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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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Smartphone Application for the Deaf and the Deaf Caring Community

Smartphone Application for the Deaf and the Deaf Caring Comm...

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International Conference on Inventive Computation Technologies (ICICT)

作者： Pinnus Pryandi Muhammad Bayu Dewantara Harco Leslie Hendric Spits Warnars Arief Ramadhan Nurulhuda Noordin Fahriza Hanis Abdul Razak Information Systems department School of Information Systems. Bina Nusantara University Jakarta Indonesia Computer Science department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Telkom University Bandung Indonesia Faculty of Computer and Mathematical Sciences Universiti Teknologi Mara (UiTM) Selangor Malaysia

In life, various challenges and problems faced by deaf people such as communication skills and other problems, including emotional, mental, and societal development However, technology is needed that can help the process. This Smart Application try to build communication between the deaf to share thoughts in group chats, including getting information about the deaf, so that the communication learning process for the deaf becomes easier. The proposed model is using Unified Modeling Languages (UML) diagrams, such as case diagrams for the current proposed idea process and class diagrams for relational tables or database stores. In addition, the User interface (UI) is implemented in this research work, Personal Home Pages (PHP) as a web server programming and MySQL database as an open-source database.

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Trend Intelligent Tutoring System 2018-2022 : Systematic Literature Review

Trend Intelligent Tutoring System 2018-2022 : Systematic Lit...

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Innovation in technology (INOCON), IEEE International Conference for

作者： Jaka Suwita Harjanto Prabowo Harco Leslie Hendric Spits Warnars Meyliana Meyliana Departement of Computer Science BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Department of Information System STMIK Insan Pembangunan Tangerang Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia

ITS is a method of teaching that uses technology to give lessons without the need for an instructor to be there. A systematic literature review (SLR) was conducted in this research to identify the components of an intelligent tutoring system, and the results are presented. The method used in this literature review is the prism method. The steps in the prism method are slr protocol, search for literature, select literature, summarize evidence and disseminate results. The slr protocol stage, it consists of determining a research question, searching for scientific reference sources with the keyword intelligent tutoring system, then sorting out the appropriate articles and making final conclusions. This article gives a detailed look at how the intelligent tutoring system changed over time during the pandemic epoch. Our contribution is complete information on the components of ITS in times of epidemic at universities, with the goal of improving their learning and practical use of the technology.

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A Knowledge-Enriched and Span-Based Network for Joint Entity and Relation Extraction

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computers, Materials & Continua 2021年第7期68卷 377-389页

作者： Kun Ding Shanshan Liu Yuhao Zhang Hui Zhang Xiaoxiong Zhang Tongtong Wu Xiaolei Zhou The Sixty-Third Research Institute National University of Defense TechnologyNanjing210007China School of Computer Science and Technology Southeast UniversityNanjing211189China Faculty of Information Technology Monash UniversityMelbourne3800Australia

The joint extraction of entities and their relations from certain texts plays a significant role in most natural language *** entity and relation extraction in a specific domain,we propose a hybrid neural framework consisting of two parts:a span-based model and a graph-based *** span-based model can tackle overlapping problems compared with BILOU methods,whereas the graph-based model treats relation prediction as graph *** main contribution is to incorporate external lexical and syntactic knowledge of a specific domain,such as domain dictionaries and dependency structures from texts,into end-to-end neural *** conducted extensive experiments on a Chinese military entity and relation extraction *** results show that the proposed framework outperforms the baselines with better performance in terms of entity and relation *** proposed method provides insight into problems with the joint extraction of entities and their relations.

关键词： Entity recognition relation extraction dependency parsing 1 Introduction

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Restaurant Customer Feedback Sentiment Analysis using Aspect Embedding Long Short-term Memory Model

Restaurant Customer Feedback Sentiment Analysis using Aspect...

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computer science, information technology and Engineering (ICCoSITE), International Conference on

作者： Yaya Heryadi Bambang Dwi Wijanarko Dina Fitria Murad Cuk Tho Kiyota Hashimoto Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta Indonesia Computer Science Department BINUS Online Learning Jakarta Indonesia Information Systems Department BINUS Online Learning Jakarta Indonesia Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Prince of Songkla University Phuket Thailand

In the past ten years, there has been a proliferation of unstructured textual data from a variety of fields, allowing for the analysis of the sentiment polarity of the text authors in each of those datasets. To analyze sentiment polarity from unstructured data, machine learning tasks such as aspect-based sentiment analysis are used. The public dataset of restaurant patron feedback was used as the input for this study's empirical results of aspect-based sentiment analysis utilizing the Aspect Embedding Long Short-Term Memory model. The primary experiment's results show that the aspect embedding long short-term memory model can predict aspect sentiment polarization from customer feedback to restaurant service and aspect text representation (aspect text embedding) as input with excellent performance. For example, the Aspect Embedding Long Short-term Memory model, which uses ReLU as its activation function in the Dense layer tends to achieve higher performance (0.97 average accuracies) than the same model equipped with Sigmoid, and Tanh functions which achieve 0.954 and 0.956 average training accuracy respectively.

关键词： Training computer science Sentiment analysis Analytical models Computational modeling Machine learning Predictive models

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Immersive Learning in Using the Metaverse of Satellite Communication Systems science

Immersive Learning in Using the Metaverse of Satellite Commu...

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International Conference on Business and Industrial Research (ICBIR)

作者： Komputerio Akbar Meyliana Harco Leslie Hendric Spits Warnars Riyanto Jayadi Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Information Systems Management Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

Education stands out as one of the most impactful applications of the metaverse, holding immense potential for the future. Within the realm of satellite communication system science education, the integration of immersive learning through the metaverse adds a layer of interest and interactivity to the teaching and learning process. Numerous design and evaluation techniques have been employed in a growing body of research, aiming to understand how immersive learning via the metaverse can effectively contribute to specific educational objectives. Hence, this research is dedicated to delving into the development of an immersive learning metaverse model for the science of satellite communication systems. The research contributes a model that advocates for a holistic learning approach by integrating metaverse technology, VR, the 6E Instructional Process Model, and the MSLQ evaluation instrument. The objective of this model is to enhance the efficiency, effectiveness, and interactivity of learning within the field of satellite communication systems science.

关键词： Metaverse Instruments Education Satellite communications Immersive learning Business

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Database management system design for COVID-19 symptom analysis 6

Database management system design for COVID-19 symptom analy...

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6th International Conference on information Management and technology, ICIMTech 2021

作者： Rahutomo, Reza Darmalim, Ferdinan Cen, Andrew Brilianto, Jayaku Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia PT. Mega Medica Pharmaceuticals IT Department Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Faculty of Technology and Design Bunda Mulia University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Applying a digital strategy is proven to be one way to reduce the infection rate of COVID-19. As a fundamental part of it, database is capable to create a data repository to predict uncertain impacts of the pandemic. The research proposed a database design for project C-Beta that emphasized on creating an ideal system to record and monitor the daily health condition of people with COVID-19. Mainly, the research adopted Connolly and Begg principles of Database Software Development Life Cycle. As a result, the database design activities produced blueprints in the forms of data dictionary, ERD, and user views. The database design delivered in the research included with several features namely user verification, restricted research membership, and flexibility in survey creation. Based on analysis and design phase, C-Beta provides a method to collect data for COVID-19 clinical study. Researchers who utilize C-Beta is able to manage multiple surveys and extract all collected records at the same time. © 2021 IEEE.

关键词： COVID-19

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Depth Estimation with Tilted Optics Using Split Color Filter Aperture

Depth Estimation with Tilted Optics Using Split Color Filter...

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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Aoi Fukino Hiroshi Ikeoka Takavuki Hamamoto Information Processing Engineering Course Graduate School of Engineering Fukuyama University Hiroshima Japan Department of Computer Science Faculty of Engineering Fukuyama University Hiroshima Japan

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

Camera-based depth estimation methods are useful for various automobile applications. For example, depth estimation methods based on stereo cameras triangulate the depth between objects and cameras. However, they are susceptible to baseline distortion owing to vibrations, aging, and thermal expansion. On the contrary, depth estimation methods based on a monocular camera, such as depth-from-defocus, use a focusing mechanism or spectroscopic optics to calculate the depth from the difference of defocus images. However, because the change in sharpness, which is the inverse of defocus, is slightly in the depth direction, it is unsuitable for deep-range estimation. Therefore, we are developing depth-estimation methods that use a monocular camera with special focus images obtained through tilted optics, which have no baseline distortion problem and have a deep estimation range. When tilted optics are used, the plane of sharp focus (POF) appears tilted, while the depth of field (DOF) lies and increases toward the depth direction. Moreover, to allow for the use of only one image-sensor, a one-shot, we studied a depth estimation method using tilted optics with two different aperture sizes for each color wavelength by introducing concentric color filter apertures. However, as with conventional methods, the Gaussian sharpness model does not strictly fit to the actual sharpness, resulting in reduced estimation accuracy. In this study, we propose a method for high-speed and high-accuracy depth estimation that involves adding a split color filter aperture to a tilted optic and using a different sharpness model for each DOF side.

关键词： Optical filters Image color analysis Computational modeling Estimation Optical distortion Apertures Optics Cameras Distortion Automobiles

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Improving Quality of Experience in Cloud Gaming Using Speculative Execution

Improving Quality of Experience in Cloud Gaming Using Specul...

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International Conference on Mobile Computing and Ubiquitous Networking (ICMU)

作者： Takumasa Ishioka Tatsuya Fukui Ryouhei Tsugami Toshihito Fujiwara Satoshi Narikawa Takuya Fujihashi Shunsuke Saruwatari Takashi Watanabe Graduate School of Information Science and Technology Osaka University Japan Department of Information and Computer Science Faculty of Engineering Kyoto Tachibana University Japan NTT Access Network Service Systems Laboratories NTT Corporation Japan

Cloud gaming has surged in popularity with the rise of mobile games. Cloud gaming systems allow players to enjoy the latest high-performance games from any location on their mobile devices. However, cloud gaming presents challenges, notably the increased latency due to network delays, creating an issue of end-to-end latency. Minimizing network delays like processing, transmission, and propagation is crucial to offer a user experience similar to playing a local game. Our research explores a speculative video transmission method on cloud gaming servers to overcome these limitations and reduce network latency. In our proposed method, the cloud game server analyzes input patterns from the user, then pre-encodes and sends the corresponding game frames. This process reduces the perceived network delay, making the game more responsive. This paper evaluates the estimated Quality of Experience (QoE) based on an existing QoE model.

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Comparing the Effect of Attention Mechanism and Aspect Embedding on the Performance of Long Short-term Memory Model for Aspect-Based Sentiment Analysis

Comparing the Effect of Attention Mechanism and Aspect Embed...

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computer science, information technology and Engineering (ICCoSITE), International Conference on

The attention mechanism is one of the key enablers which have positioned transformer models as the state-of-the-art models in Natural Language Processing. By having the attention mechanism, the first version (vanilla) transformer model can retrieve the hidden state but at the same time can maintain a low requirement on the context vector dimension by selectively choosing to which encoder hidden states to give priority attention. The objective of this study is to evaluate the effect of modified Long Short-term Memory models architecture on the model performance as a predictive model. The first model is modified by adding an attention mechanism to its architecture; whilst, the second model is modified by adding additional input to its architecture. The performance of both models is compared by assigning each model the same task: to address the aspect-based sentiment analysis task. The experiment results show that adding an attention mechanism is not significantly increase the performance of the Long Short-term Memory model in comparison to adding input to the same model. In particular, the average training accuracy of the former model is 0.885; whilst, the average training accuracy of the latter model is 0.942.

关键词： Training Analytical models Sentiment analysis Computational modeling Memory architecture Predictive models Transformers

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