New Method for 3D Shape Retrieval

The recent technological progress in acquisition, modeling and processing of 3D data leads to the proliferation of a large number of 3D objects databases. Consequently, the techniques used for content based 3D retrieval has become necessary. In this paper, we introduce a new method for 3D objects recognition and retrieval by using a set of binary images CLI (Characteristic level images). We propose a 3D indexing and search approach based on the similarity between characteristic level images using Hu moments for it indexing. To measure the similarity between 3D objects we compute the Hausdorff distance between a vectors descriptor. The performance of this new approach is evaluated at set of 3D object of well known database, is NTU (National Taiwan University) database.Comment: 10 pages, 5 figures, publication pape

An Approach of Decision-Making Support Based on Collaborative Agents for a Large Distribution Sector

International audienceThis paper applies the multi-agent systems paradigm to collaborative coordination and negotiation in a global distribution supply chain. Multi-agent computational environments are suitable for a broad class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving contexts. An agent-based distributed architecture is proposed for better management of rush unexpected orders for which the quantity of product cannot be delivered partially or completely from the available inventory. This type of orders can be generated by unexpected swings in demand or unexpected exceptions (problem of production, problem of transportation, etc.). This paper proposes a first architecture and discusses an industrial case study

A collaborative decision-making approach for supply chain based on a multi-agent system

To improve the supply chain's performance under demand uncertainty and exceptions, various levels of collaboration techniques based on information sharing were set up in real supply chains (VMI, CPR, CPFR...). The main principle of these methods is that the retailers do not need to place orders because wholesalers use information centralization to decide when to replenish them. Although these techniques could be extended to a whole supply chain, current implementations only work between two business partners. With these techniques, companies electronically exchange a series of written comments and supporting data, which includes past sales trends, scheduled promotions, and forecasts. This allows participants to coordinate joint forecasting by focusing on differences in forecasts. But if the supply chain consists of autonomous enterprises, sharing information becomes a critical obstacle, since each independent actor is typically not willing to share with the other nodes its own strategic data (as inventory levels); That is why researchers proposed different methods and information systems to let the members of the supply chain collaborate without sharing all their confidential data and information. In this chapter we analyze some of the existing approaches and works and describe an agent-based distributed architecture for the decision-making process. The agents in this architecture use a set of negotiation protocols (such as Firm Heuristic, Recursive Heuristic, CPFR Negotiation Protocol) to collectively make decisions in a short time. The architecture has been validated on an industrial case study

Runtime Requirements Monitoring Framework for Adaptive e-Learning Systems

International audienceAs academic learners and companies are turning to e-learning courses to achieve their personal and professional goals, it becomes more and more important to handle service quality in this sector. Despite scientific research conducted to personalize the learning process and meet learner's requirements under adaptive e-learning systems, however, the specification and management of quality attribute is particularly challenging due to problems arising from environmental variability. In our view, a detailed and high-level specification of requirements supported through the whole system lifecycle is needed for a comprehensive management of adaptive e-learning systems, especially in continuously changing environmental conditions. In this paper, we propose a runtime requirements monitoring to check the conformity of adaptive e-learning systems to their requirements and ensure that the activities offered by these learning environments can achieve the desired learning outcomes. As a result, when deviations (i.e., not satisfied requirements) occur, they are identified and then notified during system operation. With our approach, the requirements are supported during the whole system lifecycle. First, we specify system's requirements in the form of a dynamic software product line. This specification applies a novel requirements engineering language that combines goal-driven requirements with features and claims and avoid the enumeration of all desired adaptation strategies (i.e. when an adaptation should be applied) at the design time. Second, the specification is automatically transformed into a constraint satisfaction problem that reduces the requirements monitoring into a constraint program at runtime

Distributed System based on Cloud Computing with Wireless Sensor Networks

The main aim of this work is to provide an architectural approach based on interoperable technology for communicating the Wireless Sensor Network (WSN) entities with end users using the Cloud Computing concept. Referring to the comparative survey carried out between Java RMI, CORBA and Web services, we opted for CORBA as middleware to interconnect the various components of our distributed system; this choice is mainly based on criteria of the performances and the integration possibility with different programming language. In this architecture, we also propose real-time monitoring services, data archiving, notification and other useful services to communicate with the Wireless Sensor Network in both directions

Digital Agriculture and Intelligent Farming Business Using Information and Communication Technology: A Survey

Adopting new information and communication technology (ICT) as a solution to achieve food security becomes more urgent than before, particularly with the demographical explosion. In this survey, we analyze the literature in the last decade to examine the existing fog/edge computing architectures adapted for the smart farming domain and identify the most relevant challenges resulting from the integration of IoT and fog/edge computing platforms. On the other hand, we describe the status of Blockchain usage in intelligent farming as well as the most challenges this promising topic is facing. The relevant recommendations and researches needed in Blockchain topic to enhance intelligent farming sustainability are also highlighted. It is found through the examination that the adoption of ICT in the various farming processes helps to increase productivity with low efforts and costs. Several challenges are faced when implementing such solutions, they are mainly related to the technological development, energy consumption, and the complexity of the environments where the solutions are implemented. Despite these constraints, it is certain that shortly several farming businesses will heavily invest to introduce more intelligence into their management methods. Furthermore, the use of sophisticated deep learning and Blockchain algorithms may contribute to the resolution of many recent farming issues