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New Ecg Signal Compression Model Based on Set Theory Applied to Images

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Journal of Computer and Communications 2023年第8期11卷 29-43页

作者： Ivan Basile Kabiena eric michel deussom djomadji Emmanuel Tonye Department of Computer Engineering and Telecommunications National Advanced School of Engineering University of Douala Douala Cameroon Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Department of Electrical and Telecommunications Engineering National Advanced School of Engineering of Yaounde University of Yaounde I Yaounde Cameroon

Cardiovascular diseases are the origin of many causes of death worldwide. They impose on practitioners optimal diagnostic methods such as telemedicine in order to be able to quickly detect anomalies for daily care and monitoring of patients. The Electrocardiogram (ECG) is an examination that can detect abnormal functioning of the heart and generates a large number of digital data which can be stored or transmitted for further analysis. For storage or transmission purposes, one of the challenges is to reduce the space occupied by ECG signal and for that, it is important to offer more and more efficient algorithms capable of achieving high compression rates, while offering a good quality of reconstruction in a relatively short time. We propose in this paper a new ECG compression scheme that is based on a subset of signal splitting and 2D processing, the wavelet transform (DWT) and SPIHT coding which has proved their worth in the field of signal processing and compression. They are exploited for decorrelation and coding of the signal. The results obtained are significant and offer many perspectives.

关键词： Compression ECG DWT Sub-Set 2D

COST 231-Hata Propagation Model Optimization in 1800 MHz Band Based on Magnetic Optimization Algorithm: Application to the City of Limbé

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Journal of Computer and Communications 2023年第2期11卷 57-74页

作者： eric michel deussom djomadji Kabiena Ivan Basile Fobasso Segnou Thierry Tonye Emanuel Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Department of Electrical and Telecommunications Engineering National Advanced School of Engineering of Yaoundé University of Yaoundé I Yaoundé Cameroon Division of ICT National Advanced School of Post Telecommunication and ICT University of Yaoundé I Yaoundé Came-roon Department of Computer Engineering and Telecommunications National Advanced School of Engineering University of Douala Cameroon

Network planning is essential for the construction and the development of wireless networks. The network planning cannot be possible without an appropriate propagation model which in fact is its foundation. Initially used mainly for mobile radio networks, the optimization of propagation model is becoming essential for efficient deployment of the network in different types of environment, namely rural, suburban and urban especially with the emergence of concepts such as digital terrestrial television, smart cities, Internet of Things (IoT) with wide deployment for different use cases such as smart grid, smart metering of electricity, gas and water. In this paper we use an optimization algorithm that is inspired by the principles of magnetic field theory namely Magnetic Optimization Algorithm (MOA) to tune COST231-Hata propagation model. The dataset used is the result of drive tests carry out on field in the town of Limbe in Cameroon. We take into account the standard K-factor model and then use the MOA algorithm in order to set up a propagation model adapted to the physical environment of a town. The town of Limbe is used as an implementation case, but the proposed method can be used everywhere. The calculation of the root mean square error (RMSE) between the real data from the radio measurements and the prediction data obtained after the implementation of MOA allows the validation of the results. A comparative study between the value of the RMSE obtained by the new model and those obtained by the optimization using linear regression, by the standard COST231-Hata models, and the free space model is also done, this allows us to conclude that the new model obtained using MOA for the city of Limbe is better and more representative of this local environment than the standard COST231-Hata model. The new model obtained can be used for radio planning in the city of Limbé in Cameroon.

关键词： Radio Measurements Root Mean Square Error Magnetic Optimization Algorithm

Okumura Hata Propagation Model Optimization in 400 MHz Band Based on Differential Evolution Algorithm: Application to the City of Bertoua

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Journal of Computer and Communications 2023年第5期11卷 52-69页

作者： eric michel deussom djomadji Ivan Basile Kabiena Joel Thibaut Mandengue Felix Watching Emmanuel Tonye Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Division of ICT National Advanced School of Post Telecommunication and ICT University of Yaounde I Yaounde Cameroon Department of Computer Engineering and Telecommunications National Advanced School of Engineering University of Douala Douala Cameroon Department of Electrical and Telecommunications Engineering National Advanced School of Engineering of Yaounde University of Yaounde I Yaounde Cameroon

Propagation models are the foundation for radio planning in mobile networks. They are widely used during feasibility studies and initial network deployment, or during network extensions, particularly in new cities. They can be used to calculate the power of the signal received by a mobile terminal, evaluate the coverage radius, and calculate the number of cells required to cover a given area. This paper takes into account the standard k factors model and then uses the differential evolution algorithm to set up a propagation model adapted to the physical environment of the Cameroonian cities of Bertoua. Drive tests were made on the LTE TDD network in the city of Bertoua. Differential evolution algorithm is used as the optimization algorithm to deduct a propagation model which fits the environment of the considered town. The calculation of the root mean square error between the actual data from the drive tests and the prediction data from the implemented model allows the validation of the obtained results. A comparative study made between the RMSE value obtained by the new model and those obtained by the Okumura Hata and free space models, allowed us to conclude that the new model obtained is better and more representative of our local environment than the Okumura Hata currently used. The implementation shows that Differential evolution can perform well and solve this kind of optimization problem;the newly obtained models can be used for radio planning in the city of Bertoua in Cameroon.

关键词： Radio Measurements Root Mean Square Error Differential Evolution Algorithm

Dynamic Resource Allocation in LTE Radio Access Network Using Machine Learning Techniques

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Journal of Computer and Communications 2023年第6期11卷 73-93页

作者： eric michel deussom djomadji Ivan Basile Kabiena Valery Nkemeni Ayrton Garcia Belinga À Njere Michael Ekonde Sone Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Division of ICT National Advanced School of Post Telecommunication and ICT University of Yaounde I Yaounde Cameroon Department of Computer Engineering and Telecommunications National Advanced School of Engineering University of Douala Douala Cameroon Department of Computer Engineering Faculty of Engineering and Technology University of Buea Buea Cameroon

Current LTE networks are experiencing significant growth in the number of users worldwide. The use of data services for online browsing, e-learning, online meetings and initiatives such as smart cities means that subscribers stay connected for long periods, thereby saturating a number of signalling resources. One of such resources is the Radio Resource Connected (RRC) parameter, which is allocated to eNodeBs with the aim of limiting the number of connected simultaneously in the network. The fixed allocation of this parameter means that, depending on the traffic at different times of the day and the geographical position, some eNodeBs are saturated with RRC resources (overused) while others have unused RRC resources. However, as these resources are limited, there is the problem of their underutilization (non-optimal utilization of resources at the eNodeB level) due to static allocation (manual configuration of resources). The objective of this paper is to design an efficient machine learning model that will take as input some key performance indices (KPIs) like traffic data, RRC, simultaneous users, etc., for each eNodeB per hour and per day and accurately predict the number of needed RRC resources that will be dynamically allocated to them in order to avoid traffic and financial losses to the mobile network operator. To reach this target, three machine learning algorithms have been studied namely: linear regression, convolutional neural networks and long short-term memory (LSTM) to train three models and evaluate them. The model trained with the LSTM algorithm gave the best performance with 97% accuracy and was therefore implemented in the proposed solution for RRC resource allocation. An interconnection architecture is also proposed to embed the proposed solution into the Operation and maintenance network of a mobile network operator. In this way, the proposed solution can contribute to developing and expanding the concept of Self Organizing Network (SON) used in 4

关键词： RRC Resources 4G Network Linear Regression Convolutional Neural Networks Long Short-Term Memory Precision

Machine Learning-Based Approach for Identification of SIM Box Bypass Fraud in a Telecom Network Based on CDR Analysis: Case of a Fixed and Mobile Operator in Cameroon

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Journal of Computer and Communications 2023年第2期11卷 142-157页

作者： eric michel deussom djomadji Kabiena Ivan Basile Tchapga Tchito Christian Ferry Vaneck Kouam Djoko Michael Ekonde Sone Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Division of Information and Communications Technology National School of Posts Telecommunications and Information and Communication Technologies University of Yaoundé I Yaoundé Cameroon Department of Computer Engineering and Telecommunications National Advanced School of Engineering University of Douala Douala Cameroon

In the telecommunications sector, companies suffer serious damages due to fraud, especially in Africa. One of the main types of fraud is SIM box bypass fraud, which includes using SIM cards to divert incoming international calls from mobile operators creating massive losses of revenue. In order to provide a solution to these shortcomings that apply almost to all network operators, we developed intelligent algorithms that exploit huge amounts of data from mobile operators and that detect fraud by analyzing CDRs from voice calls. In this paper we used three classification techniques: Random Forest, Support Vector Machine (SVM) and XGBoost to detect this type of fraud;we compared the performance of these different algorithms to evaluate the model by using data collected from an operator’s network in Cameroon. The algorithm that produced a better performance was the Random Forest with 92% accuracy, so we effectuated the detection of existing fraudulent numbers on the telecommunications operator’s network.

关键词： CDR Fraud Detection Machine Learning Voice Calls

Design of a Neural Network Based Stable State Observer for Mimo Systems

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Journal of Computer and Communications 2023年第11期11卷 87-110页

作者： Jean Gutenbert Kenfack Wamba eric michel deussom djomadji Jean Claude Lionel Ng’anyogo Arsene Roger Bienvenu Fouba Alain Tiedeu Department of Electrical and Telecommunications Engineering National Advanced School of Engineering of Yaoundé University of Yaoundé I Yaoundé Cameroon Division of ICT National Advanced School of Post Telecommunication and ICT University of Yaounde I Yaoundé Cameroon Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon

MIMO (Multiple Input Multiple Output) is a key technology underpinning fourth generation or 4G networks. This technology allows 4G networks to increase throughput. However, the dynamics of the MIMO system are not under control due to the many uncertainties that destabilize the system. This work is therefore very relevant in the sense that an observer can be used to monitor the dynamics of such a system. This work presents a neuro-adaptive observer based on a radial basis function neural network for generic non-linear MIMO systems. Unlike most neuro-adaptive observers, the proposed observer uses a neural network that is non-linear in its parameters. It can therefore be applied to systems with high degrees of nonlinearity without any a priori knowledge of the system dynamics. Indeed, in addition to the fact that neural networks are very good nonlinear approximators, their adaptive behavior makes them powerful tools for observing the state without any a priori knowledge of the dynamics of the system. The learning rule of the neural network is an approach based on the modified backpropagation algorithm: A term has been added to guarantee the robustness of the observer. The proposed approach is not limited by a strong assumption. The stability of the neuro-adaptive observer is demonstrated by the direct Lyapunov method. Simulation results are presented in the context of MIMO signal transmission applied in LTE, to demonstrate the performance of our observer.

关键词： Stability Neural Network MIMO LTE Network Lyapunov Function

Demonstrating grating-based phase-contrast imaging of laser-driven shock waves

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Matter and Radiation at Extremes 2024年第4期9卷 90-97页

作者： Leonard Wegert Stephan Schreiner Constantin Rauch Bruno Albertazzi Paulina Bleuel eric Frojdh michel Koenig Veronika Ludwig Artem SMartynenko Pascal Meyer Aldo Mozzanica Michael Müller Paul Neumayer Markus Schneider Angelos Triantafyllidis Bernhard Zielbauer Gisela Anton Thilo michel Stefan Funk Plasma Physics Department GSI Helmholtzzentrum fur SchwerionenforschungPlanckstraBe 164291 DarmstadtGermany Erlangen Centre for Astroparticle Physics(ECAP) Friedrich-Alexander-Universität Erlangen-NurnbergNikolaus-Fiebiger-StraBe 291058 ErlangenGermany LULI-CNRS CEASorbonne UniversitésEcole PolytechniqueInstitut Polytechnique de ParisF-91120 Palaiseau CedexFrance Paul Scherrer Institut(Psi) Forschungsstrasse 1115232VilligenSwitzerland Karlsruhe Institute of Technology Institute of Microstructure TechnologyHermann-von-Helmholtz-Platz 176344 Eggenstein-LeopoldshafenGermany

Single-shot X-ray phase-contrast imaging is used to take high-resolution images of laser-driven strong shock *** a two-grating Talbot interferometer,we successfully acquire standard absorption,differential phase-contrast,and dark-field images of the shocked *** agreement is demonstrated between experimental data and the results of two-dimensional radiation hydrodynamics simulations of the laser-plasma *** main sources of image noise are identified through a thorough assessment of the interferometer’s *** acquired images demonstrate that grating-based phase-contrast imaging is a powerful diagnostic tool for high-energy-density *** addition,we make a novel attempt at using the dark-field image as a signal modality of Talbot interferometry to identify the microstructure of a foam target.

关键词： interaction shock phase

Propagation Model Optimization Based on Ion Motion Optimization Algorithm for Efficient Deployment of eLTE Network

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Journal of Computer and Communications 2022年第11期10卷 171-196页

作者： deussom djomadji eric michel Tsague Njatsa Austene Beldine Tonye Emmanuel Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Division of Information and Communications Technology NASPT University of Yaoundé I Yaoundé Cameroon Department of Electrical and Telecommunications University of Yaoundé I Yaoundé Cameroon

Propagation models are the foundation for radio planning in mobile networks. They are widely used during feasibility studies and initial network deployment, or during network extensions, particularly in new cities. They can be used to calculate the power of the signal received by a mobile terminal, evaluate the coverage radius, and calculate the number of cells required to cover a given area. This paper takes into account the standard K factors model and then uses the Ion motion optimization (IMO) algorithm to set up a propagation model adapted to the physical environment of each of the Cameroonian cities of Yaoundé and Bertoua for different frequencies and technologies. Drive tests were made on the CDMA network in the city of Yaoundé on one hand and on an LTE TDD network in the city of Bertoua on the other hand. IMO is used as the optimization algorithm to deduct a propagation model which fits the environment of the two considered towns. The calculation of the root-mean-square error (RMSE) between the actual data from the drive tests and the prediction data from the implemented model allows the validation of the obtained results. A comparative study made between the RMSE value obtained by the new model and those obtained by the Okumura-Hata and K factors standard models, allowed us to conclude that the new model obtained in each of these two cities is better and more representative of our local environment than the Okumura-Hata currently implemented. The implementation shows that IMO can perform well and solve this kind of optimization problem;the newly obtained models can be used for radio planning in the cities of Yaounde and Bertoua in Cameroon.

关键词： Drive Test IMO Propagation Models Root Mean Square Error

Klingsor Syndrome: An Observation in a Patient with Schizophrenia

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Open Journal of Urology 2024年第5期14卷 346-351页

作者： Mbuya Musapudi eric Ouake Hadidjatou michel Agounkpe Yevi Dodji Magloire Inès Hodonou Fred Martin Avakoudjo Josué Georges Dejinnin Department of Urology and Andrology Hubert Koutoukou Maga National Teaching Hospital Cotonou Benin Department of Surgery University Clinics of Lubumbashi Lubumbashi Democratic Republic of the Congo

Background: Klingsor syndrome refers to genital self-mutilation in man following delusional religious beliefs. Later, Schweitzer proposed expanding the term to include all psychotic disorders, drug and alcohol abuse. Apart from the noted hemorrhagic emergency and difficult surgical operation, there is a psychosocial impact, sexual and urinary complications (stenosis, urethral fistula) which make this pathology complex. Aim: The Aim of this study is to describe the clinical case of Klingsor syndrome and evaluate its management in light of the literature. Case Presentation: We report a rare case of genital self-mutilation in a 35-year-old man, non-compliant schizophrenic, received 04 days after the trauma and whose treatment consisted of remodeling of the penis stump and follow-up by psychiatrists. Conclusion: Klingsor syndrome is a rare but serious phenomenon. Its management remains complex, but it must be early and multidisciplinary.

关键词： Klingsor Syndrome Génital Self-Mutilation Schizophrenia