A Heuristic Method for Learning Path Sequencing for Intelligent Tutoring System (ITS) in E-learning

Course sequencing is one of the vital aspects in an Intelligent Tutoring System (ITS) for e-learning to generate the dynamic and individual learning path for each learner. Many researchers used different methods like Genetic Algorithm, Artificial Neural Network, and TF-IDF (Term Frequency- Inverse Document Frequency) in E-leaning systems to find the adaptive course sequencing by obtaining the relation between the courseware. In this paper, heuristic semantic values are assigned to the keywords in the courseware based on the importance of the keyword. These values are used to find the relationship between courseware based on the different semantic values in them. The dynamic learning path sequencing is then generated. A comparison is made in two other important methods of course sequencing using TF-IDF and Vector Space Model (VSM) respectively, the method produces more or less same sequencing path in comparison to the two other methods. This method has been implemented using Eclipse IDE for java programming, MySQL as database, and Tomcat as web server.

Multi-Agent Negotiation in B2C E-Commerce Based on Data Mining Methods

The Multi agent system (MAS) model has been extensively used in the different tasks of e-commerce like customer relation management (CRM), negotiation and brokering. For the success of CRM, it is important to target the most profitable customers of a company. This paper presents a multi-attribute negotiation approach for negotiation between buyer and seller agents. The communication model and the algorithms for various actions involved in the negotiation process is described. The paper also proposes a multi-attribute based utility model, based on price, response-time, and quality. In support of this approach, a prototype system providing negotiation between buyer agents and seller agents is presented.

A Framework Towards Semantic Web Service Composition Based on Multi-Agent System

A Semantic Web service composition system can be considered as a multi-agent system, in which each of the component service is considered as an agent capability. The article presents a multi-agent system based Semantic Web service composition approach. The proposed approach deals with some of the untouched issues and uses cognitive parameters and quality of service (QoS) parameters in serviceprovider selection. A new application area for the Semantic Web technology, that is, education planning involving planning the admission-process for higher-education course has been introduced and the proposed approach and models are applied on it.

Calcium and magnesium levels during automated plateletpheresis in normal donors

It is well known that citrate induces ionized hypocalcaemia by the chelating effect during plateletpheresis. However, the kinetics of serum magnesium (Mg) ions has not been well documented. We, therefore, evaluated biochemical changes in healthy donors during plateletpheresis procedure. Ten healthy donors underwent plateletpheresis on continuous cell separator (CS3000, Baxter, Round Lake, IL, USA) and 10 on intermittent flow cell separator (MCS 3p, Hemonetics, Braintree, MA, USA). Serum levels of total and ionized calcium (tCa and iCa, respectively) and Mg (tMg and iMg, respectively) were measured before, during and after the procedures. Although, the fall in tCa (from 2.62 +/- 0.12 to 2.36 +/- 0.12 mmol L(-1)) and tMg (from 0.89 +/- 0.01 to 0.79 +/- 0.01 mmol L(-1)) was modest and not significant; drop in iCa (from 1.33 +/- 0.1 to 0.84 +/- 0.1 mmol L(-1)) and iMg (from 0.53 +/- 0.01 to 0.35 +/- 0.1 mmol L(-1)) was statistically significant (P < 0.001). There were no significant differences observed between the CS3000 and MCS 3p cell separators regarding the fall in Ca and Mg. None of the donors experienced any adverse reactions during the procedures. In the study, an acute ionized hypocalcaemia and hypomagnesaemia have been observed after the plateletpheresis; therefore, measurement of both the ions may be monitored. However, there is no justification for prophylactic supplementation of either of these elements.

A knowledge based interpretation system for EMG abnormalities

The conventional method of diagnosis in electromyography is complex and time consuming, not only due to the large number of parameters, to be considered for diagnosis, but also because of the usual procedure of evaluating the different parameters of EMG signal by visual scanning of the plotted signal. So there is a clear need to make use of computer aided decision support system. In the present work an attempt has been made in the direction of integration into one automated system, the qualitative knowledge of the physician, with possibly sophisticated signal analysis tools which must replace the visual scanning. A software program (in Turbo-C) on a PC-AT has been developed to evaluate the different parameters of MUAP's (motor unit action potential) in a EMG signal. Then an Expert system (in Turbo-Prolog) has been implemented for diagnostic purposes of different muscular abnormalities by making a knowledge base from the different parameters involved in the decision making procedure of clinical electromyography. A hybrid model of rule and frame based Expert system is implemented. An attempt has been made for making a complete system, i.e., for recording, analysis and decision making for diagnosis.

A decision table and rule based interpretation system for epileptic discharges

The representation of the various features of waveforms and their correlations, in EEG recording for the diagnosis of different diseases have been carried out by many researchers due to the impact of knowledge based on expert systems development tools and techniques. The realisation of these system requires a specific hardware and software tool for its implementation, which may be a costly affair. The design and development of low cost effective system for the diagnosis of epileptic patients have been reported in this paper. Two different and linked (at certain stage) approaches (i) decision table; (ii) rule based system have been followed to model the reasoning processes of physician in the diagnosis. In the decision table the features of specific waveforms of EEG are represented in the tabular form. The features are obtained from a 8086 microprocessor based data acquisition system. The rule based system is designed with IF and THEN form of rules using Turbo-Prolog as programming language tool and is implemented on low cost PC-AT. The results obtained are at an intermediate stage of data processing by decision tables and at the final stage being carried out by rule based model. The performance of the system is evaluated by recording of EEG of some epileptic patients. The results obtained are comparable and to a certain extend appreciable in the opinion of the physician.

Microprocessor based detection of epileptic discharges

Parametric and Non-parametric methods have been developed for the detection and interpretation of EEG data for normal and abnormal patients. These methods have been implemented on mainframe computers or dedicated microcomputers. The heuristic methods are suitable for implement on dedicated microprocessor based system as they involve less degree of computation in comparison to the parametric methods. In this work a microprocessor based system has been developed and heuristic pattern recognition technique has been applied, which is based on the measurement of amplitude, duration slopes etc. for the detection of spike and sharp waves as well as the different frequency band of background activity. The computed values of amplitude and durations are shown on the graphs from which the different symptoms based on EEG are determined.