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arXiv 2022年

作者： Evtimova, Mariya Savova Momtchev, Ivan Momtchilov Faculty of Computer Systems and Control Programming Computer Technologies Department Technical University of Sofia Sofia1000 Bulgaria

Personalization is becoming very important direction in semantic web search for the users that needs to find appropriate information. In this paper, a classification of web personalization is proposed and semantic web search tools are investigated. Building user interest profile is essential for personalizing. Nowadays, semantic web tools use ontologies for personalization because of their advantages. It is important to mention that most of the semantic web search tools use agent technologies for implementation. © 2022, CC BY.

关键词： Search engines

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A Comprehensive Study on m-Polar Picture Fuzzy Graphs and Its Application

Journal of Uncertain Systems

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Journal of Uncertain Systems 2025年第1期18卷

作者： Khatun, Jasminara Amanathulla, S. Pal, Madhumangal Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721102 India Department of Mathematics Raghunathpur College Raghunathpur 723133 India

In real-life problems, information collected from multiple agents often exhibits "multipolar information," which cannot be accurately modeled by existing graph models. This paper introduces the m-polar picture fuzzy graph (mPPFG) as a more efficient model for such problems. The mPPFG offers a precise, flexible and comparable system compared to other graph models. The paper defines the mPPFG model and introduces new terms and properties such as order, degree, weighted arithmetic average (WAA) order, WAA degree, complement, homomorphism, isomorphism, eccentricity, radius, diameter and more. It also explores the concepts of m-polar antipodal picture fuzzy graphs, eccentric mPPFG, self-centered mPPFG and self-median mPPFG, highlighting their definitions and properties. The m-polar antipodal picture fuzzy graph represents a graph where each vertex is associated with an m-polar antipodal picture fuzzy set. The eccentric mPPFG focuses on highly eccentric vertices, while the self-centered mPPFG considers central vertices. The self-median mPPFG represents median vertices in the graph. The study of these graph types and their isomorphism properties contributes to a deeper understanding of the structural variations within mPPFGs. Furthermore, the paper proposes an application of the mPPFG model in evaluating the performance of ministers in India during their tenure. An algorithm is also developed for computing the performance of ministers. © 2024 World Scientific. All rights reserved.

关键词： complement diameter isomorphism m-polar antipodal PFG mPPFG Picture fuzzy graphs

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The Use of Many-valued Logics to Improve the Elements and Devices of computer Technology 3

The Use of Many-valued Logics to Improve the Elements and De...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Mezentsev, Mykola Kharchenko, Artem Gasanov, Magomediemin Orlova, Tetyana National Technical University 'Kharkiv Polytechnic Institute' Computer Engineering and Programming Department Kharkiv Ukraine Vice-rector for Scientific and Pedagogical Work National Technical University 'Kharkiv Polytechnic Institute' Kharkiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

To estimate the measure of proximity and distance in various tasks (clustering, classification, etc.), one of the most common ways to represent information about objects is a binary indications vector. At the same time, to estimate the measure of proximity, a sufficiently large number of relationships are used that describe binary indicators of similarity and distance between objects with qualitative characteristics. At the same time, during the real functioning of objects, their characteristics can change over time, which can lead to uncertainties when comparing binary vectors of qualitative indications that describe these objects. Therefore, it is advisable to use many-valued logics that can take into account such uncertainties. The paper describes approaches to the application of such logics, and also considers their modifications to determine the measures of proximity and distances for objects whose characteristics are described by vectors using many-valued logics under uncertainty. © 2022 IEEE.

关键词： Vectors

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Study of an OPTO-ASIC for a Functionally Safe Speed Sensor Using the Spatial Frequency Filter Method

Study of an OPTO-ASIC for a Functionally Safe Speed Sensor U...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Frank Wasinski Werner Bonath Ubbo Ricklefs Michael Schwarz Josef Börcsök Dept. of Electrical Engineering and Information Technology THM University of Applied Sciences Giessen Germany ICAS Institute for Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (数字)9798331528010

ISBN: (纸本)9798331528027

For decades, speed sensors based on the spatial frequency filter method have successfully proven themselves in a wide range of applications. This makes the sensor concept particularly suitable for the area of functional safety. New filter variants extend the previous measuring range to very low speeds up to standstill detection. By combining the sensor with a safety system on chip for recording and analysing measured values, a functionally safe measuring chain can be established. In order to demonstrate the variability and performance of the new filters, an optical application-specific integrated circuit was designed, which forms the basis for further extensive tests. The core components are a large number of freely configurable photodiode channels, which were realised via a redundant structure, as well as two different transimpedance amplifier concepts. In the further course of the project, the ASIC will be analysed with regard to its desired performance parameters and its robustness.

关键词： Optical filters Semiconductor device measurement Optical design Stimulated emission Safety Topology System-on-chip Optical sensors Optical amplifiers Velocity measurement

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Simulating Structural Plasticity of the Brain more Scalable than Expected

arXiv

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arXiv 2022年

作者： Czappa, Fabian Geiß, Alexander Wolf, Felix Laboratory for Parallel Programming Department of Computer Science Technical University of Darmstadt Germany

Structural plasticity of the brain describes the creation of new and the deletion of old synapses over time. Rinke et al. (JPDC 2018) introduced a scalable algorithm that simulates structural plasticity for up to one billion neurons on current hardware using a variant of the Barnes–Hut algorithm. They demonstrate good scalability and prove a runtime complexity of O(n log2 n). In this comment paper, we show that with careful consideration of the algorithm and a rigorous proof, the theoretical runtime can even be classified as O(n log n). © 2022, CC BY-NC-ND.

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of Engineering & Technology 2023.

关键词： Support vector machines

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Approximation of the Objective Functional in a Partially Defined Optimization Problem 3

Approximation of the Objective Functional in a Partially Def...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Kalinin, Yevhen Kuchuk, Nina Lysytsia, Dmytro National University of Life and Environmental Sciences of Ukraine Tractors Cars and Bioenergy Resources Department Kyiv Ukraine National Technical University «kharkiv Polytechnic Institute» Department of Computer Engineering and Programming Kharkiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

The reliable operation of today's complex technical systems often relies on remote software solutions for predicting their performance. To solve these tasks, client-server architectures, based on the database server, used to store the obtained data, as well as server-based data analyzers are taken advantage of. Due to the increasing complexity of tasks of diagnosing the state of complex technical systems, associated with the generation of higher volumes of data for assessing the current state of the diagnostic objects, the use of classical relational storage resulted in a significant increase in the requirements for cluster architectures. With the increasing use of technological solutions based on the 'Big Data' architecture, there is a contradiction associated with the need to store large amounts of unstructured data for further structuring by methods of database schema development. The mission of Data Mining is the implementation of search operations applied to the laws of behavior and overall functioning of the system under study, consisting of numerical data. An obligatory condition that arises when using Data Mining methodologies is to interpret the resulting patterns formed as a consequence of determining the practical utility of the data. In this regard, there is a need to develop a method for optimizing large amounts of data, especially in partially defined tasks, allowing the distribution of the readings of the state of complex technical systems. Thus, the paper considers the problem of objective function approximation by the linear functional in a partially defined optimization problem, when the objective function is partially defined by comparing its values on some set of vectors from the acceptance region. Necessary and sufficient conditions for the existence of the approximating linear functional and the method of recovery of its coefficients through a linear correction procedure are formulated. © 2022 IEEE.

关键词： Data mining

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Estimating Breathing Levels of Asthma Patients with Artificial Intelligence Methods

Estimating Breathing Levels of Asthma Patients with Artifici...

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International Conference on Intelligent and Fuzzy Systems, INFUS 2020

作者： Yüksel, Asım Sinan Tan, Fatma Gülşah Computer Engineering Department Süleyman Demirel University Isparta Turkey Vocational School Computer Programming Department Manisa Celal Bayar University Manisa Turkey

ISBN: (纸本)9783030511555

Pollen contains highly allergic proteins. One of the major causes of allergic diseases is the pollen in the air we breathe. Asthma patients are known to show allergic reaction to pollens. Therefore, they need to be more careful and avoid the factors that trigger asthma. In this study, the first step was taken to develop an artificial-intelligence-based decision support system to improve the quality of life of asthma patients. Finding the ratio of pollen in nature is a long process, and it is measured by using different instruments and hours of calculations in laboratories. In this study, Adaptive Network-Based Fuzzy Extraction System (ANFIS) and normalization methods were applied to meteorological data to estimate the breathing levels of asthma patients according to the amount of pollen in the air. The data were tested via the Artificial Neural Networks method, and it was found that the model produced better results that are very close to real values when compared to the results in ANFIS. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision support systems

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WIP: An Engaging Undergraduate Intro to Model Checking in Software Engineering Using TLA+

arXiv

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arXiv 2024年

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Software and Systems Laboratory Department of Computer Science Loyola University Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one’s undergraduate studies, (3) demonstrate how to address successive "failures" through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and

关键词： Students

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Research of Neural Network Methods of Visual Defectoscopy of Metal Structures

Research of Neural Network Methods of Visual Defectoscopy of...

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2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Chernikov, Alexander Smirnova, Elena Zhavoronkov, Oleg Peter the Great St. Petersburg Polytechnic University Higher School of Automation and Robotics St. Petersburg Russia Saint Petersburg State University Department of System Programming St. Petersburg Russia Computer Vision Systems Llc St. Petersburg Russia

ISBN: (纸本)9781665475952

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation - 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526. © 2023 IEEE.

关键词： computer vision

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