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Current research and future challenges in parcel hub towards logistics 4.0: a systematic literature review from a decision-making perspective

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International Journal of Production Research 2024年第23期62卷 8562-8593页

作者： Chen, James C. Anggrahini, Dewanti Chen, Tzu-Li Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Department of Industrial and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan

Parcel hub (PH), as one of the logistic system entities, plays a significant role in delivering packages. PH operations are identical to a cross-docking system. Numerous studies were conducted to examine solutions in PH and cross-docking in general. This paper aims to investigate scientific references published within the last fifteen years through a systematic literature review (SLR). The objectives are to determine the critical decisions related to PH problems, classify the applied solution approach, and identify the future challenges regarding the transformation towards intelligent logistics. This study implements an SLR methodology that consists of five stages: planning, searching, screening, analysing, and reporting. This study utilises two publication databases and one reference management system. More than four thousand documents were collected in the searching stage. Then, five assessments are conducted to sort the most relevant papers. One hundred and forty-six articles are included in the further analysis. This study classifies four important decisions associated with PH problems: truck scheduling, internal process planning, facility planning, and technology selection. In addition, this study categorises ten solution approaches employed to find the best decision in the prior research. Moreover, this study explains the future research directions and managerial implications of managing parcel hub systems. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Decision making

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Navigating Innovation within a Contractor’s Business Model: A System Dynamics Approach

Navigating Innovation within a Contractor’s Business Model:...

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IEEE International Conference on System of systems engineering (SoSE)

作者： Mariam Elazhary Cihan Dagli Islam H. El-Adaway Ph.D. Graduate Student Dept. of Civil Architectural and Environmental Engineering Missouri Univ. of Science and Technology Rolla MO Professor Dept. of Engineering Management and Systems Engineering Missouri Univ. of Science and Technology Rolla MO Professor Dept. of Civil Architectural and Environmental Engineering Dept. of Engineering Management and Systems Engineering Missouri Univ. of Science and Technology Rolla MO

ISBN: (数字)9798350365917

ISBN: (纸本)9798350365924

Innovation is essential in the construction industry, but current practices often focus narrowly on specific aspects rather than taking a comprehensive approach. To address this, systematic innovation through business model innovation (BMI) is proposed to enhance overall performance. Despite increasing interest in BMI research, it remains in its early stages, lacking quantitative analysis of its impact on business model components. This paper develops a framework using system dynamics to assess changes to a construction company’s BM when faced with a variety of innovations across various projects. This shall be accomplished by (1) establishing factors and their relationships that define a contractor’s BM over time, (2) modeling the said factors using AnyLogic using synthetic data, and (3) evaluating the emergent behavior of BM’s value creation. The study found that the impact of innovation on a contractor’s long-term value creation is not linear; it varies based on when and what type of innovation is implemented. This complexity arises from the trade-offs between cost reductions and additional expenses associated with innovation. The paper introduces a comprehensive framework to assess how innovation affects a contractor’s business model, enabling practitioners to understand better and manage their long-term value-creation strategies.

关键词： Technological innovation Systematics System dynamics Statistical analysis Navigation Data models Modeling

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EXPLOITING AUDIO-VISUAL FEATURES WITH PRETRAINED AV-HUBERT FOR MULTI-MODAL DYSARTHRIC SPEECH RECONSTRUCTION

arXiv

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arXiv 2024年

作者： Chen, Xueyuan Wang, Yuejiao Wu, Xixin Wang, Disong Wu, Zhiyong Liu, Xunying Meng, Helen Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Shenzhen International Graduate School Tsinghua University Shenzhen China Vocal Engineering Technologies Limited Hong Kong

Dysarthric speech reconstruction (DSR) aims to transform dysarthric speech into normal speech by improving the intelligibility and naturalness. This is a challenging task especially for patients with severe dysarthria and speaking in complex, noisy acoustic environments. To address these challenges, we propose a novel multi-modal framework to utilize visual information, e.g., lip movements, in DSR as extra clues for reconstructing the highly abnormal pronunciations. The multi-modal framework consists of: (i) a multi-modal encoder to extract robust phoneme embeddings from dysarthric speech with auxiliary visual features;(ii) a variance adaptor to infer the normal phoneme duration and pitch contour from the extracted phoneme embeddings;(iii) a speaker encoder to encode the speaker’s voice characteristics;and (iv) a mel-decoder to generate the reconstructed mel-spectrogram based on the extracted phoneme embeddings, prosodic features and speaker embeddings. Both objective and subjective evaluations conducted on the commonly used UASpeech corpus show that our proposed approach can achieve significant improvements over baseline systems in terms of speech intelligibility and naturalness, especially for the speakers with more severe symptoms. Compared with original dysarthric speech, the reconstructed speech achieves 42.1% absolute word error rate reduction for patients with more severe dysarthria levels.1 Copyright © 2024, The Authors. All rights reserved.

关键词： Embeddings

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Investigating the interrelationships between the barriers of green computing adoption: TISM-MICMAC-DEMATEL method

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Quality and Quantity 2024年第1期59卷 507-570页

作者： Dalvi-Esfahani, Mohammad Nilashi, Mehrbakhsh Abumalloh, Rabab Ali Thurasamy, Ramayah Ahmad, Muhammad Shakil Blockchain Fintech and Cryptocurrency Research Group University of Southampton Malaysia Johor Iskandar Puteri 79100 Malaysia UCSI Graduate Business School UCSI University No. 1 Jalan Menara Gading UCSI Heights Cheras Kuala Lumpur 56000 Malaysia Department of Computer Science and Engineering Qatar University Doha 2713 Qatar School of Management Universiti Sains Malaysia Minden Penang 11800 Malaysia Department of Information Technology and Management Daffodil International University Birulia Bangladesh Department of Management Sunway Business School (SBS) Selangor Petaling Jaya 47500 Malaysia University Center for Research & amp Development (UCRD) Chandigarh University Punjab Ludhiana 140413 India Faculty of Economics and Business Universitas Indonesia (UI) West Java Depok City 16424 Indonesia Management Information Systems Department School of Business The University of Jordan (UJ) Amman 11942 Jordan TUIBS Leadership Management & amp Human Resources Teesside University Middlesbrough United Kingdom Faculty of Business Sohar University Sohar P.C 311 Oman

While a considerable body of research addresses firms’ endeavors toward environmental sustainability, the prominence of green computing has been somewhat eclipsed by impediments hindering its swift integration and development. To address this gap, this study conducted a comprehensive analysis, identifying twelve distinct barriers categorized into adoption costs, technological challenges, and internal obstacles. Through consultation with fifteen field experts, the study employed Interpretive Structural Modeling (ISM) and Matrice d’Impacts Croises Multipication Applique´ an Classment (MICMAC) methodologies to scrutinize the influences among these barriers. The findings illuminated that firm size and legal constraints emerge as pivotal and autonomous factors exerting substantial influence on the adoption. Additionally, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was deployed to ascertain the relative importance of these barriers and delineate their causal relationships. Notably, the DEMATEL results underscored that, according to experts, adoption cost barriers hold greater significance compared to other dimensions. Transactional risk, technological complexity, and switching cost were identified as pivotal barriers within their respective dimensions. The decision-making framework formulated in this study offers valuable insights for managers and practitioners, providing a nuanced understanding of the interplay between identified barriers and their implications for implementing green computing initiatives. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.

关键词： Barriers DEMATEL Green computing MICMAC Total interpretive structural modeling

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Analysis of Vlog Transcripts using Topic Modeling, Summarizer, and Cluster Analysis 53

Analysis of Vlog Transcripts using Topic Modeling, Summarize...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Singh, Upmanyu Sikorski, Tiffany-Rose Wortham, Erica Shittu, Ekundayo Columbian College of Arts and Sciences The George Washington University WashingtonDC United States Graduate School of Education and Human Development The George Washington University WashingtonDC United States Gw Innovation Center School of Engineering and Applied Science The George Washington University WashingtonDC United States Engineering Management & Systems Engineering The George Washington University WashingtonDC United States

ISBN: (纸本)9798350336429

This paper demonstrates the use of natural language processing (NLP) models to analyze qualitative data for engineering education research purposes. Three NLP models are applied: topic modelling, which identifies salient keywords in text;summarizer, which extracts and concatenates sentences with unique meaning from a text;and cluster analysis, which groups texts together based on similar word sequences. The study applied these techniques to short video logs, or vlogs, collected as part of a case study of undergraduate engineering students' exposure to a social innovation curriculum. The curriculum aimed to teach students to use their engineering skills to identify and address issues that cause suffering for marginalized communities. In the vlogs, students responded to prompts asking them to describe what social issues they are passionate about, how they relate to these issues, and how they would propose exploring and addressing those issues. Vlogs were transcribed, pre-processed, and then examined with each technique to identify patterns within and across the prompts. Widely-recognized limitations of NLP techniques included the potential loss of important contextual information and the dependence on large volumes of data to produce valid and reliable results. Despite these limitations, the combination of three techniques was effective for locating high priority transcripts within the data corpus, identifying themes within and across vlogs, and supporting longitudinal analysis of student responses. Previous literature has documented the utility of topic modeling and other NLP techniques to analyze large volumes of written text on, for example, course evaluations or student writing assignments. Importantly, this study demonstrates the novel and meaningful application of topic modelling, summarizer, and cluster analysis to analyze a relatively small corpus of transcript data. Given these results, we are optimistic about the potential for NLP approaches to complement ot

关键词： cluster analysis Natural Language Processing social innovation topic modeling

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Stylespeech: Self-Supervised Style Enhancing with VQ-VAE-Based Pre-Training for Expressive Audiobook Speech Synthesis

Stylespeech: Self-Supervised Style Enhancing with VQ-VAE-Bas...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xueyuan Chen Xi Wang Shaofei Zhang Lei He Zhiyong Wu Xixin Wu Helen Meng Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong SAR China Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Shenzhen International Graduate School Tsinghua University Shenzhen China Microsoft Beijing China

The expressive quality of synthesized speech for audiobooks is limited by generalized model architecture and unbalanced style distribution in the training data. To address these issues, in this paper, we propose a self-supervised style enhancing method with VQ-VAE-based pre-training for expressive audiobook speech synthesis. Firstly, a text style encoder is pre-trained with a large amount of unlabeled text-only data. Secondly, a spectrogram style extractor based on VQ-VAE is pre-trained in a self-supervised manner, with plenty of audio data that covers complex style variations. Then a novel architecture with two encoder-decoder paths is specially designed to model the pronunciation and high-level style expressiveness respectively, with the guidance of the style extractor. Both objective and subjective evaluations demonstrate that our proposed method can effectively improve the naturalness and expressiveness of the synthesized speech in audiobook synthesis especially for the role and out-of-domain scenarios. 1

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Toward a Patient-Centered Care Supporting System: Integration of Multidisciplinary Health Records in Breast Cancer Care

Toward a Patient-Centered Care Supporting System: Integratio...

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34th Medical Informatics Europe Conference, MIE 2024

作者： Sugiyama, Atsuko Utsunomiya, Kazuki Okumiya, Hayato Fujimoto, Katsuhiko Shimomura, Yuka Sanuki, Masaru Kume, Keitaro Yano, Takahiro Kagawa, Rina Bando, Hiroko Canon Medical Systems Corporation Tochigi Otawara Japan Graduate School of Biomedical Engineering Tohoku University Miyagi Sendai Japan Laboratory of Mathematical Informatics in Medicine University of Tsukuba Ibaraki Tsukuba Japan Department of Biomedical Informatics and Management University of Tsukuba Hospital Ibaraki Tsukuba Japan Department of Breast-Thyroid-Endocrine Surgery Institute of Medicine University of Tsukuba Ibaraki Tsukuba Japan

ISBN: (纸本)9781643685335

An important paradigm shift within healthcare is the shift toward patient-centered care (PCC). Multidisciplinary team meetings (MDTM) are considered essential for PCC, despite being considered time-consuming and expensive. Patient-centered information (PCI) is known to improve the quality of care. This study investigated where and how the PCI of multidisciplinary professionals' health records exists, and to explore the possibility of a sustainable PCC-supporting healthcare system. We performed an exploratory pilot study of the patient records of three patients with breast cancer. We observed that PCI was documented throughout the care pathway in the cases examined. However, we also found that these data were fragmented and scattered across various medical records, and they were also from different point of views and patient care perspectives. PCI was founded to be less accessible than traditional medical records and was even hard to find using a manual search. We therefore propose that preparing PCI for MDTM may be one of the obvious burdens for healthcare professionals (HPs). We do however believe that integrating PCI from multiple professionals' records likely plays an important function in a shift towards PCC and serves to improve not only the quality of care but also the HPs' experiences without additional burden and could contribute to a more sustainable health care system. © 2024 The Authors.

关键词： Electronic health record

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LEARNING DISCRIMINATIVE FEATURES FROM SPECTROGRAMS USING CENTER LOSS FOR SPEECH EMOTION RECOGNITION

arXiv

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arXiv 2025年

作者： Dai, Dongyang Wu, Zhiyong Li, Runnan Wu, Xixin Jia, Jia Meng, Helen Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Graduate School at Shenzhen Tsinghua University Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin Hong Kong

Identifying the emotional state from speech is essential for the natural interaction of the machine with the speaker. However, extracting effective features for emotion recognition is difficult, as emotions are ambiguous. We propose a novel approach to learn discriminative features from variable length spectrograms for emotion recognition by cooperating softmax cross-entropy loss and center loss together. The softmax cross-entropy loss enables features from different emotion categories separable, and center loss efficiently pulls the features belonging to the same emotion category to their center. By combining the two losses together, the discriminative power will be highly enhanced, which leads to network learning more effective features for emotion recognition. As demonstrated by the experimental results, after introducing center loss, both the unweighted accuracy and weighted accuracy are improved by over 3% on Mel-spectrogram input, and more than 4% on Short Time Fourier Transform spectrogram input. Copyright © 2025, The Authors. All rights reserved.

关键词： Spectrographs

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Customer Load Profile Clustering Using K-means Algorithm: A Case Study in an Electric Distribution Company in the Philippines Amidst the COVID-19 Pandemic

Customer Load Profile Clustering Using K-means Algorithm: A ...

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2022 IEEE International Conference on Industrial engineering and engineering management, IEEM 2022

作者： Navarro, M.M. Young, M.N. Prasetyo, Y.T. Nadlifatin, R. Mapúa University School of Industrial Engineering and Engineering Management Manila Philippines Mapúa University School of Graduate Studies Manila Philippines Technological Institute of the Philippines Department of Industrial Engineering Quezon City Philippines Institut Teknologi Sepuluh Nopember Kampus Its Sukolilo Department of Information Systems Surabaya Indonesia

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Most of the electric distribution companies in the Philippines are interested in analyzing customer load profile, they are concerned in classifying their customer's profile into different categories based on the energy consumption, Also the user's profile will help to understand how the consumption of energy may affect the electric distribution grid. In the current condition right now, facing the COVID-19 pandemic, most Filipinos are inclined to work at home, thus the consumption of energy increased. In this paper, residential data were collected in one of the electric distribution companies in the Philippines amidst the COVID-19 pandemic conditions. The data consist of 1,048,575 customer profiles from the year 2021. This study aims to use clustering methods such as the K-means algorithm in grouping customers' profiles and validate the suitable amount of clusters using the proposed method, such as the multi-criteria model and elbow method. Results show that 2 and 7 clusters, respectively, were fitted in the data. © 2022 IEEE.

关键词： COVID-19

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Optimal Maintenance Policies of Breakwater Armored with Wave-Dissipating Blocks 27

Optimal Maintenance Policies of Breakwater Armored with Wave...

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27th ISSAT International Conference on Reliability and Quality in Design

作者： Yunlong, Dong Ito, Kodo Higuchi, Yoshiyuki Department of Social Management Engineering Graduate School of Engineering Tottori University Minami 4-101 Koyama Tottori Tottori-shi680-8552 Japan Faculty of Symbiotic Systems Science Fukushima University Kanayagawa 1-ban Fukushima Fukushima-shi960-1296 Japan

ISBN: (纸本)9798986576107

The social infrastructure has to be maintained economically and efficiently because the scale is huge, maintenance budgets of local governments are strict, and the number of skillful maintenance workers declines. Optimal policies which consider the characteristics of social infrastructure maintenance are needed for economical and efficient maintenance. We have established such optimal maintenance policies utilizing the cumulative damage model and apply them to the solution of actual problem of breakwater in a port on the Sea of Japan. Although it is known that the deterioration of breakwaters is Weibull distribution, it is not easy to calculate the optimum policy in the case of the Weibull distribution. This problem is solved by using the approximate formula, the optimum policies are obtained, and we can show that the actual policies undergone by the local government are appropriate because the same policies are obtained theoretically. © 2022 International Society of Science and Applied Technologies

关键词： Budget control

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