Search results for: community support

Authors: Jose Marie E. Ocdenaria, Riceli C. Mendoza

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Culturally, languages meet, merge, share, exchange, appropriate, donate, and divide in and to and from each other. Further, this type of recurrence manifests in East Asian cultures, where language influence diffuses across geographical proximities. Historically, China has notable impacts on Japan’s culture. For instance, Japanese borrowed words from China and their way of reading and writing. This qualitative and descriptive employing contrastive analysis study addressed the true and false cognates of Japanese-Philippine languages and Chinese-Philippine languages. It involved a rich collection of data from various sources like textual pieces of evidence or corpora to gain a deeper understanding of true and false cognates between L1 and L2. Cognates of Japanese-Philippine languages and Chinese-Philippine languages were analyzed contrastively according to orthography, phonology, and semantics. The words presented were the roots; however, derivatives, reduplications, and variants of stress were included when they shed emphases on the comparison. The basis of grouping the cognates was its phonetic-semantic resemblance. Based on the analysis, it revealed that there are words which may have several types of lexical relationship. Further, the study revealed that the Japanese language has more false cognates in the Philippine languages, particularly in Tagalog and Cebuano. On the other hand, there are more true cognates of Chinese in Tagalog. It is the hope of this study to provide a significant contribution to a diverse audience. These include the teachers and learners of foreign languages such as Japanese and Chinese, future researchers and investigators, applied linguists, curricular theorists, community, and publishers.

Keywords: Contrastive Analysis, Japanese, Chinese and Philippine languages, Qualitative and descriptive study, True and False Cognates

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Authors: Elizabeth Latham

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Aquinas has long been revered by the Catholic Church as one of the greatest theologians of all time. His most well-known and widely respected theological work, the Summa Theologica has been referenced by countless members of the clergy in support of arguments for and about the existence of God. It is surprising, then, and important that one component in his ontological arguments seems to contradict a precept upheld by the Catechism, the Catholic Church’s comprehensive document detailing their theological positions and laws. In Summa Theologica, Thomas Aquinas argued that God’s eternal existence is both an observable and necessary quality. In the Catechism, the Catholic Church argues that souls in Hell are separated from God, and only souls in Heaven are like him. After introducing research on Philosophical Psychology and the natures of consciousness and pain, this paper comes to the conclusion that in order to reconcile the theology of the Catholic Church at large with that of Thomas Aquinas, one must somehow solve the following problem: if a soul must exist eternally to suffer eternally, it must be like God; and, if a soul is in Hell, it is completely separate from God and not like him at all. Thomas Aquinas deviates at this point from the current theological holdings of the Catholic Church, and this apparent discrepancy must be resolved if the Church hopes to use him going forward as a standard for natural theology.

Keywords: aquinas, catholic catechism, consciousness, philosophical psychology, summa theologica

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Costrie Ganes Widayanti

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Learning Disabilities (LDs) are less understood by the Indonesia’s educational practitioners. As a result, students with LDs are at risk of being outcast from the learning process that requires participation, which potentially disconnects them academically and socially. Its objective is to raise the voice of students with LDs regarding their engagement in the classroom. This research is conducted in two urban regular public primary schools in Indonesia. The study uses an ethnographic case study research design, which explores the views and experiences of four (4) students with LDs. The data were collected using participant observations and interviews. The preliminary findings highlighted two areas: 1) the stigmatization about LDs; and 2) perceived membership. Having LDs was a barrier to fully engage in the academic and social life. Interestingly, they were more likely dependent on each other for support as limited assistance was offered by teachers and peers. Their peers did not take a keen interest in helping them when they found difficulties with the assignments. Furthermore, due to their low academic performance, they were not in favor of being nominated as a group member. In a situation that required them to do a group assignment, they were not expected to give a contribution, positioning themselves as incompatible. These findings indicated that such practices legitimate the hegemony of the superior over those who are powerless and left behind.

Keywords: engagement, experiences, learning disability, qualitative design

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

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Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

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Authors: Simao E. Luis

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From the 1960s to the 1990s, the social-psychological framework of language attitudes that emerged from the Canadian research tradition was very influential. Integrativeness was one of the main variables in Gardner’s theory because refugees and immigrants were motivated to learn English and French to integrate into the Canadian community. Second language (L2) scholars have expressed concerns over integrativeness because it cannot explain the motivation of L2 learners in global contexts. This study aims to investigate student motivation to learn English as a foreign language in Mozambique, and to contribute to the ongoing validation of the L2 Motivational Self System theory in an under-researched country. One hundred thirty-seven (N=137) university students completed a well-established motivation questionnaire. The data were analyzed with SPSS, and descriptive statistics, correlations, multiple regressions, and MANOVA were conducted. Results show that many variables contribute to motivated learning behavior, particularly the L2 learning experience and attitudes towards the English language. Statistically significant differences were found between males and females, with males expressing more motivation to learn the English language for personal interests. Statistically significant differences were found between older and younger students, with older students reporting more vivid images of themselves as future English language users. These findings have pedagogical implications because motivational strategies are positively correlated with student motivated learning behavior. Therefore, teachers should design L2 tasks that can help students to develop their future L2 selves.

Keywords: English as a foreign language, L2 motivational self system, Mozambique, university students

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Authors: Juan Wang, Xiuxiu Wang, Di Wang

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Engineers are an important force supporting the economic and social development of a country. As China has the largest scale of engineering education in the world, the career choice of engineering students will affect the contribution of human capital to national scientific and technological progress and economic development. A questionnaire survey shows the following: on the whole, the students surveyed were willing to engage in an engineering career, but their willingness needed to be enhanced, and their willingness was affected by such factors as their understanding of the value of the engineering career; the resources from individual benefits, resources from career and individual strengths. Also, based on in-depth interviews with some engineering students, it is found that engineering students’ career choice behaviors totally based on survival rationality, economic rationality, social rationality and other combinations. Based on this, policy support should be given to the enrollment, training, employment and other aspects of engineering education; improve the professional status and treatment of engineers through multiple measures; ensure a smooth career path to enhance the willingness of engineering students to choose careers.

Keywords: engineering students, career choice, engineer, human capital

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Authors: Andrew T. Hendrickson, Liven De Marez, Marijn Martens, Gytha Muller, Tudor Paisa, Koen Ponnet, Catherine Schweizer, Megan Van Meer, Mariek Vanden Abeele

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Quantifying and understanding the myriad ways people use their phones and how that impacts their relationships, cognitive abilities, mental health, and well-being is increasingly important in our phone-centric society. However, most studies on the patterns of phone use have focused on theory-driven tests of specific usage hypotheses using self-report questionnaires or analyses of smaller datasets. In this work we present a series of analyses from a large corpus of over 3000 users that combine data-driven and theory-driven analyses to identify reliable smartphone usage patterns and clusters of similar users. Furthermore, we compare the stability of user clusters across user- and system-initiated sessions, as well as during the hypothesized ritualized behavior times directly before and after sleeping. Our results indicate support for some hypothesized usage patterns but present a more complete and nuanced view of how people use smartphones.

Keywords: data mining, experience sampling, smartphone usage, health and well being

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Authors: Abbas Al-Refaie, Nour Bata

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A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.

Keywords: market segmentation, conjoint analysis, market strategies, optimization

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Authors: Damian A. Mooney, Michael T. P. Mc Cann, J. M. Don MacElroy, Olli Antson, Denis P. Dowling

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Atmospheric pressure plasma liquid deposition (APPLD) is a novel technology used for the deposition of thin films via the injection of a reactive liquid precursor into a high-energy discharge plasma at ambient pressure. In this work, APPLD, utilising a TEOS precursor, was employed to produce asymmetric membranes consisting of a thin (100 nm) layer of deposited silica on a microporous silica support in order to assess their suitability for high temperature gas separation applications. He and N₂ gas permeability measurements were made for each of the fabricated membranes and a maximum ideal He/N₂ selectivity of 66 was observed at room temperature. He, N₂ and CO2 gas permeances were also measured at the elevated temperature of 673K and ideal He/N₂ and CO₂/N₂ selectivities of 300 and 7.4, respectively, were observed. The results suggest that this plasma-based deposition technique can be a viable method for the manufacture of membranes for the efficient separation of high temperature, post-combustion gases, including that of CO₂/N₂ where the constituent gases differ in size by fractions of an Ångstrom.

Keywords: asymmetric membrane, CO₂ separation, high temperature, plasma deposition, thin films

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Authors: Khaled Ayfi, Morgan Dal, Frederic Coste, Nicolas Gallienne, Martina Ridlova, Philippe Lorong

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In the gas industry, contamination of equipment by metal particles is one of the feared phenomena. Indeed, particles inside equipment can be driven by the gas flow and accumulate in places where the velocity is low. As they constitute a potential ignition hazard, particular attention is paid to the presence of particles in the oxygen industry. Indeed, the heat release from ignited particles may damage the equipment and even result in a loss of integrity. The objective of this work is to support the development of new design criteria. Studying the thermomechanical behavior of this equipment, thanks to numerical simulations, allows us to test the influence of various operating parameters (oxygen pressure, wall thickness, initial operating temperature, nature of the metal, etc.). Therefore, in this study, we propose a numerical model that describes the thermomechanical behavior of various pressurized installations heated locally by the combustion of small particles. This model takes into account the geometric and material nonlinearity and has been validated by the comparison of simulation results with experimental measurements obtained by a new device developed in this work.

Keywords: ignition, oxygen, numerical simulation, thermomechanical behaviour

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Authors: Gabriela Chmelikova, Ludmila Hurajova, Pavol Bozek

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Current era has brought hand in hand with the vast and fast development of technologies enormous pressure on individuals to keep being well - oriented in their professional fields. Almost all projects in the real world require an interdisciplinary perspective. These days we notice some cases when students face that real requirements for jobs are in contrast to the knowledge and competences they gained at universities. Interlacing labor market and university programs is a big issue these days. Sometimes it seems that higher education only “chases” reality. Simulation-based learning can support students’ touch with real demand on competences and knowledge of job world. The contribution provided a descriptive study of some cases of simulation-based teaching environment in different courses at STU MTF in Trnava and discussed how students and teachers perceive this model of teaching-learning approach. Finally, some recommendations are proposed how to enhance closer relationship between academic world and labor market.

Keywords: interdisciplinary approach, simulation-based learning, students' job readiness, teaching environment in higher education

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Authors: Elena V. Syurina, Sophie Renckens, Martina Valente

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Objective: The objective of this study was to investigate the nature of the conversation around orthorexia nervosa (ON) on Instagram. Methods: The present study was conducted using mixed methods, combining a concurrent triangulation and sequential explanatory design. First, 3027 pictures posted on Instagram using #Orthorexia were analyzed. Then, a questionnaire about Instagram use related to ON was completed entirely by 185 respondents. These two quantitative data sources were statistically analyzed and triangulated afterwards. Finally, 9 interviews were conducted, to more deeply investigate what is being said about ON on Instagram and what the motivations to post about it are. Results: Four main categories of pictures were found to be represented in Instagram posts about ON: ‘food’, ‘people’, ‘text’, and ‘other.’ Savory and unprocessed food was most highly represented within the food category, and pictures of people were mostly pictures of the account holder. People who self-identify as having ON were more likely to post about ON, and they were significantly more likely to post about ‘food’, ‘people’ and ‘text.’ The goal of the posts was to raise awareness around ON, as well as to provide support for people who believe to be suffering from it. Conclusion: Since the conversation around ON on Instagram is supportive, it could be beneficial to consider Instagram use in the treatment of ON. However, more research is needed on a larger scale.

Keywords: orthorexia nervosa, Instagram, social media, disordered eating

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Authors: Liliana M. Marinelli, Cristina T. Varanese

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In the last few years, students from higher education have difficulties in grasping mathematical concepts which support physical matters, especially those in the first years of this education. Classical Physics teaching turns to be complex when students are not able to make use of mathematical tools which lead to the conceptual structure of Physics. When derivation and integration rules are not used or developed in parallel with other disciplines, the physical meaning that we attempt to convey turns to be complicated. Due to this fact, it could be of great use to see the Classical Mechanics from an axiomatic approach, where the correspondence rules give physical meaning, if we expect students to understand concepts clearly and accurately. Using the Minkowski point of view adapted to a two-dimensional space and time where vectors, matrices, and straight lines (worked from an affine space) give mathematical and physical rigorosity even when it is more abstract. An interesting option would be to develop the disciplinary contents from an axiomatic version which embraces the Classical Mechanics as a particular case of Relativistic Mechanics. The observation about the increase in the difficulties stated by students in the first years of education allows this idea to grow as a possible option to improve performance and understanding of the concepts of this subject.

Keywords: axioms, classical physics, physical concepts, relativity

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Authors: Mingxi Xiao

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This case study focused on a bilingual child named Emma and her play. Emma was a four-year-old girl born in Australia while her parents were both Chinese. Emma could speak fluent English, while her Mandarin was not as good as her spoken English. With the research question to figure out whether creative play had an impact on children’s bilingualism, this case study mainly used the anecdotes method to observe Emma’s play and this report presented five observations of Emma, describing detailed information about her play and recording her language use. Based on Emma’s interests and daily activities, this case study chose her creative play for observation, which incorporates a whole range of activities from dancing to drawing, as well as playing instruments. From the five observations, it could be seen that Emma often mixed languages to help her express her meaning. It could be seen that Emma made an effort to use her bilingualism in her creative play. In other words, play encouraged Emma to use the two languages. In conclusion, the observations with Emma showed that although her Mandarin was not good enough, she displayed confidence in speaking both languages and had gradually shifted from mixing languages to code-switching. Recommendations were provided to support Emma’s bilingual abilities for further development in the end.

Keywords: bilingual, case study, code-switching, creative play, early childhood

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Authors: Hongyu Chen, Li Jiang

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Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Cheeze Janito, Crisly Dawang

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It is important to determine the personality traits that exist in the workplace and the contribution of these personality traits in the staff’s daily work routines; a sedentary lifestyle is harmful to one’s health. This study reports the personality traits of the University of Southern Mindanao, Kabacan, Philippines, non-teaching staff, the physical activity involvement of the non-teaching staff, and the big five personality traits that shape the relationship of university non-teaching staff in engaging physical activities. A quantitative method approach, which comprised a three-part questionnaire, was used to collect the data. The fifty non-teaching staff complete the survey. The results revealed that among the big five personality traits, the university non-teaching staff scored higher in agreeableness as revealed, that there was a commonality among the respondents’ traits of consideration to the feelings of the co-workers in observance to not being rude and vividly display of respect to co-workers and workplace and scored least in the personality trait of neuroticism. The study also reported that the university non-teaching staff's main physical activity was house chores as a prime physical exercise in which respondents reported a physical activity frequency of once to twice a week; thus, this study reported that the respondents are less engaged in doing physical activities. Further, the relationship of personality traits and the physical activity of the non-teaching staff gained a p-value of .596 that indicates there is no significant relationship between the two variables, the personality trait and physical activities. This study recommends the tight promotion of staff in engaging in physical activity of at least one hundred fifty minutes of moderate-intensity activity each week. Added to this, the use of different platforms containing physical exercise literacy and the benefits of physical exercise for the holistic development of the university community.

Keywords: university staff, physical fitness, personality traits, physical activity

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Authors: Christine Myunghee Ahn, Sung Eun Baek, Sun Young Park

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The purpose of this study was to evaluate the cross-cultural validity of the Korean version of the Behavioral Assessment System for Children 2nd Edition, Parent Rating Scales - Adolescent Form (K BASC-2, PRS-A). The 150-item K BASC-2, PRS-A questionnaire was administered to a total of 690 Korean parents or caregivers (N=690) of adolescent children in middle school and high school. Results from the confirmatory and exploratory factor analyses indicate that the K BASC-2, PRS-A yielded a 3-factor solution similar to the factor structure found in the original version of the BASC-2. The internal consistencies using the Cronbach’s alpha of the composite scale scores were in the .92~ .98 range. The overall reliability and validity of the K BASC-2, PRS-A seem adequate. Structural equation modeling was used to verify the theoretical relationship among the scales of Adaptability, Withdrawal, Somatization, Depression, and Anxiety, to render additional support for internal validity. Other relevant findings, practical implications regarding the use of the KBASC-2, PRS-A and suggestions for future research are discussed.

Keywords: behavioral assessment system, cross-cultural validity, parent report, screening

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Authors: Akhmad F. K. Khitam, Yi Tai, Hsin-Yun Lee

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In the modern research of construction management, the goals of scheduling are not only to finish the project within the limited duration, but also to improve the impact of people and environment. Especially for the impact to the pedestrian and vehicles, the considerable social cost should be estimated in the total performance of a construction project. However, the site environment has many differences between projects. These interactions affect the requirement and goal of scheduling. It is difficult for schedule planners to quantify these interactions. Therefore, this study use 3D dynamic simulation technology to plan the schedule of the construction engineering projects that affect the current space users (i.e., the pedestrians and vehicles). The proposed model can help the project manager find out the optimal schedule to minimize the inconvenience brought to the space users. Besides, a roadwork project and a building renovation project were analyzed for the practical situation of engineering and operations. Then this study integrates the proper optimization algorithms and computer technology to establish a decision support model. The proposed model can generate a near-optimal schedule solution for project planners.

Keywords: scheduling, simulation, optimization, pedestrian and vehicle behavior

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Authors: Dessy Laksyana Utami

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The sick building syndrome comprises of various nonspecific symptoms that occur in the occupants of a building. It is commonly increases sickness absenteeism and causes a decrease in productivity of the workers. Evidence suggests that what is called the Sick Building Syndrome are at least three separate entities, which has at least one cause. The following are some of the factors that might be primarily responsible for Sick Building Syndrome such as: Chemical contaminants, Biological contaminants, Inadequate ventilation and Electromagnetic radiation. In many cases it is due to insufficient maintenance of the HVAC (heating, ventilation, air conditioning) system in the building. As this syndrome is increasingly becoming a major occupational hazard. It was used the analytic cross-sectional design. Based on data obtained 80% of respondents reported significant ongoing health problems in the eyes, head, and the nose. 60% had bad symptoms in the throat, the stomach and cough, 50% had gastrointestinal disorders, 40% fatigue and 25% occurred all symptoms sick building syndrome. The 40 respondents were recruited to the study, with a mean age of 35 years (range 20-55). To support the evidence of Sick Building Syndrome, further checks are needed for some of the factors in next research, i.e. measurement of Chemical contaminants, Biological contaminants, inadequate ventilation & Electromagnetic radiation.

Keywords: indoor air pollution, sick building syndrome, indoor air quality, oil gas polution

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Authors: Ngoc T. Bui

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The key issue for teachers of a modern foreign language is the creation of a pedagogic environment, and this means that an understanding of context is vital. A pedagogic environment addresses the following: time, feedback, relations with other people, curriculum integration, forms of knowledge, resources and control in the pedagogic relationship. In this light, the multiple case study of the implementation of a modern foreign language curriculum focuses on exploring Vietnamese contexts and participants’ perceptions of factors that may affect their implementation process in order to examine thoroughly how the communicative language teaching (CLT) curriculum is being implemented in second language classrooms. A mixed methods approach is utilized to investigate contextual and personal factors that may affect teachers’ implementation of curriculum and pedagogical reform in Vietnam. This project therefore has the capability to inform stakeholders of useful information and identify further changes and measures to solve potential problems to ensure the achievement of the curriculum goals. The expected outcomes may also lead to intercultural language teaching guidelines to support english as a foreign language (EFL) teachers with curriculum design, planning and how to create pedagogic environment to best implement it.

Keywords: communicative language teaching, context, curriculum implementation, modern foreign language, pedagogic environment

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Yeoju Chung

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Adolescents internet and smartphone addiction are increasing in Korea. But differences between internet addiction and smartphone addiction have been researched in these days. The main objective of this article is to explore the presence of clusters within a sample of adolescents based on dimensions associated with addiction and internet usage needs. The sample consists of 617 adolescents in the 14-19 year age group who were recruited in Korea A cluster analysis identified four groups of participants: internet overuse(IO), smartphone overuse(SO), both overuse(B) and normal(N) use group. MANOVA analysis based on internet usage showed that there are differences among four groups in internet usage needs. IO has higher cyber self-seeking needs and emotion and thought expression needs than SO. SO has higher real relationship and life needs with cyberworld than IO, B, and N. B has the highest cyber self-seeking needs and emotion and thought expression needs, however, game fun seeking needs is the highest in IO. These results support that IO seeks game fun needs, SO seeks real relationship and life needs, and B seeks cyber self and expression in cyberworld.

Keywords: addiction, internet, needs, smartphone

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Authors: Zate Zewdneh Zana

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Coffea arabica (Arabica coffee), a cornerstone of the global beverage industry, necessitates rigorous genetic conservation due to its economic significance and genetic complexity. In this study, we performed whole-genome resequencing of wild species collected from its birthplace, Ethiopia. Advanced Illumina sequencing technology facilitated the mapping of a high percentage of clean reads to the C. arabica reference genome, revealing a substantial number of genetic variants, predominantly SNPs. Our comprehensive analysis not only uncovered a notable distribution of genomic variants across the coffee genome but also identified distinct genetic groups through phylogenetic and population structure analyses. This genomic study provides invaluable insights into the genetic diversity of C. arabica, highlighting the potential of identified SNPs and InDels in enhancing our understanding of key agronomic traits. The findings contribute significantly to genetic studies and support strategic breeding and conservation efforts essential for sustaining the global coffee industry.

Keywords: population genetics, wild species, evolutionary study, coffee plant

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Authors: Leandi Steenkamp

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After being in effect since the late 1970s, first generation sectional title legislation in South Africa was completely overhauled in recent years into what is now commonly referred to as third generation sectional title legislation. The original Sectional Titles Act was split into three separate statutes, namely the Sectional Titles Schemes Management Act No. 8 of 2011, the Sectional Titles Amendment Act No. 33 of 2013 and the Community Schemes Ombud Service Act No. 9 of 2011, with various Regulations detailing how the different acts should be applied in practice. Even though some of the changes effected by the new legislation is simply technical adjustments and replications of the original first generation legislation, the new acts introduce a number of significant changes that will have an effect on accountancy and financial management aspects of sectional title schemes in future. No academic research has been undertaken on third generation sectional title legislation in South Africa from an accountancy and financial management perspective as yet. The aim of this paper is threefold: Firstly, to discuss the findings of a literature review on the new third generation sectional title legislation, with specific reference to accountancy-related aspects. Secondly, the empirical findings of accountancy-related aspects from the results of a quantitative study on a sample of bodies corporate will be discussed. The sample of bodies corporate was selected from four different municipal areas in South Africa. Specific reference will be made to the readiness of bodies corporate regarding the provisions of the new legislation. Thirdly, practical recommendations will be made on how bodies corporate can prepare for the new legislative aspects, and further research opportunities in this regard will be discussed.

Keywords: accountancy, body corporate, sectional title, third generation sectional title legislation

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Authors: B. Karthik Vasan, Rachil Maliwal, Somnath Basu

Abstract:

Generation of solid waste is a major problem confronting the iron and steel industry around the world. Disposal of untreated wastes is no longer a viable solution in view of the environmental regulations becoming more and more stringent, as well as an increase in community awareness about the long-term hazards of indiscriminate waste disposal. The current work explores the possibility of converting some of the ‘problematic’ solid wastes generated during steel manufacturing operations, viz. dust from primary steelmaking, iron ore handling, and flux calcination processes, into value-added products instead of environmentally hazardous disposal practices. It was possible to develop a synthetic calcium ferrite, which helped to enhance the dissolution of calcined basic fluxes (e.g. CaO) and reduce the overall energy consumption during steel making. This, in turn, increased process efficiency and reduced greenhouse gas emissions. The preliminary results from laboratory-scale experiments clearly demonstrate the potential of utilizing these ‘waste materials’ that are generated in-house in iron and steel manufacturing plants. The energy required for synthesis of the ferrite may be reduced further by partially utilizing the waste heat from the exhaust gases. In the longer run, it would result in significant financial benefits due to reduced dependence on purchased fluxes. The synthesized ferrite is non-hygroscopic and this provides an additional benefit during its storage and transportation, relative to calcined lime (CaO) that is widely used as a basic flux across the steel making industry.

Keywords: calcium ferrite, flux, slag formation, solid waste

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Authors: Widyani Fatwa Dewi, Subroto Athor

Abstract:

In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

Procedia PDF Downloads 167

Authors: Zhaojun Zheng, Yuanfa Liu, Jiaxin Li, Jinwei Li, Yong-jiang Xu, Chen Cao

Abstract:

Black bean is an excellent protein source for preparing hydrolysates, which attract much attention due to their biological activity. The objective of this study was to characterize the physicochemical and antioxidant properties of black bean protein, hydrolyzed by ficin, bromelain or alcalase until 300 min of hydrolysis. Results showed that bromelain and alcalase hydrolysates possessed a higher degree of hydrolysis (DH) than that of ficin, thereby presenting different ultraviolet absorption, fluorescence intensity, and circular dichroism. Moreover, all hydrolysates possessed the capacity to scavenge DPPH radical with the lowest IC₅₀ of 21.11 µg/mL, as well as to chelate ferrous ion (Fe²⁺) with the IC₅₀ values ranging from 6.82 to 30.68 µg/mL. Intriguingly, the oxidation of linoleic acid, sunflower oil, and sunflower oil-in-water emulsion was remarkedly retarded by the three selected protein hydrolysates, especially by bromelain-treated protein hydrolysate, which might attribute to their high hydrophobicity and emulsifying properties. These findings can provide strong support for black bean protein hydrolysates to be employed in food products acting as natural antioxidant alternatives.

Keywords: antioxidant activity, black bean protein hydrolysate, emulsion physicochemical properties, sunflower oil

Procedia PDF Downloads 140

Authors: Muhammad Bilal, Adil Ahmed

Abstract:

This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.

Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures

Procedia PDF Downloads 122