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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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Personalize Web Searching Strategies Classification and Comparison

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通讯和计算机（中英文版） 2016年第1期13卷 19-23页

作者： Mariya Savova Evtimova Ivan Momtchilov Momtchev Faculty of Computer Systems and Control Programming and Computer Technologies Department Technical University of SofiaSofia 1000 Bulgaria

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Comparative Study for Classification Methods to Predict and Detect Epilepsy Seizure 5

Comparative Study for Classification Methods to Predict and ...

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5th IEEE Middle East and Africa Conference on Biomedical Engineering, MECBME 2020

作者： El Halabi, Nashaat Abi Zeid Daou, Roy Achkar, Roger Hayek, Ali Boercsoek, Josef American University of Science and Technology Department of Computer and Communications Engineering Faculty of Engineering Beirut Lebanon Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon American University of Science and Technology Department of Computer and Communications Engineering Faculty of Engineering Beirut Lebanon Computer Science University of Kassel Department of Computer Architecture and System Programming Faculty of Electrical Engineering Germany Computer Science University of Kassel Department of Computer Architecture and System Programming Faculty of Electrical Engineering Germany

ISBN: (纸本)9781728123585

Epilepsy is a medical problem that tackles lots of patients. It limits the life activity of such patients due to the seizures that occur anytime and anywhere. Thus, creating a monitoring system that could make their life easier and allow them to perform daily life activities as safe as possible has been studied. This paper is a continuity for a project where a system monitors epileptic patients using a set of wearable sensors connected to several processing units, the main sensors are Electroencephalogram (EEG) for the electrical activity of the brain, electrocardiogram (ECG) for the electrical activity of the heart, and accelerometers to monitor the posture of the patient, features extracted from EEG and ECG signals are used for prediction/detection of seizures. Thus, the objective of this paper is to present a comparative study in order to choose the appropriate classification method for seizure prediction and detection. Five classification methods were studied: Decision Trees, Discriminant Analysis, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Ensemble Learning. For each of the classification methods, the accuracy, the specificity, the sensitivity, the precision, the false detection rate and the Fmeasure were studied and compared. The results for seizure prediction system show that the highest accuracy, specificity and F-Measure, and lowest false detection rate were achieved with Bagged Trees Ensemble Learning, the highest sensitivity and precision were achieved with Quadratic Support Vector Machine. However, for seizure detection system, the highest accuracy and F-Measure were achieved with Linear Support Vector, the highest sensitivity and specificity were achieved with Fine Gaussian Support Vector Machine, and the highest precision and lowest false detection rate were achieved with Subspace Discriminant Ensemble Learning. © 2020 IEEE.

关键词： Support vector machines

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Research on Building Scientific Data Ontology

Research on Building Scientific Data Ontology

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International Conference on Developments in eSystems Engineering (DESE)

作者： Mariana Goranova Bogdan Shishedjiev Juliana Georgieva Department of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria

When dealing with complex systems design and application the notion of ontologies helps the process of application integration. To solve the problems with discover, interpret and reuse data we have to recognize ontology as a concept that formalizes the management and integration of information, services and processes. In this paper we present our work towards the development and evaluation of scientific data ontology that helps the system integration architect achieve interoperability between different systems.

关键词： Ontologies OWL Semantics Data models Resource description framework Observatories Data visualization

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Parallel Multithreaded Medical Images Filtering

Parallel Multithreaded Medical Images Filtering

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Veska Gancheva Department of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria

ISBN: (纸本)9781665458429

The quality of medical images is paramount. Being of high grade, it guarantees the quality of medical diagnosis, treatment and quality of patient’s life through the means of health care or using automate intelligent systems for medical diagnosing, treatment and monitoring. The paper presents the computational challenges in medical images processing. The great challenges are to propose parallel computational models and parallel program implementations based on the algorithms for medical images filtering. Parallel computational model based on two-dimensional filters is designed. The proposed parallel model is verified by multithreaded parallel program implementation. An investigation of the efficiency of medical images filters based on parallel multithreaded program implementation, applying two-dimensional filters on a given list of compressed jpeg medical images and generating output jpeg images for each type of applied filter. The applied filters are Brightness Control, horizontal and vertical filter of Sobel, Laplace and Blur. A number of experiments have been carried out for the case of dataset consisted of 162 whole mount slide images of Breast Cancer (BCa) specimens scanned at 40x and various number of threads. Parallel performance parameters execution time and speedup are estimated experimentally. The performance estimation and scalability analyses show that the suggested model has good scalability.

关键词： Scientific computing Computational modeling Scalability Instruction sets Filtering algorithms Image filtering Medical diagnosis

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Input Data Time Range Impact on Forecast Quality Using Automated Procedures 11

Input Data Time Range Impact on Forecast Quality Using Autom...

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11th International Scientific Conference on computer Science, COMSCI 2023

作者： Koparanov, Kiril Andreev Antonova, Elena Ventseslavova Nakov, Ognyan Nakov Minkovska, Daniela Veleva Georgiev, Krasin Krasimirov Stoyanova, Lyudmila Yordanova Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd Sofia1000 Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Department of Computer Systems 8 Kliment Ohridski blvd Sofia1000 Bulgaria Technical University of Sofia Faculty of Transport Department of Air Transport 8 Kliment Ohridski blvd Sofia1000 Bulgaria

ISBN: (纸本)9798350325256

Easy access to time series forecasting provides a strong competitive advantage for any company or organization. As automated forecasting environments become more prevalent in the market, it is crucial to explore their capabilities and features to utilize them competently. This study demonstrates the influence of data coverage on prediction accuracy and validates the initial assumption. Based on the findings, recommendations have been presented to enhance the quality of predictive processes. © 2023 IEEE.

关键词： Forecasting

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Data Security and Validation Framework for a Scientific Data Processing SOA Based System

Data Security and Validation Framework for a Scientific Data...

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International Conference on Developments in eSystems Engineering (DESE)

作者： Veska Gancheva Programming and Computer Technologies Department Technical University of Sofia Sofia Bulgaria

A data security and validation framework of a SOA based system for management, storage, processing and visualization of data obtained from scientific experiments is proposed in this paper. The framework covers the three levels of data security: authorized user access, data encryption and data validation. To ensure authorized user access three access levels are provided: ownership, distribution rights and read rights. To ensure the data encryption an asymmetric 128-bit encrypting method based on public and private key is implemented. A universal approach for complete data validation has been suggested and implemented as web service. Data validation service allows validating the input data processed by each of the modules in the system. A declarative language defining the data validation and their interpretation based on XML standard is specified, by which precise rules in XML format are established and simultaneously with a library that supports this grammar is performed. In the language structures are included elements describing the data, rules and logic, which have to satisfy the input data. The actual definition is supported by a definition repository XML file and allows adding additional field types or complex validation logic as needed and easy modification of the validation rules.

关键词： XML Web services Encryption Data visualization

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A Generalization of σ-Permutability

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Communications in Mathematics and Statistics 2022年第3期10卷 565-579页

作者： Zhigang Wang Jin Guo Inna N.Safonova Alexander N.Skiba School of Science Hainan UniversityHaikou 570228HainanPeople’s Republic of China Department of Applied Mathematics and Computer Science Belarusian State University220030 MinskBelarus Department of Mathematics and Technologies of Programming Francisk Skorina Gomel State University246019 GomelBelarus

Throughout this paper,all groups are finite and G always denotes a finite group;σis some partition of the set of all primes P.A group G is said to beσ-primary if G is aπ-group for someπ∈σ.Aπ-semiprojector of G[29]is a subgroup H of G such that HN/N is a maximalπ-subgroup of G/N for all normal subgroups N of ***П⊆σ.Then we say thatχ={X_(1),...,X_(t)}is aП-covering subgroup system for a subgroup H in G if all members of the setχareσ-primary subgroups of G and for eachπ∈Пwithπ∩π(H)≠φthere are an index i and aπ-semiprojector U of H such that U≤X_(i).We study the embedding properties of subgroups H of G under the hypothesis that G has aП-covering subgroup systemχsuch that H permutes with X^(x)for all X∈χand x∈*** well-known results are generalized.

关键词： Finite group σ-nilpotent group П-semiprojector П-covering subgroup system σ-subnormal subgroup

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Automatic conversion of scientific data into canonical format

Automatic conversion of scientific data into canonical forma...

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Eurocon

作者： Mariana Goranova Bogdan Shishedjiev Juliana Georgieva Velin Achev Department of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria

The purpose of the automatic conversion of scientific data into canonical format is to provide a link between raw representation of data and database schemas. On the basis of these concepts Web services are developed for automatic XML description. They describe structurally and semantically scientific data and the conversion of the raw data layout description into canonical form based on data semantics. The canonical form looks like a relational data model where efficient methods for storage and retrieval of scientific data have been used. This paper describes the implementation of the converter compiler of raw scientific data layout description into canonical format. Using canonical XML form we have achieved better standardization of the input for data manipulation and visualization routines and minimization of their number.

关键词： Semantics Layout XML Data models Bridges Web services Particle measurements

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Knowledge Discovery Based on Data Analytics and Visualization Supporting Precision Medicine

Knowledge Discovery Based on Data Analytics and Visualizatio...

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International Conference on Mathematics and computers in Science and Engineering (MACISE)

作者： Veska Gancheva Department of Programming and Computer Technologies Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9781728166957

ISBN: (纸本)9781728166964

Major challenge in the analysis of clinical data and knowledge discovery is to suggest an integrated, advanced and efficient tools, methods and technologies for access and processing of progressively increasing amounts of data in multiple formats. The problem of adapting the personal treatment to a patient is extremely complex and the medical doctor should examine and analyze large amounts of various data of different type. A comprehensive system for precision medicine, which covers all phases of data discovery, data integration, data preprocessing, building models, data storage, data analysis and visualization can be very useful to scientists in support of precision medicine. The software system aims intelligent big genomic data management, analysis and visualization and allows scientists an easy, fast and flexible approach for data processing. They can choose the services they wish to be executed, use the available data sets in databases, or enter their own data to be processed.

关键词： Data visualization Bioinformatics Knowledge discovery Proteins Data analysis Medical diagnostic imaging Big Data

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