A Study on UGC-CARE Journals of Library and Information Science

The University Grants Commission has published the list of CARE journals of all disciplines such as Science, Social Science and Arts & Humanities. The subject Library & Information Science has also been included in the CARE list under Social Science stream. The study measures information statistically or mathematically. These CARE list of journals are analyzed from different perspectives by giving various tables highlighting different aspects of informetric measurement

Use of a student response system in Primary Schools — an empirical study

This paper reports a pilot study for a student response system (SRS) used in an English school. The technology used is the “Wireless Response System” – WRS developed at Huddersfield University, and the learning activities were conducted in Mathematics and English classes. The main concepts – activity based, problem based and opinion based learning – are adopted into the study. A case study was the method used in the investigation. The results show that the system is suitable for different sizes groups of users, who may choose their preferred question types. The school claims the use of WRS was successful, evidenced by the data collected, and the children and teachers were interested in using it. We conclude that the SRS can assist teachers in classroom teaching at primary school level, especially in the observations of engagement and effectiveness of students’ learning

Geo-tagging news stories using contextual modelling

With the ever-increasing popularity of Location-based Services, geo-tagging a document - the process of identifying geographic locations (toponyms) in the document - has gained much attention in recent years. There have been several approaches proposed in this regard and some of them have reported to achieve higher level of accuracy. The existing geo-tagging approaches perform well at the city or country level, unfortunately, the performance degrades when the same approach is applied to geo-tag at the street/locality level for a specific city. Moreover, these geo-tagging approaches fail completely in the absence of a place mentioned in a document. In this paper, we propose an algorithm to address these two limitations by introducing a model of contexts with respect to a news story. Our algorithm evolves around the idea that a news story can be geo-tagged not only using the place(s) found in the news, but also by geo-tagging certain aspects of its context. An implementation of our proposed approach is presented and its performance is evaluated on a unique data set. Our findings suggest an improvement over existing approaches in street level geo-tagging for a specific city as well as in geo-tagging a news story even when no place is mentioned in it

An artificial intelligence and NLP based Islamic FinTech model combining Zakat and Qardh-Al-Hasan for countering the adverse impact of COVID 19 on SMEs and individuals

Pursose: The ongoing Corona virus (COVID 19) pandemic has already impacted almost everyone across the globe. The focus has now shifted from spread of the disease to the economic consequences it will bring to the society. The shortage of production will result into the shortage of supply and consequently will end as loss of jobs and employment for millions of people around the world. Two of the most important section of our society i.e., daily wage laborers and Small and Medium Enterprises (SMEs) will have to bear the major burnt of this crisis. The proposed integrated Artificial Intelligence and NLP based Islamic FinTech Model combining Zakat (Islamic tax) and Qardh-Al-Hasan (benevolent loan) can help the economy to minimize the adverse impact of COVID 19 on individuals and SMEs. Design/Methodology/Approach: The present study explores the possibility of Zakat and Qardh-Al-Hasan as a financing method to fight the adverse impact of Corona virus on poor individuls and SMEs. It provides the solution by proposing an Artificial Intelligence and NLP based Islamic FinTech Model combining Zakat and Qardh-Al-Hasan. Findings: The findings of the study reveals that Islamic finance has immense potential to fight any kind of situation/pandemic. Zakat and Qardh-Al-Hasan, if combined together can prove to be a deadly combination to fight the adverse effect of COVID 19. Practical Implications: To be used as an effective way to support individuals and SMEs in the period during and after the pandemic of COVID 19. Originality/value: There is no study combining Zakat and Qardh Al-Hasan to fight the adverse effect of poor individuals and SMEs. The study will contribute massively to the existing literature and will help the government and civil societies in fighting the economic impact of COVID 19 on individuals and SMEs.peer-reviewe

Disability-aware adaptive and personalised learning for students with multiple disabilities

Purpose The purpose of this paper is to address how virtual learning environments (VLEs) can be designed to include the needs of learners with multiple disabilities. Specifically, it employs AI to show how specific learning materials from a huge repository of learning materials can be recommended to learners with various disabilities. This is made possible through employing semantic web technology to model the learner and their needs. Design/methodology/approach The paper reviews personalised learning for students with disabilities, revealing the shortcomings of existing e-learning environments with respect to students with multiple disabilities. It then proceeds to show how the needs of a student with multiple disabilities can be analysed and then simple logical operators and knowledge-based rules used to personalise learning materials in order to meet the needs of such students. Findings It has been acknowledged in literature that designing for cases of multiple disabilities is difficult. This paper shows that existing learning environments do not consider the needs of students with multiple disabilities. As they are not flexibly designed and hence not adaptable, they cannot meet the needs of such students. Nevertheless, it is possible to anticipate that students with multiple disabilities would use learning environments, and then design learning environments to meet their needs. Practical implications This paper, by presenting various combination rules to present specific learning materials to students with multiple disabilities, lays the foundation for the design and development of learning environments that are inclusive of all learners, regardless of their abilities or disabilities. This could potentially stimulate designers of such systems to produce such inclusive environments. Hopefully, future learning environments will be adaptive enough to meet the needs of learners with multiple disabilities. Social implications This paper, by proposing a solution towards developing inclusive learning environments, is a step towards inclusion of students with multiple disabilities in VLEs. When these students are able to access these environments with little or no barrier, they will be included in the learning community and also make valuable contributions. Originality/value So far, no study has proposed a solution to the difficulties faced by students with multiple disabilities in existing learning environments. This study is the first to raise this issue and propose a solution to designing for multiple disabilities. This will hopefully encourage other researchers to delve into researching the educational needs of students with multiple disabilities

Pharaoh: Conceptual Blending of Cognitive Scripts for Computationally Creative Agents

Improvisational acting is a creative group performance where actors co-construct stories on stage in real-time based on actors’ perceptions of the environment. The Digital Improv Project has been engaged in a multi-year study of the cognitive processes involved in improvisational acting. This better understanding of human cognition and creativity has led to formal computational models of some aspects of our findings. In this work, we consider enriching AI improv agents with the ability to improvise new nontraditional scenes based on existing social cognitive scripts. This paper shows how the use of Pharaoh -a context based structural retrieval algorithm for cognitive scripts- and simple blending rules can help digital improv agents to create new interesting scenes. The paper also provides an illustrative example at the end

Extractive multi document summarization using harmony search algorithm

The exponential growth of information on the internet makes it troublesome for users to get valuable information. Text summarization is the process to overcome such a problem. An adequate summary must have wide coverage, high diversity, and high readability. In this article, a new method for multi-document summarization has been supposed based on a harmony search algorithm that optimizes the coverage, diversity, and readability. Concerning the benchmark dataset Text Analysis Conference (TAC-2011), the ROUGE package used to measure the effectiveness of the proposed model. The calculated results support the effectiveness of the proposed approach

Designing Islamic Religious Education Teaching Based on Digital Innovation Creativity at Universitas Islam Negeri Antasari Banjarmasin

Designing Islamic religious education teaching based on creative digital application innovations in high rooms was an exciting and vital issue to study. For this reason, this study has met many academics from the state Islamic University of Antasari for us to hear their opinions, thoughts, and perspectives on how to design creative and innovative technology-based Islamic learning. The researcher recorded their thoughts and voices through question-and-answer, semi-chartered interviews with seven speakers, then collected the data. The researcher examined it with a phenomenological approach, namely, trying to understand some interview data to answer the problems of this study. The study process involves a phenomenological approach that coding the evaluation and interpreting the data in order to answer the problems. In addition, searchinf the data on secondary publications was also be carried out electronically with the same treatment. It examined them to get their thoughts and problem formulation. Based on the answers and analysis, it  concluded that designing Islamic religious learning with technological innovation and creativity has been done effective at Antasari State Islamic University. The technology has innovated learning creatively to produce was very high output. Keywords:  Designing Islamic Education, Digital Innovation Creativity,  Islamic Religious Educatio

A Novel Approach on Visual Question Answering by Parameter Prediction using Faster Region Based Convolutional Neural Network

Visual Question Answering (VQA) is a stimulating process in the field of Natural Language Processing (NLP) and Computer Vision (CV). In this process machine can find an answer to a natural language question which is related to an image. Question can be open-ended or multiple choice. Datasets of VQA contain mainly three components; questions, images and answers. Researchers overcome the VQA problem with deep learning based architecture that jointly combines both of two networks i.e. Convolution Neural Network (CNN) for visual (image) representation and Recurrent Neural Network (RNN) with Long Short Time Memory (LSTM) for textual (question) representation and trained the combined network end to end to generate the answer. Those models are able to answer the common and simple questions that are directly related to the image’s content. But different types of questions need different level of understanding to produce correct answers. To solve this problem, we use faster Region based-CNN (R-CNN) for extracting image features with an extra fully connected layer whose weights are dynamically obtained by LSTMs cell according to the question. We claim in this paper that a single R-CNN architecture can solve the problems related to VQA by modifying weights in the parameter prediction layer. Authors trained the network end to end by Stochastic Gradient Descent (SGD) using pretrained faster R-CNN and LSTM and tested it on benchmark datasets of VQA