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arXiv 2024年

作者： Tsai, Chung-En Wang, Guan-Ren Cheng, Hao-Chung Li, Yen-Huan Department of Computer Science and Information Engineering National Taiwan University Taiwan Graduate Institute of Networking and Multimedia National Taiwan University Taiwan Department of Electrical Engineering Graduate Institute of Communication Engineering National Taiwan University Taiwan Department of Mathematics National Taiwan University Taiwan Center for Quantum Science and Engineering National Taiwan University Taiwan Physics Division National Center for Theoretical Sciences Taiwan Quantum Computing Centre Taiwan

Consider the problems of computing the Augustin information and a Rényi information measure of statistical independence, previously explored by Lapidoth and Pfister (IEEE Information Theory Workshop, 2018) and Tomamichel and Hayashi (IEEE Trans. Inf. Theory, 64(2):1064-1082, 2018). Both quantities are defined as solutions to optimization problems and lack closed-form expressions. This paper analyzes two iterative algorithms: Augustin's fixed-point iteration for computing the Augustin information, and the algorithm by Kamatsuka et al. (arXiv:2404.10950) for the Rényi information measure. Previously, it was only known that these algorithms converge asymptotically. We establish the linear convergence of Augustin's algorithm for the Augustin information of order α ∈ (1/2, 1) ∪ (1, 3/2) and Kamatsuka et al.'s algorithm for the Rényi information measure of order α ∈ [1/2, 1) ∪ (1,∞), using Hilbert's projective metric. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization algorithms

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Robust Deep Learning-based Indoor mmWave Channel Prediction Under Concept Drift

Robust Deep Learning-based Indoor mmWave Channel Prediction ...

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IEEE Conference on Vehicular Technology (VTC)

作者： Eslam Hasan Elmahedi Mahalal Muhammad Ismail Zi-Yang Wu Mostafa M. Fouda Tiago Koketsu Rodrigues Nei Kato Department of Computer Science Tennessee Technological University Cookeville TN USA College of Information Science and Engineering Northeastern University Shenyang China Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA Graduate School of Information Sciences Tohoku University Sendai Japan

The mmWave WiGig frequency band can support high throughput and low latency emerging applications. In this context, accurate prediction of channel gain enables seamless connectivity with user mobility via proactive handover and beamforming. Machine learning techniques have been widely adopted in literature for mmWave channel prediction. However, the existing techniques assume that the indoor mmWave channel follows a stationary stochastic process. This paper demonstrates that indoor WiGig mmWave channels are non-stationary where the channel’s cumulative distribution function (CDF) changes with the user’s spatio-temporal mobility. Specifically, we show significant differences in the empirical CDF of the channel gain based on the user’s mobility stage, namely, room entering, wandering, and exiting. Thus, the dynamic WiGig mmWave indoor channel suffers from concept drift that impedes the generalization ability of deep learning-based channel prediction models. Our results demonstrate that a state-of-the-art deep learning channel prediction model based on a hybrid convolutional neural network (CNN) long-short-term memory (LSTM) recurrent neural network suffers from a deterioration in the prediction accuracy by 11–68% depending on the user’s mobility stage and the model’s training. To mitigate the negative effect of concept drift and improve the generalization ability of the channel prediction model, we develop a robust deep learning model based on an ensemble strategy. Our results show that the weight average ensemble-based model maintains a stable prediction that keeps the performance deterioration below 4%.

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A Comparative Study of Fishing Activity Detection Approaches in Maritime Surveillance

A Comparative Study of Fishing Activity Detection Approaches...

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computer science, computer engineering, & Applied Computing (CSCE), Congress in

作者： Vinicius D. Do Nascimento Tiago A. O. Alves Diego L. C. Dutra Sandip Kundu Systems Engineering and Computer Science Program (PESC) Federal University of Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Mathematics and Statistics Institute State University of Rio de Janeiro (UERJ) Rio de Janeiro Brazil Electrical and Computer Engineering (ECE) Department University of Massachusetts Amherst USA

Maritime authorities (MA) must track fishing vessels to ensure that fishing activities are limited to permitted areas. If illegal fishing is suspected, resources must be allocated to intercept and inspect the vessels. Thus, a false flag by the MA is costly, so it is important to use accurate detection methods. We compare the accuracy and computational time of the main approaches for detecting fishing activities described in the literature, using the Global Fishing Watch (GFW) dataset. We find that Long Short-Term Memory (LSTM) neural networks achieves an optimal accuracy of 1.00, while the random forest approach comes second with an accuracy of 0.87. Given the high cost of mistakes for MA, we conclude that the LSTM's high computational cost is worthwhile.

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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Information Technology and Computing (ICITCOM), International Conference on

作者： Debby Alita Imam Ahmad Rhaishudin Jafar Rumandan Moh Erkamim Widyasmoro Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Islamic Education Management Study Program Institut Agama Islam Negeri Ambon Ambon Indonesia Smart City Information Systems Study Program Universitas Tunas Pembangunan Surakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.

关键词： Pediatrics Accuracy Computational modeling Prevention and mitigation Data models Classification algorithms Decision trees Data mining Information technology Diseases

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Strategic planning in semantic crowdware large groups decision

Strategic planning in semantic crowdware large groups decisi...

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International Conference on computer Supported Cooperative Work in Design

作者： S. P. J. Medeiros D. Schneider J. M. de Souza M. G. P. Esteves DEL-POLI Department of Electrical Engineering School of Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil COPPE Graduate School of Engineering DCC-IMM Department of Computer Science Federal University of Rio de Janeiro Rio de Janeiro Brazil COPPE Graduate School of Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil

This work presents a Strategic Planning approach in the MUTIRÕ project, showing the new concepts of Crowdware in a Large Scale decision support system. The Olympic and Paralympics Games that will be hosted in the city of Rio de Janeiro in the middle of 2016 will serve as a confirmation of these concepts. The preparation plans for Rio 2016 event will demand several artifacts to allow its correct effectiveness. This series of developments will be decided by the Event Commission and many people are eager to contribute by sending novice ideas and collaborating. To aid this task, our paper intends to show a crowd-based decision support systems methods through different solutions in order to help large groups in their discussions, their alternatives generation and all group choosing process. The continental characteristic of our country creates several opportunities for these techniques establishing additional difficulties for CSCWD. While groupware focus on the technologies related to work group, crowdware synthesizes the search for artifacts that implements the principles of James Surowiecki Wisdom of the Crowds in a very large number of collaborators. The main task of this project is to help groups interested in the Rio 2016 success taking into account their socioeconomic and geographical aspect.

关键词： Thesauri Educational institutions Collaborative software Collaborative work YouTube Visualization

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Retracted: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

Retracted: Design of Decision Support System Determination o...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Iqbal, Muhammad Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Sriadhi, S. Nurmawati, N. Prasnowo, M Adhi Hasibuan, Abdurrozzaq Iskandar, Akbar Saddhono, Kundharu Abdussakir, A. Musa, Hastuti Setiawan, Muhammad Ikhsan Sagala, Youmeni Siahaan, Rumiris Sinaga, Eka Mayastika Syahputri, Anggraini Milanie, Feby Aspan, Henry Khaddafi, Muammar Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan Indonesia Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Comparing adaptation of constrained and unconstrained movements in three dimensions

Comparing adaptation of constrained and unconstrained moveme...

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IEEE International Conference on Rehabilitation Robotics (ICORR)

作者： C. Scharver J. Patton R. Kenyon E. Kersten Sensory Motor Performance Program Rehabilitation Institute of Chicago Chicago IL USA Robotics Laboratory Rehabilitation Institute of Chicago Chicago IL USA Department of Computer Science University of Illinois Chicago IL USA Biomedical Engineering Graduate Program University of Wisconsin Madison WI USA

This paper describes targeted reaching experiments conducted using a new augmented reality system. Combining a large-workspace immersive virtual environment with physical force feedback, the system distorted subjects' movements using a viscous curl force field. Following previous experiments using a different robot, half the subjects were constrained to horizontal, planar movements. The remaining subjects performed unconstrained movements throughout the 3D workspace. Examining after-effects as an indication of learning, we found that constrained subjects learned the force field. However, it was difficult to detect whether the unconstrained subjects learned forces of identical magnitude. Our results found that force fields strengths eliciting constrained 2D adaptation have difficulty exhibiting after-effects for unconstrained 3D movements. The increased motor variability for 3D reaching movements requires consideration for future experimental design.

关键词： Rehabilitation robotics Robot sensing systems Nonlinear distortion Force feedback Displays Laboratories Augmented reality Virtual environment Design for experiments Haptic interfaces

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Opposition-based shuffled PSO with passive congregation applied to FM matching synthesis

Opposition-based shuffled PSO with passive congregation appl...

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Congress on Evolutionary Computation

作者： Daniel M. Muñoz Carlos H. Llanos Leandro dos S. Coelho Mauricio Ayala-Rincón Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia Brazil

Synthesis of musical instruments or human voice is a time consuming process which requires theoretical and experimental knowledge about the synthesis engine. Commonly, performers need to deal with synthesizer interfaces and a process of trial and error for creating musical sounds similar to a target sound. This drawback can be overcome by adjusting automatically the synthesizer parameters using optimization algorithms. In this paper a hybrid particle swarm optimization (PSO) algorithm is proposed to solve the frequency modulation (FM) matching synthesis problem. The proposed algorithm takes advantage of a shuffle process for exchanging information between particles and applies the selective passive congregation and the opposition-based learning approaches to preserve swarm diversity. Both approaches for injecting diversity are based on simple operators, preserving the easy implementation philosophy of the particle swarm optimization. The proposed hybrid particle swarm optimization algorithm was validated for a three-nested FM synthesizer, which represents a 6-dimensional multimodal optimization problem with strong epistasis. Simulation results revealed that the proposed algorithm presented promising results in terms of quality of solutions.

关键词： Frequency modulation Optimization Equations Convergence Particle swarm optimization Genetic algorithms

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Chaotic and statistical analysis of multiple unit neuronal activities on the learning stimuli

Chaotic and statistical analysis of multiple unit neuronal a...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： S.Y. Cho B.Y. Kim Y.S. Jang H.T. Kim Department of Neuroscience Graduate School of East-West Medical Science Kyung Hee University Seoul South Korea Department of Electrical & Computer Engineering BK Kangwon University Kangwon South Korea Department of Computer Engineering Daejin University Kangwon South Korea Department of Psychology Korea University Seoul South Korea

Summary form only given. We are to apply the chaotic features in the analysis of neuronal activity recorded from brain area involved in learning. Neural plasticity during learning is a major theme in the neurobiology of learning and memory. We recorded the multiple-unit activities at four brain sites that involve the classical conditioning of rabbits' nictitating membrane responses. The neuronal data were analyzed using chaotic features including the box-counting dimension, fractal dimension and central tendency, as well as statistical features. The chaotic characteristics represent the change of neuronal response by learning. Each index showed the change within a trial, the change across the training sessions, and the differences between the trials showing the learned responses and the trials not showing. The chaotic characteristics could be useful indices in the representation of the neural plasticity.

关键词： Chaos Biomedical engineering Psychology Brain Rabbits Biomembranes Data analysis Fractals Statistics

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Beryllium polyhydride Be4H8(H2)2 synthesized at high pressure and temperature

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Physical Review Materials 2020年第12期4卷 125402-125402页

作者： Takahiro Matsuoka Hiroshi Fujihisa Takahiro Ishikawa Takaya Nakagawa Keiji Kuno Naohisa Hirao Yasuo Ohishi Katsuya Shimizu Shigeo Sasaki Department of Electrical Electronic and Computer Engineering Faculty of Engineering Gifu University Gifu 501-1193 Japan Material Science and Engineering Joint Institute for Advanced Materials (JIAM) The University of Tennessee Knoxville Tennessee 37996 USA National Institute of Advanced Industrial Science and Technology (AIST) Ibaraki 305-8565 Japan The Elements Strategy Initiative Center for Magnetic Materials National Institute for Materials Science Ibaraki 305-0047 Japan Materials Science and Technology Division Graduate School of Engineering Gifu University Gifu 501-1193 Japan Environmental and Renewable Energy Systems Division Gifu University Gifu 501-1193 Japan Japan Synchrotron Radiation Research Institute (JASRI) Hyogo 679-5198 Japan Center for Science and Technology under Extreme Conditions Graduate School of Engineering Science Osaka University Osaka 560-8531 Japan

We report x-ray diffraction and Raman scattering measurements in combination with density functional theory calculations that reveal the formation of beryllium polyhydride Be4H8(H2)2 by the laser heating of a Be-H2 mixture to above 1700 K at pressures between 5 and 8 GPa. Be4H8(H2)2 crystallizes in a P63/mmc structure and consists of the corner-sharing BeH4 tetrahedrons and the H2 molecules that occupy an interstitial site. Be4H8(H2)2 is stable at least to 14 GPa upon compression and stable down to 4 GPa at room temperature. Our ab initio calculations suggest that Be4H8(H2)2 is a metastable phase of the Be-H system.

关键词： Composition Pressure effects Structural properties Hydrides Ab initio calculations Density functional theory Raman spectroscopy X-ray diffraction

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