International Journal of Computer Networks and Communications Security

Volume 7, Issue 6, June 2018

 

 

Intelligent Recommendations for e-Learning Personalization Based on Learners Learning Activities and Performances
 

Intelligent Recommendations for e-Learning Personalization Based on Learners Learning Activities and Performances

Pages: 130-137 (8) | [Full Text] PDF (736 KB)
D Herath, L Jayarathne
University of Colombo School of Computing, Colombo, Sri Lanka

Abstract -
In this paper, we present the intelligent recommendations for e-Learning personalization approach which uses recommendation techniques for educational data mining specifically for identifying e-Learners learning activities, monitoring, predicting performance. Recommended learning resources are computer-based on the current learners navigational patterns, exploiting similarities and dissimilarities among learners preferences, educational contents, results obtained in various practical, exercises and interactions with different activities. The proposed framework for intelligent recommendations for e-Learning environment is composed of three modules, a learner module which uses to identify learners learning activities and preferences, a domain module which contains all the knowledge for a particular discipline and a recommendation module which pre-processes data to build a relevant recommendation list and predicting performances. Recommended resources are obtained by using level of knowledge of learners in different stages and the range of recommendation techniques based on content-based filtering and collaborative approaches. Several techniques such as classification, clustering, predictions and association rules are used to enhance personalization with filtering techniques to provide a recommendation and encourage learners to improve their performance.
 
Index Terms - E-Learning, Learning Activities, Educational Data Mining, Content-Based Filtering, Collaborative Filtering

Citation - D Herath, L Jayarathne. "Intelligent Recommendations for e-Learning Personalization Based on Learners Learning Activities and Performances." International Journal of Computer Science and Software Engineering 7, no. 6 (2018): 130-137.

Framework for Handling Data Veracity in Big Data
 

Framework for Handling Data Veracity in Big Data

Pages: 138-141 (4) | [Full Text] PDF (296 KB)
M Al-Jepoori, ZA Al-Khanjari
Computing, Canterbury Christ Church University, Canterbury, UK, Computer Science, Sultan Qaboos University,Muscat, Oman

Abstract -
Big Data is the term used for massive amount of data collected by different means and in various formats. Data Veracity refers to the uncertainty of available data; this means that the quality of the collected data cannot be trusted. This paper reports on ongoing research based on using the Semantic Web technology to verify user entered data and increase dependability on Big Data. Validating, cleaning and reducing collected data are the major activities required to enhance the quality of the collected data.
 
Index Terms - Big Data, Veracity, User generated data, automatically collected data, Crowed validation of data, Fake news

Citation - M Al-Jepoori, ZA Al-Khanjari. "Framework for Handling Data Veracity in Big Data." International Journal of Computer Science and Software Engineering 7, no. 6 (2018): 138-141.

Smart Flight Security in Airport Using IOT (Case Study: Airport of Birjand)
 

Smart Flight Security in Airport Using IOT (Case Study: Airport of Birjand)

Pages: 142-147 (6) | [Full Text] PDF (365 KB)
R Jalali, S Zeinali
Department of Computer, Islamic Azad University, Birjand, South Khorasan, Iran

Abstract -
Flight safety in airports is related to passenger authentication and controlling their loads. In this study we evaluated our proposed mechanism of using IOT in airport of Birjand in South Khorasan Province of Iran to increase the efficiency of flight security. Our proposed mechanism used RFID tags for passengers and their loads. The process of enhancing flight safety designed using a networked system (RFID readers and software client-server applications). Whole of proposed process simulated using Matlab software, and results compared with real data collected from airport of Birjand passengers and flight staff. Results showed that the proposed mechanism increased response time in various tasks including authentication, load processing, entering waiting room, entering airplane, loading airplane, but except finally returning loads to passengers in destination in comparison with previous method. So using IOT method for enhancing flight safety could be recommended to airports.
 
Index Terms - IOT, RFID, Flight Security, Airport of Birjand

Citation - R Jalali, S Zeinali. "Smart Flight Security in Airport Using IOT (Case Study: Airport of Birjand)." International Journal of Computer Science and Software Engineering 7, no. 6 (2018): 142-147.