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2nd Annual Conference of Science and Technology, ANCOSET 2020

作者： Tho, C. Heryadi, Y. Lukas, L. Wibowo, A. Department of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

Nowadays mixing one language with another language either in spoken or written communication has become a common practice for bilingual speakers in daily conversation as well as in social media. Lexicon based approach is one of the approaches in extracting the sentiment analysis. This study is aimed to compare two lexicon models which are SentiNetWord and VADER in extracting the polarity of the code-mixed sentences in Indonesian language and Javanese language. 3,963 tweets were gathered from two accounts that provide code-mixed tweets. Pre-processing such as removing duplicates, translating to English, filter special characters, transform lower case and filter stop words were conducted on the tweets. Positive and negative word score from lexicon model was then calculated using simple mathematic formula in order to classify the polarity. By comparing with the manual labelling, the result showed that SentiNetWord perform better than VADER in negative sentiments. However, both of the lexicon model did not perform well in neutral and positive sentiments. On overall performance, VADER showed better performance than SentiNetWord. This study showed that the reason for the misclassified was that most of Indonesian language and Javanese language consist of words that were considered as positive in both Lexicon model. © Published under licence by IOP Publishing Ltd.

关键词： Sentiment analysis

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Advances and Challenges in Multi-Domain Task-Oriented Dialogue Policy Optimization

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APSIPA Transactions on Signal and Information Processing 2023年第1期12卷

作者： Rohmatillah, Mahdin Chien, Jen-Tzung EECS International Graduate Program National Yang Ming Chiao Tung University Taiwan Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan

Developing a successful dialogue policy for a multi-domain task-oriented dialogue (MDTD) system is a challenging task. Basically, a desirable dialogue policy acts as the decision-making agent who understands the user's intention to provide suitable responses within a short conversation. Furthermore, offering the precise answers to satisfy the user requirements makes the task even more challenging. This paper surveys recent advances in multi-domain task-oriented dialogue policy optimization and summarizes a number of solutions to policy learning. In particular, the case study on the task of travel assistance using the MDTD dataset based on MultiWOZ containing seven different domains is investigated. The dialogue policy optimization methods, categorized into dialogue act level and word level, are systematically presented. Moreover, this paper addresses a number of challenges and difficulties including the user simulator design and the dialogue policy evaluation which need to be resolved to further enhance the robustness and effectiveness in multi-domain dialogue policy representation. © 2023 M. Rohmatillah and J.-T. Chien.

关键词： Reinforcement learning

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An Exploratory Computational Approach for Elucidating a Nonstructural Protein Interaction in Dengue Virus 2

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Procedia computer Science 2024年 245卷 470-479页

作者： Alam Ahmad Hidayat Rudi Nirwantono Bens Pardamean Mathematics Department School of Computer Science Bina Nusantara University Indonesia 11480 Biotechnology Department Faculty of Engineering Bina Nusantara University Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia 11480

As the dengue infection still impacts hundreds of millions of people globally, unprecedented efforts in dengue drug development have been more progressive in recent decades. Computational methods provide a fast, sustainable, and efficient screening of active compounds and newly created drug molecules, including those specifically targeting nonstructural proteins (NS) of dengue viruses. In this work, protein modeling for the NS proteins of DENV-2/16681 strain was performed using a template-based homology modeling for the NS3 protein and an Artificial Intelligence (AI)-based prediction via AlphaFold for the NS4B protein. Moreover, the protein-protein interaction between the two structures was predicted using the HADDOCK server, which employs information about active and passive residues of the interaction interface to guide the docking process. After the modeling and its respective refinement process, the predicted structures of NS3 and NS4B improved their steric clashing scoring from MolProbity assessment. The refined models were then docked, and the resulting docking pose was analyzed to extract the interacting residues based on the polar contacts within the interface of the two proteins. Our result presents a preliminary study to create a dataset related to in silico molecular interactions of the NS3-NS4B interaction of different DENV types. It is helpful for building a computational pipeline for elucidating protein-ligand problems in dengue drug screenings.

关键词： bioinformatics computational biology dengue protein docking structural biology

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Comparative Analysis of Normal and ASD EEG Data Using Hjorth Parameters

Comparative Analysis of Normal and ASD EEG Data Using Hjorth...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Muliyadi Muliyadi Melinda Melinda Yuwaldi Away Syahrul Gazali Doctoral Program School of Engineering Post Graduate Program Universitas Syiah Kuala Banda Aceh Indonesia Electrical Engineering Department Politeknik Negeri Lhokseumawe Aceh Indonesia Dept. Electrical Engineering and Computer Engineering Faculty Universitas Syiah Kuala Banda Aceh Indonesia Dept. Neurology Universitas Syiah Kuala Banda Aceh Indonesia Mahar Mardjono National Brain Center Hospital Jakarta Indonesia

ISBN: (数字)9798331510886

ISBN: (纸本)9798331510893

The increasing prevalence of autism spectrum disorder (ASD) in recent decades has underscored the need for more accurate and objective diagnostic methods. Electroencephalography (EEG) holds promise as a tool in ASD neurobiological research due to its ability to capture neural oscillatory activity with high temporal resolution. This study aims to analyze the neurophysiological differences between individuals with ASD and neurotypical populations by examining EEG data using Hjorth parameters. The preprocessing stage involved using a Butterworth filter to enhance EEG signal quality by eliminating noise in the frequency range of 4-40 Hz. The Hjorth parameters, including Activity, Mobility, and Complexity, were used to assess the statistical characteristics of the EEG signals. The analysis was conducted on EEG data collected from 5 typical individuals and 5 ASD ASD subjects. Our findings reveal that the Hjorth Activity parameter is notably lower in the ASD group across all regions, with the most significant differences observed in the left and right frontal areas, where average activity measures 0.236 μV 2 and 0.060 μV 2 in ASD individuals, compared to 0.512 μV 2 and 0.138 μV 2 in the neurotypical group. However, the Hjorth Complexity and Mobility values remained consistent between the two groups, implying that the fundamental structure of the EEG signals is relatively preserved. These findings offer insights into the neurobiological mechanisms of ASD and suggest the potential use of Hjorth parameters in developing more targeted interventions for individuals with ASD.

关键词： Human computer interaction Autism Frontal lobe Noise Neural activity Electroencephalography Complexity theory Signal resolution Robots Optimization

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

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

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

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

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.

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Exploring Advances in Transformers and CNN for Skin Lesion Diagnosis on Small Datasets

arXiv

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arXiv 2022年

作者： de Lima, Leandro M. Krohling, Renato A. Graduate Program in Computer Science PPGI Federal University of Espirito Santo UFES Vitória Brazil Graduate Program in Computer Science PPGI Production Engineering Department LABCIN Federal University of Espirito Santo UFES Vitória Brazil

Skin cancer is one of the most common types of cancer in the world. Different computer-aided diagnosis systems have been proposed to tackle skin lesion diagnosis, most of them based in deep convolutional neural networks. However, recent advances in computer vision achieved state-of-art results in many tasks, notably Transformer-based networks. We explore and evaluate advances in computer vision architectures, training methods and multimodal feature fusion for skin lesion diagnosis task. Experiments show that PiT (0.800±0.006), CoaT (0.780±0.024) and ViT (0.771±0.018) backbone models with MetaBlock fusion achieved state-of-art results for balanced accuracy metric in PAD-UFES-20 dataset. © 2022, CC BY.

关键词： Classification (of information)

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Convergence of Bi-Virus Epidemic Models with Non-Linear Rates on Networks - A Monotone Dynamical Systems Approach

arXiv

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arXiv 2022年

作者： Doshi, Vishwaraj Mallick, Shailaja Eun, Do Young The Operations Research Graduate Program The Department of Computer Science The Department of Electrical and Computer Engineering North Carolina State University RaleighNC United States

We study convergence properties of competing epidemic models of the Susceptible-Infected-Susceptible (SIS) type. The SIS epidemic model has seen widespread popularity in modelling the spreading dynamics of contagions such as viruses, infectious diseases, or even rumors/opinions over contact networks (graphs). We analyze the case of two such viruses spreading on overlaid graphs, with non-linear rates of infection spread and recovery. We call this the non-linear bi-virus model and, building upon recent results, obtain precise conditions for global convergence of the solutions to a trichotomy of possible outcomes: a virus-free state, a single-virus state, and to a coexistence state. Our techniques are based on the theory of monotone dynamical systems (MDS), in contrast to Lyapunov based techniques that have only seen partial success in determining convergence properties in the setting of competing epidemics. We demonstrate how the existing works have been unsuccessful in characterizing a large subset of the model parameter space for bi-virus epidemics, including all scenarios leading to coexistence of the epidemics. To the best of our knowledge, our results are the first in providing complete convergence analysis for the bi-virus system with nonlinear infection and recovery rates on general graphs. © 2022, CC BY.

关键词： Viruses

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Amico: Message Exchange Service for Elderly People

Amico: Message Exchange Service for Elderly People

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Atsushi Isozaki Kazuki Fukae Kenichi Arai Toru Kobayashi Masahide Nakamura Computer and Information Science Program Graduate School of Engineering Nagasaki University Nagasaki Japan Division of Electrical Engineering and Computer Science Graduate School of Engineering Nagasaki University Nagasaki Japan Center of Mathematical and Data Sciences Kobe University Hyogo Japan

ISBN: (纸本)9781665492331

This study is related to a system that enables elderly people to communicate interactively with young people who use existing message exchange services by simply speaking to an avatar on a tablet PC, without having to perform complicated operations of the tablet PC. On the other hand, the young people side can bring in elderly people who could not previously participate in existing message exchange services groups. The effectiveness of the system was verified through demonstration experiments with two households consisting of elderly people in their 80s.

关键词： Economics Avatars Older adults Usability Smart phones Consumer electronics Commercialization

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Implementation and Evaluation of 0.6 µm CMOS Complex RCPF for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 25-37页

作者： Sato, Lina Fukagawa, Kanta Shouno, Kazuhiro Tanimoto, Hiroshi Muto, Cosy Moriyama, Seijiro Takahashi, Chikau Yoshino, Michitaka Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan Anagix Corporation 3-22-27 Numama Kanagawa Zushi249-0004 Japan Takamori Corporation Japan Research Center for Micro-Nano Technology Hosei University 3-11-15 Midori-cho Koganei Tokyo184-0003 Japan

This paper describes the implementation and evaluation of an RC polyphase filter (RCPF) and circuitry for measuring its frequency characteristics. The integrated circuit is fabricated on a 0.6 µm CMOS process and its supply voltage is 5 V. The integrated circuit includes a filter under test (FUT), a four-phase square wave generator, several analog switches and differential amplifiers to amplify the high-impedance signals of the RCPF. This FUT is a third-order complex RCPF whose passband is 8 − 40 MHz. This paper describes the design of these circuits in detail. This integrated circuit can select two measurement methods by means of external control signals. The first method uses a four-phase square wave. The frequency characteristics are measured by using an on-chip four-phase square wave generator driven by an external clock generator and by a spectrum analyzer tuned to the fundamental frequency. The second method uses an external network analyzer. Furthermore, this integrated circuit is equipped with a calibration circuit to measure the frequency characteristics of the circuitry except FUT by passing through the input / output signals of the FUT. As a result, the frequency characteristics of the FUT itself can be accurately measured. The effectiveness is confirmed through evaluation of the fabricated integrated circuit. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Differential amplifiers

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MOE++: ACCELERATING MIXTURE-OF-EXPERTS METHODS WITH ZERO-COMPUTATION EXPERTS

arXiv

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arXiv 2024年

作者： Jin, Peng Zhu, Bo Yuan, Li Yan, Shuicheng School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China -Preferred Program Peking University Shenzhen Graduate School China Kunlun 2050 Research & Skywork AI Singapore

In this work, we aim to simultaneously enhance the effectiveness and efficiency of Mixture-of-Experts (MoE) methods. To achieve this, we propose MoE++, a general and heterogeneous MoE framework that integrates both Feed-Forward Network (FFN) and zero-computation experts. Specifically, we introduce three types of zero-computation experts: the zero expert, copy expert, and constant expert, which correspond to discard, skip, and replace operations, respectively. This design offers three key advantages: (i) Low Computing Overhead: Unlike the uniform mixing mechanism for all tokens within vanilla MoE, MoE++ allows each token to engage with a dynamic number of FFNs, be adjusted by constant vectors, or even skip the MoE layer entirely. (ii) High Performance: By enabling simple tokens to utilize fewer FFN experts, MoE++ allows more experts to focus on challenging tokens, thereby unlocking greater performance potential than vanilla MoE. (iii) Deployment Friendly: Given that zero-computation experts have negligible parameters, we can deploy all zero-computation experts on each GPU, eliminating the significant communication overhead and expert load imbalance associated with FFN experts distributed across different GPUs. Moreover, we leverage gating residuals, enabling each token to consider the pathway taken in the previous layer when selecting the appropriate experts. Extensive experimental results demonstrate that MoE++ achieves better performance while delivering 1.1∼2.1× expert forward throughput† compared to a vanilla MoE model of the same size, which lays a solid foundation for developing advanced and efficient MoE-related models. Copyright © 2024, The Authors. All rights reserved.

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