Influence of Computer Assisted Language Learning (CALL) in the Acquisition of English as a Second Language by Polytechnic Students of Sri Lanka

Levy, M. (1997) explains Computer Assisted Language Learning (CALL) as“the search for and the study of applications of the computer in language teaching andlearning.” This research investigates the effectiveness of CALL in conducting Englishcourses for polytechnic students in Sri Lanka with special reference to studentsfollowing Higher National Diploma in Engineering, Management and English at SriLanka Institute Advanced Technological Education.The hypothesis that CALL made a positive impact on the polytechnic studentsthat learnt English as a second language was supported on the objectives that motivationof the students to follow the course was sustained, that their level of attendanceincreased and that their performance in the language tests improved. Data used in thiswork was collected via questionnaires forwarded to the members of the sample selectedas well as observations of the instructors/lecturers that represented the three courses.At the end of data analysis this research found noticeable improvement in theperformance of students in English since the incorporation of CALL in English languageprogrammes followed by them. The student autonomy, authenticity of material andtechnological paraphernalia that CALL involves seemed to take their appeal resulting inthe development of their language skills. Advantages of using CALL in languageprogrammes of polytechnic students led this research to advocate the incorporation ofInternet and other language software into second language courses and at the same timeit emphasizes adequate training and awareness building initiatives for the staffconducting these courses, for enabling them to handle the technical interruptions andtrouble shooting promptly for delivering and ensuring a satisfactory learningexperience/environment for students learning English as their second language.Key words: Polytechnic, Appeal, Authenticity, Impact, Trainin

Synthesis and characterization of mixed oxide nanowires for gas sensing

A healthy and long-lasting life is the utmost wish of any living being thus aging. The aging phenomenon cannot be stopped but may be controlled to some extent when we live in appropriate environments. Usually, the outdoor environment is polluted by two means natural events (windblown dust, volcano eruptions, etc.) and man-made ones (burning of facile fuels, factories, volatile organic compounds, etc.). Pollution due to harmful air such as sulfur oxides (SO2), nitrogen oxides (NOX), carbon monoxide (CO), ammonia (NH3), methane (CH4), and volatile organic compounds (VOCs) is one of the significant issues since it is more sensitive to compromising the natural ecosystem and environment. So, exposure to these compounds worsens the aging phenomena of the living being (headache, fainting, skin and eye irradiation, respiratory infections, heart disease, lung cancer, and even superficial death). Therefore, it is necessary the detection these compounds in the environment. Accordingly, metal oxides (MOXs) gas sensors have conventionally been employed to detect and quantify harmful gases in both indoor and outdoor environments. However, one of the major problems with these sensors is achieving selective detection. Herein, we propose a novel design with two metal oxides (ZnO and Co3O4) that provide very high gas response together with superior selectivity. The proposed structure is a one-dimensional (1D) metal oxide composite; Co3O4/ZnO nanowires. The composite was prepared by in-situ thermal oxidation of metallic Co thin layer (50 nm) and evaporation of ZnO powder at a temperature of 800 ᵒC at a pressure of 0.15 mbar. The pressure was maintained by a controlled mixture of O2 and Ar. The morphological, compositional, and structural analyses are evidence of the successful growth of the Co3O4/ZnO composite nanowire with the root of Co3O4 and the tip with Pt (catalyzer) and Co3O4. The gas sensing characterization shows exciting sensing functionality towards acetone (C3H6O) compared to that of tested gases (C2H5OH, H2S, NH3, CO, NO2, and H2). The reported highest response (ΔG/G; G is the conductance) was above the value of 5000 toward 50 ppm (parts per million) C3H6O at 40 RH% air when working at 250 °C with the potential of detecting sub ppb (parts per billion) concentration levels of C3H6O. The very high C3H6O sensing performance together with exceptionally high selectivity of the sensor ascribed to Pt nanoparticle and the Co3O4 section on the tip of the Co3O4/ZnO. Moreover, the formation of heterojunctions, synergistic gas sensing, and the catalytic activity of the proposed design enhances the response of the sensors. Accordingly, scanning electron microscopic (SEM), transmission electron microscope (TEM), energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) characterization, and the sensing mechanisms are comprehensively discussed at the conference

Histoplasmosis in Sri Lanka - a masquerader in a strange land: A Case Report

We present a patient with an oral mucosal ulcer who was diagnosed with disseminated histoplasmosis. This fungal infection is endemic in the United States, and thus may be not considered in the differential diagnosis of oral ulcers in Sri Lanka. Furthermore, it may mimic many common diseases found in Sri Lanka. It is therefore important to be aware of this entity, since it is potentially curable if diagnosed and treated early.</p

Investigating word affect features and fusion of probabilistic predictions incorporating uncertainty in AVEC 2017

© 2017 Association for Computing Machinery. Predicting emotion intensity and severity of depression are both challenging and important problems within the broader field of affective computing. As part of the AVEC 2017, we developed a number of systems to accomplish these tasks. In particular, word affect features, which derive human affect ratings (e.g. arousal and valence) from transcripts, were investigated for predicting depression severity and liking, showing great promise. A simple system based on the word affect features achieved an RMSE of 6.02 on the test set, yielding a relative improvement of 13.6% over the baseline. For the emotion prediction sub-challenge, we investigated multimodal fusion, which incorporated a measure of uncertainty associated with each prediction within an Output-Associative fusion framework for arousal and valence prediction, whilst liking prediction systems mainly focused on text-based features. Our best emotion prediction systems provided significant relative improvements over the baseline on the test set of 39.5%, 17.6%, and 29.3% for arousal, valence, and liking. Of particular note is that consistent improvements were observed when incorporating prediction uncertainty across various system configurations for predicting arousal and valence, suggesting the importance of taking into consideration prediction uncertainty for fusion and more broadly the advantages of probabilistic predictions

Efficiency of the Sri Lankan Stock Market during the COVID 19 Period

The study looks into how the COVID 19 affects the Sri Lankan stock market. The purpose of this study is to determine if the COVID 19 Pandemic has made the Sri Lankan stock market more efficient or inefficient. The study employed secondary data in the form of time series for a six-month period commencing September 2nd, 2019 and concluding March 31st, 2020. The pre-COVID period runs from September 2nd to December 31st, 2019, while the COVID period runs from January 1st to March 31st, 2020. The study's findings indicated that the Sri Lankan stock market became more inefficient after COVID 19

Sepsis with cerebral lupus…. or is it? A case report on Cryptococcaemia

We present a patient with SLE, with multiple comorbidities, whose blood cultures yielded Cryptococcus neoformans. Blood cultures became positive only after twelve days of hospital admission. The patient died within two days of starting Amphotericin B. Cryptococci are an important cause of infection in SLE. Only about 10% to 30% of those with cryptococcal disease have the organism isolated by blood cultures. Due to its non-specific clinical presentation, cryptococcal infection in SLE can be misdiagnosed as psychosis due to steroids, cerebral lupus and infections due to other non-fungal pathogens. This may lead to inappropriate therapy and delays in administration of antifungal agents. Therefore, cryptococcal infection should be considered when SLE patients present with sepsis irrespective of the presence of features of meningis

Multi-Functional Carbon Fibre Composites using Carbon Nanotubes as an Alternative to Polymer Sizing

Carbon fibre reinforced polymers (CFRP) were introduced to the aerospace, automobile and civil engineering industries for their high strength and low weight. A key feature of CFRP is the polymer sizing - a coating applied to the surface of the carbon fibres to assist handling, improve the interfacial adhesion between fibre and polymer matrix and allow this matrix to wet-out the carbon fibres. In this paper, we introduce an alternative material to the polymer sizing, namely carbon nanotubes (CNTs) on the carbon fibres, which in addition imparts electrical and thermal functionality. High quality CNTs are grown at a high density as a result of a 35 nm aluminium interlayer which has previously been shown to minimise diffusion of the catalyst in the carbon fibre substrate. A CNT modified-CFRP show 300%, 450% and 230% improvements in the electrical conductivity on the ‘surface’, ‘through-thickness’ and ‘volume’ directions, respectively. Furthermore, through-thickness thermal conductivity calculations reveal a 107% increase. These improvements suggest the potential of a direct replacement for lightning strike solutions and to enhance the efficiency of current de-icing solutions employed in the aerospace industry