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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Kaito Kitazume Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

In recent years, Field-programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz... 详细信息

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

关键词： Conferences High performance computing Circuits Cluster computing Low latency communication Field programmable gate arrays

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Multi-channel Convolutional Neural Network for Hate Speech Detection in Social Media 9th

Multi-channel Convolutional Neural Network for Hate Speech D...

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9th EAI International Conference on Advancement of Science and Technology, ICAST 2021

作者： Abebaw, Zeleke Rauber, Andreas Atnafu, Solomon IT Doctoral Program Addis Ababa University Addis Ababa Ethiopia Institute of Information Systems Engineering Technical University of Vienna Vienna Austria Department of Computer Science Addis Ababa University Addis Ababa Ethiopia

ISBN: (纸本)9783030937089

As online social media content continues to grow, so does the spread of hate speech. Hate speech has devastating consequences unless it is detected and monitored early. Recently, deep neural network-based hate speech detection models, particularly conventional single-channel Convolutional Neural Network (CNN), have achieved remarkable performance. However, the effectiveness of the models depends on the type of language they are trained on and the training data size. We argue that the effectiveness of the models could further be enhanced if we use multi-channel CNN models even for under-resourced languages that have limited training data size. This is because the single-channel CNN might fail to consider the potential effect of multiple channels to generate better features, which is not well investigated for hate speech detection. Therefore, in this work, we explore the use of multi-channel CNN to extract better features from different channels in an end-to-end manner on top of a word2vec embedding layer. Tested on a new small-scale Amharic hate speech dataset containing 2000 annotated social media comments, the experimental results show that the proposed multi-channel CNN model outperforms the single-channel CNN models but underperform from the baseline Support Vector Machine (SVM) with an average F-score of 81.3%, 78.2%, and 92.5% respectively. The finding of the study implies that the proposed MC-CNN model can be used as an alternative solution for hate speech detection using a deep learning approach when dataset scarcity is an issue. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Embeddings

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Brainwave Analysis of the Correlation Between Listening to the Rain/Water Sounds and Reducing Human-Perceived Temperature 18th

Brainwave Analysis of the Correlation Between Listening to t...

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18th International Conference on Intelligent information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Tey, Fu Jie Wu, Tin-Yu Liu, Mei-Yin Chen, Yi-Kai Department of Electrical Engineering National Taiwan University of Science and Technology Taipei City Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Neipu Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan

ISBN: (纸本)9789819901043

This study focuses on the brainwave analysis of the correlation between listening to the rain and water sounds and reducing human-perceived temperature. Brainwave changes are monitored when experimental subjects listen to rain and water sounds at various frequencies. The experiment result shows that listening to the sounds of rain and water in an environment of high temperature and high humidity can boost α waves to induce feelings of calm and relaxed mental state. In order to investigate subjects’ psychological and physiological changes induced by brainwave changes while listening to rain and water sounds for different time durations in a high temperature and humidity environment, this study uses the Fourier transform to obtain the spectra of natural rain/water sounds and analyzes the sound frequencies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fourier analysis

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem 5

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Anditta, Mietha Amartya, Natashya Warnars, Laurens Spits Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Siswanto, Teddy Mantoro, Teddy Noordin, Nurulhuda Bina Nusantara University School of Computer Science Computer Science Departement Jakarta11530 Indonesia Bina Nusantara University School of Information Systems Information Systems Departement Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Departement Jakarta11530 Indonesia Telkom University Pjj Informatika Bandung40257 Indonesia Trisakti University Information Systems Department Jakarta11440 Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta12760 Indonesia Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Malaysia

ISBN: (纸本)9798350369489

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset. © 2023 IEEE.

关键词： Dynamic programming

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Exploring the Effectiveness of Work from Home: A Text Mining Analysis of Employee Perceptions and Experiences 7

Exploring the Effectiveness of Work from Home: A Text Mining...

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7th information systems International Conference, ISICO 2023

作者： Nadlifatin, Reny Persada, Satria Fadil Beatrice, Amanda Putri, Nadya Permata Young, Michael Nayat Prasetyo, Yogi Tri Redi, Anak Agung Ngurah Perwira Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department Universitas Pembangunan Nasional "Veteran" Jawa Timur Surabaya60294 Indonesia School of Industrial Engineering and Engineering Management Mapua University 658 Muralla St. Intramuros Manila1102 Philippines Industrial Engineering Department Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia

Work from home (WFH) has become a global phenomenon that continues to grow, especially since the COVID-19 pandemic hit the world. Many organizations and companies are forced to adopt a remote working model to keep their employees safe. The usefulness of WFH is still up for dispute, though. Text mining analysis can be utilized to determine how beneficial working from home is. Sentiment analysis uses text analysis to gather ten thousand data from social media Tweets. Joy emotion is predicted to dominate with 83.98 percent according to the mining performed by the vocabulary valence aware dictionary and sentiment reasoner (VADER). © 2023 The Authors. Published by Elsevier B.V.

关键词： Sentiment analysis

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Portfolio Selection Using Mean Variance Theory Based on the 30-year Historical Returns of Selected Subsectors of the Philippine Industrial Sector

Portfolio Selection Using Mean Variance Theory Based on the ...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Yamanaka, A.D. Young, M.N. Chuahay, T.N. Pratseyo, Y. Persada, S. Nadlifatin, R. School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Finance Chung Yuan University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

Portfolio selection is an important part of investment management that aims to select the right combination of assets to achieve an optimal risk-return ratio. This study integrates the Mean-Variance Theory utilizing the 30-year historical returns of the Philippine Stock Exchange. Three subsectors of the Industrial Sector were used as the investment pool. The back-test results showed that the Mean-Variance portfolios of selected subsectors can outperform the industrial sector and not the market. Stakeholders must be cautious when investing in these three subsectors, considering the values obtained from the simulations. There are recommended portfolio selections wherein companies have a specific allocation that investors and financial managers can use whenever they decide to invest in these subsectors. Overall, this study offers a framework for investors to use as a guide in diversifying their stakes in the Philippine Stock Exchange. © 2024 IEEE.

关键词： Decentralized finance

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Human-Robot Interaction through an Object Grasped with Two Fingers Based on Plastic Deformation Control

Human-Robot Interaction through an Object Grasped with Two F...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Senoo, Taku Konno, Atsushi Kawahara, Hiromichi Ishii, Idaku Course of Systems Science and Informatic Graduate School of Information Science and Technology Hokkaido University Kita 14 Nishi 9 Kita-ku Sapporo Hokkaido060-0814 Japan Smart Innovation Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8527 Japan

ISBN: (纸本)9781665481090

In this study, two-finger grasping based on plastic deformation control for human-robot interaction is designed and implemented. This control strategy is derived based on the concept that balances both retention of grasping force on objects and plastic behavior in response to external forces. The control law consists of a set of constraints and offsets with respect to the springs that appear in the Maxwell model. In particular, the inner loop that is robust against parameter errors is implemented for actual machine experiments. Simulation and actual experiments with a robotic hand are executed to validate the proposed control law. © 2024 IEEE.

关键词： Human robot interaction

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Linear Fresnel collector (LFC) for enhancing solar water desalination process 8

Linear Fresnel collector (LFC) for enhancing solar water des...

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8th International engineering Conference on Renewable Energy and Sustainability, ieCRES 2023

作者： El-Khozondar, Hala J. Elnaggar, Mohamed Elnaggar, Mohamed Ellouh, Ahmed Omar Alghaffari, Mahmoud Walid Nassar, Hamza Bassam Alnahhal, Mohammed Islamic University of Gaza Electrical Engineering and Smart Systems Department Palestine Palestine Technical College - Deir El-Balah Engineering Program Department Palestine Wadi Alshatti University Mechanical & Renewable Energy Eng. Dept Brack Libya Al-Azhar University Renewable Energy Engineering Department Gaza Palestine Islamic University of Gaza Mechanical Engineering Department Palestine Israa University-Palestine Faculty of Engineering and Information Technology Palestine

ISBN: (纸本)9798350300758

The limited availability of clean water resources in Gaza Strip is due to the increasing salinity of groundwater, which is due to unbalanced consumption. Furthermore, the increase in the poverty level among the people and the lack of fossil fuel resources, and the high intensity of solar radiation in the strip have grabbed the attention of the authors to think about a suitable alternative to produce potable water via solar energy. This study aims to investigate the linear Fresnel collector (LFC) coupled with a solar still-single effect active system. The solar still was designed to match the LFC output to avoid any heat losses that may decrease the system's effectiveness. A CFD simulation was carried out using Ansys Fluent software to predict temperature and pressure distributions to find out the efficiency of the LFC collector. The results showed that the use of LFC leads to an increase in the efficiency of the solar still, and the daily production of distilled water reaches 1.5 Litre /m2 © 2023 IEEE.

关键词： Potable water

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Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN

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IEEE Access 2023年 11卷 127388-127401页

作者： Chen, Shih-Lun Chen, Tsung-Yi Mao, Yi-Cheng Lin, Szu-Yin Huang, Ya-Yun Chen, Chiung-An Lin, Yuan-Jin Chuang, Mian-Heng Abu, Patricia Angela R. Chung Yuan Christian University Department of Electronic Engineering Taoyuan320314 Taiwan Feng Chia University Department of Electronic Engineering Taichung407102 Taiwan Chang Gung Memorial Hospital Department of General Dentistry Taoyuan61363 Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan26047 Taiwan Academy of Innovative Semiconductor and Sustainable Manufacturing Department of Program on Semiconductor Manufacturing Technology National Cheng Kung University Tainan717005 Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei243303 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon1108 Philippines

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain the prevailing means of interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven dental conditions in DPR images by utilizing Faster R-CNN. The primary objectives are to enhance dentists' efficiency and evaluate the performance of various CNN models as foundational training networks. This study contributes significantly to the field in several notable ways. Firstly, including a Butterworth filter in the training process yielded an approximately 7% enhancement in judgment accuracy. Secondly, the proposed enhancement technology tailored to different dental symptoms effectively bolstered the training model's accuracy. Consequently, all dental conditions attained an accuracy rate exceeding 95% in CNN analysis. These accuracy enhancements ranged from 1.34% to 13.24% compared to existing recognition technologies. Thirdly, this study pioneers the application of Faster R-CNN for identifying dental conditions, achieving an impressive accuracy rate of 94.18%. The outcomes of this study mark a substantial advancement compared to prior research and offer dentists a more efficient and convenient means of pre-diagnosing dental conditions. © 2013 IEEE.

关键词： Image segmentation

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Exploring ERP User Behaviour in Developing Countries: Integrating Self-efficacy and UTAUT Perspectives 5

Exploring ERP User Behaviour in Developing Countries: Integr...

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5th International Conference on Advancement in Data Science, E-Learning and information systems, ICADEIS 2023

作者： Syamsuar, Dedy Oktaharisetia, Muhammad Angga Witarsyah, Deden Luthfi, Ahmad Dell, Peter Permana, Yudistira Sira Antoni, Darius Bina Nusantara University School of Information Systems Information Systems Department Indonesia Universitas Bina Darma Program Pasca Sarjana Palembang Indonesia Telkom University School of Industrial Engineering Bandung Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Indonesia Curtin University School of Management and Marketing Faculty of Business and Law Australia Politeknik Sekayu Teknik Informatika Sekayu Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia

ISBN: (纸本)9798350303414

ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts. © 2023 IEEE.

关键词： Enterprise resource planning

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