Tassawar Iqbal

Second life for illiterates: a 3D virtual world platform for adult basic education

Illiteracy is still a dilemma, around more than 700 million adults in the world are unable to read and write. In the present modern society, technology is used to provide the techno-literacy solutions to help out the illiterates. Unfortunately, these solutions rarely consider the traditional learning theories and exploit two-dimensional (2D) platforms. Furthermore these techno-literacy solutions focus on desktop applications such as movies, recorded lectures on CDs and web-based application like 2D text-based instructional programs and games. These 2D applications are lacking the features such as self-presence, social-presence, situated-learning, embodied environment and learning by doing suggested in the traditional learning theories. There is a need to bridge the gap between technology-based solutions and traditional learning theories and to exploit emergent three-dimensional (3D) technologies to provide these lacking features. In this paper, we explore how the benefits of 3D emergent technologies like Second Life (SL) are exploited in coherence with traditional theories for Adult Basic Education (ABE). We present an immersive learning platform based on Multiple Intelligences (MI) Theory. We design and discuss an adaptive learning scenario for ABE in the SL. Finally we scrutinize the proposed platform to get an overview of the strengths and weaknesses in the intended area of application.

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F‐score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods.

Job search website for illiterate users of Pakistan

Abstract Illiteracy is a major hurdle in socio-economic development of Pakistan. Research in the Information and Communication Technology (ICT) can help in tackling this issue by developing solutions tailored for illiterate population. The work presented within this paper proposes a job search website for illiterate population of KPK province of Pakistan. The designed website does not require any human assistance while searching a job. Moreover, the website uses culturally relevant graphical and audio content. The usability of the website is tested according to the ISO-9241-11 specification. Furthermore, we have studied the effect of the participants’ characteristics, i.e., their age, computer and mobile usage experience on the usability of the website. The results show that the participants found the website usable. Specifically, they could search suitable jobs with a minimal number of clicks and in less time as compared to the usual task completion rates reported throughout the literature. None of the participants’ characteristics were found to be affecting the usability of the website. These results suggest a promising potential of ICT solutions for providing services to illiterate population of Pakistan.

Fighting adult illiteracy with the help of the environmental print material

Adult illiteracy is a major problem worldwide especially in developing countries. Adult Basic Education (ABE) programs working in this context are not very effective due to lack of motivation for the people who are not literate. The reason is inadequate learning content and content delivery methods. This situation calls for developing novel learning content and a learner-directed content delivery approach. This paper presents an exploratory study investigating the use of the Environmental Print Material (EPM) as learning content for the non-literate population of Pakistan. The EPM content is presented to the adult non-literate population in two ethnographic studies. The most frequently recognized content is selected and utilized as learning content in a Computer Assisted Learning (CAL) application. An empirical study is conducted upon two groups with 107 participants to compare the EPM-based learning content with Traditional Learning Content (TLC). As many as 54 participants participated in the experimental group (presented with EPM-based learning content), whereas 53 participants took part in the control group (presented with TLC content). The results reveal that the experimental group performed significantly better compared to the control group in recognition, pronunciation, and recall of the presented content. The meta-analysis of the results shows a large effect size of (1.05) with confidence interval in the range (0.798–1.315). The results claim that the EPM has potential to be considered as learning content in the ABE programs.

FRP: A novel fast rerouting protocol with multi-link-failure recovery for mission-critical WSN

Abstract Fast rerouting requires that a backup route is already available at each node so that traffic can immediately be shifted on it without new path discovery and convergence time delay. Handling multiple failures with least possible delay, high throughput and least overhead with regard to memory and battery is a real challenge in Wireless Sensor Networks (WSN). Current fast rerouting techniques that handle multiple failures do not specifically target mission-critical WSN applications. Fast Rerouting techniques use spanning trees, backup topologies or configurations to shift traffic immediately as and when error is detected. These techniques do not focus on finding least hop count on the backup path and therefore, end-to-end delay on the backup paths is higher than on the primary path. The proposed Fast Rerouting Protocol (FRP) establishes primary and backup routes before the start of data transfer. It creates at least one backup path towards destination from every node on the primary path. FRP therefore has the ability to handle multiple failures in mission-critical WSN environment. NS-2 simulation results of FRP against the competitor reveal that, FRP takes least time and control messages to establish shorter fast rerouting paths, produces minimum end-to-end delay, least energy consumption and higher network life time.