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International publication trends in Lean Agile management research: a bibliometric analysis

Procedia Computer Science 2023年 219卷 666-673页

作者： Julia Yumi Ito Franciane Freitas Silveira Igor Polezi Munhoz Alessandra Cristina Santos Akkari Graduate Program in Engineering and Innovation Management Federal University of ABC (UFABC) Santo Andre Brazil Federal Institute of Education Science and Technology of Sao Paulo (IFSP) Sao Paulo Brazil

Challenged by complex problems and the speed of technological, social, and environmental change, the joint approach of Lean management and the Agile Mindset has been explored in business as a management model. This paper aimed to carry out a bibliometric analysis of Lean Agile management, pointing out trends in scientific research. To this end, an exploratory and descriptive study was developed, with a quantitative approach and based on secondary data from the Web of Science and Scopus, between 1994 and 2022. Bibliometric indicators pointed to 1808 different papers in 897 sources, with 18 citations per paper, and higher scientific productivity of U.S. (276), India (221), and UK (191), with production peaks in 2018 and 2021, suggesting the diffusion and contemporaneity of the research topic. The laws of bibliometrics were not met for this research subject, and dense networks of collaboration and co-citation among researchers were identified, mainly in four application domains, including supply chain, manufacturing, sustainability, and software development as corroborated by the word network.

关键词： Lean management Lean Agile management Leagile Agile Bibliometrics Publication trends Web of Science Scopus

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The Effectiveness of Online Project-Based Learning (PJBL) to Improve Sustainability Education at Private University 7

The Effectiveness of Online Project-Based Learning (PJBL) to...

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7th International Conference on Information management and technology, ICIMTech 2022

作者： Oktavia, Tanty Prayoga, Agung Vincent Kenth Devani, Vannesa Milewis, Ivena Gaol, Ford Lumban Hosoda, Takaaki BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

Currently, online project-based learning is one of the methodologies used in university student assessment. Furthermore, this study is supported by several factors and current conditions applied to learning, such as the pandemic situation where all learning activities and assignments are carried out online and also the many applications of online project-based learning as a learning method to increase students' knowledges and abilities. The purpose of this study is to see how flow experience perception, self-efficacy, product evaluation, and learning motivation affect online PjBL effectiveness at a private university in Jakarta to improve sustain ability education. We surveyed 62 active undergraduate students with online PjBL experience and interviewed one of these five responders from various majors for more information. Flow experience perception, self-efficacy, product evaluation, and learning motivation all have a positive influence on online PjBL, according to multiple linier regression. © 2022 IEEE.

关键词： Students

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In pursuit of excellence: a historical investigation of scientific production in Indonesia’s higher education system, 1990–2020

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Higher Education 2024年第2期88卷 523-549页

作者： Fu, Yuan Chih Macasaet, Bea Treena Quetzal, Amelio Salvador Junedi, Junedi Moradel-Vásquez, Juan José Graduate Institute of Technical and Vocational Education and Office of Institutional Research and Assessment National Taipei University of Technology No. 1 Sec. 3 Zhongxiao East Rd. Taipei 10608 Taiwan Department of Social Sciences University of Luxembourg 11 Porte des Sciences Esch-Sur-Alzette L-4366 Luxembourg PhD Program in Educational Leadership and Management Development National Chung Cheng University No. 168 Sec. 1 University Rd. Minhsiung Chiayi 621302 Taiwan Graduate Institute of Technical and Vocational Education National Taipei University of Technology Taipei City Taiwan

In its pursuit of global university rankings, Indonesia introduced a series of higher education policies, one in 2014 to grant autonomy to a select group of universities, and another in 2017 to tie financial and promotional incentives to scientific publications for all researchers. To examine scientific productivity surrounding these policies, we use bibliometric data from Scopus spanning three decades from 1990 to 2020. We investigate the patterns of publication and collaboration and analyze them across journal quartiles, academic fields, and researcher cohorts. Our findings reveal that publications increased dramatically for both autonomous and non-autonomous higher education institutions after 2014. Single-university authorship was common practice and skewed publication quality towards Q3 and Q4 journals, while co-authorships with foreign organizations pulled the shift towards Q1 journals consistently across all fields. New researchers starting in 2014 published fewer Q1 and more Q3 and Q4 publications than the earlier cohort. We highlight policy implications on the need for a balance between publication quantity and quality and call on Indonesian policymakers to introduce holistic higher education reforms rather than introducing reforms that focus on the performance of the university for ranking purposes. © The Author(s), under exclusive licence to Springer Nature B.V. 2023.

关键词： Bibliometric analysis Indonesian higher education Research incentives Scientific productivity Scientific quality

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Graph Convolution-Based Recurrent Encoder-Decoder for Anomaly Diagnoses in Multivariate Time-Series Data

SSRN

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SSRN 2024年

作者： Kim, Yejin Lee, Taek-Ho Jeon, Daeseong Park, HyeRim Lee, Changyong Kim, Suhyeon Lee, Junghye Department of Industrial Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Institute of Engineering Research Seoul National University Seoul08826 Korea Republic of Department of Management Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Seoul National University Seoul08826 Korea Republic of Department of Public Administraion Korea University Seoul02841 Korea Republic of Graduate school of Data Science Kyungpook National University Daegu41566 Korea Republic of Technology Management Economics and Policy Program & Graduate School of Engineering Practice Seoul National University Seoul08826 Korea Republic of

Detecting anomalies in multivariate time-series data is an important task in various real-world industries, but doing so is non-trivial because both the temporal dependency within the time series and correlations between multiple time series must be considered. Previous studies have only addressed one issue, resulting in limited performance. To address this, we propose a graph convolution-based recurrent encoder-decoder, called GC-RED. The model incorporates intra-dependencies and inter-correlations using a graph-construction process and an encoding-decoding process that encodes the graph with an attention-enhanced graph convolutional LSTM and then restores it. Anomaly detection and root cause identification are performed based on the reconstruction error. Considering that anomalies with various durations can occur in actual situations, the model includes a vanilla model reflecting single scales and a model reflecting multiple scales. The feasibility and usefulness of GC-RED are demonstrated by intensive experiments on several benchmark and real-world datasets with comparisons to other competitive methods. © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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Tmf-Gnn: Temporal Matrix Factorization-Based Graph Neural Network for Multivariate Time Series Forecasting with Missing Values

SSRN

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SSRN 2023年

作者： Kim, Suhyeon Lee, Taek-Ho Lee, Junghye Graduate School of Data Science Kyungpook National University Daegu41566 Korea Republic of Technology Management Economics and Policy Program & Institute of Engineering Research Seoul National University Seoul08826 Korea Republic of Technology Management Economics and Policy Program & Graduate School of Engineering Practice Seoul National University Seoul08826 Korea Republic of

Missing data in multivariate time series (MTS) is a very common issue, often caused by unreliable sensors and data storage or transmission problems. Particularly, such missing data can cause some errors and biases in the MTS forecasting tasks of real-world applications, implying that proper handling of the missing data is essential. Therefore, in this study, we propose a new method for MTS forecasting with missing values, called a temporal matrix factorization-based graph neural network (TMF-GNN), to improve predictive performance outcomes. TMF-GNN basically uses the concept of TMF, which reconstructs partially observed MTS data. We newly present a data-adaptive regularization method for TMF based on graph-based and sequential deep learning algorithms to capture both the variable- and sample-wise information of MTS data affected by the concept known as missingness. We demonstrate the feasibility of the proposed method by conducting various experiments on three MTS datasets and show how it outperforms baseline methods. We believe that our study will have an impact on several MTS-related tasks and that it can be a useful alternative for handling missing values in MTS data. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Methodology for integrated building energy modeling and impact assessment of urban energy system scenarios

Methodology for integrated building energy modeling and impa...

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Energy and Sustainable Development

作者： Nat Nakkorn Aumnad Phdungsilp Suparatchai Vorarat Graduate Program in Engineering Management College of Innovative Technology and Engineering Dhurakij Pundit University Bangkok Thailand

Local governments require new techniques and innovative approaches to assess initiatives to support the transition towards carbon neutrality. This paper presents a methodological approach for integrated building energy modeling and analysis of the impacts of energy conservation measures (ECMs) and energy-related CO 2 emissions in urban areas. To accomplish this goal, the proposed methodology follows four steps: (1) developing a building stock model for urban databases using a geographic information system (GIS) and QGIS software; (2) creating a detailed archetype-based building stock model using OpenStudio and EnergyPlus; (3) carrying out a scenario analysis of possible ECMs and pathways to achieve carbon neutrality; and (4) analyzing energy savings and energy-related CO 2 emissions. The developed methodology was applied to a tourism urban area, using Pattaya city as a case study. Based on the GIS building model, six archetypes were identified from all residential buildings, including hotels located in the study area. Prototypes of representative building energy models were simulated for a reference case with four ECMs. The results indicated that the building stock in the reference case used 497,669.05 TJ annually and emitted 80,470.32 ktC02eq. Of the four ECMs, a change to double glazing with low-E coating gave the highest energy savings and reductions in CO 2 emissions. This measure led to energy savings of 9,342.82 TJ and emission reductions of 356.23 ktC02eq compared to the reference case. Local governments and stakeholders can benefit from the proposed methodological approach for decision making related to energy and carbon neutrality pathways.

关键词： Analytical models Local government Buildings Urban areas Decision making Energy measurement Prototypes Climate change

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The Water-Energy Nexus of Urban Services in a Tourism City: The Case of Pattaya City

The Water-Energy Nexus of Urban Services in a Tourism City: ...

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Energy and Sustainable Development

作者： Surasak Janchai Aumnad Phdungsilp Suparatchai Vorarat Graduate Program in Engineering Management College of Innovative Technology and Engineering Dhurakij Pundit University Bangkok Thailand

Urban services, such as water and energy resources, are usually consumed more in a tourism city, than in other city types. The water-energy nexus also contributes to the CO 2 emissions from urban areas. The purpose of this research is to investigate the link between water distribution systems, electricity consumption, and energy-related CO 2 emissions from water networks in Pattaya city, Thailand. These networks operate under the Provincial Waterworks Authority (PWA). The water distribution system was modeled in EPANET software, to simulate and examine the water supply capacity in the service pipes, to ensure that it meets the requirement set by PWA. Data were collected from PWA, in terms of the pressure and flow rate of the water supply and the amount of electricity consumption. The current water distribution system consists of 18 junctions, a with flow rate of 1,000 m 3 /hour and pressure at 45 m. The electricity consumption is 720 kWh/day and energy-related CO 2 emissions are 419.11 kgCO 2 eq/day. The water distribution system was modeled and analyzed to find the optimum flow rate and pressure for the least electricity consumption. The results show that the optimum solution is the flow rate of 1,500 m 3 /hour and a pressure at 50 m. Consequently, the electricity consumption is 300 kWh/day, while CO 2 emissions are reduced to 174.63 kgCO 2 eq/day. The findings from this study would benefit the PWA by reducing the electricity consumption and CO 2 emissions equivalent to 109 MWh/year and 63.73 tCO 2 eq, respectively.

关键词： Climate change Analytical models Energy resources Computational modeling Urban areas Distribution networks Energy conservation Water management

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CAFO: Feature-Centric Explanation on Time Series Classification

arXiv

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arXiv 2024年

作者： Kim, Jaeho Hahn, Seok-Ju Hwang, Yoontae Lee, Junghye Lee, Seulki Ulsan Korea Republic of Ulsan Korea Republic of Technology Management Economics and Policy Program Graduate School of Engineering Practice Institute of Engineering Research Seoul Korea Republic of Ulsan Korea Republic of

In multivariate time series (MTS) classification, finding the important features (e.g., sensors) for model performance is crucial yet challenging due to the complex, high-dimensional nature of MTS data, intricate temporal dynamics, and the necessity for domain-specific interpretations. Current explanation methods for MTS mostly focus on time-centric explanations, apt for pinpointing important time periods but less effective in identifying key features. This limitation underscores the pressing need for a feature-centric approach, a vital yet often overlooked perspective that complements time-centric analysis. To bridge this gap, our study introduces a novel feature-centric explanation and evaluation framework for MTS, named CAFO (Channel Attention and Feature Orthgonalization). CAFO employs a convolution-based approach with channel attention mechanisms, incorporating a depth-wise separable channel attention module (DepCA) and a QR decomposition-based loss for promoting feature-wise orthogonality. We demonstrate that this orthogonalization enhances the separability of attention distributions, thereby refining and stabilizing the ranking of feature importance. This improvement in feature-wise ranking enhances our understanding of feature explainability in MTS. Furthermore, we develop metrics to evaluate global and class-specific feature importance. Our framework’s efficacy is validated through extensive empirical analyses on two major public benchmarks and real-world datasets, both synthetic and self-collected, specifically designed to highlight class-wise discriminative features. The results confirm CAFO’s robustness and informative capacity in assessing feature importance in MTS classification tasks. This study not only advances the understanding of feature-centric explanations in MTS but also sets a foundation for future explorations in feature-centric explanations. The codes are available at https://***/eai-lab/CAFO. © 2024, CC BY-SA.

关键词： Time series

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technology Forecast of Artificial Intelligence Applied to Medication Decision Support System

Technology Forecast of Artificial Intelligence Applied to Me...

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Portland International Conference on management of Engineering and technology (PICMET)

作者： Kae-Kuen Hu Kuo-Liang Chen Mo-An Chu Chen Peng Chia-Min Lin Li-Ling Cho Professional Master's Program of Biotechnology Management National Taiwan University Taipei City Taiwan Department of Marketing and Distribution Management National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Graduate Institute of Patent National Taiwan University of Science and Technology Taipei City Taiwan

ISBN: (数字)9781890843458

ISBN: (纸本)9798350369137

This study analyzes the decision-making support system based on artificial intelligence, which provides decision-making support and suggestions for doctors' clinical medication, and its technical characteristics. The study conducted interviews with 6 experts and scholars and analyzed a total of 267 experts with questionnaires. Three rounds of questionnaire interviews and responses were conducted from the four dimensions of “technology”, “process”, “behavior” and “influence”, and a mixed method approach was adopted. The analysis method is used to analyze to clarify the technical predictions or expectations of technology developers and technology users for the application of artificial intelligence in clinical medication decision support systems. The research results indicate that the construction of the system requires a large amount of patient medical information, clinical treatment guidelines and other medical professional knowledge for technology developers. For technology users, there are issues related to “user field” and “user habits” regarding user processes and behaviors, so opinions are inconsistent. In particular, clinical experts believe that critical procedures and high-risk situations will affect the utilization rate of artificial intelligence introduction. Therefore, system development should include medical personnel to provide suggestions and feedback on the construction of the system, in terms of medical information, clinical treatment guidelines and other medical professional knowledge.

关键词： Decision support systems Drugs Supply and demand Buildings Medical services Personnel Artificial intelligence

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Energy Performance and Thermal Comfort in a Library Building: A Case Study of Dhurakij Pundit University, Thailand

Energy Performance and Thermal Comfort in a Library Building...

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Energy and Sustainable Development

作者： Auntika Thongsean Aumnad Phdungsilp Suparatchai Vorarat Rangsit Sarachitti Graduate Program in Engineering Management College of Innovative Technology and Engineering Dhurakij Pundit University Bangkok Thailand

The building sector represents high potential to address the energy use and occupants' comfort and well-being. This paper aims to proposed a methodological framework to assess energy and thermal comfort performance in buildings. The research framework was applied in an educational building using a library of Dhurakij Pundit University (DPU), Thailand as a case study. A representative building was modeled using SketchUp plugin with OpenStudio platform and EnergyPlus simulation engine for energy simulation. Thermal comfort parameters were measured in each floor of DPU's library and calculation of thermal comfort indices based on the PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) using the CBE Thermal Comfort Tool. It was found that the simulated energy is in line with the measured data with differences between -0.26% to 3.87%, depending on the floor. The energy intensity of DPU's library is 66.53 kWh/m2/year. Based on the measurements, the PMV and PPD of a reference building are -0.57 and 12%. Ten measures were simulated to assess the energy performance as well as thermal comfort conditions. It was found that seven measures can address both energy performance and thermal comfort in a case study building.

关键词： Economics Buildings Energy measurement Light emitting diodes Thermal conductivity Climate change Thermal analysis

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