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3rd International Conference on Vocational Education and Technology, IConVET 2020

作者： Setiadi, F.F. Kesiman, M.W.A. Aryanto, K.Y.E. Department of Computer Science Graduate Program Universitas Pendidikan Ganesha Singaraja Bali Indonesia

Internet of Things (IoT) is a technology that is currently on a trend. Interconnecting networks on IoT are useful in the automation process, but it has vulnerabilities to network-based disruptions and attacks;such as Denial of Service (DoS). This study aimed at implementing the Naive Bayes algorithm to predict attribute classes using training data-sets from NSLKDD with the KDD99 format and obtained testing-data from the logging process of DoS attacks on IoT-based devices. The advantage of using Naive Bayes is that this method only requires a small amount of training data to determine the estimated parameters needed in the classification process. The results of the conducted research could detect attacks on IoT devices by using the help of snort tools to capture traffic logs. The results from the log were then converted into KDD99 format and processed by the Naive Bayes method. This research uses a training dataset from NSLKDD with KDD99 format which is widely used in various studies and testing data obtained from the IDS log process on the Raspberry Pi 3. The attributes used are 9 attributes namely;service, flag, src_bytes, dst_bytes, srv_serror_rate, same_srv_rate, diff_srv_rate, dst_host_srv_diff_host_rate and dst_host_srv_serror_rate. The results of the research analysis showed an accuracy of 64.02%. These results were smaller than previous results, but some aspects were still different from the actual results because the testing data and training data were taken from two different data-sets, thereby they had different characteristics. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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The functorial semantics of Lie theory

arXiv

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arXiv 2022年

作者： MacAdam, Benjamin Graduate Program in Computer Science CalgaryAB Canada

Ehresmann’s introduction of differentiable groupoids in the 1950s may be seen as a starting point for two diverging lines of research, many-object Lie theory (the study of Lie algebroids and Lie groupoids) and sketch theory. This thesis uses tangent categories to build a bridge between these two lines of research, providing a structural account of Lie algebroids and the Lie functor. To accomplish this, we develop the theory of involution algebroids, which are a tangent-categorical sketch of Lie algebroids. We show that the category of Lie algebroids is precisely the category of involution algebroids in smooth manifolds, and that the category of Weil algebras is precisely the classifying category of an involution algebroid. This exhibits the category of Lie algebroids as a tangent-categorical functor category, and the Lie functor via precomposition with a functor ∂ : Weil1 → TGpd, bringing Lie algebroids and the Lie functor into the realm of functorial *** Codes 18F40 © 2022, CC BY.

关键词： Algebra

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Applications of Artificial Intelligence and Big Data for Strengthening the Role of Intelligence in Human Security 8

Applications of Artificial Intelligence and Big Data for Str...

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

作者： Mubarok, Ahmad Shahrul Susandi, Armi Mantoro, Teddy State Intelligence College Medical Intelligence Post-Graduate Program Bogor Indonesia Sampoerna University Media-Tech Lab Departement of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665453899

The state, through the government, should ensure national security and stability through the policies taken. For this reason, fast and accurate information and data are needed to form the basis for policymaking. Intelligence actors have an essential role in gathering information to identify and prevent threats within and outside the country. Technological advances affect changes in threats and increase the classification of these threats. Covid-19 is a real example of the threat in this era because almost all countries feel its impact. In addition to affecting health, the Covid-19 pandemic also impacts the global economic sector. The economic impact is felt by small and medium industries, goods and services products, and also the tourism sector. The method that is used in this study is a literature review from various national and international journals. AI and Big Data can be used to track viruses in real time, collect adequate public health data, and integrate vaccine use. Also, AI and Big Data can provide local decision and policy-makers with informed, evidence-based predictions. the threat of the Covid-19 pandemic and other infectious diseases that disrupt public health and have a broad impact must be anticipated and addressed in order to achieve the safety and existence of the nation and state. The author wants to emphasize the importance of the role of intelligence in anticipating threats from the visible to the invisible. © 2022 IEEE.

关键词： Artificial intelligence

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An Integrated Mobile Vision System for Enhancing the Interaction of Blind and Low Vision Users with Their Surroundings

An Integrated Mobile Vision System for Enhancing the Interac...

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3rd International Conference on Image Processing and Vision Engineering, IMPROVE 2023

作者： Chen, Jin Ramnath, Satesh Samaroo, Tyron Maksakuli, Fani Ruci, Arber Sturdivant, E’edresha Zhu, Zhigang Nearabl Inc New YorkNY10023 United States Computer Science Department The City College of New York - CUNY New YorkNY10031 United States PhD Program in Computer Science The Graduate Center - CUNY New YorkNY10016 United States

ISBN: (纸本)9789897586422

This paper presents a mobile-based solution that integrates 3D vision and voice interaction to assist people who are blind or have low vision to explore and interact with their surroundings. The key components of the system are the two 3D vision modules: the 3D object detection module integrates a deep-learning based 2D object detector with ARKit-based point cloud generation, and an interest direction recognition module integrates hand/finger recognition and ARKit-based 3D direction estimation. The integrated system consists of a voice interface, a task scheduler, and an instruction generator. The voice interface contains a customized user request mapping module that maps the user’s input voice into one of the four primary system operation modes (exploration, search, navigation, and settings adjustment). The task scheduler coordinates with two web services that host the two vision modules to allocate resources for computation based on the user request and network connectivity strength. Finally, the instruction generator computes the corresponding instructions based on the user request and results from the two vision modules. The system is capable of running in real time on mobile devices. We have shown preliminary experimental results on the performance of the voice to user request mapping module and the two vision modules. © 2023 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Palmprint recognition

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Monitoring Applications for Vehicle based on Internet of Things (IoT) using the MQTT Protocol 8

Monitoring Applications for Vehicle based on Internet of Thi...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Nurudin Sukmandhani, Arief Agus Zarlis, Muhammad Computer Science Department BinusOnline Learning Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Monitoring of vehicle conditions is needed as one of the securities in driving because one of the accident rates is negligence in checking the condition of the vehicle. This study aims to help reduce the level of accidents and increase human awareness for vehicle conditions, especially minibus type vehicles. The system works to provide information on the condition of vehicles sourced from the Engine Control Unit (ECU). ECU data cars are obtained by SNIP traffic broadcast message and ask for data directly at the ECU. The car can provide vehicle information using a Canbus communication protocol through the OBD-II socket. Vehicle information can be seen by users through the website in real time. Based on the evaluation from the user side, this system provides ease of monitoring vehicle conditions because it can be accessed via the internet using various kinds of devices. © 2023 The Authors. Published by Elsevier B.V.

关键词： Blackbox ECU OBD-II Sstem Logging

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Application of Disentanglement to Map Registration Problem

arXiv

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arXiv 2024年

作者： Song, Hae Jin Krawczuk, Patrycja Huang, Po-Hsuan Department of Computer Science University of Southern California United States Neuroscience Graduate Program University of Southern California United States

Geospatial data come from various sources, such as satellites, aircraft, and LiDAR. The variability of the source is not limited to the types of data acquisition techniques, as we have maps from different time periods. To incorporate these data for a coherent analysis, it is essential to first align different "styles" of geospatial data to its matching images that point to the same location on the surface of the Earth. In this paper, we approach the image registration as a two-step process of (1) extracting geospatial contents invariant to visual (and any other non-content-related) information, and (2) matching the data based on such (purely) geospatial contents. We hypothesize that a combination of β-VAE-like architecture [2] and adversarial training will achieve both the disentanglement of the geographic information and artistic styles and generation of new map tiles by composing the encoded geographic information with any artistic style. Copyright © 2024, The Authors. All rights reserved.

关键词： Image registration

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UC3M-PUCPR at SemEval-2022 Task 11: An Ensemble Method of Transformer-based Models for Complex Named Entity Recognition 16

UC3M-PUCPR at SemEval-2022 Task 11: An Ensemble Method of Tr...

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16th International Workshop on Semantic Evaluation, SemEval 2022

作者： Schneider, Elisa Terumi Rubel Rivera-Zavala, Renzo M. Martinez, Paloma Moro, Claudia Paraiso, Emerson Cabrera Graduate Program on Informatics Pontifícia Universidade Catolica do Paraná Brazil Computer Science and Engineering Department Universidad Carlos III de Madrid Spain

ISBN: (纸本)9781955917803

This study introduces the system submitted to the SemEval 2022 Task 11: MultiCoNER (Multilingual Complex Named Entity Recognition) by the UC3M-PUCPR team. We proposed an ensemble of transformer-based models for entity recognition in cross-domain texts. Our deep learning method benefits from the transformer architecture, which adopts the attention mechanism to handle the long-range dependencies of the input text. Also, the ensemble approach for named entity recognition (NER) improved the results over baselines based on individual models on two of the three tracks we participated in. The ensemble model for the code-mixed task achieves an overall performance of 76.36% F1-score, a 2.85 percentage point increase upon our individually best model for this task, XLM-RoBERTa-large (73.51%), outperforming the baseline provided for the shared task by 18.26 points. Our preliminary results suggest that contextualized language models ensembles can, even if modestly, improve the results in extracting information from unstructured data. © 2022 Association for Computational Linguistics.

关键词： Deep learning

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Private Data Protection as Countermeasure Against Misuses of Medical Intelligent Technology Data: A Literature Study 8

Private Data Protection as Countermeasure Against Misuses of...

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

作者： Praseptiadi Dahlian Persadha, Pratama Susandi, Armi Mantoro, Teddy State Intelligence College Medical Intelligence Post-graduate Program Bogor Indonesia Sampoema University Media-Tech Lab Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665453899

Medical Technologies develop along with the development of the Industrial Revolution 4.0 (I.R. 4.0). In I.R. 4.0, a collaborative ecosystem is formed between cyber technology and automation technology to be able to create intelligent systems to facilitate various human activities, including activities related to health. The most important thing in the system is data since it is the basis for the development of various key icons technologies in the I.R. 4.0: Cloud Computing, Internet of Things (IoT), Big Data, Artificial Intelligence (Al), Augmented Reality, and Cyber Security. Unfortunately, with the variety of I.R. 4.0 products, the data produced by these products is also scattered everywhere. Misuse of this scattered data - which the owner may not even know where the data are stored - can harm the individual concerned, and even the very existence of the state. Healthcare services now are undergoing Digital Transformation in which these data were needed to build high-quality services. The Health Digital Transformation strategy changes the direction of health services to be simpler and easier to use by the public, increasing efficiency, and thus providing a higher quality health service system so that it can trigger better economic growth. On the regulatory aspect, The Private Data Protection Bill was proposed by the Indonesian government to protect the data of the Indonesian people. Literature studies are used to obtain knowledge between the three: technology development, digital transformation in healthcare, and private data protection. This study seeks how important private data protection regulation is to realize digitally transformed healthcare. The study conducted indicates Private Data Protection Bills have the means to guarantee the rights of the data owner and prevent their data (including medical intelligence data) to be misused. © 2022 IEEE.

关键词： Intelligent systems

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Scheduling Production in the Flexible Packaging Industry Using Mathematical Models and Genetic Algorithms

Scheduling Production in the Flexible Packaging Industry Usi...

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Informatics Engineering, science & Technology (INCITEST), International Conference on

作者： Masmur Tarigan Ford Lumban Gaol Tuga Mauritsius Widodo Budiharto Computer Science Department / Computer Science Graduate Program Esa Unggul University/Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Department of Information System Management Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Minimizing time wastage is a crucial objective for all production operations. Reliable manufacturing scheduling The objective is to mitigate time-based production waste caused by excessive processing, waiting, and transportation. Industry 4.0 promotes technological innovation across all industrial sectors to increase efficiency and effectiveness while preserving high competitiveness. The implementation of artificial intelligence in Industry 4.0 is expected to result in a reduction in time wastage. Non-dominance sequencing genetic algorithms (NSGA), genetic algorithms (GA), and evolutionary algorithms (EA) are the three most common scheduling approaches, according to literature-indexed research summaries from the past five years. The examination of production scheduling in the flexible packaging business, which involves the utilization of different machines and processes and is produced on demand, had not been conducted before in this study. A mathematical scheduling model will be developed in this research to ascertain the shortest production time span in the flexible packaging industry. As a form of technological innovation, this mathematical model will be utilized in experiments employing a genetic algorithm approach. For the genetic algorithm to generate a minimum makespan in the flexible packaging industry's production scheduling process.

关键词：

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Gamification in Sustainable Smart Tourism Destinations: A Systematic Review 9

Gamification in Sustainable Smart Tourism Destinations: A Sy...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Hiererra, Siti Elda Ramadhan, Arief Supangkat, Suhono Harso Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Smart Cities and Communities Innovation Center Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Purpose - This study aims to identify, analyze, and synthesize gamification's purposes, benefits, and essential factors in the tourism industry through a systematic literature review (SLR). Methodology - The research is based on a systematic review of the literature and focuses on pertinent gamification literature in the tourism industry. The authors analyzed 30 articles published between 2013 and 2021. Findings - The authors summarize previous research into five categories of purposes for gamification: (1) engagement, (2) enjoyable experiences, (3) loyalty & brand awareness, (4) sustainable behavior, (5) competitive advantage;three benefits of gamification: (1) utilitarian, (2) hedonic, and (3) social;and two essential factors in gamification that support successful smart tourism destinations: (1) tourist motivational, and (2) game design element. The originality of the research - The study provides the SLR method to investigate gamification's purposes, benefits, and essential factors to support sustainable smart tourism destinations (SSTD). This finding helps build a complete understanding of the gamification concept to support sustainable smart tourism destinations. © 2022 IEEE.

关键词： Tourism

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