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arXiv 2017年

作者： Banerjee, Joydeep Das, Arun Sen, Arunabha Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University TempeAZ85287 United States

The critical infrastructures of the nation such as the power grid and the communication network are highly interdependent. Also, it has been observed that there exists complex interdependent relationships between individual entities of the power grid and the communication network that further obfuscates the analysis, and mitigation of faults in such multi-layered networks. In recent years, the research community has made significant efforts towards gaining insight and understanding of the interdependency relations in such multi-layered networks, and accordingly, a number of models have been proposed and analyzed towards realizing this goal. In this chapter we study existing interdependency models proposed in the recent literature and discuss their approach, and inherent features, towards modeling interdependent multi-layer networks. We also provide a brief discussion into the drawbacks of each of these models and propose an alternate model that addresses these drawbacks by capturing the interdependency relationships using a combination of conjunctive and disjunctive relations. Copyright © 2017, The Authors. All rights reserved.

关键词： Electric power transmission networks

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Sentiment Analysis in Indonesian Trading using Lexicon-based and Support Vector Machine

Sentiment Analysis in Indonesian Trading using Lexicon-based...

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computer science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Raymond Sunardi Oetama Yanfi Yanfi Masagus M. Ikhsan Assiddiq U.P Sani Muhamad Isa Information System DepartmentFaculty of Engineering and Informatics Universitas Multimedia Nusantara Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia

Many individuals now trade online utilizing trading software in the digital world. Binomo is one of Indonesia's most popular trading platforms. This is because some influencers made several promises to Binomo customers. Since many customers were deceived, this case became quite popular. This study was executed to see how Indonesians felt about the Binomo application after the case went viral. The solution taken was in the form of sentiment analysis because there had been no previous research on sentiment analysis that discussed the Binomo case. The data was scanned using Netlytic tools, a cloud-based text and social network analyzer capable of identifying any talks on social media sites such as Twitter. The sentiment analysis of Binomo trading tweets by using the Multi-Perspective Question Answering lexicon utilized the KNIME tool. But unfortunately, the accuracy of sentiment analysis results is low. Furthermore, the Support Vector Machine technique is also being conducted. The Term Frequency-Inverse Document Frequency method is applied to perform feature extraction whilst the chi-square approach is utilized to identify features that are thought to be useful for inclusion in the classification process and to exclude features that are irrelevant to the target class. The obtained accuracy is 86%. The study proposes that words from the algorithm's outputs can be utilized to improve the quality of sentiment analysis using the lexicon. As an outcome of the algorithm, positive and negative terms are added to the lexicon, increasing the accuracy of sentiment analysis using the new vocabulary from 58.984% to 71.146%.

关键词： Support vector machines Training Sentiment analysis Vocabulary Dictionaries Social networking (online) Blogs

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Movement Persuit Control of an Offshore Automated Platform via a RAM-based Neural Network

Movement Persuit Control of an Offshore Automated Platform v...

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International Conference on Control, Automation, Robotics and Vision

作者： Horacio L. Franca Joao Carlos P. da Silva Omar Lengerke Max S. Dutra Massimo De Gregorio Felipe M. G. Franca Computer Science Department Mathematics Institute Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Mechanical Engineering Program COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Istituto di Cibernetica "Eduardo Caianiello" Consiglio Nazionale delle Ricerche (CNR) Naples Italy System Engineering and Computer Science Program COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781424478149

The reproduction of the movements of a ship by automated platforms, without the use of sensors providing exact data related to the numeric variables involved, is a non-trivial matter. The creation of an artificial vision system that can follow the cadence of said ship, in six axes of freedom, is the goal of this research. Considering that a real time response is a requisite in this case, it was decided to adopt a Boolean artificial neural network system that could identify and follow arbitrary interest points that could define, as a group, a model of the movement of an observed vessel. This paper describes the development of a prototype based on the Boolean perceptron model WiSARD (Wilkie, Stonham and Aleksander's Recognition Device), that is being implemented in the C programming language on a desktop computer using a regular webcam as input.

关键词： Stewart platform weightless neural networks WiSARD

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Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things 11

Intrusion Detection using Deep Neural Network Algorithm on t...

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Ikhwan, Syariful Wibowo, Adi Warsito, Budi School of Postgraduate Studies Diponegoro University Doctoral Program of Information System Semarang Indonesia Institut Teknologi Telkom Purwokerto D3 Telecommunication Engineering Banyumas Indonesia Diponegoro University Computer Science Informatics Department of Science and Mathematics Faculty Semarang Indonesia Diponegoro University Statistics Department of Science and Mathematics Faculty Semarang Indonesia

ISBN: (纸本)9781665460309

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small. © 2022 IEEE.

关键词： Internet of things

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The Use of Support Vector Machine and Genetic Algorithms to Predict Protein Function

The Use of Support Vector Machine and Genetic Algorithms to ...

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IEEE International Conference on systems, Man, and Cybernetics

作者： Walkiria K. Resende Renato A. Nascimento Carolina R. Xavier Iara F. Lopes Cristianc N. Nobre Department of Computer Science Universidade Federal de Sao Joao del Rei - UFSJ Department of Computer Science Pontificia Universidade Catolica de Minas Gerais PUC/MG Civil Engineering Program COPPE - UFRJ

ISBN: (纸本)9781467317139

In Bio informatics, the prediction of protein function is considered a very important task but also difficult. Using a set of enzymes represented by Hydrolase, Isomerase, Ligase, Lyase, Transferase and Oxidoreductase classes, previously used by Dobson et ah, this paper proposes a self-learning process able to predict their classes, based on their primary and secondary structures, through a Support Vector Machine (SVM) classifier and genetic algorithm. An SVM can he characterized as a supervised machine learning algorithm capable of resolving linear and non-linear classification problems. During the learning process, both the training data and the corresponding output are presented to the SVM to allow its parameters to he adjusted. This study utilized genetic algorithms - optimization heuristics often used to estimate parameters - to adjust the main parameters of the classifier such as kernel function type and parameter C, which provides the relationship between the training error and the margin of separation between classes. In this specific prediction problem, the results indicate that the best function is an RBF where width is 6.1 and C is 6.9. Using these parameters, the classifier obtains an average accuracy of 79.74%.

关键词： Component: Proteins Prediction Support Vector Machine Genetic Algorithms protein structure function Support Vector Network Genetic Algorithm (GA) Classifiers Learning processes secondary structures

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Improved Chest X-Ray Image Quality Using Median and Gaussian Filter Methods

Improved Chest X-Ray Image Quality Using Median and Gaussian...

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International Conference on Informatics, Multimedia, Cyber and Information system (ICIMCIS)

作者： Lucky Indra Kesuma Ermatita Ermatita Erwin Erwin Purwita Sari Rudhy Ho Purabaya Doctoral Program in Engineering Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Universitas Sjakhyakirti Information System Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Departement of Computer System Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Informatic Management Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Information System Faculty of Computer Science Universitas Pembangunan Nasional Veteran Jakarta Jakarta Indonesia

ISBN: (纸本)9781665473286

The lungs are one of the organs of the body that are responsible for the human respiratory process and are very susceptible to dangerous diseases. For this reason, early detection and diagnosis of lung organs is needed, one of which is through examination of Chest X-Ray (CXR) images. Examination of the results of CXR images is still done manually by doctors and radiologists, this requires time and high accuracy. To facilitate the examination, it is necessary to image quality enhancement in order to get better image quality results so as to produce an accurate diagnosis. The initial stage in this research is to apply the contour improvement technique to the image using Morphology Opening, and followed by noise reduction using Median Filter and Gaussian filter. The results of the two methods of noise reduction are compared with the results of image quality in order to find out the best method that can be applied. The implementation of image quality enhancement results was measured quantitatively using Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index Metrics (SSIM). In the Morphology Opening and Median Filter methods, the values obtained are 39.187, 22.252, and 0.952, respectively. Meanwhile, the Morphology Opening and Gaussian Filter methods obtained values of 38.717, 23.917 and 0.956. Based on these results, it can be concluded that both methods are able to improve image quality well.

关键词： Image quality PSNR Multimedia systems Noise reduction Morphology Lung Medical services

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Multiobjective optimization for project portfolio selection 12

Multiobjective optimization for project portfolio selection

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14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion

作者： De Barros, Márcio O. Costa, Hélio R. Figueiredo, Fábio V. Da Rocha, Ana Regina C. Post-graduate Information Systems Program - PPGI UNIRIO Av. Pasteur 458 Urca - Rio de Janeiro RJ Brazil COPPE UFRJ System Engineering and Computer Science Department Caixa Postal: 68511 CEP: 21945-970 - Rio de Janeiro Brazil CCA-RJ Brazilian Air Force Ponta do Galeão s/no Ilha do Governador CEP: 21941-510 - Rio de Janeiro Brazil

ISBN: (纸本)9781450311786

This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of candidate projects, which is unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure. Results show evidence that the project selection technique can be used in large-scale scenarios and that GA presents better results than simpler search strategy. Copyright is held by the author/owner(s).

关键词： Multiobjective optimization

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Analyzing the Behavioral Aspects of Implementing Green IT in an Academic Environment 8

Analyzing the Behavioral Aspects of Implementing Green IT in...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Syamsuar, Dedy Triando, Fero Ulfa, Maria Antoni, Darius Mailangkay, Adele Witarsyah, Deden School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Universitas Bina Darma Postgradute Department Palembang Indonesia Universitas Bina Darma Information System Study Program Computer Science Faculty Palembang Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia School of Industrial Engineering Telkom University Bandung Indonesia

ISBN: (纸本)9798350326093

Environmental awareness has recently emerged as one of the most crucial topics. As a result, various groups advocate for these technologies and research ways to promote their usage in various contexts. This study examines the factors influencing the intention and use of green technology among academics. This study integrates Price Value (PV) and Consideration of future consequence (CFC) to Theory Planned Behavior (TPB) as a theoretical basis. Two hundred five valid replies were gathered and processed through statistical analysis. The results of this study partly support the developed hypotheses. Four hypotheses developed from TPB have presented significant relationships. However, PV and CFC were not. The findings indicate that individuals in this study did not consider CFC or PV of green IT products as critical factors in their decision-making process. Findings also suggest that for implementation success, competent parties must consider the campaign to increase individual awareness and provide financial support regarding environmental policy. © 2023 IEEE.

关键词： Decision making

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Preferences for Using Canva Apps as a Presentation Media Creation Tool Among Gen Z Students: SEM Analysis with TAM and UTAUT2 Approaches 25

Preferences for Using Canva Apps as a Presentation Media Cre...

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25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024

作者： Maulana, Fairuz Iqbal Lestari, Dian Purnomo, Agung Arifuddin, Rahman Widartha, Vandha Pradwiyasma Adi, Puput Dani Prasetyo Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Medicine Airlangga Surabaya60132 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia Research Center for Telecommunication Bandung Indonesia

ISBN: (纸本)9798350378573

The purpose of this study is to find out what makes Generation Z students accept and use Canva as a tool for making presentation materials. The conceptual framework of this study is the combination of "Technology Acceptance Model (TAM)"and the "Unified Theory of Acceptance and Use of Technology (UTAUT2)". "Structural Equation Modeling (SEM)"used for data analyzation. This research aims to understand the dynamics of Canva acceptance among students. The findings show that enjoyment, fun, and pleasure in using Canva, combined with its creative tools and design-centric approach, significantly resonate with Gen Z's preference for aesthetics. This research highlights that Canva is favored by students for creating engaging presentations. © 2024 IEEE.

关键词： Students

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Mediating process adaptation through a goal-oriented context-aware approach

Mediating process adaptation through a goal-oriented context...

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International Conference on computer Supported Cooperative Work in Design

作者： Vanessa Tavares Nunes Cláudia M. Lima Werner Flávia Maria Santoro COPPE/PESC-Systems Engineering and Computer Science Program UFRJ Rio de Janeiro Brazil NP2Tec and Postgraduate Information Systems Program UNIRIO Rio de Janeiro Brazil

Complexity and dynamism of day-to-day activities in organizations are inextricably linked, one impacting the other, increasing the challenges for constant adaptation on the way to organize work to address emerging demands. Market is demanding systems that are aware of organizations processes and able to evolve and adapt to new situations in everyday working activities. We argue that flexibility in processes could be managed in real time, by PAIS (Process-aware Information systems), using context information collected in the work environment. This paper proposes CGAdapt, a context management architecture approach that aims to improve and automate dynamic process adaptation. We explain how process adaptation may occur in real time through an existent scenario using this proposal and discuss the value of context-awareness to reason about process alternative adaptations in a goal oriented approach.

关键词： Context Materials Business Adaptation models Analytical models

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