Search results for: EFL learning/ teaching

Authors: Getaneh Berie Tarekegn

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Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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Authors: Chuen-arom Janthimachai-amorn, Chirawadee Harnrittha

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This study aims to identify the factors facilitating the knowledge management to develop the graduate study programs to achieve success and to identify the approaches in developing the graduate study programs in the Rajbhat Suansunantha University. The 10 respondents were the administrators, the faculty, and the personnel of its Graduate School. The research methodology was based on Pla-too Model of the Knowledge Management Institute (KMI) by allocating the knowledge indicators, the knowledge creation and search, knowledge systematization, knowledge processing and filtering, knowledge access, knowledge sharing and exchanges and learning. The results revealed that major success factors were knowledge indicators, evident knowledge management planning, knowledge exchange and strong solidarity of the team and systematic and tenacious access of knowledge. The approaches allowing the researchers to critically develop the graduate study programs were the environmental data analyses, the local needs and general situations, data analyses of the previous programs, cost analyses of the resources, and the identification of the structure and the purposes to develop the new programs.

Keywords: program development, knowledge management, graduate study programs, Rajbhat Suansunantha University

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Authors: Mara A. C. Lopes

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Hiring a second teacher to accompany deaf students inserted at Brazilian inclusive school system has raised questions about its role in the educational process of deaf students. Federal policies determine that deaf students inserted in regular education are accompanied by sign language interpreters, which leads to the understanding that the second teacher should assume this function. However, what those professionals do is to assume the function of teaching deaf student, instead of the classroom main teacher. Historical-Cultural Psychology was used as a reference for analysis, which aimed to identify the social function of the second teacher in the classroom. Two studies were accomplished in the public schools of Sao Paulo State: In Study 1, videotaped lectures provided by the Department of Education for collective reflection about the second teacher's role were examined, to identify the social meaning of that professional activity. Study 2 aimed to analyze the process of assigning personal sense to the teacher activity, considering the opinions of 21 professionals from Sao Paulo. Those teachers were interviewed individually with the support of a semi-structured interview. The analysis method utilized was: empirical description of data; development of categories, for reality abstraction; identifying the unit analysis; and return to reality, in order to explain it. Study 1 showed that the social meaning of the second teacher's activity is, also, to teach. However, Study 2 showed that this meaning is not shared among professionals of the school, so they understand that they must act as sign language interpreters. That comprehension causes a disruption between social meaning and the personal sense they attach to their activity. It also shows the need of both teachers at the classroom planning and executing activity together. On the contrary, a relationship of subordination of one teacher to another was identified, excluding the second teacher and the deaf student of the main activity. Results indicate that the second teacher, as a teacher, must take the responsibility for deaf student education, consciously, and to promote the full development of the subjects involved.

Keywords: deaf education, historical-cultural psychology, inclusion, teacher function

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Authors: Robert Dutkiewicz, Monika Szpringer, Mariola Wojciechowska

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Physical activity is one of the factors greatly influencing healthy lifestyle. The recent research into physical activity of the Polish society reveals that contribution of physical culture to healthy lifestyle is insufficient. Students, regardless of age, spend most of free-time in front of a TV or computer. The research attempted to identify the level of physical activity and healthy lifestyle among students of medical sciences and other students doing their teaching degrees. The findings of physical activity research conducted in 2014, which covered 364 students of medical sciences and future teachers from the University of Jan Kochanowski in Kielce were analysed. The research involved the method of diagnostic survey based on a questionnaire. It attempted to establish to what extent such factors as the field of studies, the place of residence and BMI affect students’ physical activity. Empirical material was analysed by means of SPSS/PC, the leading statistical software. The field of study significantly influences physical activity of the respondents. The students of physiotherapy and public health tend to be more physically active than students of biology and geography: 46.8% students of geography and 51.8 % biology students seldom take up physical activity. Obesity and overweight are currently serious problems of university students: 6.6% of them are obese and 19% overweight. It is alarming that these students are not willing to find ways to be more physically active. Most of the obese and overweight respondents study biology or geography and live in a rural area. Unequal chances in terms of youth physical culture are determined by the differences between rural and urban environments. Young people living in rural areas are less physically active, particularly in terms of the frequency and the amount of time devoted to physical activity. This is caused by poor infrastructure to perform physical activity, the lack of or limited number of sports clubs and centres. It is thought-provoking that most of the students claim that they do not have enough time to do sports or other activities, but at the same time they spend a lot of time at a computer or watching TV.

Keywords: BMI, healthy lifestyle, sports activity, students

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Authors: Alaa Alrakaf, Sk. Md. Mizanur Rahman

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Since the last two decades’ Arabic natural language processing (ANLP) has become increasingly much more important. One of the key issues related to ANLP is ambiguity. In Arabic language different pronunciation of one word may have a different meaning. Furthermore, ambiguity also has an impact on the effectiveness and efficiency of Machine Translation (MT). The issue of ambiguity has limited the usefulness and accuracy of the translation from Arabic to English. The lack of Arabic resources makes ambiguity problem more complicated. Additionally, the orthographic level of representation cannot specify the exact meaning of the word. This paper looked at the diacritics of Arabic language and used them to disambiguate a word. The proposed approach of word sense disambiguation used Diacritizer application to Diacritize Arabic text then found the most accurate sense of an ambiguous word using Naïve Bayes Classifier. Our Experimental study proves that using Arabic Diacritics with Naïve Bayes Classifier enhances the accuracy of choosing the appropriate sense by 23% and also decreases the ambiguity in machine translation.

Keywords: Arabic natural language processing, machine learning, machine translation, Naive bayes classifier, word sense disambiguation

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Authors: Shyam Mehraaj, Samanthi E. R. Siriwardana, Shehara A. K. G. H., Wanigasinghe N. T., Wandana R. A. K., Wedage C. V.

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A presentation is a critical tool for conveying not just spoken information but also a wide spectrum of human emotions. The single most effective thing to make the presentation successful is to practice it beforehand. Preparing for a presentation has been shown to be essential for improving emotional control, intonation and prosody, pronunciation, and vocabulary, as well as the quality of the presentation slides. As a result, practicing has become one of the most critical parts of giving a good presentation. In this research, the main focus is to analyze the audio, video, and slides of the presentation uploaded by the presenters. This proposed solution is based on the Natural Language Processing and Computer Vision techniques to cater to the requirement for the presenter to do a presentation beforehand using a mobile responsive web application. The proposed system will assist in practicing the presentation beforehand by identifying the presenters’ emotions, body language, tonality, prosody, pronunciations and vocabulary, and presentation slides quality. Overall, the system will give a rating and feedback to the presenter about the performance so that the presenters’ can improve their presentation skills.

Keywords: presentation, self-evaluation, natural learning processing, computer vision

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

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The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

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Authors: Mikkel Snorre Wilms Boysen

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From a theoretical perspective, expertise is generally considered a precondition for creativity. The assumption is that an individual needs to master the common and accepted rules and techniques within a certain knowledge-domain in order to create something new and valuable. However, real life cases, and a limited amount of empirical studies, demonstrate that this assumption may be overly simple. In this article, this question is explored through a number of semi-experimental case studies conducted within the fields of music, technology, and youth culture. The studies indicate that, in various ways, expertise plays an important part in creative processes. However, the case studies also indicate that expertise sometimes leads to an entrenched perspective, in the sense that knowledge and experience may work as a path into the well-known rather than into the unknown. In this article, these issues are explored with reference to different theoretical approaches to creativity and learning, including actor-network theory, the theory of blind variation and selective retention, and Csikszentmihalyi’s system model. Finally, some educational aspects and implications of this are discussed.

Keywords: creativity, expertise , education, technology

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Authors: Proud Arunrangsiwed, Sarinya Kongtieng

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Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: meta-regression analysis, social networking sites, academic Performances, multitasking, motivation

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Authors: Aisulu Tileukulova, Zhexebay Dauren

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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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Authors: Greeshma Sharma, Sushil Chandra, Vijander Singh, Alok Prakash Mittal

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Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory.

Keywords: memory, planning navigational ability, virtual reality

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Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

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This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

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Authors: Dalya Markovich

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In the last decade art-educators strive to integrate critical pedagogy within the art classroom. Critical pedagogy aims to deconstruct the oppressive social reality and the false consciousness in which learners from both privileged and underprivileged groups are caught. Understanding oppression as a product of socio-political conditions seeks to instigate processes of change anchored in the student's views. Yet, growing empirical evidence show that these efforts often has resulted in art projects in which art teachers play an active role in the process of critical teaching, while the students remain passive listeners. In this common scenario, the teachers/artists become authoritarian moral guides of critical thinking and acting, while the students are often found to be indifferent or play along to satisfy the teachers'/artists aspirations. These responses indicate that the message of critical pedagogy – transforming the students' way of thinking and acting – mostly do not fulfill its emancipation goals. The study analyses the critical praxis embedded in new art projects and their influence on the participants. This type of projects replaces the individual producer with a collaborative work; switch the finite work with an ongoing project; and transforms the passive learner to an engaged co-producer. The research delves into the pedagogical framework of two of these art projects by using qualitative methods. In-depth interviews were conducted with 4 of the projects' initiator and managers, in order to access understandings of the art projects goals and pedagogical methods. Field work included 4 participant observation (two in each project) during social encounters in the project's settings, focusing on how critical thinking is enacted (or not) by the participants. The analysis exposes how the new art projects avoid the prepackaged "critical" assumptions and praxis, thus turning the participants from passive carriers of critical thinking to agents that actively use criticism. Findings invite researchers to explore new avenues for understanding critical pedagogy and developing various ways to implement critical pedagogy during art education, in view of the growing need of critical thinking and acting in school/society.

Keywords: critical pedagogy, education through art, collaborative work, agency

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Authors: Mohammed Bello Sokoto, Adewumi Babatunde Adebayo, Ajit Singh

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The field experiment was conducted at the dry land Teaching and Research Farm of Usmanu Danfodiyo University, Sokoto, during the 2023 rainy season to determine the effects of organic, inorganic, soil conditioner and integrated use of soil conditioners (Agzyme) with organic (super gro) and inorganic fertilizers on the growth and yield of cowpea varieties. The research consisted of two cowpea varieties (SAMPEA-20-T and ex-GidanYunfa) and six combinations of organic and inorganic fertilizers and soil conditioners factorially combined and laid out in a Randomized Complete Block Design (RCBD) replicated three times. Data were collected on plant height, leaf area index, number of pods per plant, number of seeds per pod, days to 50% flowering, grain yield, and 100 seed weight. Results indicated that the 100% inorganic fertilizer had a significantly increased growth parameter such as plant height and number of leaves, while combined application of the organic fertilizer and soil conditioner resulted in a significant increase in yield parameters such as number of pods per plant, number of seeds per pod, 100 seed weight and grain yield. The study observed that the use of soil conditioner in combination with fertilizers supports sustainable cowpea production. Application of 50% recommended inorganic + 50% soil conditioner or 50% liquid organic + 50% soil conditioner was better in increasing the number of pods/plant, seeds/pod, 100 seed weight and grain yield. The ex-Gidan Yunfa cowpea variety generally performed better in most parameters measured, such as plant height, days to 50% flowering, number of pods per plant, number of seeds per pod, 100 seed weight and grain yield. Therefore, the combined application of 50% recommended inorganic + 50% soil conditioner or 50% liquid organic + 50% soil conditioner is effective for the sustainable production of cowpeas.

Keywords: integrated, fertilizers, growth, yield, cowpea, Sudan Savannah

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Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

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Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Lucia Vodanovic, Bryan Pirolli

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The London College of Communication is one of the only universities in the world to offer a lifestyle journalism master’s degree. A hybrid originally constructed largely out of a generic journalism program crossed with numerous cultural studies approaches, the degree has developed into a leading lifestyle journalism education attracting students worldwide. This research project seeks to present a framework for structuring the degree as well as to understand how students in this emerging field of study value the program. While some researchers have addressed questions about journalism and higher education, none have looked specifically at the increasingly important genre of lifestyle journalism, which Folker Hanusch defines as including notions of consumerism and critique among other identifying traits. Lifestyle journalism, itself poorly researched by scholars, can relate to topics including travel, fitness, and entertainment, and as such, arguably a lifestyle journalism degree should prepare students to engage with these topics. This research uses the existing Masters of Arts and Lifestyle Journalism at the London College of Communications as a case study to examine the school’s approach. Furthering Hanusch’s original definition, this master’s program attempts to characterizes lifestyle journalism by a specific voice or approach, as reflected in the diversity of student’s final projects. This framework echoes the ethos and ideas of the university, which focuses on creativity, design, and experimentation. By analyzing the current degree as well as student feedback, this research aims to assist future educators in pursuing the often neglected field of lifestyle journalism. Through a discovery of the unique mix of practical coursework, theoretical lessons, and broad scope of student work presented in this degree program, researchers strive to develop a framework for lifestyle journalism education, referring to Mark Deuze’s ten questions for journalism education development. While Hanusch began the discussion to legitimize the study of lifestyle journalism, this project strives to go one step further and open up a discussion about teaching of lifestyle journalism at the university level.

Keywords: education, journalism, lifestyle, university

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Authors: Stephen Rulisa, Aimee Nyiramahirwe

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Background: Strategies to increase the uptake of contraception services have been adopted in Rwanda, but the unmet need for family planning remains high. Women in the postpartum period are at higher risk for unintended pregnancy due to the silent conversion from lactational amenorrhea to reactivation of ovulatory cycles. The purpose of this study was to explore the role of male partners in the uptake of postpartum contraception. Methods: A prospective cross-sectional study was conducted among women who delivered at the University Teaching Hospital of Kigali for a period of 3 months with random sampling. A questionnaire was used to collect socio-demographic and antenatal data, information on male companionship, and intent to use postpartum contraception at admission. Participants were contacted six weeks later to collect data on contraceptive use. The outcome variables were uptake of postpartum contraception and types of contraceptives taken (long-acting vs. short-acting), controlling for male companionship during the antenatal period. A Chi-square test was used and a p-value ≤0.05 was considered significant. Results: A total of 209 women were recruited with a mean age of 30.8±5.2 years. The majority (60.9%) were multigravida, and 66.5% were multiparous. More than half (55%) had male partner companionship, 18.3% had companionship for four antenatal visits, and 28.2% had education on contraception with their male partner. Factors significantly associated with uptake of postpartum contraception were: age above 30 years, owning or heading a business, multigravidity, multiparity, antenatal care at a health center or district hospital, cesarean delivery, and previous utilization of contraception. Male companionship significantly increased the intent to use contraception, uptake of modern contraception in general, and uptake of long active contraceptives but did not predict the uptake of short-acting contraceptives. Conclusions: Our study demonstrates a positive association between male companionship during antenatal care, labor and delivery with the uptake of postpartum family planning. Our study suggests more sensitization to involve the male partners, improving the education on contraception during antenatal care and further research to assess the sustained uptake of contraception beyond the postpartum period.

Keywords: postpartum, family planning, contraception, male partner, uptake

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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Authors: Shizrah Jamal, Robia Ghafoor, Farhan Raza

Abstract:

Porcelain fused to metal crown is the most versatile variety of crown that is commonly placed worldwide. Various complications have been reported in the PFM crowns with use over the period of time. These include chipping of the porcelain, recurrent caries, loss of retention, open contacts, and tooth fracture. The objective of the present study was to determine the frequency of these complications in crowns cemented over a period of five years in a tertiary care hospital and also to report the survival of these crowns. A retrospective study was conducted in Dental clinics, Aga Khan University Hospital in which 150 PFM crowns cemented over a period of five years were evaluated. Patient demographics, oral hygiene habits, para-functional habits, crown insertion and follow-up dates were recorded in a specially designed proforma. All PFM crowns fulfilling the inclusion criteria were assessed both clinically and radiographically for the presence of any complication. SPSS version 22.0 was used for statistical analysis. Frequency distribution and proportion of complications were determined. Chi-square test was used to determine the association of complications of PFM crowns with multiple variables including tooth wear, opposing dentition and betel nut chewing. Kaplan- meier survival analysis was used to determine the survival of PFM crowns over the period of five years. Level of significance was kept at 0.05. A total of 107 patients, with a mean age of 43.51 + 12.4 years, having 150 PFM crowns were evaluated. The most common complication observed was open proximal contacts (8.7%) followed by porcelain chipping (6%), decementation (5.3%), and abutment fracture (1.3%). Chi square test showed that there was no statistically significant association of PFM crown complication with tooth wear, betel nut and opposing dentition (p-value <0.05). The overall success and survival rates of PFM crowns turned out to be 78.7 and 84.7% respectively. Within the limitations of the study, it can be concluded that PFM crowns are an effective treatment modality with high success and survival rates. Since it was a single centered study; the results should be generalized with caution.

Keywords: chipping, complication, crown, survival rate

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Authors: Sandra Figueiredo

Abstract:

To guarantee the well-being and the academic achievement it is crucial into the global society to develop techniques to assess language competence and control psychological aspects on the second language learning context. The current scenario of the war conflicts that are emerging mostly in Europe and Middle East have been resulting in forced immigration and refugees’ maladjustment. The inclusion is the priority for United Nations concerning the sustainability of societies. For inclusion, psychological screening tests and educational tools are urgent. Method: Approximately 100 refugees from Ukraine were assessed, in Portugal, under the administration of the PCL-5. This 20-item instrument evaluates the Post-Traumatic Disorder. Expected results: The statistical analysis will be performed with the International Database Analyzer and SPSS (v. 28). The results expected are the relationship between traumatic events caused by war and post-traumatic symptomatology (anxiety, hypervigilance, stress). Implications: The data will be discussed concerning the problems of belonging, the psychological constraints and educational attainment (language needs included) experienced by the individuals more recently arrived to the hosting societies. The refugees’ acculturation process and the emotional regulation will be addressed.

Keywords: refugees, immigration, educational needs, trauma, inclusion, second language.

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Authors: Wanghongshu Zhou

Abstract:

This study aims to explore the relationship between the L2MSS and WTC among Chinese non-English major students in order to provide pedagogical implications for English as a Foreign Language (EFL) classrooms in Chinese universities. By employing a mixed methods approach, we involved 103 Chinese non-English major students from a typical university in China, conducted questionnaire survey to measure their levels of L2WTC and L2MSS level, and then analyzed the correlation between the two above mentioned variables. Semi-structured interviews were conducted with eight participants to provide a deeper understanding and explanation of the questionnaire data. Findings show that 1) Chinese non-English major students’ ideal L2 self and L2 learning experience could positively predict their L2 WTC in EFL class; 2) Chinese non-English major students’ ought-to L2 self might have no significant impact on their L2 WTC in EFL class; and 3) self-confidence might be another main factor that will influence Chinese non-English major students’ L2 WTC in EFL class. These findings might shed light on the second language acquisition field and provide pedagogical recommendations for pre-service as well as in-service EFL teachers.

Keywords: L2 willingness to communicate, L2 motivation, self-confidence, Chinese non-English major students

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Authors: Selaphares Jatico Tajale

Abstract:

This research aims to understand the notions of quality education by conducting case studies among internationally-accredited Christian schools in Southeast Asia. Five internationally-accredited Christian schools from Cambodia, Indonesia, Malaysia, The Philippines, and Singapore will be chosen as cases for this study. This study will utilize the processes of interviews, filling up of questionnaires, and writing of reflections in order to obtain data and relevant information. These processes will be conducted through multi-sectoral respondents such as administrators, academic heads, and faculty. This study employs five aspects within the realm of education as guides in the formulation of questionnaire and guide questions in the interview, namely: a) school context, b) classroom, c) quality assurance, d) stakeholders, e) faculty and staff. Guide interview questions and questions in the questionnaires are formulated to uncover information on how those five aspects were managed to achieve desired student learning outcomes and uncover other information useful for the study.

Keywords: internationally-accredited, notions of quality education, quality education, quality education in Southeast Asia

Procedia PDF Downloads 236

Authors: Bilal Liaqat, Muhammad Umar, Zara Bashir, Hassan Rafique, Mohsin Abbasi, Zarak Khan

Abstract:

Transformational leadership is one of the most studied topics in the organization sciences. However, the impact of transformational leadership on employee’s individual attributes have not yet been studied. Purpose: This research aims to discover the relationship between transformational leadership and employee motivation, performance and creativity. Moreover, the study will also investigate the influence of transformational leadership on employee performance through employee motivation and employee creativity. Design-Methodology-Approach: The data was collected from employees in different organization. This cross-sectional study collected data from employees and the methodology used includes survey data that were collected from employees in organizations. Structured interviews were also conducted to explain the outcomes from the survey. Findings: The results of this study reveal that transformational leadership has a positive impact on employee’s individual attributes. Research Implications: Although this study expands our knowledge about the role of learning orientation between transformational leadership and employee motivation, performance and creativity, the prospects for further research are still present.

Keywords: employee creativity, employee motivation, employee performance, transformational leadership

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Authors: Bakhtiar Amen, Abduladim Ali, Joan Lu

Abstract:

Recently, wireless technologies have made tremendous influences in advanced technology era, precisely on the learning environment through PADs and smart phones to engage learners to collaborate effectively. In fact, the wireless communication technologies are widely adopted in the education sectors within most of the countries to deliver education support electronically. Today, Introducing multilingual Wireless Response System (WRS) application is an enormous challenge and complex. The purpose of this paper is to implementing internationalization testing strategy through WRS application case study and proposed a questionnaire in multilingual speakers like (Arabic, Kurdish, Chines, Malaysian, Turkish, Dutch, Polish, Russian) to measure the internationalization testing results which includes localization and cultural testing results. This paper identifies issues with each language’s specification attributes for instance right to left (RTL) screen direction related languages, Linguistic test or word spaces in Chines and Dutch languages. Finally, this paper attempt to emphasizes many challenges and solutions that associated with globalization testing model.

Keywords: mobile WRS, internationalization, globalization testing

Procedia PDF Downloads 405