Volume 1 Issue 2
Authors: M. Dyngeland; Ø. Bech; T. Kristensen
Abstract: In the Dynamic Content Management (DCM) system one focuses on removing the tight association between learning material to specific courses. In this system one defines a conceptual atomic unit of knowledge and builds the material by the organization of these knowledge elements from a repository. The system allows an educator to create an arbitrary collection of knowledge elements, tag them with meta-information as a single unit and link the unit with previously saved and similar aggregations. The DCM system uses idea of Concept Maps to model the relationships between the knowledge elements that can be created by the instructor or the educator. A pilot system has been implemented based on a client-server architecture. The server is programmed in Python and the client as a Java application made available through Java Web Start. In the paper we also present different design and implementation aspects of a future Multi-Agent System (MAS) based on the DCM model. The implementation of such a model of e-learning is based on JADE - a FIPA compliant platform.
Keywords: DCM; Knowledge Map; Learning Map; Student MAP; Client-Server; Python; Java; Multi-Agent Systems; FIPA; JADE
Authors: Miguel V. Correia; Paulo G. Costa; A. Paulo Moreira; Andry Maykol G. Pinto
Abstract: This paper revisits classical Lucas-Kanade (LK) and Horn-Schunck (HS) optical flow techniques. The aim is to provide a baseline for other researchers on these two timeless techniques. The formulations presented incorporate modern practices, namely multichannel, multi-resolution with refinement procedure (warping), non-quadratic penalisers and non-linear formulation of the brightness assumption. The experiments conducted demonstrate the performance enhancement that can be assigned to each modern practice. Thereby, the performance of the LK and HS is renewed in order to enable a fair comparison to other state-of-art techniques.
Keywords: Optical Flow; Lucas-Kanade; Horn-Schunck; Colour; Multi-Resolution
Authors: Yihe Liu; Quandeng Gou
Abstract: The RBAC (Role-Based Access Control) is an important information security model, and it is also hot issue in the domain of information security in recent years. A security model based on user group and role administration have been given out in the paper which is according to the practical application of the problem that is the actualization of role administration in our school informationization application system, and from the angle of guarantee the information security. The rules in the new model are reasonable and secure by analysis. It will play a positive role to construct information security model, and also to promote the general role administrative security model.
Keywords: Information Security Model; BLP Model; Biba Model; RBAC Model; Role Administration; User Group
Authors: Hiroshi Motoda; Kouzou Ohara; Masahiro Kimura; Kazumi Saito
Abstract: One of the interesting and important problems of information diffusion over a large social network is to identify an appropriate model from a limited amount of diffusion information. There are two contrasting approaches to model information diffusion. One is a push type model, known as Independent Cascade (IC) model and the other is a pull type model, known as Linear Threshold (LT) model. We extend these two models (called AsIC and AsLT in this paper) to incorporate asynchronous time delay and investigate 1) how they differ from or similar to each other in terms of information diffusion, 2) whether the model itself is learnable or not from the observed information diffusion data, and 3) which model is more appropriate to explain for a particular topic (information) to diffuse/propagate. We first show that there can be variations with respect to how the time delay is modeled, and derive the likelihood of the observed data being generated for each model. Using one particular time delay model, we show that the model parameters are learnable from a limited amount of observation. We then propose a method based on predictive accuracy by which to select a model which better explains the observed data. Extensive evaluations were performed using both synthetic data and real data. We first show using synthetic data with the network structures taken from four real networks that there are considerable behavioral differences between the AsIC and the AsLT models, the proposed methods accurately and stably learn the model parameters, and identify the correct diffusion model from a limited amount of observation data. We next apply these methods to behavioral analysis of topic propagation using the real blog propagation data, and show that there is a clear indication as to which topic better follows which model although the results are rather insensitive to the model selected at the level of discussing how far and fast each topic propagates from the learned parameter values. The correspondence between the topic and the model selected is well interpretable considering such factors as urgency, popularity and people’s habit.
Keywords: Social networks; Information diffusion models; Parameter learning; Model selection; Behavioral analysis
Authors: Changmin Liao
Abstract: Nucleic acids are major biological molecules essential for life, and everyday, there are large number of nucleic acids sequences that are released and searched. Now, many nucleic acids databases were used to assembly and distribute structural information related nucleic acids on the internet. In order to find or submit quickly needed nucleic acids sequences, this present paper introduced seven popular nucleic acids databases, including EMBL-Bank (European Molecular Biology Laboratory Nucleotide Sequence Database), GenBank, DDBJ (DNA Data Bank of Japan), GDB (Human Genome Database), EID (Exon-Intron Dabase), EPD (Eukaryotic Promoter Data) and RNAiDB (RNA Interference Database).
Keywords: Nucleic Acids; Database; Sequence; Submission And Search