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2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024

作者： Cristaudo, Antonio Ferraro, Vittorio Nicoletti, Francesco Palermo, Giulia Kaliakatsos, Dimitrios University of Calabria Energy and Management Engineering Department CS Rende Italy University of Calabria Department of Computer Engineering Modeling Electronics and Systems Engineering CS Rende Italy

ISBN: (纸本)9798350385014

The energy transition represents an essential process necessary to drive a shift towards a sustainable and balanced human-environment interaction. Within the residential building sector, this obj ective can be pursued by promoting both the utilization of renewable sources and the energy efficiency improvement of technical systems and the building envelope. In this regard, this article conducts an energy analysis to assess the reduction in energy requirements achieved by installing two Trombe walls on the south-facing wall of the variable orientation test station at the University of Calabria. The two passive systems were symmetrically positioned on either side of the existing window system. The evaluation of monthly energy requirements during the heating period was performed using the dynamic simulation software DesignBuilder. To define the optimal configuration of the Trombe walls, the influence on energy requirements associated with the materials used to construct the support structure of the Trombe walls, the type and number of glass panels forming the solar space, the size of the solar space, and the dimensions of the vents were assessed. The results show that the installation of the two Trombe walls, each consisting of two vents with an area of 0.1 m2 and a solar space depth of 0.20 m, supported by a PVC structure and vertically bounded by three glass walls with double low-emissivity glazing (two lateral and one frontal facing south), allows for a 60.62% reduction in winter energy requirements. © 2024 IEEE.

关键词： Energy efficiency

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High-precision CAD-based simulation for turning considering tool microgeometry

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International Journal of Mechatronics and Manufacturing systems 2023年第1期16卷 83-95页

作者： Tzotzis, Anastasios Tsagaris, Apostolos Tapoglou, Nikolaos Kyratsis, Panagiotis Department of Product and Systems Design Engineering University of Western Macedonia Kila Kozani50100 Greece Department of Industrial Engineering and Management International Hellenic University Sindos Thessaloniki57400 Greece

Surface roughness is considered to be a critical parameter when evaluating the machinability of a material, as well as the surface quality of a machined part. Thus, a number of studies exist in the literature, that deal with the simulation and prediction of the surface roughness generation during machining. This paper presents a 3D simulation method for turning, considering the full geometrical aspects of a cutting-tool, leading to high-precision simulation of the process. For the purposes of the study, a commercially available, generic CAD system was utilised, namely SolidWorks™. Specifically, the application programming interface (API) of the software was used, to write code that is capable of simulating the kinematics of the turning process. In addition, the surface roughness profile, topography, as well as typical measurements were generated, with respect to machining conditions such as, depth of cut, feed and cutting speed. For the verification of the accuracy of the code, a set of nine turning experiments were carried out, for a specified range of conditions. Finally, a comparison between the experimental and the simulated measurements for the Ra, Rz and Rt was made, showing an increased correlation. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Surface roughness

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Machine Learning-Based Channel State Estimators for 5G Wireless Communication systems

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Computer Modeling in engineering & Sciences 2023年第4期135卷 755-778页

作者： Mohamed Hassan Essai Ali Fahad Alraddady Mo’ath Y.Al-Thunaibat Shaima Elnazer Department of Electrical Engineering Faculty of EngineeringAl-Azhar UniversityQena83513Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Management Information Systems Taif UniversityTaif21944Saudi Arabia

For a 5G wireless communication system,a convolutional deep neural network(CNN)is employed to synthesize a robust channel state estimator(CSE).The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state ***,it utilizes pilots to offer more helpful information about the communication *** proposedCNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory(BiLSTM/LSTM)NNs-based *** CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based *** three different loss function-based classification layers and the Adam optimization algorithm,a comparative study was conducted to assess the performance of the presented DNNs-based *** BiLSTM-CSE outperforms LSTM,CNN,conventional least squares(LS),and minimum mean square error(MMSE)*** addition,the computational and learning time complexities for DNN-CSEs are *** estimators are promising for 5G and future communication systems because they can analyze large amounts of data,discover statistical dependencies,learn correlations between features,and generalize the gotten knowledge.

关键词： DLNNs channel state estimator 5G and beyond communication systems robust loss functions

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Just-in-time and supply chain finance: a hierarchal model development

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International Journal of Industrial and systems engineering 2024年第4期47卷 518-556页

作者： Zaman, Syed Imran Ali, Md. Ramjan Khan, Sharfuddin Ahmed School of Economics and Management Southwest Jiaotong University China Department of Business Administration Jinnah University for Women Karachi Pakistan Department of Mechanical and Production Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh Industrial Systems Engineering Department Faculty of Engineering and Applied Sciences University of Regina SK Canada

This study aims to investigate whether or not just-in-time (JIT) and supply chain finance (SCF) have a synergistic impact on overall organisation performance. The purpose of this study is to help address this knowledge gap and shed light on the role that JIT tools plays in optimising the benefits that SCF offers to an organisation as a whole. Interpretive structural modelling (ISM) and decision making trial and evaluation laboratory (DEMATEL) has been used to explore relationship, contextual link and hierarchical interpretation between JIT and SCF characteristics. Results shows that, the variables with the highest rankings in ISM and DEMATEL are employee attitude, embeddedness of continuity practice, and changing level and position of inventory maintained by businesses. Integration of JIT and SCF will help organisations to increase in revenues, a reduction in waste, an improvement in cash flow, and a reduction in supply chain hazards. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Decision making

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Enablers and barriers of communication in virtual engineering teams: the role of teamwork skills and emergent conflict

Enablers and barriers of communication in virtual engineerin...

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IISE Annual Conference and Expo 2023

作者： Pazos, Pilar Cima, Francisco Department of Engineering Management and Systems Engineering Old Dominion University NorfolkVA United States

ISBN: (纸本)9781713877851

Communication is a critical process that facilitates team members’ coordination, expertise exchange, decision-making, and, consequently, team effectiveness. A focus on effective communication is critical in virtual teams due to their lack of face-to-face interactions and social presence. Communication becomes challenging in remote settings, and specific skills emerge as more essential to success. It is known that effective teams rely on planning, execution, and interpersonal skills to be successful. Still, the specific impact of these skills on virtual team effectiveness is not well understood. Additionally, conflict can emerge as a significant barrier to collaboration for remote teams that can hinder their communication. This paper examines the role of teamwork skills and emergent conflict as predictors of the frequency of communication in virtual engineering project teams. Previously validated measures were used to assess teamwork skills and emergent conflict in a sample of virtual teams. The sample included 101 graduate engineering students working in 32 fully virtual project teams of size 3-4 to complete a semester project on systems analysis and design. Results indicate that skills associated with mission analysis and strategy formulation were the strongest predictors of the frequency of communication, while relationship conflict was associated with low levels of communication. These findings are relevant to organizations that rely on virtual team-based structures by identifying critical levers and barriers to team communication. These findings can be used to identify targets for virtual team training, including a focus on strategic planning and mission analysis, as well as conflict management strategies to prevent and resolve relationship conflict in virtual settings. © IISE and Expo *** rights reserved.

关键词： Decision making

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Proposal of a Tourist Attractions' Introduction Creating Tool Using Deep Learning 16

Proposal of a Tourist Attractions' Introduction Creating Too...

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16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Hasuike, Takashi Liang, Youheng Katagiri, Hideki Tsuda, Hiroshi Waseda University Industrial and Management Systems Engineering Tokyo Japan Kanagawa University Department of Industrial Engineering and Management Kanagawa Japan Doshisha University Faculty of Science and Engineering Kyoto Japan

ISBN: (纸本)9798350377903

By describing images of tourist attractions from different angles and generating descriptions, it is expected to make them more easily searchable by users. In this study, a system, which automatically generates attractive descriptions and introductions of tourist attractions for landscape images, is constructed. The approach is to use convolutional neural networks (CNN), recurrent neural networks (RNN), and Transformer to create factual and sensory descriptions for images, and to use CNN to identify 30 tourist attractions and output introductions. The study considered the accuracy rate of identification by tourist attraction quantity, and automatic and subjective evaluation by the machine of the descriptions. The system can propose a system to create an attractive introduction and a text to introduce tourist attractions by combining facts and sensible descriptions from landscape images. © 2024 IEEE.

关键词： Adversarial machine learning

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A Conjoint-based Approach on Determining the Factors Affecting on Preference of Subscribing a Netflix Plan

A Conjoint-based Approach on Determining the Factors Affecti...

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

作者： Park, Ji Yong Prasetyo, Yogi Tri Cahigas, Maela Madel L. Nadlifatin, Reny School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350386097

This study uses a conjoint analysis approach to determine the key factors influencing subscriber preferences for subscribing to Netflix plan. In a rapidly evolving industry, understanding the drivers of subscription choices is critical for market success. Through a designed survey, respondents are presented with different hypothetical Netflix subscription plans characterized by attributes such as price, resolution, same time watch device, downloadable device and device specs. By analyzing respondents' answers from these attributes, researchers aim to find out the relatedness of each attribute and levels with the subscription preference. The study's findings can help Netflix make more strategic decisions about plan options and pricing policies, so that it can better serve the wide range of demands and tastes of customers in the cutthroat streaming market. © 2024 IEEE.

关键词： Conjoint analysis Netflix streaming market subscription plan

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From Crisis to Strategy and Action: A Qualitative Study to Understand the Impact of COVID-19 on Implementing Knowledge management in Organizations

From Crisis to Strategy and Action: A Qualitative Study to U...

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IISE Annual Conference and Expo 2024

作者： Naderi, Iman Dickerson, Deborah E. Ashrafi, Maryam Grado Department of Industrial and Systems Engineering Virginia Tech BlacksburgVA24061 United States Department of Industrial Engineering and Management Systems Amirkabir University of Technology Tehran Polytechnic Tehran Iran

ISBN: (纸本)9781713877851

As Knowledge management (KM) offers significant benefits for organizations, its implementation is crucial for them to make sure they take advantage of those benefits. However, risks and uncertainties are undeniable when working towards a goal on almost every project. As a result, when approached as a project, Knowledge management Implementation (KMI) would require taking Risk management (RM) into account. With the changes that organizations underwent during the Coronavirus (COVID-19) Pandemic (CP), it is clear that managing risks when it comes to such a situation is exceptionally important. To address this issue, the paper utilizes an RM approach for KMI projects within organizations, with special attention to the risks particularly caused by the CP. More specifically, according to the RM standard by Project management Institute (PMI), to address each identified risk of the project, this paper suggests possible effective strategies and actions to deal with it. As a result, organizations will have a better understanding of how CP can affect KMI in their organizations and what strategies and actions would be helpful in dealing with them. Doing so can help organizations ensure that they can implement KM in their organizations more smoothly and use the KM benefits provided for them. Accordingly, it has been concluded that under the CP environment, KMI project managers should embrace a proactive approach to RM. To accomplish this, they should strive to minimize the negative repercussions of the threats they face and maximize the benefits of the opportunities they are provided. © IISE Annual Conference and Expo *** rights reserved.

关键词： Coronavirus

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Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and Autonomous Systems Institute(TASI)and the Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

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Analyzing Barriers in Adoption of Artificial Intelligence for Resilient Health Care Services to Society

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Global Journal of Flexible systems management 2024年第1期25卷 179-197页

作者： Kumar, Girish Singh, Rajesh Kumar Arya, Vedpal Mishra, Shivam Kumar Department of Mechanical Engineering Delhi Technological University Delhi 110042 India Management Development Institute (MDI) Gurgaon India Department of Industrial Systems Engineering and Management National University of Singapore Singapore Singapore

Artificial intelligence (AI) is emerging as an alternative solution in the healthcare sector, offering opportunities to enhance efficiency and optimize the utilization of precious resources. The nascent stage of AI application in the Indian healthcare sector has gained momentum during COVID-19, witnessing a surge in AI-based startups and companies specializing in diagnostic and prescriptive healthcare. This paper systematically analyzes barriers to AI application in the Indian context, incorporating the concept of flexibility, and proposes insights for fostering its adoption for resilient and sustainable healthcare practices. The identified barriers are drawn from literature and experts’ inputs. These are further investigated using the decision-making trial and evaluation and laboratory methodology. This analysis not only categorizes barriers into cause-and-effect groups but also emphasizes the need for flexibility to adapt AI solutions to the dynamic healthcare sector. The paper underscores foundational barriers, including inadequate regulations, lack of awareness, high adaptation costs, and a scarcity of skilled AI expertise. In addition to managerial and social implications concerning regulation, implementation, economic viability, and data privacy, the study promotes flexibility as a key factor in addressing the evolving challenges in healthcare. © The Author(s) under exclusive licence to Global Institute of Flexible systems management 2024.

关键词： Artificial intelligence Barriers DEMATEL Flexibility Healthcare Resilience Sustainability

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