Data mining techniques on satellite images for discovery of risk areas

The high rates of cholera epidemic mortality in less developed countries is a challenge for health fa- cilities to which it is necessary to equip itself with the epidemiological surveillance. To strengthen the capacity of epidemiological surveillance, this paper focuses on remote sensing satellite data processing using data mining methods to discover risk areas of the epidemic disease by connecting the environ- ment, climate and health. These satellite data are combined with field data collected during the same set of periods in order to explain and deduct the causes of the epidemic evolution from one period to another in relation to the environment. The existing technical (algorithms) for processing satellite im- ages are mature and efficient, so the challenge today is to provide the most suitable means allowing the best interpretation of obtained results. For that, we focus on supervised classification algorithm to process a set of satellite images from the same area but on different periods. A novel research method- ology (describing pre-treatment, data mining, and post-treatment) is proposed to ensure suitable means for transforming data, generating information and extracting knowledge. This methodology consists of six phases: (1.A) Acquisition of information from the field about epidemic, (1.B) Satellite data acquisition, (2) Selection and transformation of data (Data derived from images), (3) Remote sensing measurements, (4) Discretization of data, (5) Data treatment, and (6) Interpretation of results. The main contributions of the paper are: to establish the nature of links between the environment and the epidemic, and to highlight those risky environments when the public awareness of the problem and the prevention policies are absolutely necessary for mitigation of the propagation and emergence of the epidemic. This will allow national governments, local authorities and the public health officials to effective management according to risk areas. The case study concerns the knowledge discovery in databases related to risk areas of the cholera epidemic in Mopti region, Mali (West Africa). The results generate from data mining association rules indicate that the level of the Niger River in the wintering periods and some societal factors have an impact on the variation of cholera epidemic rate in Mopti town. More the river level is high, at 66% the rate of contamination is high

Integrating MDA and SOA for improving telemedicine services

Through telemedicine, the health sector has seized the opportunity offered by development of information and communications technology (ICT) such as the business or industrial sectors, but ICTs are constantly evolving. To benefit from technological progress it is necessary to adapt the computer applications to these technologies, however this operation is costly to health facilities especially in developing countries. In terms of scientific research, this observation explains the development of model-driven engineering of computer systems such as the Model Driven Architecture (MDA) approach. MDA is a computer design approach for the development of computer systems that considers separately the functional needs of technical needs of an application. MDA mainly uses the models and their transformations whose traces allow MDA to capitalize expertise in terms of technology and to ensure some rapid modernization of applications to new technologies which results in a significant productivity gain. Today there is a huge requirement worldwide in the interoperable services, in particular with regard to their valuable contribution to the collaboration ability of remote information technology systems. Service Oriented Architecture (SOA) is an interesting architectural pattern in which software components contribute to the collaboration and sharing of services. In this way, the principles of SOA are intended to ensure interoperability between heterogeneous and distributed applications. Web services are at the heart of SOA, which splits functions into different services, accessible over a computer network that enables users to associate and reuse them in the exploitation of applications. Health applications have a strong need to communicate with the remote institutions in order to provide the most relevant services to patients and to collaborate with other medical partners to solve complex tasks. For this purpose, the proposed research work shows how the paradigms of SOA and MDA can be configured to implement medical software applications on an e-health platform. The case study concerns the Telemedicine in French-speaking Africa (RAFT) project in which the joint use of MDA and SOA facilitates knowledge combination and reuse in the management of applications supporting a medical collaborative work environment

Deep convolution neural network for image recognition

During an epidemic crisis, medical image analysis namely microscopic analyses are made to confirm or not the existence of the epidemic pathogen in suspected cases. Pathogen are all infectious agents such as a virus, bacterium, protozoa, prion etc. However, there is often a lack of specialists in the handling of microscopes, hence allowing the need to make the microscopic analysis abroad. This results in a considerable loss of time and in the meantime, the epidemic continues to spread. To save time in the analysis of samples, we propose to make the future microscopes more intelligent so that they will be able to indicate by themselves the existence or not of the pathogen of an epidemic in a sample. To have a smart microscope, we propose a methodology based on efficient Convolution Neural Network (CNN) architecture in order to classify epidemic pathogen with five deep learning phases: (1) Training dataset of provided images (2) CNN Training (3) Testing data preparation (4) CNN generated model on testing data and finally (5) Evaluation of images classified. The resulted classification process can be integrated in a mobile computing solution on future microscopes. CNN can improve the accuracy in pathogens diagnosis that are focused on hand-tuned feature extraction implying some human mistakes. For our study, we consider cholera and malaria epidemics for microscopic images classification with a relevant CNN, respectively Vibrio cholerae images and Plasmodium falciparum images. Image classification is the task of taking an input image and outputting a class or a probability of classes that best describes the image. Interesting results have been obtained from the CNN model generated achieving the classification accuracy of 94%, with 200 Vibrio cholera images and 200 Plasmodium falciparum images for training dataset and 80 images for testing data. Although this document addresses the classification of epidemic pathogen images using a CNN model, the underlying principles apply to the other fields of science and technology, because of its performance and its capability to handle more layers than the previous traditional neural networks

Service-Oriented Computing for intelligent train maintenance

The purpose of this work is to apply the servicization of enterprise information systems in maintenance, particularly in the management of the maintenance process of the component parts of trains. Service Oriented Architecture (SOA) is an architectural approach that permits servicization since it provides a flexible set of design principles used during the modeling practices (abstraction and realization). With a view to supporting the model-driven engineering of software systems, Mode Driven Architecture (MDA) is a design approach delivering a set of guidelines for the configuring of specifications in systems development. Therefore, the combination of these two approaches can be fruitful to address the challenging issues the enterprise information system is facing today. Our study is based on a methodological approach using the MDA models for the automatic generation of web service. The case study concerns a Railways Maintenance Workshop (RMW) at Sidi Bel Abbes (Algeria). Finally, the information system for the management of maintenance of the component parts of passengers and baggage railcars, using the generated solution, is realized and deployed. This software helps to have better management of the RMW by the effective planning of interventions, improve performance by increasing reliability, traceability, and availability of the equipment (parts)

Software services for supporting remote crisis management

Crisis management specifies a series of functions or processes for the identification, analysis and forecasting of crisis issues, and the statement of specific ways that would enable an organization to prevent or cope with a crisis. There are some existing techniques for crisis management. However, to our knowledge none of them is focused on the integration of telemedicine acts especially during transportation phase and also between health structures for saving more lives. Therefore, we propose a novel methodological framework for remote crisis management with three main phases: (1) Crisis definition (2) Crisis Analysis and (3) Crisis Management. The Crisis Management phase is based on the organized collaboration of various acts of telemedicine: Teleconsultation, Teleexpertise, Telemonitoring, Teleassistance, and Medical regulation. Each act of tele- medicine provides services to others and can be represented in Software as a Service (SaaS). SaaS design principle considers a software application as a service from which we propose some collaborative services to solve complex crisis management problems. The case studied and modeled concerns the simulation exercise on the Tsunami crisis management in Cannes (France), especially during the transportation phase of patients to various health structures. The proposed methodology adds an additional layer in terms of remote collaboration and information management to improve the management of emergencies and safety, with a view for contributing to protect and save lives when minimizing damages. The expected benefits (main findings) for using the considered approach are not only to provide crisis managers with a relevant computerized decision support system, but also to minimize financial costs, reduce the response time and positively impact the crisis management

Review of AI‐based methods for chatter detection in machining based on bibliometric analysis

To improve the finish and efficiency of machining processes, researchers set out to develop techniques to detect, suppress, or avoid vibration chatter. This work involves tracing chatter detection techniques, from time–frequency signal processing methods (FFT, HHT, STFT, etc.), decomposition (WPD, EMD, VMD, etc.) to the combination with machine learning or deep learning models. A cartographic analysis was carried out to discover the limits of these different techniques and to propose possible solutions in perspective to detect chattering in the machining processes. The fact that human expert detects chatter using simple spectrograms is confronted with the variety of signal processing methods used in the literature and lead to possible optimal detecting techniques. For this purpose, the bibliometric tool R-Tool was used to facilitate a bibliometric analysis using specific means for quantitative bibliometric research and visualization. Data were collected from the Web of Science (WoS 2022) using particular queries on chatter detection. Most documents collected detect chatter with either transformation or decomposition techniques

Bases orthonormales et calcul ombral en analyse p-adique

Let p be a prime number, Zp the ring of the p-adic integers, Qp the field of the p-adic numbers and K a complete valued field, extension of Qp. Let C(Zp,K) be the Banach algebra of continuous functions from Zp to K equipped with the supremum norm. K. Conrad has given a q-analogue of Mahler's expansion for q 2 K, |q − 1| < 1. We use the techniques of umbral calculus to establish a bijective correspondence, on one hand: between a class of continuous functions which are orthonormal q-bases and a class of linear continuous operators which commute with 1 such that 1(f)(x) = f(x + 1); on the other hand between a class of orthogonal q-bases of C(Zp,K) and a class of linear continuous operators which commute with the Jackson q-derivation. We give a realization of the quantum plane and Weyl quantum algebra of two generators, in the form of concrete operators algebras. We do some calculus of norms of these operators and exhibit an interesting orthogonal family for the quantum Weyl algebra. We provide a necessary and sufficient conditions on the coefficients of the q-expansion for a continuous function to be strictly differentiable, first when q is not a root of unity and after when q is a primitive pN-th root of unity. As an application we give a q-expansion of the Volkenborn integral.Soient p un nombre premier, Zp l'anneau des entiers p-adiques, Qp le corps des nombres p-adiques et K un sur-corps valué complet de Qp. Soit C(Zp,K) l'algèbre de Banach des fonctions continues de Zp dans K munie de la norme de la convergence uniforme et soit q appartenant à K tel que Iq-1I<1. K. Conrad établit un q-analogue de la base de Mahler. A l'aide de ce dévelopement, utilisant les techniques de calcul ombral, nous établissons une correspondance bijective, d'un côté entre une classe de q-bases orthonormales de C(Zp,K) et une classe d'opérateurs commutant avec l'opérateur de translation r1 tel que r1(f)(x)=f(x+1) et une autre entre une classe de q-bases orthogonales de C(Zp,K) et une classe d'opérateurs commutant avec la q-dérivation de Jackson. Nous obtenons une réalisation du plan quantique et de l'algèbre de Weyl à deux générareurs sous forme concrète d'algèbres d'opérateurs. Nous faisons quelques calculs de normes de ces opérateurs et nous exhibons une famille orthogonale pour l'algèbre de Weyl quantique. Nous obtenons des conditions nécessaires et suffisantes sur les coefficients du développement de Conrad pour qu'une fonction continue soit strictement différentiable, d'abord lorsque q est non racine de l'unité, ensuite lorsque q est une racine primitive de l'unité d'ordre une puissance pN de p. Comme application nous donnons une q-version de l'intégrale de Volkenbor

Bases orthonormales et calcul ombral en analyse p-adique

Soient p un nombre premier, Zp l'anneau des entiers p-adiques, Qp le corps des nombres p-adiques et K un sur-corps valué complet de Qp. Soit C(Zp,K) l'algèbre de Banach des fonctions continues de Zp dans K munie de la norme de la convergence uniforme et soit q appartenant à K tel que Iq-1I<1. K. Conrad établit un q-analogue de la base de Mahler. A l'aide de ce dévelopement, utilisant les techniques de calcul ombral, nous établissons une correspondance bijective, d'un côté entre une classe de q-bases orthonormales de C(Zp,K) et une classe d'opérateurs commutant avec l'opérateur de translation r1 tel que r1(f)(x)=f(x+1) et une autre entre une classe de q-bases orthogonales de C(Zp,K) et une classe d'opérateurs commutant avec la q-dérivation de Jackson. Nous obtenons une réalisation du plan quantique et de l'algèbre de Weyl à deux générareurs sous forme concrète d'algèbres d'opérateurs. Nous faisons quelques calculs de normes de ces opérateurs et nous exhibons une famille orthogonale pour l'algèbre de Weyl quantique. Nous obtenons des conditions nécessaires et suffisantes sur les coefficients du développement de Conrad pour qu'une fonction continue soit strictement différentiable, d'abord lorsque q est non racine de l'unité, ensuite lorsque q est une racine primitive de l'unité d'ordre une puissance pN de p. Comme application nous donnons une q-version de l'intégrale de VolkenbornCLERMONT FD-BCIU Sci.et Tech. (630142101) / SudocSudocFranceF

A Recommender System Based on Multi-Criteria Aggregation

Recommender systems aim to support decision-makers by providing decision advice. We review briefly tools of Multi-Criteria Decision Analysis MCDA, including aggregation operators, that could be the basis for a recommender system. Then we develop a multi-criteria recommender system, STROMa SysTem of RecOmmendation Multi-criteria, to support decisions by aggregating measures of performance contained in a performance matrix. The system makes inferences about preferences using a partial order on criteria input by the decision-maker. To determine a total ordering of the alternatives, STROMa uses a multi-criteria aggregation operator, the Choquet integral of a fuzzy measure. Thus, recommendations are calculated using partial preferences provided by the decision maker and updated by the system. An integrated web platform is under development