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4th International Conference on Advances in Biomedical Engineering, ICABME 2017

作者： Daou, Roy Abi Zeid Maalouf, Frederic Geagea, Christian Hayek, Ali Boercsoek, Josef Lebanese German University Faculty of Public Health Biomedical Technologies Department Sahel-Alma Lebanon MART Learning Education and Research Center Chananiir Lebanon Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (纸本)9781538616420

This paper deals with the Sudden Infant Death Syndrome (SIDS) problem. The main objective is to limit it by controlling the main reasons that may lead to it. Sudden infant death syndrome is the death without specific reason of a healthy newborn, usually during sleep. Although the causes are unknown, SIDS may be related to abnormalities in the infant's brain that controls breathing and arousal from sleep. Researchers have identified several measures that increase the risk on their babies. Thus, this paper proposes a low cost system that may help in monitoring the baby vital signs responsible for the SIDS and sending notifications to parents when abnormalities are encountered. The system is based on a microcontroller that regroups all sensors' outputs and a mobile application that displays these values, controls the video coming from a camera and send notifications in case of abnormal signals. The system was tested over 10 newborns (between 1 month and 2 years) over 3 weeks and the alarms were going well. © 2017 IEEE.

关键词： Alarm systems

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Automated System for Freight Transportation Optimization on the Transport Network

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Periodica Polytechnica Transportation Engineering 2023年第4期51卷 386-393页

作者： Dekhtyaruk, Mykola Department of Information Technologies and Programming Institute of Computer Technologies Open International University of Human Development "Ukraine" 23 Lvivska Str. Kyiv03115 Ukraine

An automated system for freight traffic optimization on a transport network has been developed, which is realized in the form of a complex computer program with application of the visual design environment of Embarcadero RAD Studio. The program complex consists of the main form from which two subprograms are loaded. The search of optimum routes performed by the routing optimization subprogram is used at transportations of freight on the set transport network based on different schemes (from one vertex (the supplier) to all other vertices (consumers), serially - from each vertex to all other vertices, and from two (or several) set of vertices to all other vertices). Freight delivery between the supply and consumption points was optimized by means of the freight transportation optimization subprogram, taking into account the restrictions on the volume of freight at the points of departure and destination. © 2023 Budapest University of Technology and Economics. All rights reserved.

关键词： Freight transportation

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Artificial Intelligence in Medicine for Chronic Disease Classification Using Machine Learning 16

Artificial Intelligence in Medicine for Chronic Disease Clas...

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16th IEEE International Conference on Application of Information and Communication technologies, AICT 2022

作者： Rakhimov, Mekhriddin Akhmadjonov, Ravshanjon Javliev, Shahzod Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Artificial Intelligence Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of System and Application Programming Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Computer System Tashkent Uzbekistan

ISBN: (纸本)9781665451628

Artificial intelligence (AI) systems in medicine are one of the most important modern trends in global healthcare. Artificial intelligence technologies are fundamentally changing the global healthcare system, making it possible to radically rebuild the system of medical diagnostics while reducing healthcare costs. AI is actively used in research to develop methods for diagnosing coronary heart disease (CHD). There are different types of CHD. Before treating a disease, it is necessary to determine which class of diseases it belongs to. Based on the feature space of the disease, it is possible to classify the type of CHD. Machine learning algorithms can solve this problem. The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve classification problems. The dataset is the more important part of the supervised machine learning algorithm for training. Gathering data is the most important step in solving any supervised machine learning problem. But choosing more important part from the collected data is one of the tasks to be solved. The main purpose of this study is to select more useful parametric attributes from the dataset to obtain a high F1-score of CHD classification. © 2022 IEEE.

关键词： Diseases

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Scaling of parallel multiple sequence alignment on the supercomputer JUQUEEN

Scaling of parallel multiple sequence alignment on the super...

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2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2013

作者： Borovska, Plamenka Gancheva, Veska Ko, Soon-Heum Computer Systems Department Technical University of Sofia 1000 Kliment Ohridski 8 boul. Bulgaria Programming and Computer Technologies Department Technical University of Sofia 1000 Kliment Ohridski 8 boul. Bulgaria National Supercomputing Center Linkoping University 58183 Linkoping Sweden

ISBN: (纸本)9781479914265

In this paper is proposed optimization, scaling, performance evaluation and profiling of parallel multiple sequence alignment based on ClustalW algorithm on the supercomputer BlueGene/Q, so-called JUQUEEN, for the case study of the influenza virus sequences. For this purpose a parallel I/O interface for simultaneous and independent access to single file collectively has been designed and verified on the basis of parallel program implementation on the supercomputer JUQUEEN. © 2013 IEEE.

关键词： Supercomputers

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Securing an IoT Medical System Using AI and a Unidirectional Network Device: Application to a Driver 11

Securing an IoT Medical System Using AI and a Unidirectional...

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11th International Conference on Electronics, Communications and Networks, CECNet 2021

作者： El Hajal, Georges Daou, Roy Abi Zeid Ducq, Yves Boercsoek, Josef Univ. Bordeaux IMS Laboratory France Biomedical Technologies Department Lebanese German University Lebanon MART Learning Education and Research Center Chananir Lebanon University of Kassel Institute for Computer Architecture and System Programming Germany

ISBN: (纸本)9781643682402

Security in systems and networks has always been a major issue for IT administrators. When it comes to medical applications, this concern is much more important due to the sensitivity of data and the risks that may be caused due to alteration or falsification of such critical information. The proposed paper presents a solution to assure the best security possible in such an environment. Thus, based on an application that monitors a driver's health while driving his car, a data diode will be implemented in order to assure security of the system by forcing unidirectional flow of network data to the healthcare provider side. Added to that, an AI-based program will be developed to verify the confidentiality, the integrity and the availability of the exchanged data and to check the patient health for abnormalities. Every sub-part of the system has been tested separately and results have shown that falsified data has been filtered out of the received end, e.g. the healthcare provider side. © 2022 The authors and IOS Press.

关键词： Medical applications

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ON A UNIQUE TWO-DIMENSIONAL INTEGRAL OPERATOR HOMOGENEOUS WITH RESPECT TO ALL ORIENTATION PRESERVING LINEAR TRANSFORMATIONS

arXiv

引用

arXiv 2025年

作者： Avetisyan, Zhirayr Karapetyants, Alexey Mirotin, Adolf Department of Mathematics: Analysis Logic and Discrete Mathematics University of Ghent Krijgslaan 281 Building S8 GhentB 9000 Belgium Regional Mathematical Center Southern Federal University Rostov-on-Don344090 Russia Institute of Mathematics Mechanics and Computer Sciences Regional Mathematical Center Southern Federal University Rostov-on-Don344090 Russia Department of Mathematics and Programming Technologies Francisk Skorina Gomel State University Gomel246019 Belarus

In this paper, we consider a two-dimensional operator with an antisymmetric integral kernel, recently introduced by Z. Avetisyan and A. Karapetyants in connection to the study of general homogeneous operators. This is the unique two-dimensional operator that has an antisymmetric kernel homogeneous with respect to all orientation-preserving linear transformations of the plane. It is shown that the operator under consideration interacts naturally, both in Cartesian and polar coordinates, with projective tensor products of some classical functional spaces, such as Lebesgue, Hardy, and Hölder spaces;conditions for their boundedness as operators acting from these spaces to Banach lattices of measurable functions and estimates of their norms are *** Codes 44A05, 44A15 Copyright © 2025, The Authors. All rights reserved.

关键词： Linear transformations

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Univariate & Multivariate Forecasting of Time Series Through a Contemporary Manner

Univariate & Multivariate Forecasting of Time Series Through...

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International Conference on High Technology for Sustainable Development (HiTech)

作者： Kiril Koparanov Daniela Minkovska Elena Antonova Department of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria Department of Computer Systems Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350358100

ISBN: (纸本)9798350358117

Detailed forecasting of time series is one of the fields where the latest advancements in information technology make significant contributions. Operating with financial data poses noteworthy challenges owing to its inherent nature and substantial impact on economic dynamics within society. This study explores the utilization of automated tools as a set of resources for both unifactorial and multifactorial forecasting, drawing conclusions and providing recommendations.

关键词： Economics Accuracy Time series analysis Predictive models Data models Forecasting Sustainable development Information technology

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Hassenstein-Reichardt Detector Using Controllable Single Pulse Time-Delay Circuit for Neuromorphic Hardware

Hassenstein-Reichardt Detector Using Controllable Single Pul...

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computer Science (COMSCI), International Scientific Conference on

作者： Ianislav Trendafilov Veska Gancheva Neuromorphica Ltd. Sofia Bulgaria Department of Programming and Computer Technologies Faculty of Computer Systems and Technologies Technical University of Sofia 8 Kliment Ohridski blvd. Sofia Bulgaria

Inspired by the visual system of the fruit fly, we had created a generic building block for neuromorphic hardware that is vital for third generation neural networks. This enables time delay to be parametrized in a cheap and inexpensive way. The advantage of our proposal is the possibility of building and testing new networks using dynamicist approach in artificial intelligence.

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Advanced IOT Traffic Light Control System 5

Advanced IOT Traffic Light Control System

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5th International Conference on Advances in Computational Tools for Engineering Applications, ACTEA 2023

作者： Hamad, Martin Abou El Hajj, Antonio Daou, Roy Abi Zeid Hayek, Ali Haidar, Gaby Abou Lebanese German University Faculty of Public Health Biomedical Technologies Department Lebanon MART Learning Education and Research Center Lebanon University of Kassel Department of Computer Architecture and System Programming Kassel Germany American University of Science and Technology Engineering Faculty Zahle Lebanon

ISBN: (纸本)9798350309959

For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more and more critical, and if not treated smartly this issue will negatively affect drivers by wasting time and fuel gas while waiting for hours in lanes. This paper presents a new and smart way to mitigate this issue in an affordable cost, minimum processing power, and low power consumption. This concept takes into consideration the majority of the cases that may cause congestion and presents a smart and accurate outputs to ease traffic flow leading to the prediction of the peak hours of traffic congestion for smarter control. A model is designed to study the case of a four lanes crossroad with two traffic lights and two LCD monitors. The strategy in reading data is divided into two parts: real data from sensors and pre collected data from google maps to create a kind of a predicted pattern over a certain time interval. The responsiveness of the system is analyzed thoroughly, and the accuracy of all possible cases is carefully considered and evaluated. Each part of the system was tested alone, and the overall system is still in an ongoing testing phase. The results have shown minimum faulty errors and accepted outputs that can lead to safe traffic control decisions. Finally, integrating more IoT devices and sensors between V2V, V2P, V2I with the help of artificial intelligence will definitely optimize this system with higher accuracy. © 2023 IEEE.

关键词： Traffic congestion

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WAM Systems: Comparative Analysis of Information Support Quality

WAM Systems: Comparative Analysis of Information Support Qua...

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2020 IEEE International Conference on Problems of Infocommunications Science and Technology, PIC S and T 2020

作者： Obod, Ivan Svyd, Iryna Maltsev, Oleksandr Zavolodko, Ganna Leonov, Sergiy Kharkiv National University of Radio Electronics Dept. of Microprocessor Technologies and Systems Kharkiv Ukraine National Technical University khPI Dept. of Information Systems Kharkiv Ukraine National Technical University khPI Dept. of Computer Engineering and Programming Kharkiv Ukraine

ISBN: (纸本)9781728191775

The paper considers ways to improve the quality of information support for airspace control systems and air traffic control with the help of wide-area multi-position monitoring systems. A comparative analysis has shown that the accuracy of estimating air object coordinates by the wide area multilateration system under consideration is significantly higher than that provided by currently available wide area multilateration systems. It is shown that the introduction of active and passive methods for creating wide-area multi-position observation systems significantly broadens the number of available air object coordinate estimation techniques and, as a result, enhances the quality of information support by providing its users with the opportunity of choosing an optimal estimation method for various primary measurements of received signal parameters. Active wide area multilateration systems significantly expand the number of methods available for solving the problem of adequate information support to airspace control system users;use of secondary surveillance radar aircraft responders allows estimating air object coordinates by both single-position and multi-position method. © 2020 IEEE.

关键词： Air traffic control

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