Une approche centrée exigences pour la composition de services web

International audienceThis paper presents a requirement-centric approach for Web service composition which allows: (i) modeling users' requirements with the MAP formalism and specifying required services using an Intentional Service Model (ISM); (ii) discovering relevant Web services by querying the service search engine Service-Finder; (iii) selecting automatically relevant and high QoS services by applying Formal Concept Analysis (FCA); and (iv) generating automatically BPEL coordination processes by applying the model transformation technique. In this paper, we illustrate our approach with a conference arrangement application and we validate it empirically in terms of precision and recall on this application. MOTS-CLÉS : composition de services web, exigences des utilisateurs, QdS, AFC, transformation de modèles.Cet article présente une approche centrée exigences pour la composition de services web qui permet : (i) la modélisation des exigences des utilisateurs avec le formalisme la Carte et la spécification des services requis avec un modèle intentionnel de services (MIS) ; (ii) la découverte des services web pertinents en interrogeant le moteur de recherche de services Service-Finder ; (iii) la sélection automatique de services pertinents et de haute QdS par l'application de l'analyse formelle de concepts (AFC) ; et (iv) la génération automatique de processus de coordination BPEL par l'application de la technique de transformation de modèles. Dans cet article, nous illustrons notre approche par une application d'arrangement de conférences et nous la validons empiriquement en termes de précision et de rappel sur cette application

Selection of Composable Web Services Driven by User Requirements

International audienceBuilding a composite application based on Web services has become a real challenge regarding the large and diverse service space nowadays. Especially when considering the various functional and non-functional capabilities that Web services may afford and users may require. In this paper, we propose an approach for facilitating Web service selection according to user requirements. These requirements specify the needed functionality and expected QoS, as well as the composability between each pair of services. The originality of our approach is embodied in the use of Relational Concept Analysis (RCA), an extension of Formal Concept Analysis (FCA). Using RCA, we classify services by their calculated QoS levels and composability modes. We use a real case study of 901 services to show how to accomplish an efficient selection of services satisfying a specified set of functional and non-functional requirements

The role of the Notch pathway in healthy and osteoarthritic articular cartilage: from experimental models to ex vivo studies

Osteoarthritis is the most prevalent form of arthritis in the world. With the progressive ageing of the population, it is becoming a major public health problem. The involvement of certain signaling pathways, such as the Notch pathway, during cartilage pathology has been reported. In this review, we report on studies that investigated the expression pattern of the Notch family members in articular cartilage and the eventual involvement of this pathway in the modulation of the physiology and pathology of chondrocytes. Temporal and/or spatial modulation of this signaling pathway may help these cells to synthesize a new functional extracellular matrix and restore the functional properties of the articular cartilage

Microservices in IoT Security: Current Solutions, Research Challenges, and Future Directions

In recent years, the Internet of Things (IoT) technology has led to the emergence of multiple smart applications in different vital sectors including healthcare, education, agriculture, energy management, etc. IoT aims to interconnect several intelligent devices over the Internet such as sensors, monitoring systems, and smart appliances to control, store, exchange, and analyze collected data. The main issue in IoT environments is that they can present potential vulnerabilities to be illegally accessed by malicious users, which threatens the safety and privacy of gathered data. To face this problem, several recent works have been conducted using microservices-based architecture to minimize the security threats and attacks related to IoT data. By employing microservices, these works offer extensible, reusable, and reconfigurable security features. In this paper, we aim to provide a survey about microservices-based approaches for securing IoT applications. This survey will help practitioners understand ongoing challenges and explore new and promising research opportunities in the IoT security field. To the best of our knowledge, this paper constitutes the first survey that investigates the use of microservices technology for securing IoT applications

Solid pseudopapillary tumor of the pancreas: Ecadherin, β-catenin, CD99 new useful markers with characteristic expression (about two case reports)

Solid pseudopapillary neoplasm of the pancreas is a rare tumor that has favorable prognosis. It poses frequently diagnostic challenges. We describe two cases of solid pseudopapillary tumor of the pancreas managed in our department between 2007 and 2011. Two females have mean age of 36.5 years. Clinical presentation include: abdominal pain, bloating and palpable abdominal mass. Tumor is localized in the head of the pancreas in one case and in the tail in the other case. The mean size of the mass was 6 cm (range: 5 to 7 cm). Surgical treatment was performed in two cases. Histological examination confirms the diagnosis of solid pseudopapillary tumor of the pancreas. Immunohistochemical analysis was concordant to the literature data especially concerning CD99 which positivity was in dot, loss of positivity of E-cadherin and nuclear staining of β-catenin. CD10 and α-1-antitrypsin were also positive. One patient was dead 3 days postoperative and neither cancer recurrence nor distant metastases were detected on the follow up of the other. However, solid pseudo-papillary tumor of the pancreas has a distinctive histological appearance; some cases are problematic requiring the use of immunohistochemistry to distinguish it from other pancreatic neoplasm which prognosis is different

CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption

In the era of Industrial IoT (IIoT) and Industry 4.0, ensuring secure data transmission has become a critical concern. Among other data types, images are widely transmitted and utilized across various IIoT applications, ranging from sensor-generated visual data and real-time remote monitoring to quality control in production lines. The encryption of these images is essential for maintaining operational integrity, data confidentiality, and seamless integration with analytics platforms. This paper addresses these critical concerns by proposing a robust image encryption algorithm tailored for IIoT and Cyber-Physical Systems (CPS). The algorithm combines Rule-30 cellular automata with chaotic scrambling and substitution. The Rule 30 cellular automata serves as an efficient mechanism for generating pseudo-random sequences that enable fast encryption and decryption cycles suitable for real-time sensor data in industrial settings. Most importantly, it induces non-linearity in the encryption algorithm. Furthermore, to increase the chaotic range and keyspace of the algorithm, which is vital for security in distributed industrial networks, a hybrid chaotic map, i.e., logistic-sine map is utilized. Extensive security analysis has been carried out to validate the efficacy of the proposed algorithm. Results indicate that our algorithm achieves close-to-ideal values, with an entropy of 7.99 and a correlation of 0.002. This enhances the algorithm's resilience against potential cyber-attacks in the industrial domain

Non-Invasive Early Diagnosis of Obstructive Lung Diseases Leveraging Machine Learning Algorithms

Lungs are a vital human body organ, and different Obstructive Lung Diseases (OLD) such as asthma, bronchitis, or lung cancer are caused by shortcomings within the lungs. Therefore, early diagnosis of OLD is crucial for such patients suffering from OLD since, after early diagnosis, breathing exercises and medical precautions can effectively improve their health state. A secure non-invasive early diagnosis of OLD is a primordial need, and in this context, digital image processing supported by Artificial Intelligence (AI) techniques is reliable and widely used in the medical field, especially for improving early disease diagnosis. Hence, this article presents an AI-based non-invasive and secured diagnosis for OLD using physiological and iris features. This research work implements different machine-learning-based techniques which classify various subjects, which are healthy and effective patients. The iris features include gray-level run-length matrix-based features, gray-level co-occurrence matrix, and statistical features. These features are extracted from iris images. Additionally, ten different classifiers and voting techniques, including hard and soft voting, are implemented and tested, and their performances are evaluated using several parameters, which are precision, accuracy, specificity, F-score, and sensitivity. Based on the statistical analysis, it is concluded that the proposed approach offers promising techniques for the non-invasive early diagnosis of OLD with an accuracy of 97.6%. Keywords: Obstructive lung disease; non-invasive diagnosis; machine learning; physiological features; voting technique