Solution of Second Kind Volterra Integro Equations Using linear Non-Polynomial Spline Function

This research use linear  non-polynomial Spline function to solve second kind Volterra integro equations . An algorithem introduced with numerical examples to illustrate the proposed method. Keywords : Integro equation, Volterra second kind , Non-Polynomial Splin

The EAP course design Quagmire – juggling the stakeholders’ perceived needs

This chapter explores perspectives of administrators, ESP teachers and MBA students in a Pakistani university on the English language needs of MBA students. It further tries to explore the strife caused by the administrative differences in opinion and outlook on the university’s system that restrain it from bringing much needed change in the curriculum. In doing so the chapter also looks for a way forward, that is, a way to meet the English language needs of MBA students despite the disparity in the three respective standpoints. It also offers implications of this study to other global EAP contexts

DETECTION OF UNFOCUSED RAINDROPS ON CAR WINDSCREEN COMPARATIVE ANALYSIS USING BACKGROUND SUBRACTIONAND AND WATERSHED ALGORTIHM

Use of ADAS in top end cars has been prevalent over past decade. Electronic control and assistance in cars has proven to be a major feature resulting in passenger safety, saving lives as well as preventing fatalities. This system can be trusted or counted upon in clear weather conditions, which by now has been the only limitation questioning the usefulness of ADAS. Current research focuses to strengthen ADAS in rainy climatic conditions. This paper puts forth a novel idea to detect raindrops where ADAS can be used to increase its functionality in rainy condition to control the speed of over-speeding cars. The method basically includes image database on which Background Subtraction and Watershed algorithm are run to find out a numerical data, and to measure performance of both the method. This data can be used to improve ADAS performance in rainy conditions

ANALYSIS OF FACTORS AFFECTING THE EFFECTIVENESS OF DISTANCE LEARNING MODE IN THE PREPARATION OF TEACHERS IN COLLEGES OF EDUCATION, NIGERIA

Distance learning education has been considered as a viable tool which not only helps in solving the problem of shortage of teachers but also the high attrition rates that is often associated with study leave. It was believed that distance education has the capacity to prepare qualified teachers just as the face-to-face education mode. However, there seem to be gaps between the objectives establishing distance education and their realization. The obvious indicators to this fact are the unqualified teachers who cannot express themselves in the classroom. The study explored the factors affecting the effectiveness of distance learning mode in the preparation of teachers in Colleges of Education, Nigeria. The researcher constructed 30 questionnaire items from the literature relevant to the study.  The questionnaire yielded a reliability coefficient of 0.83. A total of 151 questionnaires were administered on 38 and 113 lecturers and students of College of Education, Minna and Mokwa study centers.  All the questionnaires were completed and retrieved. The study revealed that all the constructs constituted factors affecting the effectiveness of the distance learning mode of education in the preparation of teachers in Colleges of Education in Nigeria.  It was concluded that the nation will continue to be in dire need of adequate qualified teachers if the factors affecting the effectiveness of the program are not eliminated. It was recommended among others that institutions establishing distance learning programs should ensure that the needed facilities for the effective running of the program are properly put in place. Facilities such as; technologies that will create an interactive learning environment even at a distance

Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag

We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the known richness of M-Sn properties with potential applications in energy storage, electronics packaging, and superconductivity. For the systematic exploration of the large configuration space, we relied on our recently developed MAISE-NET framework that constructs accurate neural network interatomic potentials and utilizes them to accelerate ab initio global structure searches. The scan of over two million candidate phases at a fraction of the typical ab initio calculation cost has uncovered 29 possible intermetallics thermodynamically stable at different temperatures and pressures (1 bar and 20 GPa). Notable predictions of ambient-pressure materials include a simple hP6-NaSn$_2$ phase, fcc-based Pd-rich alloys, tI36-PdSn$_2$ with a new prototype, and several high-temperature Sn-rich ground states in the Na-Sn, Cu-Sn, and Ag-Sn systems. Our modeling work also involved ab initio (re)examination of previously observed M-Sn compounds that helped explain the entropy-driven stabilization of known Cu-Sn phases. The study demonstrates the benefits of guiding structure searches with machine learning potentials and significantly expands the number of predicted thermodynamically stable crystalline intermetallics achieved with this strategy so far

Low velocity quantum reflection of Bose-Einstein condensates

We studied quantum reflection of Bose-Einstein condensates at normal incidence on a square array of silicon pillars. For incident velocities of 2.5-26 mm/s observations agreed with theoretical predictions that the Casimir-Polder potential of a reduced density surface would reflect slow atoms with much higher probability. At low velocities (0.5-2.5 mm/s), we observed that the reflection probability saturated around 60% rather than increasing towards unity. We present a simple model which explains this reduced reflectivity as resulting from the combined effects of the Casimir-Polder plus mean field potential and predicts the observed saturation. Furthermore, at low incident velocities, the reflected condensates show collective excitations.Comment: 4 figure

Triggering Postural Movements With Virtual Reality Technology in Healthy Young and Older Adults: A Cross-Sectional Validation Study for Early Dementia Screening

With the ultimate aim of early diagnosis of dementia, a new body balance assessment system with integrated head-mounted display-based virtual reality (VR) has been developed. We hypothesized that people would sway more in anterior-posterior (AP) direction when they were exposed to a VR environment where we intentionally provoked movements in forward and backward directions. A total of 14 healthy older adults (OA) (73.14±4.26 years) and 15 healthy young adults (YA) (24.93±1.49 years) were assessed for group differences in sway behavior. Body sway speed in 22 different conditions with and without VR environments was analyzed. Significant differences and large effect sizes were observed in AP sway under the VR environments (OA with P 0.61, YA with P 0.72) compared to the baseline condition without the VR environments. In addition, significant differences were found between the two groups in AP sway in all test conditions (P < 0.01). Our study shows that a VR environment can trigger body sway in an expected direction, which may indicate that it is possible to enhance the sensitivity of balance assessment by integrating immersive VR environments. The result of this study warrants a cross-sectional study in which OA diagnosed with and without dementia are compared on their sway behavior