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50th International Conference on Computers and Industrial engineering: Sustainable Digital Transformation, CIE 2023

作者： Sleem, Ahmad Abu Alromema, Mohammed Abdel-Aal, Mohammad A.M. Industrial & Systems Engineering Department King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center of Smart Mobility & Logistics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9781713886952

This study provides a modified Bass model to deal with trend curves for basic issues of relevance to individuals from all over the world, for which we collected 16 data sets from 2004 to 2022 and that are available on Google servers as "google trends". It was discovered that the Bass model did not forecast well for curves that have a mono peak with a sharp decrease to some level then have semi-stable with small decrement sales for a long time, thus a new parameter based on r1 and r2 (ratios of average sales) was introduced, which improved the model's prediction ability and provided better results. The model was also applied to a data set taken from the Kaggle website about a subscriber digital product offering for financial services that includes newsletters, webinars, and investment recommendations. The data contain 508932 data points about the products sold during 2016-2022. Compared to the traditional Bass model, the modified model showed better results in dealing with this condition, as the expected curve shape was closer to real sales, and the sum of squares error (SSE) value was reduced to a ratio ranging between (36.35-79.3%). Therefore, the improved model can be relied upon in these conditions. © 2023 Computers and Industrial engineering. All rights reserved.

关键词： Sales

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What Matters in Accreditation? A Case Study in Chile

What Matters in Accreditation? A Case Study in Chile

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Computer Science Society (SCCC) International Conference Chilean

作者： Lucía González Sol Riquelme-Gutiérrez Cristóbal Mauricio Óscar C. Vásquez Department of Industrial Engineering Faculty of Engineering University of Santiago of Chile (USACH) Chile program for the Development of Sustainable Production Systems (PDSPS) Faculty of Engineering University of Santiago of Chile (USACH)

ISBN: (数字)9798331527891

ISBN: (纸本)9798331527907

The accreditation assessment of a program in higher education institutions is a process that verifies, promotes and guarantees educational quality. In Chile, it is carried out by the National Accreditation Commission, a public autonomous organization, which considers different criteria, ending up into the number of years the program is accredited. This work aims to investigate the most relevant criteria into this assessment, considering the official records of the institution through a statistical model suitable for pattern recognition. Particularly, we analyze on Master programs related to Industrial engineering. Preliminary results allow us to distinguish the main variables for improving decision-making practices, it is noted that the most prominent one is the criterion associated to the prestige of the institution where the master's program is hosted.

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Development of LiFx/Al2O3/ITO Multilayer Antireflection Coatings for Reflectance Reduction in Silicon Heterojunction Solar Cells

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Physica Status Solidi (A) Applications and Materials Science 2025年第0期

作者： Aida, Maha Nur Khokhar, Muhammad Quddamah Yousuf, Hasnain Chu, Mengmeng Rahman, Rafi Ur Alamgeer, Khan Bae, Junhan Jang, Seokjin Yi, Junsin Department of Future Energy Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of

This study focuses on the optimization of antireflection coatings (ARCs) to enhance the performance of silicon heterojunction (SHJ) solar cells. SHJ solar cells face a significant challenge in achieving their theoretical efficiency limits due to light reflection at the air–cell interface. This reflection reduces photon absorption, which limits photocurrent generation and hinders the widespread adoption of SHJ technology. To address this, the optimization of ARCs using single, double, and triple-layer designs with a graded refractive index material as the active layer is investigated. The optimization process is simulated by calculating the layer thicknesses using OPAL2 software and validated through experimental deposition. The results demonstrate that a triple-layer ARC structure consisting of 80/50/95 nm of indium tin oxide (ITO), aluminum oxide (Al2O3), and lithium fluoride (LiFx) significantly improves SHJ performance. This configuration leads to a 1.04 mA cm−2 increase in short-circuit current density (Jsc), reaching 39.85 mA cm−2, and an efficiency of 21.62%, compared to a single-layer ARC. This study presents a promising solution to improve SHJ solar cell efficiency by reducing reflection losses and optimizing optical properties, contributing to the advancement of SHJ technology and facilitating the development of more efficient and cost-effective photovoltaic systems for sustainable energy transition. © 2025 Wiley-VCH GmbH.

关键词： Antireflection coatings

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LATTICE-VALUED BOTTLENECK DUALITY

arXiv

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arXiv 2024年

作者： Ghrist, Robert Gould, Julian Lopez, Miguel Department of Mathematics Department of Electrical & Systems Engineering and Program in Applied Mathematics & Computational Science University of Pennsylvania United States

This note reformulates certain classical combinatorial duality theorems in the context of order lattices. For source-target networks, we generalize bottleneck path-cut and flow-cut duality results to edges with capacities in a distributive lattice. For posets, we generalize a bottleneck version of Dilworth’s theorem, again weighted in a distributive lattice. These results are applicable to a wide array of non-numerical network flow problems, as shown. All results, proofs, and applications were created in collaboration with AI language models. An appendix documents their role and *** Codes 06D05, 90C35, 06A07 © 2024, CC BY.

关键词： Combinatorial optimization

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Performance Evaluation of Hierarchical Federated Learning on Resource-Constrained IoT systems

Performance Evaluation of Hierarchical Federated Learning on...

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IEEE Conference on Vehicular Technology (VTC)

作者： Mumin Adam Uthman Baroudi Department of Computer Engineering Interdisciplinary Center for Intelligent Secure Systems King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

The Internet of Things (IoT) has transformed how smart cities operate, significantly improving their inhabitants’ efficiency and overall quality of life. However, the massive volume of sensitive data generated by IoT devices presents challenges, including privacy concerns and communication overheads. Traditional centralized data processing can compromise privacy and require significant communication, leading to scalability problems and power drains. Federated Learning (FL) offers a solution by processing data locally and transmitting only the model parameters. Vanilla FL faces challenges in IoT environments due to latency, bandwidth constraints, and power drain. Hierarchical FL (HFL) effectively addresses these issues by hierarchically leveraging the processing capabilities of both cloud and edge servers to optimize resource utilization and efficiently minimize latency. This paper evaluates HFL using IoT-derived datasets, develops and implements the HFL framework for resource-constrained IoT systems, and conducts the first known HFL tests on relevant datasets to demonstrate its performance.

关键词： Data privacy Vehicular and wireless technologies Federated learning Smart cities Computational modeling Scalability Data models Internet of Things Resource management Servers

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Optimizing Multi-Objective Reverse Logistics Network Structure through Analytical Hierarchical Process and Decision Tree Analysis 50

Optimizing Multi-Objective Reverse Logistics Network Structu...

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50th International Conference on Computers and Industrial engineering: Sustainable Digital Transformation, CIE 2023

作者： Hussain, Aamir AlDurgam, Mohammad M. Industrial and Systems Engineering Department King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Smart Mobility & Logistics King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9781713886952

Reverse logistics is an important aspect of supply chain management, as it involves the return and disposal of products, materials, and equipment. To make strategic and cost-effective decisions about reverse logistics, companies need to have a systematic method for evaluating and comparing different options. In this study, we propose the use of the analytical hierarchical process (AHP) and decision tree analysis (DTA) as decisionmaking tools for configuring a reverse logistics network. The AHP allows the decision-makers to consider a wide range of factors when making decisions and to weigh the relative importance of each factor, while DTA provides a measure of the investment cost under uncertainty. We demonstrate the use of AHP and DTA through a case study of an electronics company that has multiple return channels and different disposition actions for returned products (i.e. refurbish or dispose off). Our results show that AHP and DTA can be used together to make informed, objective decisions about reverse logistics and to optimize the efficiency and cost of the reverse logistics network. © 2023 Computers and Industrial engineering. All rights reserved.

关键词： Supply chain management

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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

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Computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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Comparing the efficacy of AR-based training with video-based training

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2022年第1期66卷 1862 - 1866页

作者： Shivangi Dwivedi John Hayes Isabella Pedron John Kang Lindsey J. Brenner Connor Barnes Ashley Bailly Kyle Tanous Cassidy Nelson Jason Moats JosephL. Gabbard Ranjana K. Mehta Department of Industrial and Systems Engineering Department of Chemical Engineering Department of Interdisciplinary Engineering Department of Biomedical Engineering Texas A&M University Texas Department of Industrial and Systems Engineering Virginia Tech Virginia Texas A&M Engineering Extension Service Texas

In recent years, US Emergency Medical Services (EMS) have faced a massive shortage of EMS workers. The sudden outbreak of the pandemic has further exacerbated this issue by limiting in-person training. Additionally, current training modalities for first responders are costly and time-consuming, further limiting training opportunities. To overcome these challenges, this paper compares the efficacy of augmented reality (AR), an emerging training modality, and video-based training to address many of these issues without compromising the quality of the training with reduced instructor interaction. We examined performance, subjective, and physiological data to better understand workload, user engagement, and cognitive load distribution of 51 participants during training. The statistical analysis of physiological data and subjective responses indicate that performance during AR and video-based training and retention phases depended on gender perception of workload and cognitive load (intrinsic, germane, extraneous). However, user engagement was higher in AR-based training for both genders during training.

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Efficient Spectrum Sensing via a Multi-Scale Dual-Path Segmentation Network

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IEEE Wireless Communications Letters 2025年

作者： Le, Truong-Thinh da Costa, Daniel Benevides Huynh-The, Thien Ho Chi Minh City University of Technology and Education Department of Computer and Communications Engineering Ho Chi Minh City71307 Viet Nam Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia

This paper introduces an advanced spectrum sensing (SS) method for next–generation wireless networks that utilize dual–path architecture called DPSegNet. This innovative model is designed to precisely segment 5G new radio (NR) and long–term evolution (LTE) signals by identifying the spectral content based on the frequency and time occupied by the signals. DPSegNet incorporates a context path to capture high–level semantic information, a spatial path to preserve detailed spatial features, and a novel feature fusion mechanism to effectively combine information from both pathways. This architecture effectively learns both local and global spectral features, thereby significantly enhancing its segmentation performance. The experimental results highlight the efficiency and effectiveness of DPSegNet, with a compact architecture consisting only 7M parameters, it achieves high performance with a global accuracy of 97.25% and a mean intersection–over–union (IoU) of 94.76%. These results demonstrate that DPSegNet is a highly promising solution for next–generation wireless communication systems. © 2012 IEEE.

关键词： Semantic Segmentation

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LINEAR AND NON-LINEAR MODELS FOR MASTER SCHEDULING OF DYNAMIC RESOURCES PRODUCT MIX 50

LINEAR AND NON-LINEAR MODELS FOR MASTER SCHEDULING OF DYNAMI...

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50th International Conference on Computers and Industrial engineering: Sustainable Digital Transformation, CIE 2023

作者： Mohammed, Ayman R. Sleem, Ahmad A.B.U. Abdel-Aal, Mohammad A.M. Industrial & Systems Engineering Department King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center of Smart Mobility & Logistics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9781713886952

The literature on master production scheduling for product mix problems under the Theory of Constraints (TOC) was considered by many previous studies. Most studies assume a static resources availability. In this study, the raw materials supplied to the manufacturer is considered as dynamic depending on the results of the problem. Thus, an integer linear heuristic, an integer non-linear optimization model, and a basic non-linear model are developed to find a good solution of the problem. The results of the three models were compared to each other in terms of profit, raw materials costs, inventory costs and raw materials utilization. Recent studies in the field are reviewed and conclusions are drawn. © 2023 Computers and Industrial engineering. All rights reserved.

关键词： Nonlinear programming

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