anger, fear, surprise, and neutral. The gesture recognition component interprets hand signals to convey messages like “need help” or “need water.” An innovative aspect of this work is the extension of emotion recognition to animals, particularly focusing on species like dogs and monkeys. Implemented primarily in Python, the system leverages libraries such as OpenCV and DeepFace. By combining these different modalities of nonverbal communication analysis, the project presents a versatile solution with potential applications in human-computer interaction, mental health monitoring, security, and animal welfare.

关键词： Hands Human computer interaction Emotion recognition Computer vision Accuracy Animals Face recognition Computational modeling Gesture recognition Mental health

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The radiative decay of scalar glueball from lattice QCD

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Science China(Physics,Mechanics & Astronomy) 2024年第11期67卷 63-74页

作者： Jintao Zou Long-Cheng Gui Ying Chen Wen Qin Jian Liang Xiangyu Jiang Yibo Yang Department of Physics Hunan Normal University and Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of EducationChangsha 410081China Synergetic Innovation Center for Quantum Effects and Applications(SICQEA) Hunan Normal UniversityChangsha 410081China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China Key Laboratory of Atomic and Subatomic Structure and Quantum Control(MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of MatterInstitute of Quantum MatterSouth China Normal UniversityGuangzhou 510006China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing CenterSouth China Normal UniversityGuangzhou 510006China CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China International Centre for Theoretical Physics Asia-Pacific Beijing 100190China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

We perform the first lattice QCD study on the radiative decay of the scalar glueball to the vector mesonφin the quenched *** calculations are carried out on three gauge ensembles with different lattice spacings,which enable us to do the continuum *** first revisit the radiative J/ψdecay into the scalar glueball G and obtain the partial decay widthΓ(J/ψ→γG)=0.578(86)keV and the branching fraction Br(J/ψ→γG)=6.2(9)×10^(-3),which are in agreement with the previous lattice *** then extend the similar calculation to the process G→γφand get the partial decay widthΓ(G→γφ)=0.074(47)keV,which implies that the combined branching fraction of J/ψ→γG→γγφis as small as O(10^(-9))such that this process is hardly detected by the BESⅢexperiment even with the large J/ψsample of O(10^(10)).With the vector meson dominance model,the two-photon decay width of the scalar glueball is estimated to beΓ(G→γγ)=0.53(46)e V,which results in a large stickiness S(G)~O(10^(4))of the scalar glueball by assuming the stickiness of f_(2)(1270)to be one.

关键词： lattice QCD scalar glueball radiative decay

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Enhanced fast boolean matching based on sensitivity signatures pruning

arXiv

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arXiv 2021年

作者： Zhang, Jiaxi Ni, Liwei Zheng, Shenggen Liu, Hao Zou, Xiangfu Wang, Feng Luo, Guojie Center for Energy-Efficient Computing and Applications Peking University Beijing China Peng Cheng Laboratory Shenzhen China Advanced Institute of Information Technology Peking University Hangzhou China

Boolean matching is significant to digital integrated circuits design. An exhaustive method for Boolean matching is computationally expensive even for functions with only a few variables, because the time complexity of such an algorithm for an n-variable Boolean function is O(2n+1n!). Sensitivity is an important characteristic and a measure of the complexity of Boolean functions. It has been used in analysis of the complexity of algorithms in different fields. This measure could be regarded as a signature of Boolean functions and has great potential to help reduce the search space of Boolean matching. In this paper, we introduce Boolean sensitivity into Boolean matching and design several sensitivity-related signatures to enhance fast Boolean matching. First, we propose some new signatures that relate sensitivity to Boolean equivalence. Then, we prove that these signatures are prerequisites for Boolean matching, which we can use to reduce the search space of the matching problem. Besides, we develop a fast sensitivity calculation method to compute and compare these signatures of two Boolean functions. Compared with the traditional cofactor and symmetric detection methods, sensitivity is a series of signatures of another dimension. We also show that sensitivity can be easily integrated into traditional methods and distinguish the mismatched Boolean functions faster. To the best of our knowledge, this is the first work that introduces sensitivity to Boolean matching. The experimental results show that sensitivity-related signatures we proposed in this paper can reduce the search space to a very large extent, and perform up to 3x speedup over the state-of-the-art Boolean matching methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Boolean functions

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Entanglement-Assisted Concatenated Quantum Codes: Parameters and Asymptotic Performance

arXiv

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arXiv 2025年

作者： Fan, Jihao Cheng, Wei Luo, Gaojun Li, Zhou Cao, Meng School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Laboratory for Advanced Computing and Intelligence Engineering Wuxi214083 China LTCI Télécom Paris Institut Polytechnique de Paris Palaiseau91120 France School of Mathematics Nanjing University of Aeronautics and Astronautics Nanjing211106 China School of Computer Electronics and Information Guangxi University Nanning530004 China Beijing Institute of Mathematical Sciences and Applications Beijing101408 China

Entanglement-assisted concatenated quantum codes (EACQCs) are constructed by concatenating two entanglement-assisted quantum error-correcting codes (EAQECCs). By selecting the inner and outer component codes carefully, it is able to construct state-of-the-art EACQCs with parameters better than previous quantum codes. In this work, we use almost maximum-distance-separable (MDS) codes and ℏ-MDS codes as the outer codes to construct EACQCs. Because the range of code length of almost MDS and ℏ-MDS codes is much more free than that of the commonly used MDS codes. We derive several families of new EACQCs with parameters better than the previously best known EAQECCs and standard quantum error-correcting codes (QECCs) of the same length and net transmissions. Moreover, we demonstrate that EACQCs are with maximal entanglement if both the inner and outer component codes are with maximal entanglement. As a result, we construct three new maximal-entanglement EACQCs which have optimal parameters. In addition, we present several new maximal-entanglement EACQCs whose minimum distance is only one less than the minimum distance of the optimal codes. In particular, we propose two new families of asymptotically good maximal-entanglement EACQCs with explicit constructions by using entanglement-assisted quantum algebraic geometry codes as the outer codes. At last, we prove that EACQCs can attain the quantum Gilbert-Varshamov bound for EAQECCs asymptotically. © 2025, CC BY.

关键词： Quantum entanglement

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Reinforcement Learning Algorithms for Online Single-Machine Scheduling 15

Reinforcement Learning Algorithms for Online Single-Machine ...

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15th Federated Conference on Computer Science and Information Systems, FedCSIS 2020

作者： Li, Yuanyuan Fadda, Edoardo Manerba, Daniele Tadei, Roberto Terzo, Olivier Links Foundation-Advanced Computing and Applications Torino10138 Italy Politecnico di Torino Department of Control and Computer Engineering Torino10129 Italy University of Brescia Department of Information Engineering Brescia25123 Italy

ISBN: (纸本)9788395541674

Online scheduling has been an attractive field of research for over three decades. Some recent developments suggest that Reinforcement Learning (RL) techniques have the potential to deal with online scheduling issues effectively. Driven by an industrial application, in this paper we apply four of the most important RL techniques, namely Q-learning, Sarsa, Watkins's Q(lambda), and Sarsa(lambda), to the online single-machine scheduling problem. Our main goal is to provide insights on how such techniques perform. The numerical results show that Watkins's Q(lambda) performs best in minimizing the total tardiness of the scheduling process. © 2020 Polish Information Processing Society - as it is since 2011.

关键词： Reinforcement learning

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0305 Can We Rely on Wearable Sleep-Tracker Devices for Fatigue Management?

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Sleep 2024年第SUPPLEMENT_1期47卷 A131–A132页

作者： Reifman, Jaques Priezjev, Nikolei Vital-Lopez, Francisco Department of Defense Biotechnology High Performance Computing Software Applications Institute Telemedicine and Advanced Technology Research Center U.S. Army Medical Research and Development Command

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