Artificial Intelligence and Tutoring Systems

Journal of Visual Communication and Image Representation

It has come to our attention that Dr Herb Thompson, professor of Economics and Chair of the Economics department, devotes his first assignment to discovering exactly that. He asks his students to fill an on-line questionnaire on Learning Styles and to hand him the results of this questionnaire. We have asked him to write a piece on “learning styles” for our New Chalk Talk series. We have also asked him to share the results of the questionnaires which he has conducted over two semesters in his Microeconomics class. Dr Thompson has agreed to do this and for that we thank him very much. New Chalk Talk will devote the next two or three issues to this subject. They will appear starting next Tuesday.

Learning and Teaching Styles

On the Move to Meaningful Internet Systems

Energy load balancing is an essential issue in designing wireless sensor networks (WSNs). Clustering techniques are utilized as energy-efficient methods to balance the network energy and prolong its lifetime. In this article, we propose an improved soft- $k$ -means (IS- $k$ -means) clustering algorithm to balance the energy consumption of nodes in WSNs. First, we use the idea of clustering by fast search and find of density peaks (CFSFDPs) and kernel density estimation (KDE) to improve the selection of the initial cluster centers of the soft $k$ -means clustering algorithm. Then, we utilize the flexibility of the soft- $k$ -means and reassign member nodes considering their membership probabilities at the boundary of clusters to balance the number of nodes per cluster. Furthermore, the concept of multicluster heads is employed to balance the energy consumption within clusters. Extensive simulation results under different network scenarios demonstrate that for small-scale WSNs with single-hop transmission, the proposed algorithm can postpone the first node death, the half of nodes death, and the last node death on average when compared to various clustering algorithms from the literature.

Improved Soft- k -Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks

Energy efficiency is the most critical challenge in wireless sensor network The transmission energy is the most consuming task in sensor nodes, specifically in large distances Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN This approach is based on K-Means clustering algorithm and LEACH protocol The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime

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Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Networks

The extension of network life time is the major constraint in wireless sensor network. Routing protocols have a significant impact on the overall energy dissipation and lifespan of these networks. It is important to optimize the energy efficiency performance of communication protocols in order to enhance the system lifetime. Clustering technique is one of the most routing approaches used in WSN for energy efficiency. Several clustered routing protocols have been proposed. However, latterly, clustering algorithms have shown their limitation in extending the network duration. In this paper, we propose a new clustering approach MZ-SEP based on multiple triangle zones distribution and SEP protocol. The partition of sensor deployment field into multiple zones enhances the communication between cluster heads and their members. The obtained simulation results displayed the energy effectiveness of the proposed protocol and show that MZ-SEP approach outperforms SEP protocol by significantly improving the network lifetime and the stability period.

Multi-zonal approach clustering based on stable election protocol in heterogeneous wireless sensor networks

Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period.

/pdf/an-energy-efficient-clustering-protocol-using-fuzzy-logic-2l6zoerm13.pdf

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

In this paper, we present our approach in the field of case-based reasoning (CBR). This approach is based on the reuse of previous traces that are similar to the current situation in a dynamic way. Several approaches have been used in this area, but they suffer from some limitations in automated real-time management dynamic parameters. We propose a generic approach multi-agent multi-layer able to learn automatically from their experiences. This approach involves (1) the use of incremental dynamic case-based reasoning (IDCBR) able to study dynamic situations (recognition, prediction and learning situations); (2) the use of multi-agents system and (3) the use of the user traces. When interacting with the platform such as e-service, e-learning, e-business and e-commerce, every user leaves his or her traces in the machine. The traces are stored in database, this operation enriches collective past experiences. Via monitoring, comparing and analysing these traces, the system keeps a constant intelligent watch on the platform.

Intelligent dynamic case-based reasoning using multi-agents system in adaptive e-service, e-commerce and e-learning systems

In this paper we present our approach in the field of Intelligent Tutoring System (ITS), in fact the risk of dropping out for learners have emerged as crucial issues to be solved. So it is necessary to ensure an individualized and continuous learner's follow-up during learning process. Several research effort has been spent on the development of ITS. However the available literature does not generally concentrate on the individual realtime continuous follow up of learners. Our contribution in this field is to design and implement a computer system able to initiate learning and provide an individualized monitoring of learners. This approach involves 1) the use of Dynamic Case Based Reasoning to retrieve the past experiences that are similar to the learners' traces (traces in progress), and 2) the use of Multi-Agents System. Our Work focuses on the use of the learner traces. When interacting with the platform, every learner leaves his/her traces in the machine. The traces are stored in database, this operation enriches collective past experiences. Via monitoring, comparing and analyzing these traces, the system keeps a constant intelligent watch on the platform, and therefore it detects the difficulties hindering progress, and it avoids possible dropping out. The system can support any learning subject.

El Mokhtar En-Naimi

Papers

Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Networks

Multi-zonal approach clustering based on stable election protocol in heterogeneous wireless sensor networks

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Intelligent dynamic case-based reasoning using multi-agents system in adaptive e-service, e-commerce and e-learning systems

Intelligent tutoring systems founded of incremental dynamic case based reasoning and multi-agent systems (ITS-IDCBR-MAS)