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12th International Conference on Learning Representations, ICLR 2024

作者： Liu, Chenyu Zhou, Xinliang Zhu, Zhengri Zhai, Liming Jia, Ziyu Liu, Yang School of Computer Science and Engineering Nanyang Technological University Singapore School of Electronic and Information Engineering Beijing Jiaotong University China School of Computer Science Central China Normal University China Institute of Automation Chinese Academy of Sciences China

The research on human emotion under electroencephalogram (EEG) is an emerging field in which cross-subject emotion recognition (ER) is a promising but challenging task. Many approaches attempt to find emotionally relevant domain-invariant features using domain adaptation (DA) to improve the accuracy of cross-subject ER. However, two problems still exist with these methods. First, only single-modal data (EEG) is utilized, ignoring the complementarity between multimodal physiological signals. Second, these methods aim to completely match the signal features between different domains, which is difficult due to the extreme individual differences of EEG. To solve these problems, we introduce the complementarity of multi-modal physiological signals and propose a new method for cross-subject ER that does not align the distribution of signal features but rather the distribution of spatio-temporal relationships between features. We design a Variational Bayesian Heterogeneous Graph Neural Network (VBH-GNN) with Relationship Distribution Adaptation (RDA). The RDA first aligns the domains by expressing the model space as a posterior distribution of a heterogeneous graph for a given source domain. Then, the RDA transforms the heterogeneous graph into an emotion-specific graph to further align the domains for the downstream ER task. Extensive experiments on two public datasets, DEAP and Dreamer, show that our VBH-GNN outperforms state-of-the-art methods in cross-subject scenarios. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Emotion Recognition

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Developing Lexicons for Enhanced Sentiment Analysis in Software engineering:An Innovative Multilingual Approach for Social Media Reviews

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computers, Materials & Continua 2024年第5期79卷 2771-2793页

作者： Zohaib Ahmad Khan Yuanqing Xia Ahmed Khan Muhammad Sadiq Mahmood Alam Fuad AAwwad Emad A.A.Ismail School of Automation Beijing Institute of TechnologyBeijing100081China Department of Computer Science and Technology University of Science and Technology BannuKPKBannu28100Pakistan School of Computer Science and Engineering Central South UniversityChangsha410083China Department of Quantitative Analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

关键词： Emotional assessment regional dialects SentiWordNet naive bayesian technique lexicons software engineering user feedback

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Analyzing Cross-Layer Design Approaches for Quality of Service in Wireless Networks 15

Analyzing Cross-Layer Design Approaches for Quality of Servi...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Shreenidhi, H.S. Acharjya, Kalyan Saraswat, Nidhi Jain School of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & technology Uttar Pradesh India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350370249

Analyzing move-Layer layout procedures for satisfactory of provider (Qu 's) in Wi-Fi networks is of widespread importance to enhance network overall performance. Go-Layer optimization integrates distinct layers consisting of the physical, medium get right of entry to control (MAC), and community layers. Those layers are combined to successfully model the stop-to-cease network performance for each Wi-Fi and wired systems. Go-layer optimization can be used to improve the Qu's via numerous mechanisms, which include aid allocation, scheduling, adaptive modulation, and energy manipulate. These optimization techniques can be used to implement several Qu's-oriented functions together with safety in opposition to congestion, resilience to node and link failures, and adaptive visitors engineering. In this paper, we analyses numerous procedures to move-layer optimization that are appropriate for adapting the Qu's to dynamic situations in Wi-Fi networks. We talk the advantages and downsides of each method, and offer a complete overview on the modern-day studies trends. Eventually, we advise a framework for further research in this region. © 2024 IEEE.

关键词： Adaptive Optimization Performance Procedures Satisfactory Successfully Techniques

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Fano Resonance Biosensor of Asymmetric Splitting Ring in The-Band 12

Fano Resonance Biosensor of Asymmetric Splitting Ring in The...

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12th IEEE International Conference on Information and Communication Networks, ICICN 2024

作者： He, Quanlin Li, Qiming Yang, Hongyan Yang, Yuhang Sun, Hongrui Li, Jianqing Chen, Yunyi School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin China School of Computer Science and Engineering Macau University of Science and Technology 999078 China

ISBN: (纸本)9798350355802

Metasurface is a kind of artificial layered material whose thickness is less than the wavelength, which can flexibly and effectively control the polarization, amplitude, phase, polarization mode and propagation mode of electromagnetic waves. In this paper, a split ring metasurface structure with two openings is designed to excite Fano resonance by breaking the symmetry of the structure. Based on the finite element method (FEM), the asymmetric splitting ring of Thz metsurface is studied. It is shown that the peak value of Fano resonance and the quality factor (Q) can be modulated by changing the inner and outer diameters of the splitting ring. The Fano resonance is very sensitive to the asymmetry of the structure. A small asymmetry will excite the Fano resonance with high intensity, high quality factor and very narrow resonance linewidth. The refractive index sensitivity of the designed sensor reaches 7.23THz/RIU, and the Q value is up to 93.33. It can be used as a sensor to monitor the ambient refractive index, ambient temperature and liquid concentration. © 2024 IEEE.

关键词： Terahertz waves

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Real-time Health Monitoring of Patients in Emergencies Through Machine Learning And IoT Integrated With Edge Computing 14

Real-time Health Monitoring of Patients in Emergencies Throu...

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14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Mishra, Amit Kumar Sharma, Rahul Singh, Jagendra Singh, Prabhishek Diwakar, Manoj Tiwari, Mohit Graphic Era Hill University Department of Computer Science & Engineering Dehradun India D. Y. Patil International University Pune India School of Computer Science Engineering and Technology Bennett University Greater Noida India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Bharati Vidyapeeth's College of Engineering Dept. of Computer Science & Engineering Delhi India

ISBN: (纸本)9798350344837

With employing the Internet of Things (IoT) sensors and modern-day machine learning algorithms, this study presents a modern inquiry at the intersection of healthcare and era. This have a look at studies the capability of Long ShortTerm Memory (LSTM) and Artificial Neural Network (ANN) fashions in forecasting affected person fitness consequences by utilising the exploitation of sensor facts inclusive of temperature, blood strain, ECG, EEG, and pulse price. The study extensively examines the models' performance utilising a broad variety of performance benchmarks. Results demonstrate that once compared to the LSTM model, the ANN version performs better in terms of prediction accuracy, precision, do not forget, and Fl score. This enhanced accuracy indicates how effectively the ANN model can spot challenging patterns in the dataset. The predicted fitness possibilities for 15 human individuals also are proved in a result table, reaffirming the ANN models constant advantage in prediction. This look at proactive patient care, more intelligent treatment regimens, and improved overall patient outcomes is driving the business and is a significant step towards personalised, data-driven healthcare solutions. © 2024 IEEE.

关键词： Forecasting

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Intelligent Production Industrial Internet Platform Based on Multi-Scale Collaborative Analysis

Intelligent Production Industrial Internet Platform Based on...

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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Qian Liu, Yijun Huang, Xiaowei Chongqing University of Science and Technology Engineering Research Center Waste Oil Recovery Technology and Equipment Ministry of Education Chongqing Technology and Business University School of Computer Science and Engineering School of Artificial Intelligence Chongqing China Chongqing University of Science and Technology School of Computer Science and Engineering School of Artificial Intelligence Chongqing China

ISBN: (纸本)9798331527624

This platform leverages digital twin technology, focusing on intelligent production as the research subject, aiming to achieve intelligent comprehensive evaluation and supervision of the pork production process. Through digital twin modeling, a three-level performance evaluation model is constructed, encompassing model mapping, behavior mapping, and state mapping, to comprehensively reflect pork production capacity. To address imbalances in the production process, the system introduces an intelligent supervision module, utilizing elastic time windows and dynamic flow matching methods to enhance the robustness of the monitoring system. The entire system includes a big data platform based on 5G transmission technology, an intelligent pig farming model, and a digital twin-based intelligent pork production model, forming a multi-scale collaborative intelligent analysis platform that provides scientific support for improving pork production efficiency. © 2024 IEEE.

关键词： Smart manufacturing

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Challenges of Integrating Blockchain Technology into Educational Institutions

Challenges of Integrating Blockchain Technology into Educati...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Ali, Abbas Hussein Yavanoǧlu, Uraz Graduate School of Informatics Gazi University Dept. Of Computer Science Ankara Turkey Gazi University Faculty of Engineering Dept. of Computer Engineering Ankara Turkey

ISBN: (纸本)9798350364910

The latest advancements in blockchain technology have significantly influenced several sectors, such as banking, healthcare, and supply chain networks. Because of its distinct attributes, like decentralization, trustworthiness, and security, this technology has recently been employed in the field of education. While the blockchain is bright, several problems, such as legal, immutability, and scalability questions, continue to hinder its adoption in education. In this paper, we look at educational application system in terms of blockchain-based solutions that have been created for educational purposes, as well as the potential challenges of blockchain technology in the field of education. © 2024 IEEE.

关键词： Blockchain technology educational application

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Minimum Epsilon-Kernel Computation for Large-Scale Data Processing

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Journal of computer science & Technology 2022年第6期37卷 1398-1411页

作者： Hong-Jie Guo Jian-Zhong Li Hong Gao School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China

Kernel is a kind of data summary which is elaborately extracted from a large *** a problem,the solution obtained from the kernel is an approximate version of the solution obtained from the whole dataset with a provable approximate *** is widely used in geometric optimization,clustering,and approximate query processing,etc.,for scaling them up to massive *** this paper,we focus on the minimumε-kernel(MK)computation that asks for a kernel of the smallest size for large-scale data *** the open problem presented by Wang et *** whether the minimumε-coreset(MC)problem and the MK problem can be reduced to each other,we first formalize the MK problem and analyze its *** to the NP-hardness of the MK problem in three or higher dimensions,an approximate algorithm,namely Set Cover-Based Minimumε-Kernel algorithm(SCMK),is developed to solve *** prove that the MC problem and the MK problem can be Turing-reduced to each ***,we discuss the update of MK under insertion and deletion operations,***,a randomized algorithm,called the Randomized Algorithm of Set Cover-Based Minimumε-Kernel algorithm(RA-SCMK),is utilized to further reduce the complexity of *** efficiency and effectiveness of SCMK and RA-SCMK are verified by experimental results on real-world and synthetic *** show that the kernel sizes of SCMK are 2x and 17.6x smaller than those of an ANN-based method on real-world and synthetic datasets,*** speedup ratio of SCMK over the ANN-based method is 5.67 on synthetic ***-SCMK runs up to three times faster than SCMK on synthetic datasets.

关键词： approximate query processing kernel large-scale dataset NP-hard

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Investigation of XLPE Power Cable Insulation Degradation Under Chemical, Electrical, and Mechanical Stress 50

Investigation of XLPE Power Cable Insulation Degradation Und...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Abuelrub, Abdelaziz Refaat, Shady S. Kameli, Sayed Mohammad Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom

ISBN: (纸本)9781665464543

High voltage (HV) power cables are exposed to various stresses, such as chemical, electrical, mechanical, and thermal. These stresses contribute to the eventual failure of electrical power cables in an unpredictable manner. Cross-linked polyethylene (XLPE) is an essential component of a power cable’s insulation layers, and unwanted stresses negatively affect the insulation layers’ performance in various ways. In this paper, three 3D Maxwell finite element analysis (FEA) models of a single core, 30 kV DC power cable are built to study the effects of chemical stress, electrical stress, and mechanical stress on the characteristics of polymer insulation material. The main parameter utilized for determining insulation health in this work is the polarization index. Temporal evolution in the polarization index is investigated, as aging-induced stresses degrade the XLPE’s structure. The severity of chemical stress, electrical stress, and mechanical stress is estimated and compared based on the polarization index, with a focus on chemical stress, highlighting the severity of the deformation caused within the inner polymeric structure of XLPE. The severity is obtained for the innermost and outermost insulation layers. It was discovered that the insulation layer’s proximity to the cable’s core is the main factor influencing degradation. Moreover, the obtained results successfully demonstrate the polarization index’s ability to detect degradation after the 95-day mark, indicated by the substantial increase in polarization index values, common between all stress types applied. © 2024 IEEE.

关键词： Crosslinking

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Transition metal anchored on C_(9)N_(4) as a single-atom catalyst for CO_(2) hydrogenation: A first-principles study

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Chinese Physics B 2022年第10期31卷 520-528页

作者： Jia-Liang Chen Hui-Jia Hu Shi-Hao Wei Department of Microelectronic Science and Engineering School of Physical Science and TechnologyNingbo UniversityNingbo 315211China Department of Electronic and Information Engineering School of Electrical Engineering and Computer ScienceNingbo UniversityNingbo 315211China

To alleviate the greenhouse effect and maintain the sustainable development, it is of great significance to find an efficient and low-cost catalyst to reduce carbon dioxide(CO_(2)) and generate formic acid(FA). In this work, based on the first-principles calculation, the catalytic performance of a single transition metal(TM)(TM = Cr, Mn, Fe, Co, Ni, Cu, Zn,Ru, Rh, Pd, Ag, Cd, Ir, Pt, Au, or Hg) atom anchored on C_(9)N_(4) monolayer(TM@C_(9)N_(4)) for the hydrogenation of CO_(2) to FA is calculated. The results show that single TM atom doping in C_(9)N_(4) can form a stable TM@C_(9)N_(4) structure, and Cu@C_(9)N_(4) and Co@C_(9)N_(4) show better catalytic performance in the process of CO_(2) hydrogenation to FA(the corresponding maximum energy barriers are 0.41 eV and 0.43 e V, respectively). The partial density of states(PDOS), projected crystal orbital Hamilton population(p COHP), difference charge density analysis and Bader charge analysis demonstrate that the TM atom plays an important role in the reaction. The strong interaction between the 3d orbitals of the TM atom and the non-bonding orbitals(1πg) of CO_(2) allows the reaction to proceed under mild conditions. In general, our results show that Cu@C_(9)N_(4) and Co@C_(9)N_(4) are a promising single-atom catalyst and can be used as the non-precious metals electrocatalyst for CO_(2) hydrogenation to formic acid.

关键词： first-principles calculation CO_(2)hydrogenation catalysts electronic structure reaction mechanisms reaction paths

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