Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

A comparative study of education systems : from traditional education to massive open online courses

This thesis compares traditional education approaches to the new forms of online education in order to identify the major differences between the systems. It is done through research about sample cases, expert conversations and existing literature. The comparison provides evidence how Massive Open online courses contribute to reach and richness of education. The study finds that the newest online offering, namely Massive Open Online Courses offers higher flexibility than traditional education, as well as more interactivity and richer Media than existing online offerings. The use of information technology in education can address current needs, including tuition costs and access to education. Traditionally, there existed a tradeoff between educating many learners and providing them with a rich experience. The use of information technology in education can address current needs as tuition cost and access to education. New forms of online education suggest a pattern of reach and richness, where the tradeoff is smaller than traditionally. Educating online increases reach tremendously compared to traditional education. In the same time the design of the new online courses provides a richer experience compared to existing online offerings, coming closer to a traditional experience

Development of portable charger for mobile phone using arduino microcontroller during disaster recovery

In the recent years, hundreds to thousands of people have been killed in many disasters across Asian region, such as tsunami, floods, earthquakes and so on. During disaster, most of the electricity supply will be disrupted, then the telecommunication networks will fail. During emergency response, the necessity to have portable charger for mobile phone arises as the victim could communicate with the relevant authorities or volunteers. The objective of this research is to design and develop portable charger for mobile phone using Arduino microcontroller, which can be used effectively during disaster event. Three main circuits have been implemented, including energy harvesting and DC/DC boost converter, intermediate battery charging, and Li-Ion charging. The energy harvester circuit will be the combination of mechanical and solar panel. Performance evaluation have been conducted to evaluate the best DC motor and solar panel, as well as the final charging time for Li-Ion battery

Automatic classification of documents with an in-depth analysis of information extraction and automatic summarization

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.Includes bibliographical references (leaves 78-80).Today, annual information fabrication per capita exceeds two hundred and fifty megabytes. As the amount of data increases, classification and retrieval methods become more necessary to find relevant information. This thesis describes a .Net application (named I-Document) that establishes an automatic classification scheme in a peer-to-peer environment that allows free sharing of academic, business, and personal documents. A Web service architecture for metadata extraction, Information Extraction, Information Retrieval, and text summarization is depicted. Specific details regarding the coding process, competition, business model, and technology employed in the project are also discussed.by Joseph Brandon Hohm.M.Eng

Third international workshop on Authoring of adaptive and adaptable educational hypermedia (A3EH), Amsterdam, 18-22 July, 2005

The A3EH follows a successful series of workshops on Adaptive and Adaptable Educational Hypermedia. This workshop focuses on models, design and authoring of AEH, on assessment of AEH, conversion between AEH and evaluation of AEH. The workshop has paper presentations, poster session and panel discussions

The Effects of Elaborative Interrogation and Summarization on Student Comprehension, Retention, and Satisfaction in Online, Self-Paced Instruction

The purpose of this study was to investigate the effects of two elaboration strategies, elaborative interrogation questioning (EIQ) and summarization, on student comprehension, retention, and satisfaction in a self-paced online environment. There were four treatment groups: (a) Control (no treatment); (b) EIQ only; (c) Summarization only; and (d) EIQ and Summarization. Both undergraduate and graduate students (mean age = 25.84 years) volunteered and completed the study (N=191). Results revealed a significant interaction between strategy type and age on comprehension. Older participants in the Control and EIQ/Summarization strategy groups comprehended more than the younger participants, and the younger participants in the EIQ and the Summarization groups comprehended more than the older participants. Retention was tested one month later and was significantly affected by prior knowledge. Those with more prior knowledge had higher mean scores ( M=63.89) than those with less prior knowledge (M=58.03). Both the EIQ and summarization strategies—alone and in combination—while effective when tested immediately following module completion, were evidently not effective one month later. Learners with more prior knowledge of the to-be-learned material retained more information than those with less prior knowledge. Lastly, satisfaction results revealed a significant interaction between age and gender and strategy type and age. As age increased, females were more satisfied than males, however as age decreased, females were less satisfied than males in the online instruction module. Furthermore, younger participants were more satisfied in the EIQ group than older participants, and younger participants were less satisfied in the Summarization group than older participants. Specifically, participants using the EIQ strategy were 87 percent satisfied with this learning strategy, 86 percent were satisfied with the Summarization strategy, and 81 percent were satisfied using the combination of EIQ/Summarization strategies. Overall, 93 percent of the participants were satisfied with this self-paced online module

S3PSO: Students’ Performance Prediction Based on Particle Swarm Optimization

Nowadays, new methods are required to take advantage of the rich and extensive gold mine of data given the vast content of data particularly created by educational systems. Data mining algorithms have been used in educational systems especially e-learning systems due to the broad usage of these systems. Providing a model to predict final student results in educational course is a reason for using data mining in educational systems. In this paper, we propose a novel rule-based classification method, called S3PSO (Students’ Performance Prediction based on Particle Swarm Optimization), to extract the hidden rules, which could be used to predict students’ final outcome. The proposed S3PSO method is based on Particle Swarm Optimization (PSO) algorithm in discrete space. The S3PSO particles encoding inducts more interpretable even for normal users like instructors. In S3PSO, Support, Confidence, and Comprehensibility criteria are used to calculate the fitness of each rule. Comparing the obtained results from S3PSO with other rule-based classification methods such as CART, C4.5, and ID3 reveals that S3PSO improves 31 % of the value of fitness measurement for Moodle data set. Additionally, comparing the obtained results from S3PSO with other classification methods such as SVM, KNN, Naïve Bayes, Neural Network and APSO reveals that S3PSO improves 9 % of the value of accuracy for Moodle data set and yields promising results for predicting students’ final outcome