294 research outputs found
Teachers’ Code-Switching in a Content-Focused English as a Second Language (ESL) Classroom: Patterns and Functions
As Pakistan is a multilingual country where educational institutions are inevitably bilingual and cannot sustain freeing themselves from the influence of bilinguality, both the teachers and the students have to switch from English to Urdu or Urdu to English during the learning process as both belong to bilingual or multilingual backgrounds. Keeping in view these issues, the present research has aimed to investigate those factors which aid to create bilingual or multilingual English as a Second Language classroom. These factors along with other issues have been analyzed on the hypotheses of students’ and teachers’ attitudes towards code switching, functions and patterns of switching and finally, and the effect of code switching in the classroom. The research is a mixed kind of research based on both quantitative and qualitative analyses in which relation between the use of code switching with learning success has been explored. The results of the study show that code switching does play an important role in English as a Second Language classroom. Both the participants, teachers and students, do not want to eliminate this strategy and favour it as a supportive tool in learning English. Keywords:Teacher’s code-switching to L1 (Urdu), attitudes, patterns, functions, and effects
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Automated Testing and Debugging for Big Data Analytics
The prevalence of big data analytics in almost every large-scale software system has generated a substantial push to build data-intensive scalable computing (DISC) frameworks such as Google MapReduce and Apache Spark that can fully harness the power of existing data centers. However, frameworks once used by domain experts are now being leveraged by data scientists, business analysts, and researchers. This shift in user demographics calls for immediate advancements in the development, debugging, and testing practices of big data applications, which are falling behind compared to the DISC framework design and implementation. In practice, big data applications often fail as users are unable to test all behaviors emerging from interleaving dataflow operators, user-defined functions, and framework's code. "Testing based on a random sample" rarely guarantees the reliability and "trial and error" and "print" debugging methods are expensive and time-consuming. Thus, the current practice of developing a big data application must be improved and the tools built to enhance the developer's productivity must adapt to the distinct characteristics of data-intensive scalable computing. By synthesizing ideas from software engineering and database systems, our hypothesis is that we can design effective and scalable testing and debugging algorithms for big data analytics without compromising the performance and efficiency of the underlying DISC framework. To design such techniques, we investigate how we can build interactive and responsive debugging primitives that significantly reduce the debugging time, yet do not pose much performance overhead on big data applications. Furthermore, we investigate how we can leverage data provenance techniques from databases and fault-isolation algorithms from software engineering to pinpoint the minimal subset of failure-inducing inputs efficiently. To improve the reliability of big data analytics, we investigate how we can abstract the semantics of dataflow operators and use them in tandem with the semantics of user-defined functions to generate a minimum set of synthetic test inputs capable of revealing more defects than the entire input dataset.To examine the first hypothesis, we introduce interactive, real-time debugging primitives for big data analytics through innovative and scalable debugging features such as simulated breakpoint, dynamic watchpoint, and crash culprit identification. Second, we design a new automated fault localization approach that combines insights from both the software engineering and database literature to bring delta debugging closer to a reality in the big data applications by leveraging data provenance and by constructing systems optimizations for debugging provenance queries. Lastly, we devise a new symbolic-execution based white-box testing algorithm for big data applications that abstracts the implementation of dataflow operators using logical specifications instead of modeling their implementations and combines them with the semantics of any arbitrary user-defined function. We instantiate the idea of an interactive debugging algorithm as BigDebug, the idea of an automated debugging algorithm as BigSift, and the idea of symbolic execution-based testing as BigTest. Our investigation shows that the interactive debugging primitives can scale to terabytes---our record-level tracing incurs less than 25% overhead on average and provides up to 100% time saving compared to the baseline replay debugger. Second, we observe that by combining data provenance with delta debugging, we can identify the minimum faulty input in just under 30% of the original job execution time. Lastly, we verify that by abstracting dataflow operators using logical specifications, we can efficiently generate the most concise test data suitable for local testing while revealing twice as many faults as prior approaches. Our investigations collectively demonstrate that developer productivity can be significantly improved through effective and scalable testing and debugging techniques for big data analytics, without impacting the DISC framework's performance. This dissertation affirms the feasibility of automated debugging and testing techniques for big data analytics---techniques that were previously considered infeasible for large-scale data processing
Assessing the Effects of School Support Facilities on Academic Achievement at Punjab Education Foundation Partner Schools
School supporting facilities provides a base for quality teaching and learning. The objective of this article was to assess the effect of school support facilities at Punjab Education Foundation partner schools on academic achievement. The present study was descriptive in nature; survey approach was used for data collection. Study was delimited to Punjab province. The sample of the study was comprised of 146 Principals from Sahiwal division of Punjab chosen through multi-stage random sampling technique. A Check List for School Support Facilities (CLSSF) consisted of 28 items was self developed, validated before actual survey. The survey data was analyzed by running multiple regression statistics. The dependent variable academic achievement assessed from the academic marks of students obtained in 2017 Punjab Examination Commission of Punjab. The findings of the study showed that school support facilities like tablet, I.T Lab, ventilation, first aid medical box, gas, store room, ECE/kids room, staff room and library contributed about 15.8% towards academic achievement at Punjab Education Foundation partner schools significantly. The Punjab Education Foundation may provide support facilities to their partner schools for the academic promotion
Navigating roundabouts and unprotected turns in autonomous driving
© 2024 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TFR.2024.3421389The development of a fully autonomous driving vehicle (AV) requires various traffic situations to be handled efficiently. One of the most common driving manoeuvres which an AV experiences in daily traffic is giving way (yielding) to other traffic participants. In this paper, we propose a simple yet efficient method of yielding that doesn’t query yielding areas of interests from map API making it hassle free to use without having to rely on digitized yielding areas. We incorporated our method into one of the well-known open-source autonomy stacks called Autoware. The proposed method makes use of high-definition (HD) map elements including lanes and stoplines for filtering vehicles which participate in yielding decision making. Our method estimates future collisions of filtered vehicles of interest with AV’s planned trajectory and outputs a binary yielding decision for ego vehicle. Our method covers different yielding areas including a roundabout and an unprotected turn. We tested and evaluated the decision making of our method on various simulated scenarios and afterwards successful real-world tests were conducted using an in-house AV. An in-depth analysis of our approach shows that the proposed yielding solution works reasonably well i.e. 87% successful yielding area navigation ratio on real data.Peer reviewe
Study of Effects of ICT on Professional Development of Teachers at University Level
Information and communication technology (ICT) has brought revolutionary changes to enhance professional development of teachers. At present several ICT related instructional devices like computers, smart phones, laptops, tablets, LCD, multimedia and projectors are used in classrooms for making more attractive and productive teaching and learning process. The objectives of the study were to explore perceptions of teachers regarding use of information communication technology and to find out the effects of ICT for improving teachers’ professional development at university level. The study was descriptive type survey in nature. Simple random sampling technique was adopted for sample selection. All public and private educational institutions providing higher education of central Punjab were the population of the study. The sample of the study comprised of 90 faculty members, 120 students and 12 heads of different departments were selected on random basis. A self-developed questionnaire for faculty members, students and structured interview schedule for heads of departments were administered for collection of desired information. Data analysis was carried out by using percentage, mean score and standard deviation. The results of the study revealed that ICT has positive effects on enhancing professional development of teachers. It was found that university teachers were facing many difficulties in preparing their lectures with technological innovations and utilization of ICT in classrooms. The study recommended that ICT related refresher courses may be organized to improve professional development of academician
Examining the Impact of Corruption on Financial Sector Development in Arab League Countries
Arab League Countries have seen major regulatory and financial reforms in the last two decades and during this period these counties have been marred by corruption. In this background, this study explores the impact of corruption on financial sector development in Arab League countries from 2001 to 2020. By using the dynamic panel data estimation technique of the Generalized Method of Moments on a sample of 20 Arab League countries, the study reports its findings. The finding shows that there is a significant negative effect of corruption on financial sector development. These results favor the notion of the “sand the wheels” hypothesis. The findings of this study highlight the insensitiveness of financial development to corruption during Global Financial Crisis (2008). The results also indicate that there is an adverse effect of corruption on financial development after Arab Spring. The study acknowledges the moderation role of rule of law in the relationship between corruption and financial development. 
Water deficit-induced regulation of growth, gas exchange, chlorophyll fluorescence, inorganic nutrient accumulation and antioxidative defense mechanism in mungbean [Vigna radiata (L.) Wilczek]
The study was conducted to appraise the influence of water deficit conditions on growth, yield, gas exchange characteristics, and antioxidative defense system in two mungbean [Vigna radiata (L.) Wilczek) lines, 97001 and 97012. The plants of both lines were grown for 30 days under normal natural conditions, after which time two drought regimes [control (well-watering and 60% field capacity)] were applied. Data for various attributes were recorded after 30 days of drought application while at maturity, yield attributes were recorded. Water deficit conditions caused a considerable reduction in growth attributes, net CO2 assimilation rate, stomatal conductance, electron transport ratio, total phenolics, leaf Ca2+ and yield attributes. Imposition of water deficit conditions significantly increased leaf tocopherol contents and activity of catalase in both mungbean lines. Both lines showed a considerable variation in growth attributes, the line 97001 being better in performance compared with 97012 under water deficit conditions
Trade Liberalisation and Industrial Productivity: Evidence from Manufacturing Industries in Pakistan
This study examines the impact of trade liberalisation on the
industrial productivity for a panel of twenty seven 3-digit
manufacturing industries in Pakistan over the period 1980-2006. Using a
variant of the Cobb-Douglas production function for industrial sector,
we estimated output elasticities. The results show positive output
elasticities with respect to labour, capital and raw materials for the
pre-trade liberalisation period (1981 –1995) as well as post-trade
liberalisation period (1996-2006). For the pre-liberalisation period, we
observe positive output elasticity with respect to energy, while it
turns out to be negative in the post-liberalisation period probably due
to energy crisis in Pakistan. In the second stage, we calculate total
factor productivity (TFP) and examine the impact of trade liberalisation
on TFP for pre-and post-trade liberalisation periods. The results reveal
that trade liberalisation proxied by import duty has positive but
negligible impact on the TFP in the pre-as well as post-liberalisation
periods. On the other hand, effective rates of protection exert large
negative impact on the TFP in the post-liberalisation than the
pre-liberalisation period. JEL Classifications: F14, F13, O53, L60
Keywords: Trade Liberalisation, Total Factor Productivity, Manufacturing
Sector of Pakista
Role of corporate branding, customer involvement and customer relationship proneness in luxury fashion branding
The main purpose of the current research is to develop and test a theoretical framework that captures the role of corporate branding (corporate association, symbolic benefits, and functional benefits), customer involvement and customer relationship proneness on customers emotional attachment and brand loyalty in the luxury fashion industry. The nature of this study is quantitative, cross-sectional and non-contrived. This study used a convenient sampling technique for the collection of data. Data were gathered from 315 customers who used to buy luxury fashion brands. This study has adopted a causal analytical approach by which hypotheses were developed and tested. For data analysis, correlation, regression, and descriptive statistics tests were carried out with the help of SPSS and mediation analysis was carried through AMOS. Findings approved that corporate association; symbolic benefits have limited impact on brand loyalty while functional benefits customer involvement and customer relationship proneness have a significant impact on brand loyalty. Findings suggest that emotional attachment fully mediates the relationship of corporate association, symbolic benefits, customer involvement, and brand loyalty, while emotional attachment partially mediates the relationship of functional benefits, customer relationship proneness, and brand loyalty
The effects of drought stress and type of fertiliser on generalist and specialist herbivores and their natural enemies
Abiotic stresses such as drought and nutrient availability can affect invertebrate herbivores feeding on plants, and potentially cascade up to impact their predators and parasitoids. Although these two factors separately been the subject of many studies, there are few tests of their combined effects in the context of pest species and their natural enemies on cultivated plants. Climate change models predict an increase in the frequency and severity of droughts, while the type and amount of fertiliser applied to crops is more under the control of growers. Understanding how these two abiotic factors may interact is key to utilising the potential of natural enemies to control pests under a future climate. To address this, a range of drought and fertiliser type treatments were applied to a model Brassica system in a factorial design, and the performance of two ubiquitous aphid species and their parasitoids was assessed. One aphid species was a specialist on Brassicas (Brevicoryne brassicae, with parasitoid Diaeretiella rapae) and the second a generalist aphid species (Myzus persicae, with parasitoid Aphidius colemani). The performance of both aphid species responded in a similar way to the treatments, and was maximised on plants growing in organic fertilisers under medium levels of drought stress. The strongest effects of drought and fertiliser cascaded up to affect parasitoids. Parasitoid performance responded in a broadly similar way to their aphid host performance in relation to fertiliser type. Some of the smaller effects of fertiliser treatments on aphid performance were not found for parasitoid performance. Aphid performance was greatest on plants under medium drought stress, but the parasitoids only responded consistently to the high drought stress treatment, on which their performance was reduced. Interactions between the drought and fertiliser did not have a large effect on aphid or parasitoid performance, compared with the strong main effects found for each treatment. These results are discussed in the context of previous and future research on the impacts of abiotic stresses on invertebrate herbivores and their natural enemies
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