Moulay Driss Rahmani

A new approach to build a geographical taxonomy of adjacency automatically using the latent semantic indexing method

In this paper, we introduce an approach for constructing a geographical taxonomy of adjacency for a country, to be used in reformulating spatial queries. The proposed approach uses the best-ranked documents retrieved by the search engine while submitting the spatial entity composed of a spatial relationship and a noun of a city A. Then, apply to it the Latent Semantic Indexing method to found the nearest cities Bi to A, and proceed to a step of validation of each link by verifying if A is also found in the results of the cities Bi. In our experiments, we constructed a geographical taxonomy of adjacency for Morocco. We varied the spatial relationship used in the step of documents retrieving to compare the results of the different spatial relationships, and we used google web services as a search engine to compare the results returned in every case. Then we used the constructed taxonomy in geographical query reformulation. We have used the Un-interpolated Average Precision (UAP) to compare the returned documents before and after reformulation. According to our results, we note that reformulating geographical queries based on our built taxonomy improves widely the precision of the queries.

Towards a Framework for Context-Aware Mobile Information Systems

Design and development of context-aware Information Systems (ISs) is particularly complex, owing to the increasing dependency of people on computing support for making simple decisions or performing their daily tasks. Thus, the need of designing more attractive, adaptable and proactive systems is persistent. In this paper, we present a state of the art of context-aware approaches that are compared and classified. Furthermore, this work tries to support the development of context-aware IS by proposing a context model and defining a modeling context-aware requirements at a suitable level of abstraction by goal-oriented method.

A Conceptual Architecture for a Cloud-Based Context-Aware Service Composition

In today’s ubiquitous environments, more and more companies use cloud computing services to achieve their everyday operations and processes. However, the development of these services is a tedious and time consuming task. Moreover, existing solutions rarely take into account the personalization and the adaptation of services to the context of their use. In this paper, we propose an architecture for context-aware service composition in cloud environments to address the challenges mentioned above. The architecture takes advantage of service composition as a way to create new composite services from a set of atomic or composite ones, causing the reduction of development efforts and time to market, and also, the introduction of context-awareness to manage the dynamics of ubiquitous environments.

Context Modeling and Metamodeling: A State of the Art

Due to advances in sensor technology, sensors are becoming more powerful, cheaper and smaller. This evolution generates big amounts of data, which may have no value unless we have the ability of analyzing, interpreting and understanding it. Context-awareness computing (collection, modeling, metamodeling, reasoning and distribution of context) plays a significant role in this challenge. This paper tries to contribute by analyzing, comparing and consolidating works in this sense especially in context modeling and metamodeling.

A modified full velocity difference model based on time to collision as a safely indicator for braking state

Car-following models play an important role in the field of road traffic system, and one of its important issues is the vehicle formation. To conduct the analysis of braking state vehicle formation, this paper introduces the concept of inverse of time to collision and gives a detailed analysis the optimal velocity (OV), the modified optimal velocity (MOV), the full velocity difference (FVD), and the modified full velocity difference (MFVD) models. In this paper, we proposed a modified car following model based on the Full Velocity Difference (FVD) model, with the new optimal velocity as function of spacing and relative speed which introduced the weighting factor that based on inverse time to collision. The modified full velocity difference shows that can simulate the motions of cars is better than the modified OV model.

Inspired from Ants Colony: Smart Routing Algorithm of Wireless Sensor Network

In brief, Wireless Sensor Networks (WSNs) are a set of limited power nodes, used for gathering the determined data of an area. Increasing the lifetime is the main challenge to optimize WSNs routing protocols, since the sensors’ energy in most cases is limited. In this respect, this article introduces a novel smart routing algorithm of wireless sensor networks, consisting of stable nodes randomly dispersed, and this approach is inspired from ant colonies. The proposed algorithm takes into consideration the distance between two nodes, the chosen path length and the nodes’ residual energy so as to update the choice probability of the next node among the neighbouring nodes, contrary to several routing algorithms; on the one hand, the nodes are aggregating data of their predecessors and sending to all to their successors; on the other hand, the source is almost always changed in each iteration. Consequently, the energy consumption is balanced between the nodes. Hence, the network lifetime will be increased. Detailed descriptions and a set of simulation using Matlab is provided to measure the network lifetime and the energy consumed by nodes of the proposed approach are presented. The replications’ consequences of simulations prove the success of our future routing algorithm (SRA).

Toward a Smart Tourism Recommender System: Applied to Tangier City

Context-awareness has captivated a lot of attention, especially in the field of mobile and pervasive computing. Indeed, an important demand for real-world location data within the virtual world is growing. Yet, user’s context is more than its location. Most information systems do not take into account the diversity of users’ need and preferences because of its complexity to manage. Context-Aware Systems (CAS) are self-adaptive. Thus, automating the development of such systems and the interpretation of user’s preferences is a real challenge. One way to achieve this challenge is by discovering knowledge for prediction regarding actions of users with the systems (their history and so on). In this article, we explore how context information can be exploit to create intelligent and adaptive recommender systems. It provides an overview of the multiform notion of context with a discussion of several context oriented approaches and systems, and illustrates the usage of such approaches in several application areas. In this paper, we present our vision of the notion of context through a context metamodel. We also present an effective tourist recommendation system that respect personal preferences and capture usage, personal, social and environmental contextual parameters. A case study applied has been conducted to Tangier, a Moroccan city where a new intelligent international city will be constructed for the next decade. The article concludes by discussing the challenges and future research directions for context-aware recommender systems.

C2IoT: A framework for Cloud-based Context-aware Internet of Things services for smart cities

Abstract The smart city vision was born by the integration of ICT in the day to day city management operations and citizens lives, owing to the need for novel and smart ways to manage the cities resources; making them more efficient, sustainable and transparent. However, the understanding of the crucial elements to this integration and how they can benefit from each other proves difficult and unclear. In this article, we investigate the intricate synergies between different technologies and paradigms involved in the smart city vision, to help design a robust framework, capable of handling the challenges impeding its successful implementation. To this end, we propose a context-aware centered approach to present a holistic view of a smart city as viewed from the different angles (Cloud, IoT, Big Data). We also propose a framework encompassing elements from the different enablers, leveraging their strengths to build and develop smart-x applications and services.

Study of Energy Consumption in Wireless Sensor Networks Using S-Rhombus, S-Square and S-Circle Deployment.

In this paper we have proposed three methods of static multi-hop routing, the nodes are scattered over the vertices of a 4 \(*\) 4 array. The distance between vertices at the beginning is 10 m, after it takes the following values: 20 m, 30 m, 40 m, 50 m, 60 m, 70 m, 80 m. These methods are called: S-Square, S-Rhombus and S-Circle. The simulation results show that the S-Square is better than S-Rhombus and that one is better than S-Circle.

A Novel Modeling based Agent Cellular Automata for Advanced Residential Mobility Applications

Nowadays, residential mobility (RM) is usually interconnected with other urban phenomena to give more realistic and effective to the simulation models in order to support urban planners and decision makers. Recent RM research works to describe models from a functional view; however researchers do less focus in providing software modeling of their RM applications. Based on this note, the article presents an agent cellular automata based modeling for advanced RM applications. The proposed modeling contains six models based on UML 2.0 diagrams which models parts of the system from different views. The work could be of interest for specialists (researchers, designers and developers) when modeling advanced RM applications.