Evaluation of usage patterns for web-based educational systems using web mining

Virtual courses often separate teacher and student physically from one another, resulting in less direct feedback. The evaluation of virtual courses and other computer-supported educational systems is therefore of major importance in order to monitor student progress, guarantee the quality of the course and enhance the learning experience for the student. We present a technique for the usage evaluation of Web-based educational systems focussing on behavioural analysis, which is based on Web mining technologies. Sequential patterns are extracted from Web access logs and compared to expected behaviour

An evaluation of scaffolding for virtual interactive tutorials

Scaffolding refers to a temporary support framework used during construction. Applied to teaching and learning it describes measures to support a learner to become confident and self-reliant in a subject. In a Web environment scaffolding features need to replace the instructor. We discuss our approach to Web-based scaffolding based on the cognitive apprenticeship and activity theories. We suggest a set of four scaffold types that have made our scaffolding-supported virtual interactive tutorial successful. We present a novel evaluation approach for virtual tutorials that is embedded into an iterative, evolutionary instructional design

A comparative study of the AHP and TOPSIS methods for implementing load shedding scheme in a pulp mill system

The advancement of technology had encouraged mankind to design and create useful equipment and devices. These equipment enable users to fully utilize them in various applications. Pulp mill is one of the heavy industries that consumes large amount of electricity in its production. Due to this, any malfunction of the equipment might cause mass losses to the company. In particular, the breakdown of the generator would cause other generators to be overloaded. In the meantime, the subsequence loads will be shed until the generators are sufficient to provide the power to other loads. Once the fault had been fixed, the load shedding scheme can be deactivated. Thus, load shedding scheme is the best way in handling such condition. Selected load will be shed under this scheme in order to protect the generators from being damaged. Multi Criteria Decision Making (MCDM) can be applied in determination of the load shedding scheme in the electric power system. In this thesis two methods which are Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were introduced and applied. From this thesis, a series of analyses are conducted and the results are determined. Among these two methods which are AHP and TOPSIS, the results shown that TOPSIS is the best Multi criteria Decision Making (MCDM) for load shedding scheme in the pulp mill system. TOPSIS is the most effective solution because of the highest percentage effectiveness of load shedding between these two methods. The results of the AHP and TOPSIS analysis to the pulp mill system are very promising

Special Issue on Smart Data and Semantics in a Sensor World

Introduction Since its first inception in 2001, the application of the Semantic Web [1, 2] has carried out an extensive use of ontologies [3–5], reasoning, and semantics in diverse fields, such as Information Integration, Software Engineering, Bioinformatics, eGovernment, eHealth, and social networks. This widespread use of ontologies has led to an incredible advance in the development of techniques to manipulate, share, reuse, and integrate information across heterogeneous data sources. In recent years, the growth of the IoT (Internet of Things) required to face the challenges of “Big Data” [6–10]. The cost of sensors is decreasing, while their use is expanding. Moreover, the use of multiple personal smart devices is an emerging trend and all of them can embed sensors to monitor the surrounding environment. Therefore, the number of available sensors is exploding. On the one hand, the flows of sensor data are massive and continuous, and the data could be obtained in real time or with a delay of just a few seconds. Then, the volume of sensor data is increasing continuously every day. On the other hand, the variety of data being generated is also increasing, due to plenty of different devices and different measures to record. There are many kinds of structured and unstructured sensor data in diverse formats. Moreover, data veracity, which is the degree of accuracy or truthfulness of a data set, is an important aspect to consider. In the context of sensor data, it represents the trustworthiness of the data source and the processing of data. The need for more accurate and reliable data was always declared, but often overlooked for the sake of larger and cheaper..

Association Rules for Web Data Mining in WHOWEDA

The authors discuss association rules which can be discovered from Web data. The association rules are discussed within the scope of our WHOWEDA (warehouse of Web data) project. WHOWEDA is supported by a Web data model and a set of algebraic operators. The Web data model allows a uniform and integrated view of Web data gathered using a user\u27\u27s query graph. A user\u27\u27s query graph describes the query by example (what the user perceives as the query) and the Web coupling query gathers instances of such a query graph from the Web and stores them in the form of subgraphs (called Web tuples) in a Web table. We discuss association rules within this domain. An association rule defines an association between the nodes and links attributes of Web tuples within a Web table. There are two different classes of association rules that can be developed from data in a Web table. There are two different classes of association rules that can be developed from data in a Web table. Node-to-node associations are those rules that relate the content (defined by metadata attributes) between two or more nodes within a Web tuple. Link associations are rules that show the connectivity of different URLs. Distinguishing the two types of associations provides a view of the structure of the Web data. The goal of performing Web association mining on Web data is to better organize searching patterns through hyperlinked document

Computer Science's Digest Volume 1

This series is dedicated to the students of the Systems Department, to give them reading material related to computer science in a second language. This book covers the Introduction to Computer Science, Computer Communications, Networking and Web Applications