Experimental Study of Physio-Mechanical and Engineering Properties of Clayey Soil Incorporating Hydraulic Lime and Nano-Silica

Soil is one of the most abundant and frequently used materials in geotechnical engineering and construction. Soil is heterogenous material with different minerals some of which are classified as problematic minerals. The soil is classified as unacceptable for construction purpose if some of these minerals are present in the soil. Soil improvement utilizing nano materials is a novel technique to upgrade engineering and shear strength parameters of problematic soils. The effects of varying amounts of nano-silica and lime in clayey soil are investigated in this study. For this purpose, soil samples were moulded by incorporating 0, 3, 6, 9% nano silica and 0, 5, and 10% lime. The samples were tested for Atterberg limits, Plasticity index, optimum moisture content OMC, maximum dry density MDD, swelling, and unconfined compressive strength (UCS) at 7 and 28 days. The results revealed that addition of nano-silica in lime treated high plastic clay improved the plasticity index as well as UCS and swelling behaviour by a significant margin. Results highlighted that incorporation of nano silica reduced the plasticity index. UCS values of the soil increased by adding nano silica 28 days UCS increased by 10 times as compared to 7 days strength. The swelling in soil samples with 10% lime and 9% nano silica is reduced by almost 32% as compared to controlled samples. OMC is also increased by 17% meanwhile MDD is reduced by 9% when nano silica was added. The findings of this study can be used in any project that requires improved engineering and geotechnical properties of high plastic clayey soil for shallow foundation

Investigating the Impact of CALL Integration on ESL Learners’ Listening Comprehension: A Case Study of ‘Indus Valley School System (IVSS)’ Hyderabad

The use of Computer Assisted Language learning (CALL) has become a significant feature in English Language Teaching (ELT). It is used for effective English language teaching and learning. This study investigated the impact of CALL integration on ESL Learners’ Listening Comprehension. The method for this research was a case study. Pre-test, post-test and questionnaire were used as instruments to collect data from forty learners of grade eight of Indus Valley School System (IVSS) Hyderabad, Pakistan. The main purpose of this study was to investigate the CALL’s role in improving their listening comprehension and their motivation in listening through CALL. The findings show the improvement in learners. Keywords: CALL integration, Listening Comprehension, ESL learners. DOI: 10.7176/JLLL/88-02 Publication date:May 31st 202

Automatic Speaker Identification System for Urdu Speech

Speaker recognition is the process of recognizing a speaker from a verbal phrase. Such systems generally operates in two ways: to identify a speaker or to verify speaker’s claimed identity. Availability of valuable research material witnessed efforts paid to Automatic Speaker Identification (ASI) in East Asian, English and European languages. But unfortunately languages of South Asia especially “Urdu” have got very less attention. This paper aims to describe a new feature set for ASI in Urdu speech, achieving improved performance than baseline systems. Classifiers like Neural Net, Naïve Bayes and K nearest neighbor (K-NN) have been used for modeling. Results are provided on the dataset of 40 speakers with 82% correct identification. Lastly, improvement in system performance is also reported by changing number of recordings per speaker

Validated digital literacy measures for populations with low levels of internet experiences

A growing body of evidence suggests that digital literacy is an important barrier constraining adoption and use of Internet and digital technologies in the developing world. By enabling people to effectively find valuable information online, digital literacy can play a crucial role in expanding economic opportunities, thereby leading to human development and poverty reduction. Unfortunately, there is a dearth of validated survey measures for capturing digital literacy of populations who have limited prior exposure to technology. We present a novel approach for measuring digital literacy of low literacy and new Internet users, an important segment of users in developing countries. Using a sample of 143 social media users in Pakistan, which includes a significant fraction of low literacy individuals, we measure digital literacy by observing the effectiveness of participants in completing a series of tasks and by recording a set of self-reported survey responses. We then use machine learning methods (e.g., Random Forest) to identify a parsimonious set of survey questions that are most predictive of ground truth digital literacy established through participant observation. Our approach is easily scalable in low-resource settings and can aid in tracking digital literacy as well as designing interventions and policies tailored to users with different levels of digital literacy

The spread of (mis)information: A social media experiment in Pakistan

This randomized experiment on a social media platform in Pakistan measures the impact of two treatments that fully control access to misinformation relative to a more standard ex-post approach to controlling misinformation. In the first treatment, no misinformation was allowed on the platform, while in the second, it was allowed with an official rebuttal. The experiment focuses on misinformation regarding COVID-19 and is combined with an intervention to disseminate official information about the pandemic on the platform. Controlling misinformation through either treatment reduces platform usage. It also reduces exposure to official information by more than it reduces exposure to misinformation