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4th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2020

作者： Sardjono, W. Sudirwan, J. Priatna, W. Putra, G.R. Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Informatics Engineering Engineering Bhayangkara University Jakarta Raya Indonesia Computer Science Study Program Faculty of Mathematics and Natural Sciences Pakuan University Bogor Indonesia

An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets submitted by users who have not been able to reach ideal conditions. To overcome this problem, we need an appropriate reference model, the ERP system user acceptance model in companies. The study conducted factors that influence the level of acceptance of SAP ERP users in the XYZ group to then determine a model that is able to explain practically the level of ERP system user acceptance, which in turn can produce concrete proposals to increase ERP system user acceptance. Research is quantitative descriptive using factor analysis and regression analysis methods. The research method uses a questionnaire with a total of 107 valid respondents coming from 8 company names under the XYZ group in 6 Southeast Asian countries. The conclusion of the study is that there are 24 indicators and 4 factors that influence user acceptance of the SAP ERP system. These four factors are the low contribution of the ERP system, the quality of ERP systems and data, the development of ERP systems, and also the low quality of ERP system supporters. It is hoped that by optimizing the value of the 4 factors, the XYZ group can increase user acceptance of the SAP ERP system so that the system can provide benefits expected by the company to be competitive advantage. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Factor analysis

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Auxiliary Classifier based Residual RNN for Image Captioning

Auxiliary Classifier based Residual RNN for Image Captioning

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European Signal Processing Conference (EUSIPCO)

作者： Özkan Çaylı Volkan Kılıç Aytuğ Onan Wenwu Wang Electrical and Electronics Engineering Graduate Program İzmir Katip Çelebi University Turkey Department of Computer Engineering İzmir Katip Çelebi University Turkey Centre for Vision Speech and Signal Processing (CVSSP) University of Surrey UK

ISBN: (数字)9789082797091

ISBN: (纸本)9781665467995

Image captioning aims to generate a description of visual contents with natural language automatically. This is useful in several potential applications, such as image understanding and virtual assistants. With recent advances in deep neural networks, natural and semantic text generation has been improved in image captioning. However, maintaining the gradient flow between neurons in consecutive layers becomes challenging as the network gets deeper. In this paper, we propose to integrate an auxiliary classifier in the residual recurrent neural network, which enables the gradient flow to reach the bottom layers for enhanced caption generation. Experiments on the MSCOCO and VizWiz datasets demonstrate the advantage of our proposed approach over the state-of-the-art approaches in several performance metrics.

关键词： Measurement Deep learning Visualization Recurrent neural networks Virtual assistants Semantics Neurons

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Automated Image Captioning with Multi-layer Gated Recurrent Unit

Automated Image Captioning with Multi-layer Gated Recurrent ...

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European Signal Processing Conference (EUSIPCO)

作者： Özge Taylan Moral Volkan Kiliç Aytug Onan Wenwu Wang Electrical and Electronics Engineering Graduate Program Izmir Katip Celebi University Turkey Department of Computer Engineering Izmir Katip Celebi University Turkey Centre for Vision Speech and Signal Processing (CVSSP) University of Surrey UK

ISBN: (数字)9789082797091

ISBN: (纸本)9781665467995

Describing the semantic content of an image via natural language, known as image captioning, has recently attracted substantial interest in computer vision and language processing communities. Current image captioning approaches are mainly based on an encoder-decoder framework in which visual information is extracted by an image encoder and captions are generated by a text decoder, using convolution neural net-works (CNN) and recurrent neural networks (RNN), respectively. Although this framework is promising for image captioning, it has limitations in utilizing the encoded visual information for generating grammatically and semantically correct captions in the RNN decoder. More specifically, the RNN decoder is ineffective in using the contextual information from the encoded data due to its limited ability in capturing long-term complex dependencies. Inspired by the advantage of gated recurrent unit (GRU), in this paper, we propose an extension of conventional RNN by introducing a multi-layer GRU that modulates the most relevant information inside the unit to enhance the semantic coherence of captions. Experimental results on the MSCOCO dataset show the superiority of our proposed approach over the state-of-the-art approaches in several performance metrics.

关键词： Measurement Visualization Recurrent neural networks Semantics Natural languages Europe Logic gates

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Contribution of Virtual Reality Technology to Increase Student Interest in Vocational High Schools

Contribution of Virtual Reality Technology to Increase Stude...

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2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021

作者： Maulana, Fairuz Iqbal Pangestu, Gusti Sano, Albert Verasius Dian Purnomo, Agung Rahmadika, Sandi Widartha, Vandha Pradwiyasma Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia Graduate School Pknu Pukyong National University Interdisciplinary Program of Information Security Busan Korea Republic of Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia

ISBN: (纸本)9781665428477

This research investigates the feasibility of school-based learning using Virtual Reality technology in Electric Power Generation learning during the COVID-19 pandemic. This research employs a qualitative approach. Vocational High School Nurul Jadid Paiton Probolinggo is the site of this study. Data was gathered through observation, literature review, and interviews. In the Electrical engineering section, interviews were conducted with a teaching instructor. Triangulation was used to investigate the data's authenticity, in addition to further interviews with the curriculum staff and instructors at the school. The teacher's assessment of learning media using Virtual Reality application technology shows valid criteria with an average value of 3.6. In comparison, after using the Virtual Reality application learning media, the assessment of students obtained an average value of 3.77 compared to conventional assessments with an interval of 2.71. The use of Virtual Reality technology has proven that it can help and facilitate student learning. The use of technologies of Virtual Reality as a means of learning in classrooms will also be an alternate option for virtual laboratories during the COVID-19 pandemic. © 2021 IEEE.

关键词： Virtual reality

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Towards a Double Hybrid VTOL UAV System∗∗This work was supported by CAPES grant number 001 17

Towards a Double Hybrid VTOL UAV System∗∗This work was sup...

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17th Latin American Robotics Symposium, 12th Brazilian Symposium on Robotics and 11th Workshop on Robotics in Education, LARS-SBR-WRE 2020

作者： Lucena, Alysson N. Goncalves, Luiz M.G. Graduate Program in Electrial and Computer Engineering of Universidade Federal Do Rio Grande Do Norte Natal59.076-200 Brazil

ISBN: (纸本)9780738111537

We draw complete efforts towards the development of a double hybrid tailsitter UAV system, which is basically composed of a multirotor with 2 electric powertrain sets and a flying wing with combustion powertrain set. Our goal is to design a UAV that diminishes consumption for vertically taking off and landing and to perform the horizontal flight with greatest possible autonomy on flight time and distance. Considering these requirements, the UAV is conceptualized and built as a flying wing propelled by a pusher configuration powerplant, with combustion engine propeller, a multi-engine composed of two powerplant sets with electric motors and propellers, positioned on the leading edge of the wing, and two standard elevation control surfaces and two vertical stabilizers that also have the support function for takeoff and landing. Several takeoff, flight, and transition tests were carried out successfully, but autonomy (time and distance) tests due to the COVID19 pandemic. Results show versatility of the hybrid tailsitter for operations in the flight field, in a limited location. The built prototype has proven to be functional and the hybrid system effective, to date. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Leverage from Blockchain in Commodity Exchange: Asset-Backed Token with Ethereum Blockchain Network and Smart Contract 4th

Leverage from Blockchain in Commodity Exchange: Asset-Backed...

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4th International Conference on Smart Trends for Computing and Communications, SmartCom 2020

作者： Richard Heryadi, Yaya Lukas Trisetyarso, Agung Information Systems Department School of Information Systems Bina Nusantara University Jakarta11840 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara Univesity Jakarta11840 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (纸本)9789811552236

Ethereum is one of the most popular blockchain platforms with a high number of adoption in the blockchain world today. Ethereum token (ERC-20) can tokenize any real-world object while it is also possible to exchange the token across the network participants. This utility from the token drives many blockchain enthusiasts to create decentralized applications. ERC-20 token could be used to collect project funds, decision voting, or even can be used to provide investment platforms for people that want to hedge the volatility of the currency with buying an asset that is back to back with the crypto-token. This research shows the main characteristics of asset-backed token and its implementation on a complete end-to-end "digitalization assets system" (assets buy and assets redemption). The result shows that asset-backed token needs support from government and other legalizing parties to verify the legitimacy of the asset that backing the token itself. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Interpretable ECG Analysis for Myocardial Infarction Detection through Counterfactuals

arXiv

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arXiv 2023年

作者： Tanyel, Toygar Atmaca, Sezgin Gökçe, Kaan Balık, M. Yiğit Güler, Arda Aslanger, Emre Öksüz, İlkay Biomedical Engineering Graduate Program Istanbul Technical University Istanbul Turkey Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital Istanbul Turkey Department of Computer Science Aalto University Espoo Finland Department of Cardiology Başakşehir Pine and Sakura City Hospital Istanbul Turkey Department of Computer Engineering Istanbul Technical University Istanbul Turkey

In the evolving landscape of ECG signal analysis, the challenge of limited transparency in machine learning models remains a significant barrier to their effective integration into clinical practice. This study addresses this issue by investigating the use of counterfactual explanations to improve model interpretability for clinicians, particularly in differentiating healthy subjects from myocardial infarction patients. Utilizing the PTB-XL dataset, we developed a methodology for systematic feature extraction and refinement to prepare for counterfactual analysis. This led to the creation of the Visualizing Counterfactual Clues on Electrocardiograms (VCCE) method, designed to improve the practicality of counterfactual explanations in a clinical setting. The validity of our approach was assessed using custom metrics that reflect the diagnostic relevance of counterfactuals, evaluated with the help of two cardiologists. Our findings suggest that this approach could support future efforts in using ECGs to predict patient outcomes for cardiac conditions, achieving interpretation validity scores of 23.29 ± 1.04 and 20.28 ± 0.99 out of 25 for high and moderate-quality interpretations, respectively. Clinical alignment scores of 0.83 ± 0.12 for high-quality and 0.57 ± 0.10 for moderate-quality interpretations underscore the potential clinical applicability of our method. The methodology and findings of this study contribute to the ongoing discussion on enhancing the interpretability of machine learning models in cardiology, offering a concept that bridges the gap between advanced data analysis techniques and clinical decision-making. The source code for this study is available at https://***/tanyelai/vcce. © 2023, CC BY-NC-SA.

关键词： Contrastive Learning

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Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning

arXiv

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arXiv 2023年

作者： Jin, Peng Huang, Jinfa Xiong, Pengfei Tian, Shangxuan Liu, Chang Ji, Xiangyang Yuan, Li Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China -Preferred Program Peking University Shenzhen Graduate School Shenzhen China Shopee Shenzhen China Department of Automation BNRist Tsinghua University Beijing China

Contrastive learning-based video-language representation learning approaches, e.g., CLIP, have achieved outstanding performance, which pursue semantic interaction upon pre-defined video-text pairs. To clarify this coarse-grained global interaction and move a step further, we have to encounter challenging shell-breaking interactions for fine-grained cross-modal learning. In this paper, we creatively model video-text as game players with multivariate cooperative game theory to wisely handle the uncertainty during fine-grained semantic interaction with diverse granularity, flexible combination, and vague intensity. Concretely, we propose Hierarchical Banzhaf Interaction (HBI) to value possible correspondence between video frames and text words for sensitive and explainable cross-modal contrast. To efficiently realize the cooperative game of multiple video frames and multiple text words, the proposed method clusters the original video frames (text words) and computes the Banzhaf Interaction between the merged tokens. By stacking token merge modules, we achieve cooperative games at different semantic levels. Extensive experiments on commonly used text-video retrieval and video-question answering benchmarks with superior performances justify the efficacy of our HBI. More encouragingly, it can also serve as a visualization tool to promote the understanding of cross-modal interaction, which have a far-reaching impact on the community. Project page is available at https://***/HBI/. Copyright © 2023, The Authors. All rights reserved.

关键词： Game theory

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A Bioinformatics Analysis and Homology 3D Modeling of Dihydroxy-orotate-dehydrogenase of Plasmodium ovale

A Bioinformatics Analysis and Homology 3D Modeling of Dihydr...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Rudi Nirwantono Khoirunnisa Assidqi Alam Ahmad Hidayat Joko Pebrianto Trinugroho Bens Pardamean Biotechnology Department Faculty of Engineering Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Food Biotechnology Research Center Bina Nusantara University Jakarta Indonesia Mathematics Departement School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

The infection of Plasmodium vivax is relatively less virulent than the deathliest Plasmodium falciparum. However, it still can lead to a fatal case and often induces recurring malaria due to dormant parasites in the liver. Thus, the research to study the drug to treat Plasmodium vivax is essential, where the enzyme dihydroorotate dehydrogenase (DHODH) has recently become a new drug target. However, the drug-enzyme interaction study has only recently been conducted in Plasmodium falciparum (pfDHODH) due to the lack of the 3D structure of enzyme DHODH from Plasmodium vivax that is crucial for the study. Therefore, this study aimed to perform the modelling study of Plasmodium vivax DHODH (PvDHODH) to create a 3D structure as a basis for drug-protein interaction study in upcoming studies. Sequence pvDHODH (Accession: SCO68359.1) was used in homology modelling using Modeller 10.2 with the crystal structure of DHODH from DHODH (Accession: 7KZY) as a template. Overall, the model generated from the homology modelling was considered a good model, and the 3D structure was close to the native state according to several parameters, including DOPE score, GA341 score, QMEAN4 value, 3D-1D score, ERRAT2 score, and ProSA score. Ramachandran plot also revealed that almost all amino acids were distributed in the desirable and allowed area (99.1%), and only 0.9% were in generously allowed regions. Superimposition of the model with the template also indicated that the model has an almost similar structure and amino acids positioning, including in the binding pocket and active site. Therefore, the model can be used for downstream analysis in drug-protein interaction studies. Nevertheless, some improvements can still be performed to upgrade the quality of the model by deleting unaligned residues on the C-terminal and realigning the residues at the doubting site.

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

arXiv

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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

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