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8th Innovations in Theoretical computer Science Conference, ITCS 2017

作者： Babichenko, Yakov Barman, Siddharth William Davidson Faculty of Industrial Engineering and Management Technion-Israel Institute of Technology Haifa Israel Department of Computer Science and Automation Indian Institute of Science Bangalore India

ISBN: (纸本)9783959770293

We consider a multi-receivers Bayesian persuasion model where an informed sender tries to persuade a group of receivers to take a certain action. The state of nature is known to the sender, but it is unknown to the receivers. The sender is allowed to commit to a signaling policy where she sends a private signal to every receiver. This work studies the computation aspects of finding a signaling policy that maximizes the sender's revenue. We show that if the sender's utility is a submodular function of the set of receivers that take the desired action, then we can efficiently find a signaling policy whose revenue is at least (1 - 1/e) times the optimal. We also prove that approximating the sender's optimal revenue by a factor better than (1 - 1/e) is NP-hard and, hence, the developed approximation guarantee is essentially tight. When the sender's utility is a function of the number of receivers that take the desired action (i.e., the utility function is anonymous), we show that an optimal signaling policy can be computed in polynomial time. Our results are based on an interesting connection between the Bayesian persuasion problem and the evaluation of the concave closure of a set function.

关键词： Polynomial approximation

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Applying d-RSA with login system to speed up decryption process in client side 3

Applying d-RSA with login system to speed up decryption proc...

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3rd IEEE International Conference on engineering Technologies and Social Sciences, ICETSS 2017

作者： Somsuk, Kritsanapong Thammawongsa, Nopparat Department of Computer and Communication Engineering Faculty of Technology Udon Thani Rajabhat University Udon Thani Thailand Department of Electronic and Automation Systems Faculty of Technology Udon Thani Rajabhat University Udon Thani Thailand

ISBN: (纸本)9781538616116

Login System is the important process to identify the right for accessing the application by identifying and authenticating. Usually, username and password are the personal details of user for accessing the system. However, if both of them are stolen over the insecure channel, then the system is broken. With this problem, some of cryptographic algorithms are chosen to apply with the login system to avoid breaking the system. In the beginning of this year, the strong login system was proposed by applying with two different cryptographic algorithms, RSA and One Time Pad (OTP). RSA which is the asymmetric key cryptosystem is chosen for exchanging the OTP's key. One the other hand, user's password will be protected by using OTP. Although the improved login system is very strong and is very difficult for attackers to trap the information, the speed becomes very slow especially the decryption process of RSA taking very high computation time. In this paper, the new modified login system is proposed to speed up the login process with the same security level when it is compared with the login system applying with RSA and OTP. In fact, d-RSA is chosen instead of RSA by choosing the new private key with the lower Hamming weight in comparison to the private key. In particularly, with the lower Hamming weight, it implies that the new modified login system applying with d-RSA and OTP is faster than the login system with RSA and OTP. The experimental results show that the new modified system can speed up the login system although it becomes slower in registration process. The reason is that in registration process, it must also take time to find the new private key with the lower Hamming weight. However, the registration system is the process that will be implemented only the first time for user to sign up the application. © 2017 IEEE.

关键词： Authentication

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Preface

Methodologies and Intelligent Systems for Technology Enhance...

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Methodologies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference, 2019 2020年 1007卷 v-vi页

作者： Gennari, Rosella Vittorini, Pierpaolo De la Prieta, Fernando Di Mascio, Tania Temperini, Marco Silveira, Ricardo Azambuja Carranza, Demetrio Arturo Ovalle Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Computer Science and Automation Control University of Salamanca SalamancaSalamanca Spain Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Dipartimento di Ingegneria Informatica Automatica e Gestionale Sapienza Università di Roma Rome Italy Department of Computer Science and Statistics Federal University of Santa Catarina Florianópolis Brazil Universidad Nacional de Colombia Medellin Colombia

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Conceptual model of the VR module for “Virtual plaza for interactive presentation of Bulgarian cultural heritage”

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AIP Conference Proceedings 2019年第1期2172卷

作者： Angel Bachvarov Dimo Chotrov Yordan Yordanov Zlatka Uzunova 1Technical University Sofia Faculty of Mechanical Engineering Department Automation of Discrete Production Engineering Bulgaria 2Technical University Sofia Faculty of Computer Systems and Technologies Department Programming and Computer Technologies Bulgaria 3Technical University Sofia Faculty of German Engineering Education and Industrial Management Bulgaria 4Research and Development and Innovation Consortium Virtual and Augmented Reality Laboratory Bulgaria

In the last years, Virtual Reality (VR) has been established itself as a highly promising media technology for reconstruction and presentation of cultural heritage sites to a wide audience. Virtual Reality enables not only an exploration of a single artefact but of many virtual objects spatially and temporally arranged into a single scene. The users enter an artificially created space and get a feeling of being a part of it. They can perceive and interact with the objects in the virtual environment in natural way. In this paper we propose a conceptual model of the VR module for the “Virtual Plaza for Immersive Representation of Bulgarian Cultural Heritage Sites”. It contains an analysis of the possible input data and the developed workflows to help experts from the cultural heritage domain to implement various scenarios for presentation of single artefacts and complete scene par of cultural heritage site using the benefits of Virtual Reality as visualization medium.

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Common Limitations of Image Processing Metrics: A Picture Story

arXiv

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arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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AAANE: Attention-based adversarial autoencoder for multi-scale network embedding

arXiv

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arXiv 2018年

作者： Sang, Lei Xu, Min Qian, Shengsheng Wu, Xindong School of Computer and Information Hefei University of Technology Faculty of Engineering and IT University of Technology Sydney National Lab of Pattern Recognition Institute of Automation Chinese Academy of Sciences School of Computing and Informatics University of Louisiana Lafayette United States

Network embedding represents nodes in a continuous vector space and preserves structure information from the Network. Existing methods usually adopt a "one-size-fits-all" approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different scales play different roles in the embedding learning. In this paper, we propose an Attention-based Adversarial Autoencoder Network Embedding(AAANE) framework, which promotes the collaboration of different scales and lets them vote for robust representations. The proposed AAANE consists of two components: 1) Attention-based autoencoder effectively capture the highly non-linear network structure, which can de-emphasize irrelevant scales during training. 2) An adversarial regularization guides the autoencoder learn robust representations by matching the posterior distribution of the latent embeddings to given prior distribution. This is the first attempt to introduce attention mechanisms to multi-scale network embedding. Experimental results on real-world networks show that our learned attention parameters are different for every network and the proposed approach outperforms existing state-of-the-art approaches for network embedding. Copyright © 2018, The Authors. All rights reserved.

关键词： Network embeddings

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Machine learning for diagnosis of disease in plants using spectral data

Machine learning for diagnosis of disease in plants using sp...

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2018 International Conference on Artificial Intelligence, ICAI 2018 at 2018 World Congress in computer Science, computer engineering and Applied Computing, CSCE 2018

作者： Owomugisha, Godliver Melchert, Friedrich Mwebaze, Ernest Quinn, John A. Biehl, Michael University of Groningen Johann Bernoulli Institute for Mathematics and Computer Science P.O. Box 407 AK Groningen9700 Netherlands Fraunhofer Institute for Factory Operation and Automation IFF Sandtorstrasse 22 Magdeburg39106 Germany Makerere University School of Computing and Informatics Technology P.O. Box 7062 Kampala Uganda Busitema University Faculty of Engineering P. O. Box 236 Tororo Uganda

ISBN: (纸本)1601324804

Automating crop disease diagnosis is an important task, particularly for regions with few experts. Most current methods detect disease by analyzing leaf images, particularly for diseases that manifest on the aerial part of the plant. To train a good classifier one requires a huge image dataset and the appropriate methods to extract relevant features from the images that represent the disease unambiguously. Image data also tends to be prone to effects of occlusion that make consistent analysis of the data hard. In this paper we take a look at the use of spectral data collected from leaves of a plant. We analyse spectral data from visibly diseased parts of a leaf as well as parts that are visibly healthy. We employ prototype based classification methods and standard classification models in a three-class classification problem configuration. Results presented show significant improvement in performance when spectral data is used and the possibility of early detection of disease before the crops become visibly symptomatic, which for practical reasons is very important. CSREA Press ©.

关键词： Crops

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PID2018 benchmark challenge: Learning feedforward control

arXiv

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arXiv 2018年

作者： Zhao, Yang Dehghan, Sina Ates, Abdullah School of Control Science and Engineering Center for Robotics Shandong University Jinan Shandong250061 China University of California Merced MercedCA95340 United States School of Automation Southeast University Nanjing210096 China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey

The design and application of learning feedforward controllers (LFFC) for the one-staged refrigeration cycle model described in the PID2018 Benchmark Challenge is presented, and its effectiveness is evaluated. The control system consists of two components: 1) a preset PID component and 2) a learning feedforward component which is a function approximator that is adapted on the basis of the feedback signal. A B-spline network based LFFC and a low-pass filter based LFFC are designed to track the desired outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet. Encouraging simulation results are included. Qualitative and quantitative comparison results evaluations show that, with little effort, a high-performance control system can be obtained with this approach. Our initial simple attempt of low-pass filter based LFFC and B-spline network based LFFC give J=0.4902 and J=0.6536 relative to the decentralized PID controller, respectively. Besides, the initial attempt of a combination controller of our optimized PI controller and low-pass filter LFFC gives J=0.6947 relative to the multi-variable PID controller. Copyright © 2018, The Authors. All rights reserved.

关键词： Feedforward control

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Heuristic approaches to stochastic quadratic assignment problem: Var and cvar cases 23

Heuristic approaches to stochastic quadratic assignment prob...

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23rd International Conference on Soft Computing, MENDEL 2017

作者： Matoušek, Radomil Popela, Pavel Kudela, Jakub Brno University of Technology Faculty of Mechanical Engineering Institute of Automation and Computer Science Technická 2896/2 Brno616 69 Czech Republic Brno University of Technology Faculty of Mechanical Engineering Institute of Mathematics Technická 2896/2 Brno616 69 Czech Republic

The goal of this paper is to continue our investigation of the heuristic approaches of solving the stochastic quadratic assignment problem (StoQAP) and provide additional insight into the behavior of difierent formulations that arise through the stochastic nature of the problem. The deterministic Quadratic Assignment Problem (QAP) belongs to a class of well-known hard combinatorial optimization problems. Working with several real-world applications we have found that their QAP parameters can (and should) be considered as stochastic ones. Thus, we review the StoQAP as a stochastic program and discuss its suitable deterministic reformulations. The two formulations we are going to investigate include two of the most used risk measures-Value at Risk (VaR) and Conditional Value at Risk (CVaR). The focus is on VaR and CVaR formulations and results of test computations for various instances of StoQAP solved by a genetic algorithm, which are presented and discussed. © 2017 Brno University of Technology. All rights reserved.

关键词： Genetic algorithms

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Research on temperature cascade control of distillation column based on smith-fuzzy-PID

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Paper Asia 2017年 2卷 91-94页

作者： Wang, Yeqin Chen, Yunhao Liu, Qihui Zhang, Yue Faculty of Automation Huaiyin Institute of Technology Huaian China Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huaian China

The efficiency and quality of oil recovery depend largely on the temperature control in distillation column, a Smith-Fuzzy-PID cascade control system for the distillation column proposed to overcome the drawback of single loop control in terms of rapidity and stability. Fuzzy-PID controller is designed in vice loop to achieve the coarse control by controlling the material flow. The Smith predictor was introduced into the feedback loop of the main loop to solve the time-delay in the traditional PID control. The simulated results show that the proposed control system has good characteristic in terms of dynamic and steady-state performance and robustness. © 2017 SHPMedia Sdn Bhd. All rights reserved.

关键词： Distillation columns

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