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作者： Yeh, Chia-Hung Kang, Li-Wei Lee, Ming-Sui Lin, Cheng-Yang Department of Electrical Engineering National Sun Yat-sen University 804 Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 640 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 106 Taiwan

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior. ©2013 Optical Society of America.

关键词： Pixels

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GA optimization of OBF TS fuzzy models with linear and non linear local models

GA optimization of OBF TS fuzzy models with linear and non l...

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9th Brazilian Symposium on Neural Networks, SBRN'06

作者： Medeiros, Anderson V. Amaral, Wagner C. Campello, Ricardo J. G. B. State University of Campinas School of Electrical and Computer Engineering Campinas SP 13083-970 Brazil Catholic University of Santos Graduate Program in Computer Science Santos SP 11070-906 Brazil

ISBN: (纸本)0769526802

OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. Although encouraging application results have been obtained, no automatic procedure had yet been developed to optimize the design parameters of these models. This paper elaborates on the use of a genetic algorithm (GA) especially designed for this task, in which a fitness function based on the Akaike information criterion plays a key role by considering both model accuracy and parsimony aspects. The use of linear (actually affine) and nonlinear local models is also investigated. The proposed methodology is evaluated in the modeling of a real nonlinear magnetic levitation system. © 2006 IEEE.

关键词： Fuzzy sets

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Prediction of Internet Broadband Connectivity Classification in West Java Indonesia using Machine Learning

Prediction of Internet Broadband Connectivity Classification...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Kusuma Atmaja, Wahyu Haris Heryadi, Yaya Sonata, Ilvico Lukas Suparta, Wayan Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department West Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Engineering Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

A location's Take-up Rate was significantly influenced by its Internet connectivity and availability. The purpose of this research is to answer concerns about internal Internet Service Provider issues that affect Internet connectivity in clusters of West Java, Indonesia. It also aims to evaluate the results of models that forecast how these internal factors will affect internet connectivity. According to the research findings, the FTTH Cluster has eight significant Internet predictor connectivity out of 18 elements. Activation delay and Administration Documentation of Activation with Connectivity were the two major parameters modeled out of the 18 components. Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree (DT) models were used to predict Internet Broadband Connectivity Classification based on the two most important variables. According to the study, ANN is the best model, with 99% accuracy and 99.6% precision when compared to SVM and DT. Furthermore, it exceeds previous studies that used the ANN model and achieved 97.92% accuracy. © 2023 IEEE.

关键词： Prediction models

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Guest editorial nonlinear optimization of communication systems

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IEEE Journal on Selected Areas in Communications 2006年第8期24卷 1421-1423页

作者： Chiang, Mung Low, Steven H. Luo, Zhi-Quan Shroff, Ness B. Yu, Wei Steenstrup, M. Princeton University Department of Electrical Engineering Program in Applied and Computational Mathematics Princeton NJ 08544 United States California Institute of Technology Department of Computer Science Pasadena CA 91125 United States University of Minnesota Department of Electrical and Computer Engineering Minneapolis MN 55455 United States Purdue University School of Electrical and Computer Engineering West Lafayette IN 47907 United States University of Toronto Edward S. Rogers Sr. Department of Electrical and Computer Engineering Toronto Ont. M4S 3G5 Canada

No abstract available

关键词： Communication systems Design optimization Communication system control Optimization methods Protocols Distributed algorithms Power system modeling Nonlinear control systems Lagrangian functions Surges

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Multiple pivots in statistical machine translation for low resource languages 33

Multiple pivots in statistical machine translation for low r...

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33rd Pacific Asia Conference on Language, Information and Computation, PACLIC 2019

作者： Budiwati, Sari Dewi Aritsugi, Masayoshi Computer Science and Electrical Engineering Graduate School of Science and Technology Kumamoto University Japan School of Applied Science Telkom University Indonesia Big Data Science and Technology Faculty of Advanced Science and Technology Kumamoto University Japan

We investigate many combinations of multiple pivots of four phrase tables on a low resource language pair, i.e., Japanese to Indonesia, in phrase-based Statistical Machine Translation. English, Myanmar, Malay, and Filipino from Asian Language Treebank (ALT) were used as pivot languages. A combination of four phrase tables was examined with and without a source to target phrase table. Linear and Fillup Interpolation approaches were employed with two measurement parameters, namely, data types and phrase table orders. The dataset was divided into two data types, i.e., sequential and random. Furthermore, phrase table orders comprise of two, viz., descending and ascending. Experimental results show that the combination of multiple pivots outperformed the baseline. Moreover, the random type significantly improved BLEU scores, with the highest improvement by +0.23 and +1.02 for Japanese to Indonesia (Ja-Id) and Indonesia to Japanese (Id-Ja), respectively. Phrase tables order experiments show a different result for Ja-Id and Id-Ja. The descending order has a higher percentage as much as 87.5% compared to the ascending order in Ja-Id. Meanwhile, the ascending order obtained more than 90% in Id-Ja. Finally, the combination of multiple pivots attempt shows a significant effect to reduce perplexity score in Ja-Id and Id-Ja. Copyright © 2019 Sari Dewi Budiwati and Masayoshi Aritsugi.

关键词： computer aided language translation

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Back propagation neural network experiment on team matchmaking MOBA game 1

Back propagation neural network experiment on team matchmaki...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Tanuar, Evawaty Abbas, Bahtiar Saleh Trisetyarso, Agung Kang, Chul-Ho Gaol, Ford Lumban Suparta, Wayan Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Electrical Engineering Sanata Dharma University Yogyakarta55282 Indonesia

ISBN: (纸本)9781538609545

Backpropagation is one of the famous method for learning, Implementing Backpropagation techniques in games is part of AI in game. This paper aim to analyzed the best team composition in a Moba Game type in learning using neural network. Mobile Legend: Bang Bang is one of MOBA game for mobile phone. In this experiment, the 2 hidden layers back-propagation neural network algorithm is used to analyze the Mobile Legend game. 5000 training steps was done to reach the stability. This also a way of learning to find the best composition in a team played. Research in area AI and game is very wide and open, a huge opportunity to be explore in future. The objective of this research is to produce the good combination of team which can be resulted in a greater winning chance. © 2018 IEEE.

关键词： Backpropagation

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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Parametric sensitivity analysis of cOptBees optimal clustering algorithm 14

Parametric sensitivity analysis of cOptBees optimal clusteri...

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2014 14th International Conference on Intelligent Systems Design and Applications, ISDA 2014

作者： Cruz, Dávila Patrícia Ferreira Maia, Renato Dourado De Castro, Leandro Nunes Graduate Program in Electrical Engineering Mackenzie University São Paulo Brazil Computer Science Department State University of Montes Claros Montes Claros MG Brazil

ISBN: (纸本)9781479979387

Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same group are more similar to one another than to objects belonging to other groups. Many algorithms to solve data clustering problems have been presented in the literature. Recently, bee-inspired clustering algorithms have been proposed, presenting good performance to find groups in data. This paper aims to present the parametric sensitivity analysis of cOptBees, a bee-inspired clustering algorithm designed to find optimal clusters in datasets. The algorithm was run for different parameter configurations to assess the influence of each parameter in its performance. © 2014 IEEE.

关键词： Clustering algorithms

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IoT-based tire pressure monitoring system for air and temperature pressure using MPX5500D and LM35 sensor 8

IoT-based tire pressure monitoring system for air and temper...

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8th IEEE International Conference on Computing, engineering and Design, ICCED 2022

作者： Pangestu, Agung Sodikin, Iing Yusro, Muhammad Sapundani, Rum Al Hakim, Rosyid Ridlo Wilyanti, Sinka Jakarta Global University Faculty of Engineering and Computer Science Electrical Engineering Department Depok Indonesia State University of Jakarta Faculty of Engineering Department of Electronic Engineering Jakarta Indonesia University of Muhammadiyah Purwokerto Electromedical Engineering Technology Faculty of Health Science Purwokerto Indonesia Jakarta Global University Graduate Program in Electrical Engineering Faculty of Engineering and Computer Science Depok Indonesia

ISBN: (纸本)9781665453899

Research has been carried out to monitor vehicle tires before they are used and can reduce damage, including overcoming vehicle fuel waste because air pressure is continuously monitored. This research aims to utilize the MPX5500DP sensor as an air pressure device, the LM35 sensor as a temperature reader, and a buzzer based on IoT to build a tire pressure monitoring system (TPMS). The MPX5500DP and LM35 sensor inputs to the Arduino Uno microcontroller are distributed by the NodeMCU, fitted with a Wi-Fi module. The Blynk application sends and displays the data on a smartphone using the IoT-based. Based on this research, data on the percentage of errors in monitoring air pressure and tire temperature on vehicles were obtained by comparing the data to the pressure gauge and thermometer: 1-the results of the average reading of the sensor error value. MPX5500DP air pressure against pressure gauge is 5.3%. 2-the average reading of the LM35 sensor error value on the temperature thermometer is 6.8%. With this research, the air pressure and temperature in the tires can be monitored in real-Time via a smartphone using the IoT-based. © 2022 IEEE.

关键词： Thermometers

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Ti02-based Flexible Integrated Photonics for High-sensitivity Temperature Sensing

Ti02-based Flexible Integrated Photonics for High-sensitivit...

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2022 Conference on Lasers and Electro-Optics, CLEO 2022

作者： Zhao, Xuan Fan, Bo Veeraraghavan, Ashok Robinson, Jacob Applied Physics Graduate Program Smattey-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University HoustonTX77005 United States

We report a flexible temperature sensor based on Ti02 photonics that shows double the sensitivity compared to silicon photonics. This high sensitivity and biocompatibility pave the way towards point-of-care temperatur... 详细信息

ISBN: (纸本)9781957171050

关键词： Biocompatibility

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