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IEEJ Transactions on Electronics, information and Systems 2021年第11期141卷 1162-1174页

作者： Murao, Toshiyuki Koshio, Yusuke Kawai, Hiroyuki Yamauchi, Junya Hatanaka, Takeshi Fujita, Masayuki College of Engineering Kanazawa Institute of Technology 7-1 Ohgigaoka Nonoichi-shi Ishikawa921-8501 Japan Graduate Program in Mechanical Engineering Kanazawa Institute of Technology 7-1 Ohgigaoka Nonoichi-shi Ishikawa921-8501 Japan Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan School of Engineering Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8550 Japan

This paper presents passivity-based cooperative dynamic control for human-rigid body networks. In the human-rigid body network, a human operator sends a command signal to and receives visual information from only a part of the robotic group. In this setting, the proposed dynamic control scheme achieves not only pose synchronization of all mobile robots but also convergence to the reference pose that the human operator specifies. First, we derive robot dynamics of an omni-directional mobile robot through the Newton-Euler equation. Second, we design a control input to the robots with dynamics and show the passivity property of the robot system. Next, we discuss convergence analysis of the closed-loop system through the Lyapunov stability theorem and the LaSalle's invariance principle. The main advantage of the proposed method is to guarantee convergence of not only the position but also the orientation to the reference ones in the human-rigid body network. Finally, we provide simulation results and experimental results using four ground vehicles and a tablet PC to illustrate the performance of the proposed control method. © 2021 The Institute of Electrical Engineers of Japan.

关键词： Mobile robots

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Towards Emotionally Intelligent Software Engineers: Understanding Students' Self-Perceptions After a Cooperative Learning Experience

Towards Emotionally Intelligent Software Engineers: Understa...

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ICSE Workshop on Cooperative and Human Aspects on Software Engineering, CHASE

作者： Allysson Allex Araújo Marcos Kalinowski Matheus Paixao Daniel Graziotin Center for Science and Technology Federal University of Cariri Juazeiro do Norte Brazil Department of Informatics Pontifical Catholic University of Rio de Janeiro Rio de Janeiro Brazil Graduate Program in Computer Science State University of Ceará Fortaleza Brazil Department of Information Systems and Digital Technologies University of Hohenheim Stuttgart Germany

ISBN: (数字)9798331538712

ISBN: (纸本)9798331502539

Background] Emotional Intelligence (EI) can impact Software Engineering (SE) outcomes through improved team communication, conflict resolution, and stress management. SE workers face increasing pressure to develop both technical and interpersonal skills, as modern software development emphasizes collaborative work and complex team interactions. Despite EI's documented importance in professional practice, SE education continues to prioritize technical knowledge over emotional and social competencies. [Objective] This paper analyzes SE students' self-perceptions of their EI after a twomonth cooperative learning project, using Mayer and Salovey's four-ability model to examine how students handle emotions in collaborative development. [Method] We conducted a case study with 29 SE students organized into four squads within a projectbased learning course, collecting data through questionnaires and focus groups that included brainwriting and sharing circles, then analyzing the data using descriptive statistics and open coding. [Results] Students demonstrated stronger abilities in managing their own emotions compared to interpreting others' emotional states. Despite limited formal EI training, they developed informal strategies for emotional management, including structured planning and peer support networks, which they connected to improved productivity and conflict resolution. [Conclusion] This study shows how SE students perceive EI in a collaborative learning context and provides evidence-based insights into the important role of emotional competencies in SE education.

关键词： Training Productivity Federated learning Software Encoding Data models Planning Faces Software engineering Software development management

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Energy consumption of high-rise double skin façade buildings, a machine learning analysis

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Journal of Building Engineering 2024年 89卷

作者： Rezaie, Maedeh Kariminia, Shahab Band, Shahab S. Ameri, Rasoul Farokhi, Maryam Pai, Hao-Ting Gocer, Ozgur Rismanchi, Behzad Shooshtarian, Salman Department of Architecture Advancement in Architecture and Urban Planning Research Center Najafabad Branch Islamic Azad University Najafabad Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Department of Information Management National Yunlin University of Science and Technology Taiwan Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan School of Architecture Design and Planning The University of Sydney SydneyNSW Australia Renewable Energy and Energy Efficiency Group Department of Infrastructure Engineering Faculty of Engineering and Information Technology The University of Melbourne Australia School of Property Construction and Project Management RMIT University Melbourne Australia

Most energy exchanges take place through the building skin. The skin characteristics play a decisive role in the extent of these exchanges, but they are somewhat more varied in the double skin façade (DSF). Among these characteristics, cavity segmentation has a noticeable effect on the implementation of the DSF in different directions during the hot and cold seasons. The aim of this study was to investigate the role of DSF segmentation in energy consumption and natural ventilation of high-rise buildings in hot and dry climates. This study used DesignBuilder software to study sixty-four segmentation component scenarios in an eight-story residential building in Isfahan, Iran. Moreover, a proposed hybrid model utilizing the hybridization of the Hunger Game Search and Gradient Boosting (HGS-GB) algorithm was employed to estimate energy consumption in various scenarios involving lighting, heating, cooling, and total scenarios. The available outcomes revealed that the HGS-GB model had a better performance in comparison with other individual models, such as Gradient Boosting (GB), Random Forest (RF), and K-nearest neighbors (KNN). The R2 values for lighting, heating, cooling, and total energy estimation were 0.9993, 0.9958, 0.9991, and 0.9922, respectively. The findings of this study suggest the significance of DSF segmentation in energy consumption and natural ventilation in high-rise buildings in hot and dry climates. © 2024 Elsevier Ltd

关键词： Forestry

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Player's stress reduction in competitive online game by presenting calm scent 9

Player's stress reduction in competitive online game by pres...

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9th IEEE Global Conference on Consumer Electronics, GCCE 2020

作者： Goto, Toshiki Shibuya, Yu Kyoto Institute of Technology Master's Program of Information Science Graduate School of Science and Technology Kyoto Japan Kyoto Institute of Technology Faculty of Information and Human Sciences Kyoto Japan

ISBN: (纸本)9781728198026

Playing competitive online games is usually fun but sometimes player feels unpleasant and is stressed regardless of games content. When a player is stressed, her/his motivation for games decrease. The purpose of this study is to make competitive online games more enjoyable by reducing player's stress. We propose a system that detects player's stress in a competitive online game by her/his RRI and automatically presents calm scent of lavender oil with an aroma diffuser and a fan when she/he is stressed. In the proposed system, each player wears an armband-type pulse sensor and plays a game with a controller while looking at the display. The system get the player's heart rate from armband-type pulse sensor in real time. Next, the system calculates the RRI from heart rate and determines that the player is stressed when her/his RRI is greater than the threshold. To evaluate the proposed system, we are going to experiment to check the functionality of the proposed system, investigate how long to play the game and under what conditions to detect participants' stress in the game and evaluate whether the proposed system can reduce participants stress in a real environment. © 2020 IEEE.

关键词： Computer games

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Non-contact digital signage allowing users to change contents with their face orientation 9

Non-contact digital signage allowing users to change content...

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9th IEEE Global Conference on Consumer Electronics, GCCE 2020

作者： Kurono, Haruka Shibuya, Yu Kyoto Institute of Technology Master's Program of Information Science Graduate School of Science and Technology Kyoto Japan Kyoto Institute of Technology Faculty of Information and Human Sciences Kyoto Japan

ISBN: (纸本)9781728198026

In today's society, digital signage is widely used in various places such as commercial facilities and train stations. Most digital signages use a liquid crystal display or LED panel. One of the advantages of digital signage is the ability to dynamically change the content of the advertisement. However, the method of change is not due to the viewer's intention, but rather to elapsed time to show, and it is merely a sequential display of static advertisements. In this study, we propose and implement a non-contact interactive digital signage system using a web camera that allows users to change the content according to their face orientation. In the implementation, we use OpenCV for showing the content and image processing, and the machine learning library, named dlib, is used for detecting user's face and identifying its orientation. The proposed system changes the layout and enlarges the content in which the user is interested. The user does not need to wear any device and to do any special action. Furthermore, the proposed system offers an intuitive interaction manner to the user. In this paper, some experimental designs are also described. © 2020 IEEE.

关键词： Eye tracking

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Mobile Application Implementation as Agriculture 4.0 Strategy for Sugarcane Yield Prediction

Mobile Application Implementation as Agriculture 4.0 Strateg...

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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Hangger Gahara Mawandha Reza Rahutomo Teddy Suparyanto Bens Pardamean Faculty of Agricultural Technology Institut Pertanian Stiper Yogyakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350304084

ISBN: (纸本)9798350304091

information engineering strategies play a significant and transformative role in shaping the landscape of digital agriculture. It drives innovation and efficiency in modern farming practices, with a specific focus on enhancing the value of agricultural commodities, such as sugarcane. The application of mobile technology plays a crucial part in achieving increased sugarcane productivity. Mobile applications, equipped with advanced developer features, offer rapid and user-friendly access to vital information. Traditional methods of estimating sugarcane production relied on manual data recording on paper, followed by data transfer to computer systems, typically managed by sugar factory junior plant officers. This conventional approach presents several inherent weaknesses, including time and effort intensiveness during data recording and entry. Additionally, the potential for errors in calculation and data input is a concern. The storage capacity for paper-based documents is finite, and farmers are often unable to autonomously assess their production potential. The objective of this research is to confront these obstacles by creating a sugarcane production application for Android. This application functions as an information engineering approach focused on forecasting sugarcane yields for plantation owners and their assistants. The development procedure adhered to the systematic waterfall method, following the principles of the Software Development Life Cycle (SDLC) model. Data collection was carried out through observations, while interviews with junior plant officers provided valuable insights into sugarcane estimation techniques. Analysis involved the synthesis of observational and interview data to inform the design of the application’s interface and algorithmic system. The resulting application significantly simplifies the process of estimating production potential for farmers, enabling them to access sugarcane productivity data during harvest. Consequently, sugar

关键词： Productivity Operating systems Estimation Production facilities Raw materials Mobile applications Recording

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Analysis of Seismic Hazard Prediction Using Non Parametric Conic Multivariate Adaptive Regression Splines (C-Mars) Methods 1

Analysis of Seismic Hazard Prediction Using Non Parametric C...

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1st International Conference on Advanced information Scientific Development, ICAISD 2020

作者： Priyanto, Dadang Zarlis, Muhammad Mawengkang, Herman Efendi, Syahril Graduate Program of Computer Science Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

The data mining process requires a data set that can be used in determining a number of specific patterns to gain new knowledge. Large data sets (Big data) require special methods to get effective results. Included in this study are using big data related to the earthquake in Lombok. Earthquake research, especially in Lombok, is needed because Lombok is on three active plates in Indonesia, so that the danger of earthquake damage can be minimized. Earthquake data obtained from the Geophysical Station (BMKG) of Mataram has different characteristics and is complex, an appropriate method is needed, namely by detecting a non-parametric method with the Multivariate Adaptive Regression Spline (MARS). The use of the backward stepwise algorithm with the Conical Quadratic programming (CQP) framework of MARS, referred to as CMARS (Conic Multivariate Adaptive Regression Splines), is used for optimizing the results. The conclusions of this study are 1. A mathematical model with a total of 12 basis functions (BF) has contributed to the prediction analysis of the PGA dependent variable. 2. Contributions of the influence of independent variables on the PGA value are the epicenter distance (R e pi) of 100% and the Magnitude (Mw) of 31.08608%, while the temperature of the incident location (SUHU) of 5.48525% and depth (Depth) of 3,52988%. 3. Acquired areas that haveearthquake hazard levels in the order of the most vulnerable are Malaka, Genggelang, Tegal Maja, Senggigi and Mangsit. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Quadratic programming

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ASSESSMENT OF CO-GASIFICATION OF MUNICIPAL SOLID WASTE AND TORREFIED URBAN FOREST WASTE: A LIFE CYCLE ASSESSMENT PERSPECTIVE 32nd

ASSESSMENT OF CO-GASIFICATION OF MUNICIPAL SOLID WASTE AND T...

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32nd European Biomass Conference and Exhibition, EUBCE 2024

作者： Lamas, Giulia Cruz Gonzales, Thiago da Silva Rodrigues, Thiago Oliveira Brasil, Augusto Protásio, Thiago de Paula Caldeira-Pires, Armando Rousset, Patrick Silveira, Edgar A. University of Brasília Mechanical Sciences Graduate Program Laboratory of Energy and Environment DF Brasilia70910-900 Brazil Brazilian Institute of Information in Science and Technology-Ibit DF Brasília70070-912 Brazil Faculty of Gama University of Brasília DF Brasília Brazil Department of Forest Sciences CP. 3037 MG Lavras37200-000 Brazil CIRAD UPR BioWooEB MontpellierF-34398 France BioWooEB Univ. Montpellier CIRAD Montpellier France

This study presents a comprehensive techno-environmental evaluation of co-gasification using hybrid blends of municipal solid waste (MSW) and torrefied urban forest waste (UFW) in Brasília, Brazil. Utilizing experimental data from torrefaction treatment, gasification modeling via a thermodynamic equilibrium model, and Life Cycle Assessment (LCA), two syngas production scenarios were examined: (i) hydrogen-rich gas and (ii) enhanced calorific value gas. The optimized gasification system operated at 600°C, exploring two ideal conditions: 0.9 S/B with a blend of 31% MSW and 69% torrefied UFW at 275°C, and 0.4 S/B with a blend of 23% MSW and 77% torrefied UFW at 275°C. Employing LCA Expert (Sphera-GaBi) software with the CML 2001 methodology, the LCA identified primary environmental impacts, focusing on Global Warming Potential (GWP) and Acidification Potential (AP). Scenario (i) exhibited lower GWP impacts (0.779 kg CO2 eq./Nm³ syngas) compared to Scenario (ii) (0.840 kg CO2 eq./Nm³ syngas) while demanding less from the energy matrix (0.154 vs. 0.181 kg CO2 eq.). In the Acidification Potential (AP) category, although scenario (i) (9.04E-04 kg SO2 eq./Nm³ syngas) also demonstrates lower impact compared to scenario (ii) (1.06E-03 kg SO2 eq./Nm³ syngas), only the energy demand was identified as a contributor to the impacts, with no significant emissions to air, in both the torrefaction and gasification processes. The results highlight the necessity of considering environmental, technological, and economic factors for informed decision-making in waste management, advocating for the integration of torrefaction and gasification processes as a viable pathway for sustainable energy production, and aligning with global trends toward cleaner hydrogen energy sources. Further research expanding the LCA to a cradle-to-grave approach is recommended to assess the benefits of these integrated processes fully. © 2024, ETA-Florence Renewable Energies. All rights reserved.

关键词： Decision making

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha D Bhandarkar Aruna Sri Rongali Mohamed Dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Shahzad, Sahibzada Adil Hashmi, Ammarah Peng, Yan-Tsung Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Multimodal manipulations (also known as audiovisual deepfakes) make it difficult for unimodal deepfake detectors to detect forgeries in multimedia content. To avoid the spread of false propaganda and fake news, timely detection is crucial. The damage to either modality (i.e., visual or audio) can only be discovered through multi-modal models that can exploit both pieces of information simultaneously. Previous methods mainly adopt uni-modal video forensics and use supervised pre-training for forgery detection. This study proposes a new method based on a multi-modal self-supervised-learning (SSL) feature extractor to exploit inconsistency between audio and visual modalities for multi-modal video forgery detection. We use the transformer-based SSL pre-trained Audio-Visual HuBERT (AV-HuBERT) model as a visual and acoustic feature extractor and a multi-scale temporal convolutional neural network to capture the temporal correlation between the audio and visual modalities. Since AV-HuBERT only extracts visual features from the lip region, we also adopt another transformer-based video model to exploit facial features and capture spatial and temporal artifacts caused during the deepfake generation process. Experimental results show that our model outperforms all existing models and achieves new state-of-the-art performance on the FakeAVCeleb and DeepfakeTIMIT datasets. © 2023, CC BY.

关键词： Audio acoustics

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