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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Kira Bobrovnikova Oleg Savenko Sergii Lysenko Ivan Hurman Department of Computer Engineering and Information Systems Khmelnitsky National University Khmelnitsky Ukraine Department of Computer Engineering and System Programming Khmelnitsky National University Khmelnitsky Ukraine

ISBN: (纸本)9798350333053

Today, the Internet of Things has been widely used and is becoming an increasingly vital part in various areas of human activity, which helps to effectively solve various real-life tasks and problems. The infrastructure of the Internet of Things includes a lot of heterogeneous devices with limited capacities, which makes it difficult to control them in order to detect cyberattacks. The increase in the number of attacks on the infrastructure of the Internet of Things indicates the relevance of developing new solutions for detecting attacks on the networks of the Internet of Things. One of the possible approaches to identify attacks is to analyze the physical parameters associated with IoT devices that describe the behavior of devices on the network, such as power consumption. Power analysis allows you to detect power-hungry attacks such as crypto mining and denial-of-service attacks. The paper proposes a new method for cyberattack detection in the infrastructure of the Internet of Things that is based on the analysis of energy consumption. In order to improve the accuracy of detecting cyberattacks, the approach also uses the analysis of the actions of the IoT software. The proposed approach makes it possible to detect attacks such as DoS/DDoS with high efficiency with a level of detection up to 99.95%.

关键词： Energy consumption Power demand Software Behavioral sciences Internet of Things Object recognition Data mining

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Food Resources in Food system Technology: Bifunctional Food system Technology Based on Pickering Emulsions 6

Food Resources in Food System Technology: Bifunctional Food ...

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6th Smart Cities Symposium, SCS 2022

作者： Potoroko, Irina Kadi, Ammar Paymulina, Anastasia Bagale, Uday Abotaleb, Mostafa El-Kenawy, El-Sayed M. Department of Food and Biotechnology South Ural State University Chelyabinsk454080 Russia Siberian Federal Scientific Center of Agro-Bio Technologies of the Russian Academy of Sciences Novosibirsk region Krasnoobsk Russia Department of System Programming South Ural State University Chelyabinsk454080 Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt

ISBN: (纸本)9781839538544

The development of domestically generated food additives based on eco-technologies with specified functional-technological and bioactive qualities is now a significant focus of contemporary study. Pickering emulsions are more stable both physically and chemically, making them a highly promising method of introducing biologically active chemicals into the body. The purpose of this research was to determine if ultrasound could be used to create a bioactive colloidal Pickering emulsion system using flax cellulose or brown algal polysaccharides as a stabilizer. Pickering emulsions stabilized with fucoidan, sodium alginate, or flax cellulose, based on a lipid fraction of sunflower oil and cinnamon oil blend, or a lipid fraction of linseed oil, were applied to the subjects, who were then subjected to ultrasound treatment at 630W/l for 16 min (4 min on, 3 min off) at a controlled temperature of 50 °C. The results obtained demonstrate the effectiveness of using ultrasonic exposure to create bioactive Pickering emulsion colloidal systems. Fucoidan stabilizes pickering emulsion, with the highest AOA values (5.120±0.005 DPPH, %) and a rise in AOA values in linseed oil-based emulsion samples from 30% to 100% in comparison to emulsion samples based on a blend of lipid phases. The viscoelastic characteristics of Pickering emulsions with various oil fractions vary dramatically for the integrated structure-forming components. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Flax

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Sinkhorn Transformations for Single-Query Postprocessing in Text-Video Retrieval

arXiv

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arXiv 2023年

作者： Yakovlev, Konstantin Polyakov, Gregory Alimova, Ilseyar Podolskiy, Alexander Bout, Andrey Nikolenko, Sergey Piontkovskaya, Irina Huawei Noah’s Ark Lab Moscow Russia Ivannikov Institute for System Programming of the RAS Moscow Russia St. Petersburg Department the Steklov Institute of Mathematics St. Petersburg Russia

A recent trend in multimodal retrieval is related to postprocessing test set results via the dual-softmax loss (DSL). While this approach can bring significant improvements, it usually presumes that an entire matrix of test samples is available as DSL input. This work introduces a new postprocessing approach based on Sinkhorn transformations that outperforms DSL. Further, we propose a new postprocessing setting that does not require access to multiple test queries. We show that our approach can significantly improve the results of state of the art models such as CLIP4Clip, BLIP, X-CLIP, and DRL, thus achieving a new state-of-the-art on several standard text-video retrieval datasets both with access to the entire test set and in the single-query setting. Copyright © 2023, The Authors. All rights reserved.

关键词： Information retrieval

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Design and Implementation of an Instrumented walking cane for Detection of Freezing of Gait 3

Design and Implementation of an Instrumented walking cane fo...

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3rd IEEE International Multidisciplinary Conference on Engineering Technology, IMCET 2021

作者： Haidar Ahmad, Joelle El-Asmar, Alain Abi Zeid Daou, Roy Hayek, Ali Boercsoek, Josef Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon MART Learning Education and Research Center Chananir Lebanon University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany

ISBN: (纸本)9781665405874

Independent mobility is an important feature of an individual's normal life and with the elderly population continually growing, assistive devices such as walkers and canes provide help and guidance to users. Freezing of Gait (FoG) is an episodic phenomenon that is a common symptom of an age-related disease known as Parkinson Disease (PD). This paper is headed toward implementing a detection, diagnosis and correction system for FoG episodes. The proposed cane will generate visual, auditory and tactile cues to help patients overcome this problem, therefore reducing fall risks. In addition, a vibrating calf cuff will be attached to the calf for muscle stimulation. A compatible android phone application is designed to display heart rate measurements of the patient as well as his exact location in case of fall detection. The system is considered to be an electrically safe, portable, comfortable and a low-cost device. The performance of this system is analyzed thoroughly and the accuracy of all methodologies is considered carefully and evaluated. The results have shown no faulty errors and good accuracy and detection percentages. © 2021 IEEE.

关键词： Diagnosis

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Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

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Computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

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Pulse DRFM Jamming Formation and Its Mathematical Simulation

Pulse DRFM Jamming Formation and Its Mathematical Simulation

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Ukrainian Microwave Week (UkrMW), IEEE

作者： Viacheslav P. Riabukha Andrii V. Semeniaka Yevhen A. Katiushyn Dmytro V. Atamanskiy department of system analysis modeling and programming Limited liability company “Radionix” Kyiv Ukraine Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

The paper describes the principles for formation of a simulated pulse DRFM jamming in response to a sounding linear frequency modulated (LFM) pulse, the technique and results of mathematical (simulation) modeling of s... 详细信息

ISBN: (纸本)9798350331530

关键词： Target tracking Frequency modulation Chirp modulation Radar Radar tracking Microwave theory and techniques Mathematical models

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Modelling the Process of Determining the Tourist Demand Based on Fishbein's Multi-Attribute Model 15

Modelling the Process of Determining the Tourist Demand Base...

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15th IEEE International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2020

作者： Hovorushchenko, Tetiana Glukhov, Vladyslav Hovorushchenko, Olha Computer Engineering and System Programming Department Khmelnytskyi Ukraine Khmelnytskyi Lyceum No. 17 Khmelnytskyi Ukraine

ISBN: (纸本)9781728174433

The purpose of this paper is automating the analysis of tourist demand by developing a web-service for surveying tourists (both real and potential) and for presenting the survey results in the form of determining the tourist demand. The model of the process of determining the tourist demand based on Fishbein's multi-attribute model has been developed. The most important attributes, by which tourists evaluate their travels, and the relative importance of such attributes are identified. Rules for translating the thoughts and ratings of the user into an acceptable for the developed model 7-point bipolar scale have been developed. The web-service, which provides automating the calculation of tourist attraction of different countries, has been developed. © 2020 IEEE.

关键词： Web services

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Understanding of Data De-identification: Issues of Relevance and Problems

Understanding of Data De-identification: Issues of Relevance...

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2021 International Conference on Information Science and Communications Technologies, ICISCT 2021

作者： Ganiev, Abdukhalil A. Kerimov, Kamil F. Azizova, Zarina I. Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Information Security Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of System and Application Programming Tashkent Uzbekistan

ISBN: (纸本)9781665432580

This paper presents the process of data anonymisation and de-identification, the use of de-identification techniques as a means of data protection, and analyses de-identification and their relevance to the tasks they perform. There is also understanding re-identification risks and reasons to attempt a re-identification attacks. In addition, it also focuses on the actuality of solving the problem of data anonymisation and the problems of its implementation. © 2021 IEEE.

关键词： Data privacy

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Forecasting and modeling on average rainwater and vapor pressure in Chelyabinsk Russia using deep learning models

Forecasting and modeling on average rainwater and vapor pres...

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6th Smart Cities Symposium (SCS 2022)

作者： M. Abotaleb T. Makarovskikh A. Ali Subhi H. Alkattan A.O. Adebayo Department of System Programming South Ural State University Chelyabinsk Russia University of Diyala Diyala Iraq Information Communication and Technology Department Lagos State University Lagos Nigeria

Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future performance of rainfall data and vapor in Chelyabinsk by using a machine learning technique. The data series is divided into a training set (60%) and a test set (40%) for model developing a validation purpose. We further developed deep learning models such as, LSTM, BILSTM, GRU and compared on the basis of ME, RMSE, MAE, MPE, MAPE, ACF1 on the training data set. For testing data set, we compared these deep learning models based on RMSE. LSTM model acts as a superior machine learning model over BILSTM and GRU in this data series. Forecasting performance of these three models significantly at par. This finding may be significant to build a strong literature of the Chelyabinsk weather's forecast, which can be helpful for policy makers and researchers. Also, we strongly believe that, this work could be used as a literature adaptation of machine learning technique for complex time series over statistical models.

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Design and Implementation of a Smart Human Posture Monitoring Device Using a Wearable Vest 7

Design and Implementation of a Smart Human Posture Monitorin...

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7th International Conference on Advances in Biomedical Engineering, ICABME 2023

作者： Daou, Roy Abi Zeid Geha, Elio Aoun, Youssef Hayek, Ali Boercsoek, Josef Olmedo, Jose Javier Serrano Université la Sagesse Biomedical Engineering Department Furn El Chebbak Beirut Lebanon Mart Learning Education and Research Center Chananir Lebanon Lebanese German University Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon University of Applied Science Hamm-Lippstadt Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 Hamm59063 Germany University of Kassel Faculty of Electrical Engineering /Computer Science Department of Computer Architecture and System Programming Germany Universidad Politecnica de Madrid Lab of Bioinstrumentation and Nanomedicine Centro de Tecnologia Biomedica Spain

ISBN: (纸本)9798350325850

Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pain may manifest suddenly in some cases, it often develops gradually and persists for weeks, and in untreated cases, it can linger for years. Hence, the utilization of assistive devices such as wearable posture-monitoring vests can offer valuable assistance and guidance to users. This research paper is dedicated to the development of a system for detecting, diagnosing, and correcting poor posture, specifically leaning posture. The vest is designed to provide users with visual, auditory, and tactile cues to help them address this issue, thereby reducing the risk associated with leaning. Additionally, an integrated electrical box has been designed to consolidate all components directly onto the main board in a secure enclosure. This box also displays the daily count of instances where the user has leaned. This system is characterized by its electrical safety, portability, compactness, comfort, and affordability. A comprehensive analysis of the system's performance has been conducted with a meticulous evaluation of accuracy. Each component of the system has undergone successful testing, and the system as a whole is currently in the testing phase. The results of these tests have indicated a lack of faulty errors and have demonstrated outstanding accuracy and detection rates. Over 100 individuals of varying ages, genders, and BMI categories were involved in testing, with each person wearing the device for an average of six hours. The accuracy rate achieved was 98.85%, with an average of 54.35 instances of poor posture detected per participant. © 2023 IEEE.

关键词： Wearable technology

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