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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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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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Advanced IOT Traffic Light Control system

Advanced IOT Traffic Light Control System

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

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

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.

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Investigation of a safety parameter observer for wireless communication

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International Journal of Circuits, systems and Signal Processing 2020年 14卷 1005-1005页

作者： Schwarz, Michael H. Gaus, Larissa Börcsök, Josef Dept. Computer architecture and System programming University Kassel Kassel Germany Dept. Computer architecture and system programming Universität Kassel Kassel Germany

This paper investigates the possibilities to monitor the degree of disturbances of a wireless communication and to use this information to calculate online the necessary safety parameters in order to estimate the probability of failure per hour (PFH) and the safety integrity level (SIL). Depending of the degree of disturbances, addition actions are performed with the intention of keeping the current safety level. A hardware set-up is introduced to get process data and to evaluate the results. © 2020, North Atlantic University Union NAUN. All rights reserved.

关键词： Hamming distance

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Machine Learning Model for Predicting Failures in the Context of Autonomous Vehicles

Machine Learning Model for Predicting Failures in the Contex...

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International Conference on system Reliability and Science (ICSRS)

作者： Abderrahim Krini Aymen Ouertani Habil. Josef Börcsök Engineering of Reliability and Quality Functional Safety Robert Bosch GmbH Schwäbisch Gmünd Germany Institute of Functional Safety & Cyber Security Baden-Wuerttemberg Cooperative State University Lörrach Germany Computer Architecture und System Programming University of Kassel Kassel Germany

In general, failure data is obtained in the automotive industry during the warranty period. If these contain the expression of a service life characteristic for each failure, statements can be made about the reliability and availability of the systems. For this purpose, estimation methods are used to adapt empirical lifetime distributions to theoretical lifetime distributions. By means of the distribution characteristics, a prognosis of the reliability and availability to be expected is also possible beyond the observation time. In addition to the data basis to be investigated, which is available completely in test bench and experimental trials or re-censored in the field, various methods can be used for estimation. In the past, several methods have been used, such as the estimators according to Eckel [1], Kaplan-Meier [2] or the estimators according to Pauli [3]. In general, a field failure is subject to several stresses, which can be described by expressions of several lifetime characteristics. For this application case, which occurs in the automotive industry, the known estimation methods, [1]–[3], cannot be used. In this paper, the necessity of multidimensional estimation methods will be introduced first. Then, a new estimation method for multidimensional metrics is presented. In a further step, mathematical proof is given that the new method can provide realistic results. Finally, two example data sets from bench testing and field are presented. Furthermore, some recommendations for the use of the new method are concretized in this context.

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Novel Approach of a Smart Medical Mirror system for Medical Applications 5

Novel Approach of a Smart Medical Mirror System for Medical ...

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

作者： Halaby, Shady Khoury, George Zeid Daou, Roy Abi Hayek, Ali Boercsoek, Josef Lebanese German University Biomedical Technologies Department Jounieh Lebanon Lebanese German University Biomedical Technologies Department Jounieh Lebanon Lebanese German University Biomedical Technologies Department Jounieh Lebanon University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany

ISBN: (纸本)9781728123585

Humans always face problems when it comes to medical check-up due to lack of time or laziness. However, lots of medical problems and fatal illnesses can be detected at earlier stages if the person is subject to continuous check-up. Hence, the idea of the proposed system is to design a tool enabling the measurement of the basic vital signs with the smallest effort possible from the person's side. Thus, this paper proposes a smart medical mirror system that acts as a normal mirror and also delivers the basic vital signs of the user such as the heart rate, SPO2, body temperature, and Body Mass Index (BMI). The system takes five seconds for initialization and starts the measurements and displays the results. The user will not lose time as this check-up can be performed every morning while the person is wearing his clothes and getting ready to start his daily activities. The system was tested by multiple users having different body statuses. The recorded values showed very small differences with the exact ones. At the end, the system was able to meet the user specifications concerning its portability, sensitivity, accuracy and, most importantly, its low cost. © 2020 IEEE.

关键词： Mirrors

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Improvement and verification methods for components/systems in automobile applications in the field of reliability forecasting with respect to one and two dimensions of stress factors 30

Improvement and verification methods for components/systems ...

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30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM15 2020

作者： Krini, Abderrahim Börcsök, Josef Engineering of Remanufacturing and Quality Robert Bosch GmbH Schwäbisch Gmünd Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (纸本)9789811485930

The details of future failures of systems that are serially produced are important for the remanufacturing departments to frame an optimal strategy for the post series supply. The existing one-dimensional and two-dimensional reliability prediction models predict field failures as a function of time based on the stress which the components/systems experience in the field until failure. In day-to-day situations the failure forecasts depend on many external factors like registration delay, which is the delay between the production of a system and its registration in market, reporting delay, which is the delay between the field failure and its reporting time, the export of vehicles to other countries or permanent damage caused to the vehicles. The improvement procedures are integrated into the existing reliability forecast models to reduce the incompleteness of the warranty data due to the influence of external factors using MATLAB. The verification process is to compare the forecasted field failures by the existing models with the actual field failures. The prognosis is carried out based on different failures data sets. With the help of sales data from Original Equipment Manufacturers, the forecasted failures Year to Date are verified. A validation of the results is carried out to check the impact of the influencing factors. © ESREL2020-PSAM15 *** by Research Publishing, Singapore.

关键词： Forecasting

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Reliability Forecasting for Components/systems with respect to 1-, 2- And 3- Dimensions of Stress Factors 30

Reliability Forecasting for Components/Systems with respect ...

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30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020

作者： Krini, Abderrahim B rcs k, Josef Engineering of Remanufacturing and Quality Robert Bosch GmbH Schw bisch Gm nd Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (纸本)9789811485930

Remanufacturing, a popular term in the automotive industry, helps to reduce the need for raw materials, increase profitability, is an effective solution to the challenges of postal items and also benefits the environment. For the remanufacturing department, the reliability and failure rate of serial products is particularly important, and therefore the accurate prediction of failure rates is also important. It must be ensured that the product meets its reliability requirements. Existing one, two and three dimensional reliability prediction models predict field failures as a function of time, based on the stress experienced by the components/systems in the field until failure. The existing models have been extended to include the parameters that allow us to predict the reliability of refurbished systems. Improvements such as registration delays, reporting delays and the corrected candidate calculation, which deals with whether the product is still within the warranty period after the observation period, are present in the models and are applied to the systems. This reduces the incompleteness of warranty data due to the influence of external factors with MATLAB. The reliability of systems can be predicted with the lifetime prediction and further conclusions can be drawn for future development. In the verification process, the predicted field failures of the models are compared with the real field failures. ©ESREL2020-PSAM15 Organizers.

关键词： Failure rate

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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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Improvement approaches in the field of reliability forecasting for components/systems in automobile applications with respect of multivariate stress factors 29

Improvement approaches in the field of reliability forecasti...

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29th European Safety and Reliability Conference, ESREL 2019

ISBN: (纸本)9789811127243

To remanufacture automobile systems, it is important to understand the future failure rate of the serially produced systems. In addition, remanufacturing departments need the information about the number of cores to remanufacture, the condition of these cores, as well as the number of replacement systems the market needs. Based on the existing univariate, bivariate and multivariate models a new improved forecasting model is developed, which considers practical factors like export of the vehicle to other countries, damage of the entire vehicle, reporting delay between production and in-market time or between vehicle failure and failure reporting time. This paper presents all necessary tools to achieve the improvement and its implementation in MATLAB. Copyright © 2019 European Safety and Reliability Association.

关键词： Commerce

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