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arXiv 2023年

作者： Fischer-Abaigar, Unai Kern, Christoph Barda, Noam Kreuter, Frauke Dept. of Statistics LMU Munich Germany Munich Center for Machine Learning Germany Joint Program in Survey Methodology University of Maryland United States Dept. of Software and Information Systems Engineering Dept. of Epidemiology Biostatistics and Community Health Sciences Ben-Gurion University of the Negev Israel

AI-driven decision-making systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, these systems face the challenge of aligning machine learning (ML) models with the complex realities of public sector decision-making. In this paper, we examine five key challenges where misalignment can occur, including distribution shifts, label bias, the influence of past decision-making on the data side, as well as competing objectives and human-in-the-loop on the model output side. Our findings suggest that standard ML methods often rely on assumptions that do not fully account for these complexities, potentially leading to unreliable and harmful predictions. To address this, we propose a shift in modeling efforts from focusing solely on predictive accuracy to improving decision-making outcomes. We offer guidance for selecting appropriate modeling frameworks, including counterfactual prediction and policy learning, by considering how the model estimand connects to the decision-maker’s utility. Additionally, we outline technical methods that address specific challenges within each modeling approach. Finally, we argue for the importance of external input from domain experts and stakeholders to ensure that model assumptions and design choices align with real-world policy objectives, taking a step towards harmonizing AI and public sector objectives. © 2023, CC BY-NC-ND.

关键词： Crime

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Spherical scanning 3-D microwave imaging of near-field scatterers mutually coupled with an antenna array

TechRxiv

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TechRxiv 2021年

作者： Watanabe, Takuma Yamada, Hiroyoshi Fujitsu Ltd. Kawasaki2118588 Japan the Smart Information Systems Program Faculty of Engineering Niigata University Niigata9502181 Japan

In this article, we propose a 3-D synthetic aperture imaging method with spherical antenna scanning to identify scatterers located close to an antenna array, such as fixtures or support of the antenna. Previous studies have shown that 2-D and 3-D synthetic aperture imaging techniques with planar, circular, and cylindrical scanning can successfully reconstruct spatial images of near-field scatterers. The spherical scanning approach considered in this article is expected to improve the 3-D image resolution because more angular diversity can be achieved in the elevation direction. However, as we show in this study, simple extension of the previous techniques to the spherical case results in undesired blur artifacts in the reconstructed image. To overcome this problem, we introduce a correction factor in the image reconstruction. The proposed imaging algorithm is validated by numerical electromagnetic simulation based on the method of moments. © 2021, CC BY.

关键词： Antenna arrays

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COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT systems IMPLEMENTATION TO OPTIMIZE BUSINESS SUSTAINABILITY 9

COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYS...

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9th International Conference on information Technology: IoT and Smart City, ICIT 2021

作者： Sardjono, Wahyu Lusia, Erma Utomo, Hargo Sukardi, Samudra Rahmasari, Aninda Regent Montororing, Yuri Delano Information Systems Management Department Binus Graduate Program Bina Nusantara University Indonesia Research Capacity Building Research & Development Bina Nusantara University Indonesia Department of Management Faculty of Economic and Business Gajah Mada University Indonesia Graduate Program Faculty of Economy and Business University of Indonesia Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Indonesia Industrial Engineering Study Program Bhayangkara University Indonesia

ISBN: (纸本)9781450384971

Complaint resolution that arise due to internal and external factors in a company can be monitored through the Service Recovery Index (SRI), and SRI is developed through a number of factors that influence it. Meanwhile, the SRI model needs to be developed to see the business sustainability through implementation knowledge management system in the organization. The data collection method was carried out, starting with building a research instrument based on knowledge management theory and continued with observation and distributing questionnaires to respondents who were involved in the business process of managing SRI. The data analysis method was used to process the data from the questionnaire, factor analysis method was used and the method to build the model used was the regression analysis method. The results obtained from this study are the discovery of 4 (four) factors with a number of indicators that are grouped on each formed factor, which can then be made and built a readiness model that reflects current conditions, so that it can be used to build predictions in the future related to readiness. implementation of knowledge management system development in order to support increased understanding of the service recovery index in the organization. © 2021 ACM.

关键词： Knowledge management

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking System Activities

Learner Action Patterns in the Problem-Solving Process Relat...

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International Conference on Informatics and Computing (ICIC)

作者： Aulia Akhrian Syahidi Ahmad Afif Supianto Tsukasa Hirashima Yutaka Watanobe Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin City Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency (BRIN) Bandung City Indonesia Learning Engineering Laboratory Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Higashihiroshima Japan Department of Computer Science and Engineering Division of Information Systems University of Aizu Aizu-Wakamatsu City Fukushima Japan

ISBN: (纸本)9798350345728

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the “if-then” rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process.

关键词： Visualization Codes Media Data models Recording Data mining Problem-solving

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Semantic Communications for Artificial Intelligence Generated Content (AIGC) Toward Effective Content Creation

arXiv

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arXiv 2023年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In Shen, Xuemin The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada

Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potential, especially when integrating with semantic communication (SemCom). In this paper, a novel comprehensive conceptual model for the integration of AIGC and SemCom is developed. Particularly, a content generation level is introduced on top of the semantic level that provides a clear outline of how AIGC and SemCom interact with each other to produce meaningful and effective content. Moreover, a novel framework that employs AIGC technology is proposed as an encoder and decoder for semantic information, considering the joint optimization of semantic extraction and evaluation metrics tailored to AIGC services. The framework can adapt to different types of content generated, the required quality and the semantic information utilized. By employing a Deep Q Network (DQN), a case study is presented that provides useful insights into the feasibility of the optimization problem and its convergence characteristics. © 2023, CC BY.

关键词： Wireless networks

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Portfolio Selection and Comparative Portfolio Analysis of Transportation Services, Hotel and Leisure, and Education Subsectors Against Service Sector in the Philippine Market Using Mean-variance Model

Portfolio Selection and Comparative Portfolio Analysis of Tr...

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IEEE International Conference on Industrial engineering and engineering Management

作者： E. L. Cruz M. N. Young T. N. Chuahay Y. Prasetyo S. Persada R. Nadilfatin M. Contreras School of Industrial Engineering and Engineering Management Mapua University Manila Philippines School of Graduate Studies Mapua University Manila Philippines Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This paper presents a framework for portfolio selection in the transportation services, hotel and leisure, and education subsectors of the Philippine market using the mean-variance model. Using the service sector and the broader market as benchmarks, this study spans 7,670 test days from January 1, 1993, to December 31, 2022, identifying optimal risk-return factors (RRFs) of $\mathbf{0. 4}$ for transportation, 0.2 for hotel and leisure, and 0.3 for education. Furthermore, the higher percentage allocations the investors are recommended to invest in are International Container Terminal Services, Inc., Waterfront Philippines, Incorporated, and Far Eastern University, Incorporated. Paired t-test results, with p-values below 0.01 and 0.05, indicate these subsectors can outperform the service sector. The study also conducted a comparative analysis with 30-year historical data to crisis periods like the Global Financial Crisis (GFC) and the COVID-19 pandemic, exhibiting distinct performance trends and emphasizing the need for tailored strategies during economic disruptions. The findings of this research may provide an alternative portfolio selection model for investors seeking to optimize their investment portfolios.

关键词： COVID-19 Analytical models Pandemics Education Transportation Stability analysis Resource management Stock markets Portfolios Resilience

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A Consideration on Neutral-Point Potential Balancing of 3-Level PWM Rectifier Applying Space Vector Modulation of Matrix Converter

A Consideration on Neutral-Point Potential Balancing of 3-Le...

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International Conference on Electrical Machines and systems (ICEMS)

作者： Junnosuke Haruna Masato Wakabayashi Masaki Yoshihara Hirohito Funato Information Electronics and Optics Course School of Engineering Utsunomiya University Utsunomiya Japan Division of Engineering and Agriculture Graduate Program in Information Electrical & Electronic Systems Engineering Graduate School of Regional Development and Creativity Utsunomiya University Utsunomiya Japan

This paper proposes voltage balance control for 3-level PWM rectifier using a space vector modulation of a matrix converter. When space vector modulation of matrix converter is applied to 3-level PWM rectifier, it can keep balanced DC-link voltage of 3-level PWM rectifier. However, when the DC-link voltage unbalance occurs, SVM of matrix converter cannot balance the DC-link voltage. In this paper, phase angle of input current reference is generated by PI controller in order to keep the phase angle of DC-link voltage to $\pi /6$ rad. The proposed control can adapt not only voltage unbalance, but also a load unbalance. The validity of the proposed control is demonstrated by the simulation results.

关键词： Support vector machines Electric potential PI control Simulation Capacitors Rectifiers Pulse width modulation

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Analysis of Maturity Level of the Management System in Hotel Sector Companies

Analysis of Maturity Level of the Management System in Hotel...

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International Conference on Tourism, Technology and systems, ICOTTS 2020

作者： Muñoz, Alexander Parody Lara, Malory Beatriz Guerra Lopesierra, Wilfrido Montes Morales, Bulmaro Fuentes Santana, Miguel Industrial Engineering Program Universidad Libre Seccional Barranquilla Barranquilla Colombia Master in Integrated Management Systems Bogota Colombia Universidad de La Guajira Riohacha La Guajira Colombia PhD in Information Technology Integration in Organizations Barranquilla Colombia Universidad de La Costa Barranquilla Colombia

ISBN: (纸本)9789813342590

The main purpose of this research is to evaluate the impact of maturity in quality management systems on assets, income and current ratio in companies of the hotel sector in the city of Barranquilla and its metropolitan area, based on the analysis of the level of maturity of the system and the application of multivariate statistical models. To achieve this, the Business Management strategies of this sector were characterized, based on a structured model of variables and based on field data referring to a representative sample of companies in the sector (n = 64). With this information, the determining factors in the level of maturity of the quality management systems were identified, which allowed to know if the processes developed in a management system, such as these, in the Hotel Sector, impact positively or negatively on the performance of the sector’s companies based on assets, income and the current ratio by means of a multiple regression model, since, although these processes are being implemented, there are no current studies that evidence the contributions to the performance of the sector’s companies. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality control

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Single sheet separation method from piled fabrics using roller hand mechanism

Single sheet separation method from piled fabrics using roll...

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IEEE International Conference on Intelligence and Safety for Robotics (ISR)

作者： K. Manabe X. Tong Y. Aiyama Master's Program in Intelligent Interaction Technologies University of Tsukuba Tsukuba Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781665438629;9781665411486

In order to automate the work in a garment factory, we developed a method of single sheet separation from piled fabrics by a roller hand mechanism with a rotating mechanism added to the tip of a robot hand. As a result, we succeeded in separating only single sheet of fabrics with a high probability. It is necessary to eliminate failures for practical use. However, it is difficult to eliminate failure completely due to the characteristics of fabrics. We also devised a method to judgement the success or failure of the separation to improve the reliability of the operation. As a result, the thickness of the fabric could be accurately measured and the confidence level was successfully improved.

关键词： Conferences Clothing Fabrics Production facilities Safety Reliability Separation processes

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Adaptive Contextual Caching for Mobile Edge Large Language Model Service

arXiv

引用

arXiv 2025年

作者： Liu, Guangyuan Liu, Yinqiu Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updates. To address these issues, we propose an Adaptive Contextual Caching (ACC) framework that anticipates user needs by proactively caching semantically relevant data for mobile-edge LLMs. ACC utilizes a deep reinforcement learning (DRL) module to refine cache replacement policies, balancing user context, document similarity, and the overhead associated with cache misses. Experimental results demonstrate that ACC increases cache hit rates to over 80% after only 11 training episodes, outperforming FIFO, LRU, and semantic-only caching while reducing retrieval latency by up to 40%. In particular, ACC also reduces local caching overhead (i.e., the cost of updating the cache when a miss occurs) by as much as 55%, enabling scalable, low-latency LLM services in resource-constrained edge environments. © 2025, CC BY.

关键词： Deep reinforcement learning

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