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2nd International Workshop on information, Computation, and Control Systems for Distributed Environments, ICCS-DE 2020

作者： Babenko, M. Tchernykh, A. Golimblevskaia, E. Hung, Nguyen Viet Chaurasiya, V.K. North-Caucasus Federal University Stavropol Russia CICESE Research Center Ensenada BC Mexico South Ural State University Chelyabinsk Russia Ivannikov Institute for System Programming Moscow Russia LeQuyDon Technical University Hanoi Viet Nam Indian Institute of Information Technology Allahabad India

When designing and using distributed storage systems with cloud technology, the security issues become crucial. One of the promising mechanisms is the computationally secure threshold secret sharing scheme. We propose a computationally secure secret sharing scheme based on the minimally redundant modular code. It reduces the computational complexity of data encoding and decoding and reduce data redundancy. We show that it is computationally secure and provides data redundancy equivalent to the redundancy of the Rabin system. We demonstrate that the minimally redundant modular code does not satisfy the criterion of compactness of a sequence, but it can be used as an asymptotically ideal secret sharing scheme. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Redundancy

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Cybernetic Theory of informational Modeling of Teacher's Behavior in the Learning Process based on Fuzzy Logic

Cybernetic Theory of Informational Modeling of Teacher's Beh...

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Joint IFSA World Congress and NAFIPS Annual Meeting

作者： Shahnaz N. Shahbazova Department of Information Technology &Programming Azerbaijan Technical University 25 H.Cavid Ave. Baku AZ1073 Azerbaijan

ISBN: (纸本)9781479903467

Purpose of this work is to develop norms, knowledge and algorithms that will make a real shift most of the educational process on the computer environment. On the basis of artificial neural networks, a mechanism, which allows taking into account, the subjective opinion of experts without requiring changes to the system. With the help of fuzzy logic developed an original method of monitoring the student's knowledge as closely mimics the behavior of the teacher in the student survey, which combines the power and brevity, not previously accessible to automated systems.

关键词： Learning Process teacher brevity

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Improving the distributed elementwise processing implementation in D-Clean

Improving the distributed elementwise processing implementat...

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10th Symposium on programming Languages and Software Tools, SPLST 2007

作者： Zsok, Viktoria Hernyak, Zoltan Horvath, Zoltan Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University Pazmany Peter setany 1/C H-1117 Budapest Hungary Department of Information Technology Eszterházy Károly College Eszterházy tér 1 H-3300 Eger Hungary

ISBN: (纸本)9789634639251

The skeleton computing the distributed elementwise processing in D-Clean splits the input data, then applies an elementwise process-able function on the divided input, and finally composes the result from the already computed subresults. This paper presents improvements and refinements of the generalized skeleton implementation. The distributed and functional skeleton of the elementwise processing is implemented using the D-Clean coordination language with a new technique.

关键词： Musculoskeletal system

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Recent Developments and the New Direction in Soft-Computing Foundations and Applications 1

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丛书名： Studies in Fuzziness and Soft Computing

1000年

作者： Shahnaz N. Shahbazova Janusz Kacprzyk Valentina Emilia Balas Vladik Kreinovich

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & technology 2023.

关键词： Machine learning

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Faster R-CNN Deep Learning Model for Pedestrian Detection from Drone Images

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SN Computer Science 2020年第2期1卷 1-9页

作者： Hung, Goon Li Sahimi, Mohamad Safwan Bin Samma, Hussein Almohamad, Tarik Adnan Lahasan, Badr Intelligent Biometric Group School of Electrical and Electronic Engineering Engineering Campus Universiti Sains Malaysia Penang Nibong Tebal 14300 Malaysia Department of Computer Programming Faculty of Education–Shabwa University of Aden Shabwa Yemen School of Information Science and Technology Xiamen University Malaysia Jalan Sunsuria Bandar Sunsuria Selangor Darul Ehsan Sepang 43900 Malaysia

Pedestrian detection from a drone-based images has many potential applications such as searching for missing persons, surveillance of illegal immigrants, and monitoring of critical infrastructure. However, it is considered as a very challenge computer vision problem due to the variations in camera point of view, distance from pedestrian, changes in illuminations and weather conditions, variation in the surrounding objects, as well as present of human-like objects. Recently, deep learning-based models are getting more attention, and they have proven a great success in many object detection problems such as the detection of faces, breast masses, and vehicles. As such, this work aims to develop a deep learning-based model that will be applied for the problem of pedestrian detection from a drone-based images. Particularly, faster region-based convolutional neural network (Faster R-CNN) will be used to search for the present of a pedestrian inside the captured drone-based images. To assess the performances, a total of 1500 images were collected by S30W drone and these images were captured at different places, with various views and weather conditions, and at daytime and night-time. Results show that Faster R-CNN was able to achieve a promising result with 98% precision, 99% recall, and 98% F1 measure. Further analysis has been conducted by comparing the outcomes of Faster R-CNN with YOLO deep model on UAV123 publicly available dataset. The reported results indicated that both detection models almost reported very similar results. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Deep learning Drone images Faster R-CNN Pedestrian detection

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Cyber-Physical-Social System Self-Organization: Ontology-Based Multi-level Approach and Case Study

Cyber-Physical-Social System Self-Organization: Ontology-Bas...

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International Conference on Self-Adaptive and Self-Organizing Systems (SASO)

作者： Alexander Smirnov Alexey Kashevnik Nikolay Shilov Information technology and programming department ITMO University St.Petersburg Russia Laboratory of Computer Aided Integrated Systems SPIIRAS St.Petersburg Russia

This paper presents a multi-level approach for self-organization of in cyber-physical system resources. Cyber-physical system consists of physical part and cyber part. For implementation of joint actions by devices in physical part, they have to interact in cyber part. It is proposed to use the smart space technology for exchange information between these devices in cyber part of cyber-physical system. Smart Space -- is a computational environment consisting of multiple heterogeneous services (electronic and computational devices, Internet pages, data based, etc.) which has intelligent behavior, can proactively provide information taking into account current situation. Smart spaces allow unifying different levels of services, implement self-organization of services in each level, and providing politics from upper to lower level. Self-organization on every level is implemented based on ontology-based context management techniques and ontology matching method that provides semantic interoperability between interacted robots. Discussed in the paper case study solve the task of self-organization three types of robots based on politics from operation planning services and context situation in smart space. For the scenario implementation the Smart-M3 information sharing platform is used. It provides easy-to-use interfaces for information sharing through the RDF ontologies and publish / subscribe mechanism for connected services.

关键词： Ontologies Robots Semantics information management Organizations Interoperability Pipelines

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Research and Development of Reflectarray Antennas

Research and Development of Reflectarray Antennas

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International Conference on Mathematical Methods in Electromagnetic Theory (MMET)

作者： Viktor Hoblyk Nadiia Hoblyk Department of Electronics and Information Technology Lviv Polytechnic National University Lviv Ukraine Department of Computational Mathematics and Programming Lviv Polytechnic National University Lviv Ukraine

This work presents results of computer simulation of a flat reflective array of rectangular waveguides and results of the investigation of the influence of phase errors on the formation of the radiation field.

关键词： Electromagnetic waveguides Reflector antennas Antenna arrays Antenna radiation patterns Mathematical model Apertures

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The Problem of Morphological Synthesis and Methods, Algorithms for Handling Errors in Word Forms

The Problem of Morphological Synthesis and Methods, Algorith...

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Informatics, Electronics, and Radio Engineering (PIERE), International Conference Problems of

作者： Buazhar O. Kochkonbaeva Julduz S. Egemberdieva Abdugany D. Satybaev Department of Information Technology and Programming Osh State University Osh Kyrgyzstan Department of Information Technology Kyrgyz-Uzbek International University after named B. Sydykov Osh Kyrgyzstan Department of Information Technology and Management Osh Technological University after named academican M.M. Adyshev Osh Kyrgyzstan

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

Morphological synthesis is a key aspect of natural language processing that focuses on the generation of word forms from their base components - roots, stems, prefixes, affixes, and inflectional morphemes. It plays a crucial role in understanding and generating various grammatical forms of words in different languages. This process is essential for tasks such as machine translation, speech synthesis, text generation, and information retrieval. In agglutinative languages, words are formed by stringing together affixes that each represent a single grammatical function. Each morpheme retains its distinct meaning and function, making synthesis relatively predictable. In this article, using Kyrgyz as an example, we have examined the rules governing the attachment of affixes to words and assessed whether these affixes are correctly attached or if there are issues with morphological synthesis. This is, of course, a very topical issue. Because the first step in the problems of artificial intelligence is to pay attention to the features and ways of language creation.

关键词： Translation information retrieval information age Speech synthesis Machine translation Artificial intelligence Informatics

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The prediction of students' Academic performances with a classification Model Built using Data Mining Techniques 6

The prediction of students' Academic performances with a cla...

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6th Smart Cities Symposium, SCS 2022

作者： Alkattan, Hussein Abotaleb, Mostafa Subhi, Alhumaima Ali Adelaja, Oluwaseun A. Kadi, Ammar Ibrahim Al-Mahdawi, Hassan K. Department of System Programming South Ural State University Chelyabinsk454080 Russia Electronic and Computer Center University of Diyala BaqubahMJJ2+R9G Iraq Information Communication and Technology Department Lagos State University Lagos102101 Nigeria Department of Food and Biotechnology South Ural State University Chelyabinsk454080 Russia

ISBN: (纸本)9781839538544

In the purview of most educational sectors today, numerous reviews regarding data mining have been the primary focus, with goals of discovering vast knowledge patterns for students' data. This paper focuses on building model that predicted the performance of computer science students in some courses they were examined through classification technique. The model built for the purpose of classification via decision tree classifier which was adopted in WEKA and KNIME analytics platform. The workflow model basically connected nodes to generate the decision trees while J4.8 Decision Tree Classifier programmable outputs were generated for the courses to obtain the confusion matrix and other instances. Bar Charts were plotted to display the students' performance in the courses. The mean absolute errors, RMS error and relative absolute error all read 0% while the kappa value obtained from the analysis ranged between 0.991 - 1.00 which perfectly agrees for most statistical values. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Decision trees

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