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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Wu, Jun-Wei Lin, Lydia Hsiao-Mei Tsai, Richard Tzong-Han National Central University Department of Computer Science and Information Engineering Taoyuan Taiwan National Taipei University of Technology Department of Interaction Design Taipei Taiwan Center for Gis Research Center for Humanities and Social Sciences Academia Sinica Taipei Taiwan

ISBN: (纸本)9798350360721

ESG reporting, covering environmental, social, and governance aspects, is a crucial resource for investors, companies, and governments to understand a company's value. However, the sheer volume of data and information in the reports makes it difficult to retrieve specific information on ESG. ESG-BERT models are developed to categorize the content of ESG reports based on the relevant field. However, the accurate prediction of multiple classifications is difficult due to unevenly distributed labels. To address this problem, we used a self-made assistant based on GPT to label the data and then resampling technology to adjust the balance of the data set. After the data set was balanced, we adjusted to ESG-BERT to improve its multi-label classification accuracy. We evaluated multiple resampling methods and determined the most suitable strategy for classifying ESG report content. Thus, the accuracy of ESG content analysis was improved through more refined model adjustment and preprocessing methods. The results indicated that balancing the data for improved classification ensures fairness and objectivity in distributing content for ESG reports with multiple labels. © 2024 IEEE.

关键词： Classification (of information)

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Applications of Artificial Intelligence in the Economy, Including Applications in Stock Trading, Market Analysis, and Risk Management

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IEEE Access 2023年 11卷 80769-80793页

作者： Rahmani, Amir Masoud Rezazadeh, Bahareh Haghparast, Majid Chang, Wei-Che Ting, Shen Guan National Yunlin University of Science and Technology Future Technology Research Center Yunlin Douliou64002 Taiwan Islamic Azad University Science and Research Branch Department of Computer Engineering Tehran*** Iran University of Jyväskylä Faculty of Information Technology Jyväskylä40014 Finland

In an increasingly automated world, Artificial Intelligence (AI) promises to revolutionize how people work, consume, and develop their societies. science and technology advancement has led humans to seek solutions to problems;however, AI-based technology is not novel and has a wide range of economic applications. This paper examines AI applications in economics, including stock trading, market analysis, and risk assessment. A comprehensive taxonomy is proposed to investigate AI applications in various scopes of the proposed categories. Furthermore, we will discuss this area's most significant AI-based techniques and evaluation criteria. As a final step, we will identify challenges, open issues, and future work suggestions. © 2013 IEEE.

关键词： Decision making

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Bio-inspired Hybrid Feature Selection Model for Intrusion Detection

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computers, Materials & Continua 2022年第10期73卷 133-150页

作者： Adel Hamdan Mohammad Tariq Alwada’n Omar Almomani Sami Smadi Nidhal ElOmari Computer Science Department The World Islamic Sciences and Education UniversityAmmanJordan Network and Cybersecurity Department Teesside UniversityMiddlesbroughUnited Kingdom Information and Network Security The World Islamic Sciences and Education UniversityAmmanJordan Software Engineering The World Islamic Sciences and Education UniversityAmmanJordan

Intrusion detection is a serious and complex *** due to a large number of attacks around the world,the concept of intrusion detection has become very *** research proposes a multilayer bioinspired feature selection model for intrusion detection using an optimized genetic ***,the proposed multilayer model consists of two layers(layers 1 and 2).At layer 1,three algorithms are used for the feature *** algorithms used are Particle Swarm Optimization(PSO),Grey Wolf Optimization(GWO),and Firefly Optimization Algorithm(FFA).At the end of layer 1,a priority value will be assigned for each feature *** layer 2 of the proposed model,the Optimized Genetic Algorithm(GA)is used to select one feature set based on the priority *** are done on standard GA to perform optimization and to fit the proposed *** Optimized GA is used in the training phase to assign a priority value for each feature ***,the priority values are categorized into three categories:high,medium,and ***,the Optimized GA is used in the testing phase to select a feature set based on its *** feature set with a high priority will be given a high priority to be *** the end of phase 2,an update for feature set priority may occur based on the selected features priority and the calculated *** proposed model can learn and modify feature sets priority,which will be reflected in selecting *** evaluation purposes,two well-known datasets are used in these *** first dataset is UNSW-NB15,the other dataset is the *** evaluation criteria are used,such as precision,recall,and *** experiments in this research suggest that the proposed model has a powerful and promising mechanism for the intrusion detection system.

关键词： Intrusion detection Machine learning Optimized Genetic Algorithm(GA) Particle Swarm Optimization algorithms(PSO) Grey Wolf Optimization algorithms(GWO) FireFly Optimization Algorithms(FFA) Genetic Algorithm(GA)

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A Zero-Watermark Scheme Based on Quaternion Generalized Fourier Descriptor for Multiple Images

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computers, Materials & Continua 2022年第5期71卷 2633-2652页

作者： Baowei Wang Weishen Wang Peng Zhao Naixue Xiong School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing210044China Department of Mathematics and Computer Science Northeastern State UniversityTahlequahOK74464USA

Most of the existing zero-watermark schemes for medical images are only appropriate for a single grayscale *** they protect a large number of medical images,repeating operations will cause a significant amount of time and storage ***,this paper proposes an efficient zero-watermark scheme for multiple color medical images based on quaternion generalized Fourier descriptor(QGFD).Firstly,QGFD is utilized to compute the feature invariants of each color image,then the representative features of each image are selected,stacked,and reshaped to generate a feature matrix,which is then binarized to get a binary feature *** information can be converted into the copyright image by using QR code technology,which contains more ***,the zero-watermark image is constructed by executing the XOR operation on the copyright image and the feature image scrambled by the Cat *** the experiment,different parameters are selected to determine the maximum number of images that the proposed scheme can protect simultaneously while achieving good *** experimental results demonstrate that the proposed scheme can effectively resist common attacks,geometric attacks and joint attacks,and effectively improve the operation efficiency of the algorithm,thus effectively decreasing the time and storage cost of copyright protection for lots of medical images.

关键词： Copyright protection color medical image zero-watermark QGFD

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A Study on Optimal Release Schedule for Multiversion Software

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INFORMS Journal on Computing 2024年第1期36卷 121-140页

作者： Huang, Yeu-Shiang Fang, Chih-Chiang Chou, Chun-Hsuan Tseng, Tzu-Liang Department of Industrial and Information Management Center for Innovative FinTech Business Models National Cheng Kung University Tainan70101 Taiwan School of Computer Science and Software Zhaoqing University Zhaoqing526061 China Department of Industrial and Information Management National Cheng Kung University Tainan70101 Taiwan Department of Industrial Manufacturing & Systems Engineering University of Texas El PasoTX79968 United States

Research on software reliability growth models (SRGMs) has been extensively conducted for decades, and the models were often developed based on two assumptions: (1) once the errors are detected, they can be completely removed instantly, and (2) errors can be removed eternally, and the debugging tasks will not produce any new errors. However, both assumptions are unrealistic. This study proposes an SRGM that ignores these restricted assumptions by introducing a detection process that may remove an error after a period of time once it has been detected and by considering imperfect debugging, which indicates that new errors may emerge through corresponding debugging tasks. In addition, because software can be upgraded to respond on a timely basis to constantly changing consumer expectations and thus extend product life in the market, the proposed SRGM also considers software upgrades for the multiversion software, and a dynamic programming approach is used to effectively obtain the optimal release schedule with consideration of the constraint of budget. Real data sets are used to examine the effectiveness of the proposed model, and the fitting results show that the proposed model outperforms other existing models. The results of numerical validation indicate that the proposed dynamic programming method with information updating outperforms the sequential solution method in determining the optimal release time for each version. Moreover, decision makers should carefully evaluate the parameters because overestimating the parameters of the mean value functions will cause serious software risk due to excessively shortening the testing time. © 2023 INFORMS.

关键词： Software reliability

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An Enhanced Authentication Protocol Suitable for Constrained RFID Systems

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IEEE Access 2024年 12卷 61610-61628页

作者： Hosseinzadeh, Mehdi Servati, Mohammad Reza Rahmani, Amir Masoud Safkhani, Masoumeh Lansky, Jan Janoscova, Renata Ahmed, Omed Hassan Tanveer, Jawad Lee, Sang-Woong Duy Tan University Institute of Research and Development Da Nang550000 Viet Nam Duy Tan University School of Medicine and Pharmacy Da Nang550000 Viet Nam Shahid Rajaee Teacher Training University Department of Computer Engineering Tehran16788-15811 Iran National Yunlin University of Science and Technology Future Technology Research Center Douliou Yunlin64002 Taiwan School of Computer Science Tehran19395-5746 Iran University of Finance and Administration Faculty of Economic Studies Department of Computer Science and Mathematics Prague101 00 Czech Republic University of Human Development Department of Information Technology Sulaymaniyah0778-6 Iraq Sejong University Department of Computer Science and Engineering Seoul05006 Korea Republic of Gachon University Pattern Recognition and Machine Learning Laboratory Department of Ai Software Seongnam-si13557 Korea Republic of

RFID technology offers an affordable and user-friendly solution for contactless identification of objects and individuals. However, the widespread adoption of RFID systems raises concerns regarding security and privacy. Vulnerabilities such as message tampering, interception, and eavesdropping pose significant risks to the integrity of the system. This study examines the effectiveness of two recently proposed ultra-lightweight RFID authentication protocols, URASP and KUAJB, in addressing these security challenges. Surprisingly, our findings reveal that both URASP and KUAJB protocols are susceptible to secret disclosure attacks, despite their claims of providing robust security. Consequently, the development of a truly ultra-lightweight protocol that ensures adequate security becomes a formidable task. As a potential solution, the enhancement of the URASP protocol through the integration of a simple cryptographic primitive is suggested to bolster its security measures. © 2013 IEEE.

关键词： Hash functions

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基于Seed-PCG法的列车-轨道-地基土三维随机振动GPU并行计算方法

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Journal of Central South University 2024年第1期31卷 302-316页

作者：朱志辉冯杨杨啸李昊邹有 National Engineering Research Center of High-speed Railway Construction Technology Changsha 410075China School of Civil Engineering Central South UniversityChangsha 410075China School of Computer Science and Engineering Center South UniversityChangsha 410083China Information and Network Center Central South UniversityChangsha 410083China

为了解决列车-轨道-地基土三维有限元模型随机多样本计算效率低的问题,本文提出了一种基于Seed-PCG法的高效并行计算方法。基于有限元法和虚拟激励法建立轨道不平顺激励下的三维列车-轨道-地基土耦合随机振动分析模型;针对车致地基土随... 详细信息

为了解决列车-轨道-地基土三维有限元模型随机多样本计算效率低的问题,本文提出了一种基于Seed-PCG法的高效并行计算方法。基于有限元法和虚拟激励法建立轨道不平顺激励下的三维列车-轨道-地基土耦合随机振动分析模型;针对车致地基土随机振动分析产生的多右端项线性方程组求解问题,采用Seed-PCG方法进行求解。通过PCG方法求解种子系统得到的Krylov子空间进行投影,以改进其余线性方程组的初始解和对应的初始残量,有效提高了PCG法的收敛速度,最后,在MATLABCUDA混合平台上开发了并行计算程序。数值算例表明:相同计算平台下的该方法相比多点同步算法获得了104.2倍的加速;相比PCG法逐个求解方案减少了18%的迭代次数,获得了1.21倍的加速。

关键词： Seed-PCG法多右端项线性方程组随机振动 GPU并行计算列车-轨道-地基土耦合模型

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Cleo: Smart Glasses to Monitor Consumption of Alcohol and Cigarettes

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SN computer science 2023年第1期4卷 1-13页

作者： Sethuraman, Sibi Chakkaravarthy Kompally, Pranav Mohanty, Saraju P. Raju, Bksp Kumar Cruz, Meenalosini Vimal School of Computer Science and Engineering and Center of Excellence in Artificial Intelligence and Robotics (AIR) VIT-AP University Amaravati India Department of Computer Science and Engineering University of North Texas Denton 76207 TX United States Department of Information Technology Allen E. Paulson College of Engineering and Computing Georgia Southern University Statesboro GA United States

It is estimated that over 60% of people around the globe consume alcohol and cigars daily. Many people use them beyond the permitted limit, which causes lung cancer, liver and kidney failure. If there is a system that could monitor their intake level, it will alert them in case of excess consumption, which could help them control the intake. To help the users monitor their consumption, we introduce Cleo Eyeglasses in this paper. Cleo is a wearable spectacle device with a mounted camera and single onboard computer that performs custom trained object recognition to identify alcoholic beverages and cigarettes. Upon recognition, a log is automatically maintained in the corresponding mobile application. If the intake exceeds the user threshold, then our system generates an alert to both the user and concerned medical personnel. Cigarette/alcohol consumption can immediately affect the body without noticeable symptoms. Cleo addresses this with keen monitoring of vital body parameters and generates an alert when abnormalities are detected. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Alcohol monitoring CNN computer vision Deep learning Smart glasses Smoke monitoring

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A Music Recommendation System based on Emotions 15

A Music Recommendation System based on Emotions

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Charan, S.N. Suhas, G.K. Department of Information Science & Engineering Akshaya Institute of Technology Affiliated to Visvesvaraya Technological University Tumkur572106 India Research center for Computer & Information Sciences Akshaya Institute of Technology Affiliated to Visvesvaraya Technological University Tumkur572106 India

ISBN: (纸本)9798331300579

This research delves into the contemporary landscape of emotion recognition models trained on the FER 2013 *** project introduces a real-time emotion detection system coupled with personalized song recommendations from *** model architecture, leveraging Keras and TensorFlow, is outlined, along with the challenges encountered in *** dataset's characteristics, imbalances, and the model's training process are ***, the paper discusses the incorporation of database functionality for improved song recommendations, scheduled playlist updates, and the aspiration to shift video streaming to the client side for *** the current accuracy of approximately 66%, the study proposes further training and potential exploration of alternative models, such as the Vision Transformer Model. © Grenze Scientific Society, 2024.

关键词： Emotion Recognition

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Smartphone-based colorimetric detection of formaldehyde in the air

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Building Simulation 2024年第11期17卷 2007-2015页

作者： Meng Yang Jin Ye Tao Yu Ying Song Hua Qian Tianyi Liu Yang Chen Junqi Wang Shi-jie Cao Cong Liu School of Energy and Environment Southeast UniversityNanjing210096China School of Energy and Power Jiangsu University of Science and TechnologyZhenjiangJiangsu212100China Wuhan Second Ship Design and Research Institute Wuhan430205China Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test Hubei Provincial Institute for Food Supervision and TestWuhan430075China Laboratory of Image Science and Technology the School of Computer Science and EngineeringSoutheast UniversityNanjingChina Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast UniversityNanjingChina School of Cyber Science and Engineering Southeast UniversityNanjingChina Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of EducationNanjingChina School of Architecture Southeast UniversityNanjingChina Jiangsu Province Engineering Research Center of Urban Heat and Pollution Control Southeast UniversityNanjingChina Global Centre for Clean Air Research(GCARE) University of SurreyGuildfordUK

Adverse impacts of exposure to formaldehyde on human health significantly increases attention in monitoring formaldehyde concentrations in the *** formaldehyde detection methods typically rely on large and costly instruments and requires high skills of expertise,preventing it from being widely accessible to *** study introduced a novel approach utilizing smartphone-based colorimetric *** of green channel signals of digital images by a smartphone successfully capture variation of purple color of 4-amino-3-hydrazino-5-mercapto-1,2,4-triazol solution,which is proportional to formaldehyde *** is because that green and purple are complimentary color pairs.A calibration curve was established between green channel signals and formaldehyde concentrations,with a correlation coefficient of *** limit of the smartphone-based method is 0.008 mg/m^(3).Measurement errors decrease as formaldehyde concentrations increase,with median relative errors of 34%,17%,and 6%for concentration ranges of 0–0.06 mg/m^(3),0.06–0.12 mg/m^(3),and 0.12–0.35 mg/m^(3),*** method replaced scientific instrumentation with ordinary items,greatly reducing cost and operation *** would provide an opportunity to realize onsite measurements for formaldehyde by occupants themselves and increase awareness of air quality for better health protection.

关键词： indoor air quality VOC RGB color identification machine vision

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