Search results for: learning text

Authors: Mahfoodh Saleh Al Sabbagh, Venkoba Rao

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There is plenty of research, both in academic and consultancy circles, about the importance and benefits of employee engagement and customer engagement and how it gives organization an opportunity to reduce variability and improve performance. Customer engagement is directly related to the engagement level of the organization's employees. It is therefore important to measure both. This research drawing from the work of Human Sigma by Fleming and Asplund, attempts to assess engagement level of customer and employees - the human systems of business - in an educational setup. Student is important to an educational institute and is a customer to be served efficiently and effectively. Considering student as customer and faculty as employees serving them, in–depth interviews were conducted to analyze the relationship between faculty and student engagement in two leading colleges in Oman, one from private sector and another from public sector. The study relied mainly on secondary data sources to understand the concept of engagement. However, the search of secondary sources was extensive to compensate the limited primary data. The results indicate that high faculty engagement is likely to lead to high student engagement. Engaged students were excited about learning, loved the feeling of they being cared as a person by their faculty and advocated the organization to other. The interaction truly represents an opportunity to build emotional connection to the organization. This study could be of interest to organizations interest in building and maintaining engagement with employees and customers.

Keywords: customer engagement, consumer psychology, strategy, educational institutes

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Authors: Abhijeet Ostawal, Parmjit Lall

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The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

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Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

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Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: Waleed Alanzi

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The purpose of this qualitative study was to add to the existing literature and provide a more detailed understanding of the individual experiences and perceptions of 15 Deans at the University of Kuwait regarding their first year of planning, developing, and implementing crisis distance education (CDE) in response to the COVID-19 epidemic. An interpretative phenomenological approach was applied, using the thematic analysis of interview transcripts to describe the challenging journeys taken by each of the Deans from the first-person point of view. There was objective evidence, manifested by four primary themes (“Obstacles to the implementation of CDE”; “Planning for CDE”; “Training for CDE,” and “Future Directions”) to conclude that the faculty members, technical staff, administrative staff, and students generally helped each other to overcome the obstacles associated with planning and implementing CDE. The idea that CDE may turn homes into schools and parents into teachers was supported. The planning and implementation of CDE were inevitably associated with a certain amount of confusion, as well as disruptions in the daily routines of staff and students, as well as significant changes in their responsibilities. There were contradictory ideas about the future directions of distance education after the pandemic. Previous qualitative research on the implementation of CDE at higher education institutions in the Arab world has focused mainly on the experiences and perceptions of students; however, little is known about the experiences and perceptions of the students at the University of Kuwait during the COVID19 pandemic, providing a rationale and direction for future research.

Keywords: distance learning, qualitative research, COVID-19 epidemic, Kuwait university

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Christopher Leung, Tony Kim, Rebecca Lendzion, Scott Mackenzie

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Retroperitoneal abscesses are a rare but serious condition with often delayed diagnosis, non-specific symptoms, multiple causes and high morbidity/mortality. With the advent of more readily available cross-sectional imaging, retroperitoneal abscesses are treated earlier and better outcomes are achieved. Occasionally, a retroperitoneal abscess is present as a huge retroperitoneal abscess, as evident in this 53-year-old male. With a background of chronic renal disease and left partial nephrectomy, this gentleman presented with a one-month history of left flank pain without any other symptoms, including fevers or abdominal pain. CT abdomen and pelvis demonstrated a huge retroperitoneal abscess spanning from the diaphragm, abutting the spleen, down to the iliopsoas muscle and abutting the iliac vessels at the pelvic brim. This large retroperitoneal abscess required open drainage as well as drainage by interventional radiology. A long course of intravenous antibiotics and multiple drainages was required to drain the abscess. His blood culture and fluid culture grew Proteus species suggesting a urinary source, likely from his non-functioning kidney, which had a partial nephrectomy. Such a huge retroperitoneal abscess has rarely been described in the literature. The learning point here is that the basic principle of source control and antibiotics is paramount in treating retroperitoneal abscesses regardless of the size of the abscess.

Keywords: retroperitoneal abscess, retroperitoneal mass, sepsis, genitourinary infection

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: Soofia Malik

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The purpose of this study is to develop an instrument to measure undergraduate students’ attitudes toward mathematics (MAT) and to assess the data collected from the instrument for validity and reliability. The instrument is developed using five subscales: anxiety, enjoyment, self-confidence, value, and technology. The technology dimension is added as the fifth subscale of attitude toward mathematics because of the recent trend of incorporating online homework in mathematics courses as well as due to heavy reliance of higher education on using online learning management systems, such as Blackboard and Moodle. The sample consists of 163 (M = 82, F = 81) undergraduates enrolled in College Algebra course in the summer 2017 semester at a university in the USA. The data is analyzed to answer the research question: if and how do undergraduate students’ attitudes toward mathematics load using Principal Components Analysis (PCA)? As a result of PCA, three subscales emerged namely: anxiety/self-confidence scale, enjoyment, and value scale. After deleting the last five items or the last two subscales from the initial MAT scale, the Cronbach’s alpha was recalculated using the scores from 20 items and was found to be α = .95. It is important to note that the reliability of the initial MAT form was α = .93. This means that employing the final MAT survey form would yield consistent results in repeated uses. The final MAT form is, therefore, more reliable as compared to the initial MAT form.

Keywords: college algebra, Cronbach's alpha reliability coefficient, Principal Components Analysis, PCA, technology in mathematics

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Authors: Qiao Mao

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There is a growing number of studies concerning STEM (Science, Technology, Engineering, and Mathematics) and STEAM (Science, Technology, Engineering, Arts, and Mathematics). However, the research is little on STEAM competitions from Arts' perspective. This study takes the annual PowerTech STEAM competition in Taiwan as an example. In this activity, students are asked to make wooden bionic mechanical beasts on the spot and participate in a model and speed competition. This study aims to explore how Arts influences STEM after it involves in the making of mechanical beasts. A case study method is adopted. Through expert sampling, five prize winners in the PowerTech Youth Science and Technology Creation Competition and their supervisors are taken as the research subjects. Relevant data which are collected, sorted out, analyzed and interpreted afterwards, derive from observations, interview and document analyses, etc. The results of the study show that in the PowerTech Youth Science and Technology Creation Competition, when Arts involves in STEM, (1) it has an impact on the athletic performance, balance, stability and symmetry of mechanical beasts; (2) students become more interested and more creative in making STEAM mechanical beasts, which can promote students' learning of STEM; (3) students encounter more difficulties and problems when making STEAM mechanical beasts, and need to have more systematic thinking and design thinking to solve problems.

Keywords: PowerTech, STEAM contest, mechanical beast, arts' role

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, Samut Songkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: 1. The identity of Amphur (District) Mueang, Samut Songkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. 2. The communication of the identity of Amphur Mueang, Samut Songkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of Amphur Mueang, Samut Songkram province 2) Wat Phet Samut Worrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep Amphur Mueang, Samut Songkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: David Ross Cameron

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In an attempt to alleviate the educational planning problem, double-shift schools have been created throughout various regions in Jordan, namely communities closer to the Syrian border, where a large portion of the refugee population settled, allowing Jordanians to attend the morning-shift and Syrians to attend the afternoon-shift. Subsequently, overcrowded classrooms have added a significant amount of stress on school facilities and teacher capacities. Established national policies and the implementation of inclusive educational practices have been jeopardized. In particular, teachers’ and student’s attitudes of the importance of inclusive education provisions in the classroom have deteriorated. To have a more comprehensive understanding of the current situation and possible plan for intervention, a focus study was carried out at a double-shift Jordanian/Syrian girls’ public school in Irbid, Jordan. Interviews and surveys of 29 students with physical, learning, emotional and behavioral disabilities, 33 students without any special needs and nine teachers were included with a mixed-method social research approach to highlight the current attitudes that students and teachers held and factors that contributed to shaping their inclinations and beliefs of inclusive education.

Keywords: capacity building, development, double-shift, Irbid, inclusive education, Jordan, pedagogy, planning, policy, refugee, special education, special needs, vulnerable population

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Dudu Ka Ruth Mkhize

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Adolescents are at the front and centre of poor mathematics performance in schools. Literature has concluded in some countries that there is a permanent and perpetual mathematics crisis in schools of the persistent poor performance in mathematics by teens. There is no shortage of interventions and research to solve this problem. However, none has capitalised on the cognitive prowess of adolescents, which was revealed at the turn of the century by the introduction of neuroimaging technologies such as structural and functional magnetic resonance imaging (sMRI and fMRI). This research found that brain growth during adolescence results in enhanced cognitive abilities essential for mathematics learning. This paper is based on the four-year case study of rural high school adolescents who had a negative attitude towards mathematics and hence were failing mathematics. But through a ten-day intervention where teaching revolved around invoking their cognitive ability, their attitude and motivation for mathematics changed for the better. The paper concludes that despite educational psychology being part of teacher education as well as education systems, there are numerous overlooked gems of psychological theories which have the potential to enhance academic achievement for youth in schools. A recommendation is made to take cues from positive psychology, whose establishment was a rejection of the dominance of the disease model in psychology. Similarly, the general perspective of poor mathematics performance can take a u-turn towards the cognitive ability acquired by adolescents because of their developmental stage.

Keywords: adolescence, cognitive growth, mathematics performance

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Kathryn Norgang, Sarah Howrath, Auni Idi Muhire, Pacifique Umubyeyi

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Description : A group of nurses address the shortage of trained staff to respond to critical patients at Rwanda Military Hospital (RMH) by developing a training program and a resuscitation response team. Members of the group who received the training when it first launched are now trainer of trainers; all components of the training program are organized and delivered by RMH staff-the clinical mentor only provides adjunct support. This two day training is held quarterly at RMH; basic life support and exposure to interventions for advanced care are included in the test and skills sign off. Seventy staff members have received the training this year alone. An increased number of admission/transfer to ICU due to successful resuscitation attempts is noted. Lessons learned: -Number of staff trained 2012-2014 (to be verified). -Staff who train together practice with greater collaboration during actual resuscitation events. -Staff more likely to initiate BLS if peer support is present-more staff trained equals more support. -More access to Advanced Cardiac Life Support training is necessary now that the cadre of BLS trained staff is growing. Conclusions: Increased access to training, peer support, and collaborative practice are effective strategies to strengthening resuscitation capacity within a hospital.

Keywords: resuscitation, basic life support, capacity building, resuscitation response teams, nurse trainer of trainers

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Authors: Nur Amalina Dayana Abd Aziz

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Assessment is an integral part of teaching and learning in any syllabus in the world. Recently, a new assessment system, School-Based Assessment (SBA) was introduced and implemented in the Malaysian education system to promote a more holistic, integrated and balanced assessment system. This effort is part of the reformation made in the Government Transformation Plan (GTP) to produce a world-class human capital as we are reaching and achieving the Vision 2020 in the near future. However, this new change has raised awareness and concerns from teachers, students, parents and non-profit organizations on how the new assessment is to be implemented and how it is affecting the students and teachers particularly. Therefore, this paper aims to investigate the issues that teachers face in implementing SBA in primary schools, the measures taken to address the issues and to propose ways of managing school-based assessment. Five national primary schools focusing in the urban areas in the Selangor state are chosen for this study to carry out. Data for the study will be gathered from interviews with teachers from each school, surveys and classrooms observation will be conducted in each school, and relevant documents are collected from the selected schools. The findings of this study will present the current issues that teachers from various types of national primary schools are facing and what actions they took to overcome the problems in carrying out SBA. Suggestions on how to better manage school-based assessment for teachers are also provided in this paper.

Keywords: community of practice, curriculum, managing change, school-based assessment

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Authors: Yasser Aminifard, Hamdollah Askari

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This study aimed at investigating any difference between Iranian senior high school students' performance on Academic Words (AWs) and Everyday-Life Words (ELWs). To this end, in the first phase, a number of 120 male senior high school students were randomly selected from among twelve high schools in Gachsaran to serve as the participants of the study. In the second phase, using purposive sampling, six high school teachers holding an MA in TEFL and with over twenty years of teaching experience were interviewed. Two multiple-choice tests, each comprising 40 items, were given to the participants in order to determine their performance on AWs and ELWs and follow-up semi-structured interviews were conducted to explore teachers' opinions about participants' performance on the two tests. To analyze the data, a paired-samples t-test was carried out to compare the results of both tests and the interviews were also transcribed to pinpoint important themes. The results of the t-test indicated that the participants performed significantly better on AWs than on ELWs. Additionally, results of the interviews boiled down to the fact that the English textbooks designed for Iranian high school students are fundamentally flawed on the grounds that there is a mismatch between students' real language learning needs and what is presented to them as "teaching-to-the-test" materials via these books. Finally, the implications and suggestions for further research are discussed.

Keywords: everyday-life words, academic words, textbooks, washback

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Authors: Hanae Ait Hattani, Nohaila Ait Hattani

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Globalization, with the rapid technological progress, is affecting every life aspect. The 21st century higher education faces a major challenge in preparing well-rounded and competent graduates to compete in the global marketplace. Worldwide, educational policies work to develop the quality of instruction at all educational levels by focusing on promoting students’ qualifications and skills, considering both academic activities and non-academic attributes. In fact, extracurricular activities (ECAs) complement the academic curriculum and enhance the student experience by improving their interpersonal skills and attitudes. This study comes to examine the potential of extracurricular activities as a vital tool for soft skills’ development. Using empirical research, the study aims to measure and evaluate the extent to which university students’ engagement in extracurricular activities contribute in positively changing their learning experience, fostering their soft skills and fostering their behaviors and attitudes. Findings emanating from a questionnaire and semi-structured interviews add a number of contributions to the literature. They support the assumption suggesting that ECAs can be considered a valuable way to acquire, develop, and demonstrate softs skills that students today need to evidence in a variety of contexts, such as communication skills, team work, leadership, problem-solving, to name but a few.

Keywords: extracurricular activities (ECAs), soft skills, education, university, attitude

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: image registration techniques, medical images, neural networks, optimisaztion, transformation

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Authors: Nicholas P. Fenlon, Aisling Lavelle, David Mclean, Margaret O'riordan

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Background: The case for continuing professional development has been well made, and was formalized in Ireland in recent years through the enactment of the Medical Practitioner’s Act, which requires registered medical practitioners to complete a minimum of 50 hours CPD each year. The ICGP, who have been providing CPD opportunities to its members for many years, have responded to this need by developing a series of evidence-based, high-quality, multimedia modules across a range of clinical and non-clinical areas. (More traditional education opportunities are still being provided by the college also). Overview of Programme: The first module was released in September 2011, since when the eLearning program has grown steadily, and there are currently almost 20 modules available, with a further 5 in production. Each module contains three to six 10-minute video lessons, which use a combination of graphics, images, text, voice-over and clinical clips. These are supported by supplementary videos of expert pieces-to-camera, Q&As with content experts, clinical scenarios, external links and relevant documentation and other resources. Successful completion of MCQs will result in a Certificate of Completion, which can be printed or stored in Professional Competence portfolio. The Medical Practitioner’s Act requires doctors to gather CPD credits across 8 domains of practice, and various eLearning modules have been developed to address each. For instance, modules with a strong clinical content would include Management of Hypertension, Management of COPD, and Management of Asthma. Other modules focus on health promotion such as Promoting Smoking Cessation, Promoting Physical Activity, and Addressing Childhood Obesity. Modules where communication skills are keys include modules on Suicide Prevention and Management of Depression. Other modules, currently in development include non-clinical topics around risk management, including Confidentiality, Consent etc. Each module is developed by a core group, which includes where possible, a GP with a special interest in the area, and a content expert(s). The college works closely with a medical education consultant and a production company in developing and producing the modules. Modules can be accessed (with password) through the ICGP website and are available free to all ICGP members. Summary of Evaluation: There are over 1700 registered users to date (over 55% of College membership). The program was evaluated using an online survey in 2013 (N = 144/950 – 12%) and results were very positive overall but provided material for the further improvement of the program also. Future Plans: While knowledge can be imparted well through eLearning, skills and attitudes are more difficult to influence through an online environment. The college is now developing a series of linked workshops, which will lead to ICGP Professional Competence Awards. The first pilot workshop is scheduled for February 2015 and is Cardiology-themed. Participants will be required to complete the following 4 modules in advance of attending – Management of Hypertension, Management of Heart Failure, Promoting Smoking Cessation, and Promoting Physical Activity. The workshop will be case-based and interactive, addressing ECG Interpretation in General Practice. Conclusions: The ICGP have responded to members needs for high-quality evidence-based education delivered in a way that suits GPs.

Keywords: CPD opportunities, evidence-based, high quality, multimedia modules across a range of clinical and non-clinical areas, medical practitioner’s act

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Authors: Twarakavi Venkata Suresh Kumar, Sailaja Kumar, B. Eswara Reddy

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In a world of tremendous technical developments, effective and efficient higher education has always been a major challenge. The rising number of educational institutions have made it mandatory for healthy competitions among the institutions. To evaluate the qualitative competence of these educations institutions in engineering and technology and related disciplines, an efficient assessment technique in internal and external quality has to be followed. To achieve this, the curriculum is to be developed into courses, and each course has to be presented in the form teaching lesson plan consisting of topics and session outcome known as Course Outcomes (COs), that easily map into different Programme Outcomes (POs). The major objective of these methodologies is to provide quality technical education to its students. Detailed clear weightage in CO-PO mapping helps in proper measurable COs and to devise the POs attainment is an important issue. This ensures in assisting the achievement of the POs with proper weightage to POs, and also improves the successive curriculum development. In this paper, we presented a methodology for mapping CO and PO considering the key elements supported by each PO. This approach is useful in evaluating the attainment of POs which is based on the attainment of COs using the existing data from students' marks taken from various test items. Such direct assessment tools are used to measure the degree to which each student has achieved each course learning outcome by the completion of the course. Hence, these results are also useful in measuring the PO attainment for improving the programme vision and mission.

Keywords: attainment, course outcomes, programme outcomes, educational institutions

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Authors: Syahruddin Sumardi Samindjaya, Indra Fajar Alamsyah, Junaidah Hashim

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Purpose: This study attempts to explore and presents a proposed recruitment model in Islamic university which aligned with holistic role. Design/methodology/approach: It is a conceptual paper in nature. In turn, this study is designed to utilize exploratory approach. Literature and document review that related to this topic are used as the methods to analyse the content found. Findings: Recruitment for any organization is fundamental to achieve its goal effectively. Staffing in universities is vital due to the important role of lecturers. Currently, Islamic universities still adopt the common process of recruitment for their academic staffs. Whereas, they have own characteristics which are embedded in their institutions. Furthermore, the FCWC (Foundation, Capability, Worldview and Commitment) model of recruitment proposes to suit the holistic character of Islamic university. Research limitation/implications: Further studies are required to empirically validate the concept through systematic investigations. Additionally, measuring this model by a designed means is appreciated. Practical implications: The model provides the map and alternative tool of recruitment for Islamic universities to determine the process of recruitment which can appropriate their institutions. In addition, it also allows stakeholders and policy makers to consider regarding Islamic values that should inculcate in the Islamic higher learning institutions. Originality/value: This study initiates a foundational contribution for an early sequence of research.

Keywords: academic staff, Islamic values, recruitment model, university

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Authors: Neusa Fernanda Torres, Buyisile Chibi, Lyn E. Middleton, Vernon P. Solomon, Tivani P. Mashamba-Thompson

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Background: Self-medication with antibiotics (SMA) is a global concern, with a higher incidence in low and middle-income countries (LMICs). Despite intense world-wide efforts to control and promote the rational use of antibiotics, continuing practices of SMA systematically exposes individuals and communities to the risk of antibiotic resistance and other undesirable antibiotic side effects. Moreover, it increases the health systems costs of acquiring more powerful antibiotics to treat the resistant infection. This review thus maps evidence on the factors influencing self-medication with antibiotics in these settings. Methods: The search strategy for this review involved electronic databases including PubMed, Web of Knowledge, Science Direct, EBSCOhost (PubMed, CINAHL with Full Text, Health Source - Consumer Edition, MEDLINE), Google Scholar, BioMed Central and World Health Organization library, using the search terms:’ Self-Medication’, ‘antibiotics’, ‘factors’ and ‘reasons’. Our search included studies published from 2007 to 2017. Thematic analysis was performed to identify the patterns of evidence on SMA in LMICs. The mixed method quality appraisal tool (MMAT) version 2011 was employed to assess the quality of the included primary studies. Results: Fifteen studies met the inclusion criteria. Studies included population from the rural (46,4%), urban (33,6%) and combined (20%) settings, of the following LMICs: Guatemala (2 studies), India (2), Indonesia (2), Kenya (1), Laos (1), Nepal (1), Nigeria (2), Pakistan (2), Sri Lanka (1), and Yemen (1). The total sample size of all 15 included studies was 7676 participants. The findings of the review show a high prevalence of SMA ranging from 8,1% to 93%. Accessibility, affordability, conditions of health facilities (long waiting, quality of services and workers) as long well as poor health-seeking behavior and lack of information are factors that influence SMA in LMICs. Antibiotics such as amoxicillin, metronidazole, amoxicillin/clavulanic, ampicillin, ciprofloxacin, azithromycin, penicillin, and tetracycline, were the most frequently used for SMA. The major sources of antibiotics included pharmacies, drug stores, leftover drugs, family/friends and old prescription. Sore throat, common cold, cough with mucus, headache, toothache, flu-like symptoms, pain relief, fever, running nose, toothache, upper respiratory tract infections, urinary symptoms, urinary tract infection were the common disease symptoms managed with SMA. Conclusion: Although the information on factors influencing SMA in LMICs is unevenly distributed, the available information revealed the existence of research evidence on antibiotic self-medication in some countries of LMICs. SMA practices are influenced by social-cultural determinants of health and frequently associated with poor dispensing and prescribing practices, deficient health-seeking behavior and consequently with inappropriate drug use. Therefore, there is still a need to conduct further studies (qualitative, quantitative and randomized control trial) on factors and reasons for SMA to correctly address the public health problem in LMICs.

Keywords: antibiotics, factors, reasons, self-medication, low and middle-income countries (LMICs)

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Authors: Momen Yaseen M. Amin

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Despite widespread coverage of language policy in the literature, there has been scant research probing into English language education policy at tertiary levels in general and in the case of higher education context of Iraqi Kurdistan in particular. The present qualitative study investigated the results of a questionnaire on attitudes toward English language education policy in terms of attitudes toward the English language in general, the current English education policy, and the purposes for learning English among Kurdish EFL university students. Moreover, this study aimed to investigate this topic in light of the participants’ gender and major. To this end, an adapted version of Yang’s (2012) questionnaire was administered to university EFL students majoring in soft and hard sciences (N=300, male 34%, female 67%, four and two disciplines, respectively) at two-state and private universities in Iraqi Kurdistan. The findings revealed positive attitudes toward English as an international language in both soft and hard sciences. While strongly subscribing to the idea that all Iraqi Kurdish students should learn the English language and the courses to be offered in English as well as Kurdish, the majority of the participants expressed their readiness and enthusiasm to excel in English and considered such competency a significant academic accomplishment. However, a good number felt dissatisfied with the status quo of English education at their institutions. This paper provides some implications and recommendations for English education policies makers, administrators, and English language instructors at tertiary levels.

Keywords: attitudes, language policy, English language education, Iraqi Kurdistan

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Authors: Rewadee Ungpho

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The research on the musical culture of Sea Gypsies in Bulon archipelago, Satun Province, is considered as an anthropology research. Research objectives were to study the history and information culture and also to find the basis information for the restoration and preservation of the music culture of Sea Gypsies who live in Bulon archipelago. Findings of the research are as follows: 1) Musical characteristics of Sea Gypsies in Bulon archipelago is still traditional. It does not mix with any external musical influence such as musical instruments, language, and other musical characteristics. There are various kind of songs which can play a complete melody and rhythm, including a total of 8 songs as follows; Lagu-Ayam-Dide, Lagu-Sitipayong, Lagu-Bulong-pute, Lagu-Chemamat, Laguduwo, Lagu-Ma-I-nang, Lagu-Mana-Ikan. 2) The roles of culture/music in Bulon archipelago correlate with Urak Lawoi society. They use music in the ceremony of votive offering, in the floating ceremony held in Lipe Island and in various festivals. Therefore, music is a spiritual sacrifice and a spiritual instrument that conveys an Urak Lawoi, which makes the Urak Lawoi still unique and has a sense of ethnic identity. 3) The inheritance of Urak Lawoi music is still being made in a traditional way, as an oral tradition with no record. The teaching and learning must be one on one, and it required length of time to practice and accumulate the knowledge. Due to above mentioned reasons, a few people attend in the inheritance. Those who are interested may not be able to practice constantly. As a result, there is only a few, or even none, descendants left.

Keywords: sea gypsy, music, Bulon archipelago, ethnomusicology

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

Procedia PDF Downloads 435