The engineering of systems-of-systems (SoSs) is a critical issue that requires the definition of multiple viewpoints that are dedicated to various concerns of stakeholders. To address this challenge, this article contributes to the definition of a reusable framework handling the design of SoSs' architectures by adopting a conceptual model of architecture framework ‘ISO42010.' The proposed framework extends this standard by using well-defined software development processes to identify and implement the different architectural viewpoints. Besides, these processes are used in a way to take advantage of managing a set of diagrams given by a UML profile, and then, to verify that the parts of the architecture form a consistent whole. In this context, the authors define four main viewpoints dedicated to the various stakeholders and which are essential to allow them to implement different SoSs. To guide the coordination of the development tasks, this framework provides again a development processes model that allows the stakeholders to explicitly design the viewpoint they want using an SoS-UML profile.
Forest fires cause significant human losses and natural damage and threaten the biodiversity on our planet. Several researchers have studied the potential of wireless sensor networks (WSNs) to manage a forested area and have proven the real potential of this paradigm. Such systems generate a large amount of heterogeneous data in a short time, which may lead to network congestion and delay in data transmission. Processing such data in a short time frame is challenging for a traditional WSN. This article presents a multi-layered architecture for wildfire prevention, detection, and intervention based on WSN, IoT, cloud, and fog computing technologies. The proposed architecture is validated using the iFogSim simulation tool. Two models are compared, cloud-only and fog-cloud-based scenarios. The experimental results show that the cloud-fog model minimizes latency and significantly reduces bandwidth consumption compared to the cloud-only model. To bring fast fire extinguishing ability to the system, the authors recommend the employment of drones equipped with fire extinguishing balls.
In the change management context, handling web service evolution is a challenging issue that aims to adapt deployed business processes to the perpetual changes occurring in enterprises environments. While existing approaches deal with the problem by focusing only on migratable instances, in this approach the authors propose a paradigm shift based on reconfigurable objects nets (RONs) to allow running service instances continuing their execution according to the evolved protocol specifications. In this approach, service protocols are modelled as petri nets, and changes are perceived as transformation rules. Further, reachability graphs are deployed for calculating migratable services instances after evolution. The conceived framework allows migrating active instances from the old protocol version to the evolved one. Web service protocol compatibility and replaceability aspects are addressed to distinguish migratable services instances from non-migratable ones. The authors illustrate their contribution and highlight advantages of using RONs through a real-world scenario related to the visa application service.
In this article, the authors treat the problem of container storage in the export direction, exactly in the containership loading process. The authors propose an approach to the problem of container placement in a containership by describing a decision model to help decision-makers (handling operators) to minimize the total container movement. This is obtained by using a multicriteria decision method AHP (analytic hierarchy process) to identify the best location of any container. Here, the authors consider four criteria: the container destination, the container weight, the departure date of the container, and the container type.
In this paper a novel collective method for DDoS detection is introduced. The method is distributed and implemented as a multi-agent system, and where local decision is based on an information-based heuristic, namely the entropy. According the calculated entropy a router exchange data with its neighbors aiming at collectively decide if a DDoS is ongoing or not. Most of the works of the literature that are based on the entropy they have used source addresses. The authors' method is based on the entropy of the distances traveled by the packets, so spoofing IP packets will be hard to perform by hackers. Each router combines its decision with those of its neighbors. Such a collective detection allows to apply defense against the attack despite the victim is out of service or cannot perform DDoS mitigation because the traffic is congested in its neighborhood. Conducted experiments using the platform OMNet++ show the potential of the new method for efficient collaborative and distributed detection and mitigation of DDoS attacks.
The increase use of social media allows unprecedented access to the behaviors, thoughts and feelings of individuals. We are interested here in the evolution of the emotional states of individuals captured through microblogging services such as Twitter. According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have committed suicide. Suicide is a major health concern worldwide. Our objective was to produce a new algorithm inspired by the spotted hyenas life (SHO) to detect person in suicide situation through the analysis of the twitter social network. So in this paper, we propose our approach to prediction suicidal tweets that can be published by people who suspect by their suicidal intentions. The proposed algorithm gives better performance compared to machine learning algorithms such as Naïve Bayes (NB), K-Nearest Neighbors (KNN), the Decision Tree (DT) and Support Vector Machine (SVM).
One of the goals that a company sets is the customer's satisfaction, which is a priority item. This clearly shows that the concerns of companies are focused on the customer and how this later could be served quickly. This work addresses the problem of optimization of the location of the distribution centers of a final product to customers, in a given region. The problem addressed in this paper is the location of the position (emplacement) to build a new distribution center (warehouses), taking into account the constraint of the distance between a distribution center and the various points of sale, and the constraint of the cost of land to build a distribution center. The optimization method used for this problem is the artificial bee colony algorithm (ABC), which was initially applied to numerical function optimization problems, inspired from the behavioral model bees during foraging.
Today, Mobile devices are receiving a wide recognition as a cutting-edge technology to assist teaching and learning strategies that harness individual learners’ context. As mobile technology is being resorted to in education systems, tools that help accessing information have changed. In similar fashion, concepts such as Mobile Learning have emerged. Mobile learning is widespread. Furthermore, students nowadays are able to learn regardless of time and place. This is accomplished by mobile technologies and wireless internet connections. Nevertheless, there are still critical challenges regarding this new learning paradigm. In fact, researchers are meeting a difficulty related to providing accessibility for all students. This paper introduces a New Cloud-based Adaptive Mobile Learning System using a Multi-agent paradigm. The system provides adaptive learning content and personalised to the learner’s style and preferences, to increase learner satisfaction and facilitate the learning process. The system was implemented and will be tested with students in a real educational environment.
In this paper, we propose an approach for the development of real time systems and applications with a formal support based on rewrite logic. The design pattern based development process permits to represent the real time design patterns according to the new profile “DPP-RTSA” and provide, so, a manner to correctly execution of the instantiation and the composition of patterns. The obtained design from the application of the proposed process is translated into formal specification in rewriting logic (RT-Maude). The execution of this RT-Maude specification serve to perform the verification of the modelled system proprieties.
Nowadays, with the massive development of technologies, documents are usually made, modified and published digitally. Unlike paper documents, digital documents are easily falsified, and it is difficult to verify the authenticity of these advanced documents in effective and fast ways. Mushaf Al-Quran is one of the most sensitive digital documents that deserves to be preserved due to the divine messages it carries. There is no way to maintain an immutable document, as today's blockchain technology has proven. Therefore, to take advantage of blockchain technology, this article presents a decentralized web application (dApp) to authenticate and verify the digital Mushaf based on smart contracts and the Ethereum network. The results show the efficiency of the blockchain technology in preserving immutable documents and its effectiveness in protecting and proving the authenticity of the digital Mushaf Al-Quran.
Automatic word sense disambiguation is a major challenge in natural language processing domain. In recent years, many of supervised and knowledge-based approaches were developed to solve this problem. The use of a sense inventory as a knowledge background to disambiguate words is a very useful technique rather than supervised approaches, with its need of a large pre-trained text corpus. This paper proposes a new approach to disambiguate words in text based on WordNet ontology, as sense inventory. The authors introduce a new technique called Gloss+ for word-sense disambiguation (WSD), which is based on using of the glosses of WordNet synonyms of the target word and the local context in which this word is used. This technique exploits a special behavior of the polysemous synsets. This behavior is detected during the disambiguation process and is used to improve the results obtained. In the experiment part, the authors compare the proposed approach to the methodologies which use synonyms or glosses only.
Agriculture is one of the most important economic sectors that societies have relied on since ancient times. The developing countries have reached now and late to smart agriculture, or precision agriculture, which uses the latest developments in the field of informatics and the internet of things. Many scientific projects have contributed to the development of smart agriculture, however, these projects focus on partial aspects without addressing other aspects. The application of the results of these projects becomes either a partial or a composite application of different heterogeneous works, which renders the desired results ineffective. Accordingly, this paper proposes a comprehensive reference regulatory approach for an advanced agricultural information system that accommodates the agricultural sector within its interconnected levels, public and private, and its various aspects (Monitor, Prediction, Optimization, Control) within a modern information technology vision based on the internet of things (IoT), artificial intelligence and optimization technologies.
In the face of tremendous demographic change, the number of vehicles on the roads is expanding as well. As a result, obtaining an empty parking space has become difficult, especially in certain areas or at important times. Supporting a solution in this direction allows for the resolution of a number of social, economic, and environmental issues. An efficient parking system is required to address some of these issues because it assists vehicle drivers in finding parking spaces as soon as possible, reducing driving time, better managing fuel consumption or energy provided by vehicles or road traffic, reducing air pollution, assisting specialized parking management services in selecting appropriate parking spaces, avoiding congestion, accidents, and ensuring road safety. This paper will examine a variety of recent studies employing on-street parking as a solution. Additionally, this research analyzes and discusses the advantages and drawbacks of many parking systems and provides opportunities for future research.
Understanding large amounts of online research works is extremely complex and time-consuming nowadays. The European and scientific commissions have recently highlighted the importance of implementing a research data management system in higher education institutes which combines technical as well as organizational solutions. In this paper, a semi-automated crowdsourcing approach is proposed to engage humans in the summarization task of scientific data. Semantic wiki technology is used to enable self-organization of crowdworkers and collaboration between them. In order to deal with these problems, the analysis and summarization of research findings is a task that can be outsourced to a crowd of researchers. A scientific data ontology and a crowdsourcing approach are proposed. They represent the main aspects of a collaborating research community that exploits data crowdsourcing to derive state of the art and/or survey reports. It is designed to fit the requirements for a quality report reflecting a timely tracking of research progress in a given domain
The goal of this paper is to design a hybrid architecture based on blockchain technology and smart contracts for healthcare applications. The problem that will be addressed is how to achieve a balance between the three standard concepts of the success of the health system, which are: “privacy,” “security,” and “efficiency and effectiveness of data usage.” The authors proposed a hybrid architecture for a more balanced approach by storing the light information in the blockchain (distributed and decentralized storage), except for large media files, which are in the central storage, which reduces the cost of storing large files and raises the protection of critical information. For demonstration, an application was developed based on the proposed architecture and using smart contracts with the help of an IPFS server as a document storage method, and using MetaMask application as an authentication tool.
Nowadays, with the massive development of technologies, documents are usually made, modified and published digitally. Unlike paper documents, digital documents are easily falsified, and it is difficult to verify the authenticity of these advanced documents in effective and fast ways. Mushaf Al-Quran is one of the most sensitive digital documents that deserves to be preserved due to the divine messages it carries. There is no way to maintain an immutable document, as today's blockchain technology has proven. Therefore, to take advantage of blockchain technology, this article presents a decentralized web application (dApp) to authenticate and verify the digital Mushaf based on smart contracts and the Ethereum network. The results show the efficiency of the blockchain technology in preserving immutable documents and its effectiveness in protecting and proving the authenticity of the digital Mushaf Al-Quran.
A mobile ad hoc network (MANET) is an autonomous system of mobile platforms called nodes which are free to move around randomly and without constraint. The Communication in this type of network is subject to many security issues such as jamming attacks, identifying the jamming attacks are challenging, which can increase the security threats, so security has now become a fundamental requirement. This threat is the reason to do this study aims to propose a new anti-jamming strategy for MANET. we have proposed an anti-jamming technique which combines two techniques (FHSS and DSSS). to estimate the efficiency and efficacy of jammers; to validate the security metrics of MANET; and to enhance the performance of our anti-jamming strategy. And in order to confirm the improvements made by our technique, we carried out a simulation using the NS3 network simulator.
Drug development is the hardest phase for the pharmaceutical industry because it is extremely costly and time consuming. Though, due to the growing demand to produce safe and innovative medicines faster and more cost-effectively, the scientific community changed its objective into enhancing the lead identification and the lead optimization at the early discovery phase. This could be achieved using recent intelligent technologies that allow virtual screening as well as quantitative structure-activity relationship (QSAR) modeling to define the possible relationships between chemical compounds and biological activities. Among recent technologies, artificial intelligence (AI) has been introduced as a powerful solution to address problems related to drug discovery and development. In particular, machine learning (ML) has been meaningfully instrumental in the production of new drug candidates. In this work, we review the fundamental principles of machine learning algorithms, study and discuss their application and current issues in drug development.
The social groups in social network applications in their current form have major problems related to structural inertia, group growth period, multilingualism, research and identification, group’s privacy settings, and authority of the Admin. This work uses the concept of ontology as a solution to these problems through an approach that makes the automatic creation and growth of social groups, the democratization of social groups by separating the concept of structure and the concept of views. In addition, this approach opens up a new type of social group «multilingual dynamics groups»; using the conceptual indexing of social groups to distinguish between the definition of the concept (Interest) and the definition of the term (multi-lingual). This work constitutes an important addition and contribution for renewing the concept of social groups through automatic growth, democracy (Self-management), dynamic (generalization, specialization, union, intersect and minus), semantic relationships, multiple languages, mono name ontological concept.
Nowadays, getting around has become an essential aspect of everyday life, whether it be public transport or personal vehicles, the vast network formed by these means of transport is immensely complex to manage. Unfortunately, this activity presents serious problems in most cities around the world. In this paper we upgrade traffic capacity of intersections using Genetic algorithm in order to decrease traffic congestion and crossing time of a road network. The main focus of this study is on improving the quality of solutions for the traffic light optimization problem. This proposition calculated and simulated through programming. As it shows, It improve results for solving the cycle traffic light problem (CTLP).
