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FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks

IEEE Transactions on Knowledge and Data engineering 2023年第1期35卷 469-481页

作者： Hsu, Yi-Ling Tsai, Yu-Che Li, Cheng-Te National Taiwan University Master Program in Statistics Taipei10617 Taiwan National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan National Cheng Kung University Institute of Data Science Tainan701 Taiwan

Financial technology (FinTech) has drawn much attention among investors and companies. While conventional stock analysis in FinTech targets at predicting stock prices, less effort is made for profitable stock recommendation. Besides, in existing approaches on modeling time series of stock prices, the relationships among stocks and sectors (i.e., categories of stocks) are either neglected or pre-defined. Ignoring stock relationships will miss the information shared between stocks while using pre-defined relationships cannot depict the latent interactions or influence of stock prices between stocks. In this work, we aim at recommending the top-K profitable stocks in terms of return ratio using time series of stock prices and sector information. We propose a novel deep learning-based model, Financial Graph Attention Networks (FinGAT), to tackle the task under the setting that no pre-defined relationships between stocks are given. The idea of FinGAT is three-fold. First, we devise a hierarchical learning component to learn short-term and long-term sequential patterns from stock time series. Second, a fully-connected graph between stocks and a fully-connected graph between sectors are constructed, along with graph attention networks, to learn the latent interactions among stocks and sectors. Third, a multi-task objective is devised to jointly recommend the profitable stocks and predict the stock movement. Experiments conducted on Taiwan Stock, S&P 500, and NASDAQ datasets exhibit remarkable recommendation performance of our FinGAT, comparing to state-of-the-art methods. © 1989-2012 IEEE.

关键词： Forecasting

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Comparative Assessment of Off-shore Wind Converters and Wave Energy Converters in the Philippines 15

Comparative Assessment of Off-shore Wind Converters and Wave...

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15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Alquiza, Laurence Keith P. Recto, King Harold A. Loresco, Pocholo James M. Villalobos, Jesus Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines Feu Institute of Technology Department of Electronics Engineering Manila Philippines Institut Catholique d'Arts et Métiers International Program in General Engineering Toulouse France

ISBN: (纸本)9798350381177

The Republic of the Philippines is confronted with rebuilding its energy landscape, which now depends heavily on imported fossil fuels for a substantial supply. The Department of Energy (DOE) has established lofty objectives to enhance the nation's renewable energy (RE) capability;nevertheless, these objectives are still to be achieved. This research supports DOE's goals by studying other possible renewable energy sources. In particular, the primary aim of this research is to examine the viability of Offshore Wind Converters (OWCs) and Wave Energy Converters (WECs) as viable sustainable energy options for the Philippines. Ocean wave converters (OWCs) provide inherent benefits in terms of dependability and have widespread societal acceptance. Conversely, wave energy converters (WECs) harness the vast energy potential contained within ocean waves. A comparative evaluation was undertaken to analyze the differences between these two potential renewable energy sources. The assessment concludes that OWCs possess a minor advantage over WECs regarding their economic viability and higher societal acceptability. It recommended that the government adopts a diversified energy portfolio, which may include the incorporation of WECs to effectively navigate the changing dynamics of the energy sector, enhance sustainability, and ensure the long-term security of the nation's energy supply. © 2023 IEEE.

关键词： Water waves

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Joint Design of Spirograph Method and Reconfigurable Intelligent Surface for Future Communication Systems

Joint Design of Spirograph Method and Reconfigurable Intelli...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Yafis, Balqis Huang, Jane-Hwa Yu, Chih-Min Wang, Li-Chun National Yang Ming Chiao Tung University Eecs Int'l Graduate Program Hsinchu Taiwan National Chi Nan University Dept. of Electrical Engineering Nantou County Taiwan Chung Yuan Christian University Department of Information and Computer Engineering Taoyuan City Taiwan

ISBN: (纸本)9798350351255

Reconfigurable Intelligent Surface (RIS) is a transformative technology using the passive beamforming capabilities to create the programmable wireless environments. However, the control overhead is a challenging issue. The system needs to deliver the high-precision reflection coefficients to the RIS controller, for adjusting the phase shifts of the numerous RIS elements. Therefore, we propose a Spirograph-based discrete beamdirection strategy, which selects a set of non-uniformly distributed beam directions based on the generic patterns generated by the Spirograph (SG). We evaluate the achievable data rate and the number of controlling bits of SG-based method. We compare the SG-based method, the ideal continuous phase-shift method, and the SISO method. Simulation results show that with the properly-selected discrete beam directions, the SG-based method can achieve a comparable data rate as the ideal method, while having a lower control overhead. © 2024 IEEE.

关键词： Beamforming

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A Design for Improvement of Visual SLAM in Dynamic Environments Using Feature-Point Removal of Moving Persons

A Design for Improvement of Visual SLAM in Dynamic Environme...

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2023 International Automatic Control Conference, CACS 2023

作者： Song, Kai-Tai Meng, Ching-Hao National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering Hsinchu886-3-5731865 Taiwan National Yang Ming Chiao Tung University Graduate Degree Program of Robotics College of Engineering Hsinchu Taiwan

ISBN: (纸本)9798350306354

This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization accuracy of a mobile robot in an environment with moving persons. Instance segmentation and motion tracking are intergrated to identify motion state of people in an image. ORB feature points belonging to moving persons are removed for further processing of the vSLAM pipeline. The advantage of this method is that the vSLAM can remove feature points of moving people, while retain those belonging to static people in the environment, which improves the accuracy of robot pose estimation. The improved ORB-SLAM2 algorithm has been implemented in a NVIDIA Xavier embedded system, which is integrated to a mobile robot. In practical robot navigation experiments, the average positioning error of the proposed method is within 4cm for 22.4m travel distance. Compared with conventional ORB-SLAM2, the average accuracy of our vSLAM method improves 97% in a dynamic environment with moving people. © 2023 IEEE.

关键词： Mobile robots

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Evaluation of time-series database on microservice architecture for health monitoring system

Evaluation of time-series database on microservice architect...

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2022 International Symposium on Electronics and Smart Devices, ISESD 2022

作者： Simanjuntak, Eko Surantha, Nico Isa, Sani Muhamad Bina Nusantara University Binus Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia Tokyo City University Electronic and Communication Engineering Faculty of Engineering Department of Electrical Tokyo Japan

ISBN: (数字)9798350396607

ISBN: (纸本)9798350396607

Recently, the research on daily health monitoring using a wearable sensor has been continually evolving. In the future, when this system is actually implemented, a vast amount of data transmission will be conducted from multiple sensors to the cloud server. A system capable of transmitting, storing, processing, and visualizing massive volumes of data is necessary for health monitoring. This research aims to develop a health monitoring system that can accommodate a high amount of data with high performance. The proposed techniques include numerous modifications to system architecture and technology. In the system architecture, a multi-database is proposed to enhance the reliability of the system. As an enhancement to the technology aspect, a time series database and MQTT server are proposed. As the result, the proposed system achieves significantly better performance in terms of throughput, database-writing speed, and database-reading speed compared to the existing system. © 2022 IEEE.

关键词： Database systems

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Blockchain and API Development to Improve Relational Database Integrity and System Interoperability 7

Blockchain and API Development to Improve Relational Databas...

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7th International Conference on computer Science and Computational Intelligence, CSCI 2022

作者： Ramadhan, Andhika Naafi Pane, Kharisma Naufal Wardhana, Kun Rifki Suharjito Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Industrial Engineering Department BINUS Graduate Program-Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

Technological developments have resulted in a trend of cryptocurrencies that use a technology called blockchain to create and record all transactions made into a digital ledger. Along with the emergence of the trend of cryptocurrencies, this development has also resulted in crimes that hit the digital world, such as data leakage and cyber espionage. This threat can be prevented by applying blockchain technology to the database that has been used. Therefore, we need a system that can facilitate the use of blockchain technology and can process data from an existing relational database into a blockchain-based database. The system developed in this study was built with the FastAPI framework that uses the Python programming language and the React framework that uses the Javascript programming language. This system was tested using Katalon and Wireshark software to perform throughput testing and man-in-The-middle attacks. Evaluation of this system is assessed based on the average throughput time and also the results of Wireshark packet capture. The system designed in this research is expected to help overcome interoperability problems when using blockchain and improve relational database integrity. The results of the test show that the system is safe from man-in-The-middle attacks while sending data through API and has a faster throughput time than BigchainDB system by 4.151 seconds. © 2022 Elsevier B.V.. All rights reserved.

关键词： Blockchain

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Curriculum-based Reinforcement Learning for an Effective Multi-Agent Path Planning Algorithm in Warehouse Scenarios 15

Curriculum-based Reinforcement Learning for an Effective Mul...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： de Oliveira, Iure Rosa L. de Carvalho, Kevin B. Brandão, Alexandre S. Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Viçosa Viçosa Brazil

ISBN: (纸本)9798350314182

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training. © 2023 IEEE.

关键词： Curriculum Learning Mobile Robotics Multi-Agent System Reinforcement Learning Transfer Learning

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Analysis of Gait Data Based on Deep Learning to Predict Multiple Balance Scale Scores

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IEEE Sensors Journal 2024年第1期24卷 920-930页

作者： Lin, Chueh-Ho Peng, Chih-Wei Lee, I-Jung Wu, Chi-Ming Lin, Bor-Shing Taipei Medical University International Ph.D. Program in Gerontology and Long-Term Care Taipei City110 Taiwan Taipei Medical University Research Center in Nursing Clinical Practice Wan Fang Hospital Taipei City110 Taiwan Taipei Medical University School of Biomedical Engineering College of Biomedical Engineering Taipei City110 Taiwan Taipei Medical University School of Gerontology and Long-Term Care College of Nursing Taipei City110 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City237 Taiwan National Taipei University College of Electrical Engineering and Computer Science New Taipei City237 Taiwan

Unbalanced walking is increasingly common among older adults;therefore, routinely assessing the balance of older adults is crucial. The traditional method of assessing balance uses scales, requires the supervision of a physical therapist (PT), and is time-consuming. The present study, therefore, proposes a deep learning (DL) model architecture that combines a convolutional neural network (CNN) and a long short-term memory (LSTM) network model to predict the scores of three scales, namely the Berg balance scale (BBS), timed up and go (TUG), and single-leg stance (SLS). The gait data of 15 m of walking were collected from seven inertial measurement units (IMUs) and input into the CNN-LSTM model for evaluation. The BBS and TUG only require the participants to wear two IMUs on the left and right thighs, respectively, for accurate predictions. The mean absolute errors (MAEs) of predicting the scores of the BBS and TUG are 1.2562 and 1.4016 s, respectively;however, the MAE of score predictions of SLS is higher than that of the BBS and TUG, indicating that gait data cannot be used for assessing SLS;moreover, participants only wear one IMU on the right calf for BBS and TUG evaluations, which yield MAEs of 1.4334 and 1.5229 s, respectively. The proposed system can quickly and accurately predict the scores of the BBS and TUG. The proposed model can assist PTs with making clinical decisions. © 2001-2012 IEEE.

关键词： Long short-term memory

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Industry-Academy Collaboration in Agile Methodology: a Systematic Literature Review 17

Industry-Academy Collaboration in Agile Methodology: a Syste...

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17th Iberian Conference on Information Systems and Technologies, CISTI 2022

作者： Marques, Denis de Gois de A. Dallegrave, Tamara Larissa D. Lima Barbosa, Luis E. de Oliveira Rodrigues, Cleyton M. Santos, Wylliams Barbosa Graduate Program in Computer Engineering Polytechnic School of Pernambuco POLI/UPE Recife Brazil University of Pernambuco UPE Caruaru Brazil

ISBN: (纸本)9789893334362

Industry-Academy Collaborative Research (IAC) in Software engineering is being applied and developed widely in practice. These collaborative, research practices help both academic and software industry environments. As a way of observing what is being developed in SE, the objective of this article is to present an exploratory and empirical study of IAC practices in the context of Agile Software Development (ASD), exploring and characterizing solutions and practices, the challenges encountered in the application of the IAC and in collaboration. A Systematic Literature Review (SLR) was carried out in the five main academic databases, and snowballing was applied, evaluating/analyzing 8.460 articles, totaling 21 articles approved following the proposed criteria. As a result of the data analysis, 76 good practices and 37 challenges in carrying out the IAC were described. As well, practical collaborative models for the application of the IAC were detailed. © 2022 IEEE computer Society. All rights reserved.

关键词： Application programs

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Resume Recommendation using RNN Classification and Cosine Similarity 7th

Resume Recommendation using RNN Classification and Cosine Si...

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7th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2023

作者： Huseyinov, Ilham Diallo, Issa Raed, Mhd Wasim Software Engineering Department Istanbul Aydin University Istanbul Turkey Graduate Institute of Science Artificial Intelligence and Data Science Program Istanbul Aydin University Istanbul Turkey Computer Engineering Department Istanbul Aydin University Istanbul Turkey

ISBN: (纸本)9783031437885

One way to save time and resources in the human recruitment and hiring process is to post open job positions on the Internet, but the overload of applications creates challenges for hiring managers and companies to select an adequate candidate. One of the solutions is to apply intelligent tools such as Deep Learning and recommender system algorithms to speed up the hiring process and identify the right candidates. In this paper, we propose a two-fold algorithmic approach to 1) building an RNN classifier for resume classification;2) using cosine similarity for resume recommendation to find a candidate that fits job requirements best after selecting all the resumes that belong to the right category. The performance of the proposed RNN classifier is evaluated in terms of accuracy, precision, recall, F1-score, and confusion matrix criteria. The experiment results have shown that the RNN classifier performs better than the other classifiers such as GNB, Linear SVM, RF, and BERT on the same dataset. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Recommender systems

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