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Multifunctional composite magnet realizing record-high transverse thermoelectric generation

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arXiv 2024年

作者： Ando, Fuyuki Hirai, Takamasa Alasli, Abdulkareem Sepehri-Amin, Hossein Iwasaki, Yutaka Nagano, Hosei Uchida, Ken-Ichi National Institute for Materials Science Tsukuba305-0047 Japan Department of Mechanical Systems Engineering Nagoya University Nagoya464-8603 Japan Department of Advanced Materials Science Graduate School of Frontier Sciences The University of Tokyo Kashiwa277-8561 Japan

Permanent magnets are used in various products and essential for human society. If omnipresent permanent magnets could directly convert heat into electricity, they would lead to innovative energy harvesting and thermal management technologies. However, achieving such "multifunctionality" has been difficult due to poor thermoelectric performance of conventional magnets. In this work, we develop a multifunctional composite magnet (MCM) that enables giant transverse thermoelectric conversion while possessing permanent magnet features. MCM comprising alternately and obliquely stacked SmCo5/Bi0.2Sb1.8Te3 multilayers exhibits an excellent transverse thermoelectric performance at room temperature by optimizing its anisotropic structure. Owing to the extremely low interfacial electrical and thermal resistivities, the experimentally determined figure of merit zxyT reaches 0.20 close to the analytically calculated ideal value. The MCM-based thermopile module generates 204 mW in maximum at a temperature difference of 152 K, whose power density normalized by heat transfer area and temperature gradient is not only record-high among transverse thermoelectric modules but also comparable to that of commercial thermoelectric modules utilizing the Seebeck effect. The multifunctionality of our MCM provides unprecedented opportunities for energy harvesting and thermal management everywhere permanent magnets are currently used. © 2024, CC BY.

关键词： Permanent magnets

Analysis of Improving Sales Process Efficiency with Salesforce Industries CPQ in CRM 7th

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Analysis of Improving Sales Process Efficiency with Salesfor...

7th International Conference on Microelectronics and Telecommunication engineering, ICMETE 2023

作者： Pathak, Pritesh Pal, Souvik Maity, Saikat Jeyalaksshmi, S. Adhikari, Saurabh Akila, D. Liverpool Business School Liverpool John Moores University Liverpool United Kingdom Department of Management Information Systems Saveetha College of Liberal Arts And Sciences Saveetha Institute of Medical And Technical Sciences Chennai India Kolkata India Department of Information Technology Vels Institute of Science Technology and Advanced Studies Chennai India School of Engineering Swami Vivekananda University Kolkata India Department of Computer Applications Saveetha College of Liberal Arts And Sciences Saveetha Institute of Medical And Technical Sciences Chennai India

ISBN: (纸本)9789819995615

The successful execution of Configure, Price, Quote (CPQ) protocols is of utmost importance for businesses that handle intricate product portfolios within their sales processes. The objective of these approaches is to optimise the generation of competitive quotations by leveraging data from diverse business systems, leading to a decrease in processing time and enhancement of operational efficiency. Salesforce's Industries CPQ for Communications Cloud, previously referred to as Vlocity CPQ, assumes a crucial function within the Salesforce platform by facilitating the automation of the quotation creation process for sales teams. Designed specifically for the communications industry, this solution enables communications service providers (CSPs) to effectively provide a wide array of products and services to their customers in a streamlined manner. By implementing Industries CPQ, Communication Service Providers (CSPs) have the potential to save expenses associated with customisation and maintenance, while also accelerating their time-to-market. In order to assess the practical ramifications of Salesforce Industries CPQ, the researcher intends to deploy the aforementioned system within ABC Insurance Company. The objective of the study is to evaluate the program's influence on sales efficiency and profitability by conducting interviews with a targeted cohort of employees who have employed the software in their sales endeavours. Furthermore, the study will include hypothesis testing to analyse the timing of quotation production across various policy configurations utilising Salesforce Industries CPQ, aiming to provide further validation of its benefits. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sales

Distributional Utility Preference Robust Optimization Models in Multi-Attribute Decision Making

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arXiv 2022年

作者： Hu, Jian Zhang, Dali Xu, Huifu Zhang, Sainan Department of Industrial and Manufacturing Systems Engineering University of Michigan - Dearborn DearbornMI48128 United States Sino-US Global Logistics Institute Antai College of Economics and Management Shanghai Jiao Tong University Shanghai200030 China Department of Systems Engineering & Engineering Management The Chinese University of Hong Kong N.T. Shatin Hong Kong

Utility preference robust optimization (PRO) has recently been proposed to deal with optimal decision-making problems where the decision maker’s (DM’s) preference over gains and losses is ambiguous. In this paper, we take a step further to investigate the case that the DM’s preference is random. We propose to use a random utility function to describe the DM’s preference and develop distributional utility preference robust optimization (DUPRO) models when the distribution of the random utility function is ambiguous. We concentrate on data-driven problems where samples of the random parameters are obtainable but the sample size may be relatively small. In the case when the random utility functions are of piecewise linear structure, we propose a bootstrap method to construct the ambiguity set and demonstrate how the resulting DUPRO can be solved by a mixed-integer linear program. The piecewise linear structure is versatile in its ability to incorporate classical non-parametric utility assessment methods into the sample generation of a random utility function. Next, we expand the proposed DUPRO models and computational schemes to address general cases where the random utility functions are not necessarily piecewise linear. We show how the DUPRO models with piecewise linear random utility functions can serve as approximations for the DUPRO models with general random utility functions and allow us to quantify the approximation errors. Finally, we carry out some performance studies of the proposed bootstrap-based DUPRO model and report the preliminary numerical test results. The paper is the first attempt to use distributionally robust optimization methods for PRO problems. Copyright © 2022, The Authors. All rights reserved.

关键词： Decision making

An AI-Driven VM Threat Prediction Model for Multi-Risks Analysis-Based Cloud Cybersecurity

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arXiv 2023年

作者： Saxena, Deepika Gupta, Ishu Gupta, Rishabh Singh, Ashutosh Kumar Wen, Xiaoqing Department of Computer Science & Engineering The University of Aizu Japan Bangalore India Indian Institute of Information Technology Bhopal India The Department of Computer Applications National Institute of Technology Kurukshetra India the Department of Creative Informatics The Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka8208502 Japan

Cloud virtualization technology, ingrained with physical resource sharing, prompts cybersecurity threats on users’ virtual machines (VM)s due to the presence of inevitable vulnerabilities on the offsite servers. Contrary to the existing works which concentrated on reducing resource sharing and encryption/decryption of data before transfer for improving cybersecurity which raises computational cost overhead, the proposed model operates diversely for efficiently serving the same purpose. This paper proposes a novel Multiple Risks Analysis based VM Threat Prediction Model (MR-TPM) to secure computational data and minimize adversary breaches by proactively estimating the VMs threats. It considers multiple cybersecurity risk factors associated with the configuration and management of VMs, along with analysis of users’ behaviour. All these threat factors are quantified for the generation of respective risk score values and fed as input into a machine learning based classifier to estimate the probability of threat for each VM. The performance of MR-TPM is evaluated using benchmark Google Cluster and OpenNebula VM threat traces. The experimental results demonstrate that the proposed model efficiently computes the cybersecurity risks and learns the VM threat patterns from historical and live data samples. The deployment of MR-TPM with existing VM allocation policies reduces cybersecurity threats up to 88.9%. © 2023, CC BY.

关键词： Risk analysis

Leishmaniases in a tropical area of Brazil: a spatio-temporal analysis

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Journal of Parasitic Diseases 2023年第3期47卷 556-561页

作者： Filho, Carlos Roberto Cruz Ubirajara Lima, Thiago Antonio Rodrigues Freire de Barros, Lílian Silva Sampaio Giannelli, Alessio Alves, Leucio Câmara de Carvalho, Gílcia Aparecida Ramos, Rafael Antonio Nascimento Graduate Program in Animal Biosciences Federal Rural University of Pernambuco PE Recife Brazil Laboratory of Parasitology Federal University of the Agreste of Pernambuco PE Garanhuns Brazil Department of Cartographic Engineering Federal University of Pernambuco PE Recife Brazil V Regional Health Management Health Secretariat of the State of Pernambuco PE Garanhuns Brazil Inovet Hoge Mauw 900 Arendonk 2370 Belgium Department of Veterinary Medicine Federal Rural University of Pernambuco PE Recife Brazil

Leishmaniases are a group of tropical and neglected diseases caused by the protozoa of the genus Leishmania which are transmitted by insect sandflies. Despite of the major efforts undertaken at global level for the control of these diseases, a recent spreading to non-endemic areas been observed. In this study we analyzed the spatio-temporal distribution of Visceral Leishmaniasis (VL) and Tegumentary Leishmaniasis (TL) cases notified in a tropical region of Brazil. A retrospective evaluation was carried out using secondary data (e.g., demographics, origin, age and area of occurrence) of human patients obtained from 2009 to 2019. Choropleth maps with levels of color intensity represented the spatial distribution of VL and TL cases. Overall, 116 (10.5 ± 8.5) cases of leishmaniases were registered in the study area during the whole period. Of those, 61 (5.5 ± 5.5) and 55 (5 ± 4.3) were diagnosed as VL and TL, respectively. VL cases were recorded in 61.9% (13/21) and TL cases in 42.8% (9/21) of the municipalities. Most of the cases were predominantly notified in men from rural areas, and specifically for TL with an age range of 30–59 years old. These findings will be useful to drive strategies of control (e.g., vector control, dog surveillance and notification of suspected cases) against these neglect diseases, preventing the spreading to non-endemic areas. © 2023, Indian Society for Parasitology.

关键词： Epidemiology Geoinformation Leishmania Neglected zoonosis Retrospective study

Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

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arXiv 2024年

作者： Liu, Guangyuan Van Huynh, Nguyen Du, Hongyang Hoang, Dinh Thai Niyato, Dusit Zhu, Kun Kang, Jiawen Xiong, Zehui Jamalipour, Abbas In Kim, Dong The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom The School of Electrical and Data Engineering University of Technology Sydney Australia The School of Computer Science and Engineering Nanyang Technological University Singapore College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China 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 School of Electrical and Information Engineering University of Sydney Australia The College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans. However, learning and coordinating movements and actions for a large number of unmanned vehicles in complex and dynamic environments introduce significant challenges to conventional AI methods. Generative AI (GAI), with its capabilities in complex data feature extraction, transformation, and enhancement, offers great potential in solving these challenges of unmanned vehicle swarms. For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms. Specifically, we first present an overview of unmanned vehicles and unmanned vehicle swarms as well as their use cases and existing issues. Then, an in-depth background of various GAI techniques together with their capabilities in enhancing unmanned vehicle swarms are provided. After that, we present a comprehensive review on the applications and challenges of GAI in unmanned vehicle swarms with various insights and discussions. Finally, we highlight open issues of GAI in unmanned vehicle swarms and discuss potential research directions. © 2024, CC BY.

关键词： Metadata

New perspectives of a 5G operating model

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New perspectives of a 5G operating model

International Conference on Telecommunication, Electronic and Computer engineering 2019, ICTEC 2019

作者： Suryanegara, Muhammad Graduate Program in Telecommunications Management Department of Electrical Engineering Depok Universitas Indonesia Indonesia

The way 5G operators manage infrastructure, enterprise and customers will be radically different compared to preceding generations. This paper aims to provide new perspectives on the 5G operating model by presenting a visual guide on how mobile network operators should deliver value to their prospective 5G customers. The model presented enriches the eTOM framework by elaborating on the implications of virtual network operations, the consequences of an mmWave band, the value of the non-human customer, the security concerns, the role of the content provider in a new ecosystem, and the anticipation of the next generation technological platform. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Network management

Non-Negative Tensor Factorization of Infant Spontaneous Movements: A Pilot Study for ASD Risk Evaluation of Newborn Infants

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Non-Negative Tensor Factorization of Infant Spontaneous Move...

IEEE/SICE International Symposium on System Integration

作者： Rikuya Yonei Akira Furui Hirokazu Doi Koji Shimatani Hideaki Hayashi Midori Yamamoto Kenichi Sakurai Chisato Mori Toshio Tsuji Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Japan Department of Information and Management Systems Engineering Nagaoka University of Technology Niigata Japan Faculty of Health and Welfare Prefectural University of Hiroshima Hiroshima Japan Institute for Datability Science Osaka University Osaka Japan Department of Sustainable Health Science Center for Preventive Medical Sciences Chiba University Chiba Japan Department of Nutrition and Metabolic Medicine Center for Preventive Medical Sciences Chiba University Chiba Japan Department of Bioenvironmental Medicine Graduate School of Medicine Chiba University Chiba Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Early detection of infants with autism spectrum disorder (ASD) can lead to effective developmental support. In clinical practice, early screening of 18-month-old infants is implemented using a parent-completed questionnaire. However, research has suggested that signs of ASD may also appear in movement characteristics during the first few months of age. In this paper, we propose a method to evaluate infant movement from videos based on non-negative tensor factorization (NTF) and apply it to ASD risk assessment in the neonatal period. The proposed method applies NTF to pose data estimated from videos, and decomposes the infant’s movements into multiple components while considering the linkage between body parts. In the experiment, we evaluated the effectiveness of the proposed method using 36 low-risk infants and 13 high-risk infants for ASD, with the aim of applying the method to ASD risk assessment. The results showed that the proposed method captured the tendency for infants to perform different movements depending on their risk level. Machine learning analysis revealed that the proposed method identified ASD risk with an accuracy exceeding 70%, which was comparable or superior to the existing video evaluation method based on heuristically designed indicators.

关键词： Couplings Pediatrics Autism Tensors Pose estimation System integration Machine learning Risk management Spectrogram Videos

Identifying Features for the Improvement of IoT Services: A Kano Model Approach 2

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Identifying Features for the Improvement of IoT Services: A ...

2nd International Conference on Electrical, Communication and Computer engineering, ICECCE 2020

作者： Prasetyo, DImas Agung Suryanegara, Muhammad Graduate Program in Telecommunications Management Universitas Indonesia Department of Electrical Engineering Depok Indonesia

ISBN: (纸本)9781728171166

This paper aims to identify what new features need to be improved in the IoT services implemented in the Jakarta Smart City platform. We use sequential steps to construct the Kano Model and first define 10 attributes representing features as recommended improvements for the future IoT. The relevant survey was conducted among institutional users of the IoT services under the platform of the Jakarta Smart City. The findings show that 2 attributes fall into the category of Must Be, which are strongly expected by the users. These are the features that improve working productivity and efficiency and those that guarantee security and privacy. The rest of the attributes fall into the category of Indifferent, which users do not consider as significantly affecting their satisfaction in the future. © 2020 IEEE.

关键词： Internet of things