Search results for: student support

Authors: Zainab Khalifah, Wong Chiet Bing, Noor Hazarina Hashim

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The evolution of customer behavior in purchasing products or services through the Internet leads to airline companies engaging in the e-ticketing process in order to maintain their business. A well-designed website is vitally significant for the airline companies to provide effective communication, support, and competitive advantage. This study was conducted to identify the dimensions of website quality for low cost airline and to investigate the relationship between the website quality and customer e-satisfaction at low cost airline. A total of 381 responses were conveniently collected among local passengers at Low Cost Carrier Terminal, Kuala Lumpur via questionnaire distribution. This study found that the five determinant factors of website quality for AirAsia were Information Content, Navigation, Responsiveness, Personalization, and Security and Privacy. The results of this study revealed that there is a positive relationship between the five dimensions of website quality and customer e-satisfaction, and also information content was the most significant contributor to customer e-satisfaction.

Keywords: website quality, customer e-satisfaction, low cost airline, e-ticketing

Procedia PDF Downloads 405

Authors: Ananda Perera

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Computer-Assisted Medical Evaluation of Symptoms (CAMEOS) is a medical expert system designed to help General Practices (GPs) make an accurate diagnosis. CAMEOS comprises a knowledge base, user input, inference engine, reasoning module, and output statement. The knowledge base was developed by the author. User input is an Html file. The physician user collects data in the consultation. Data is sent to the inference engine at servers. CAMEOS uses set theory to simulate diagnostic reasoning. The program output is a list of differential diagnoses, the most probable diagnosis, and the diagnostic reasoning.

Keywords: CDSS, computerized decision support systems, expert systems, general practice, diagnosis, diagnostic systems, primary care diagnostic system, artificial intelligence in medicine

Procedia PDF Downloads 139

Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

Procedia PDF Downloads 415

Authors: Emily Hickmann, Peggy Richter, Maren Kaehlig, Hannes Schlieter

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Patient engagement is a cornerstone of high-quality care and essential for patients with chronic diseases to achieve improved health outcomes. Through digital transformation, possibilities to engage patients in their personal healthcare have multiplied. However, the exploitation of this potential is still lagging. To support the transmission of patient engagement theory into practice, this paper’s objective is to give a state-of-the-art overview of patient engagement tools and methods. A systematic literature review was conducted. Overall, 56 tools and methods were extracted and synthesized according to the four attributes of patient engagement, i.e., personalization, access, commitment, and therapeutic alliance. The results are discussed in terms of their potential to be implemented in digital health solutions under consideration of the “computers are social actors” (CASA) paradigm. It is concluded that digital health can catalyze patient engagement in practice, and a broad future research agenda is formulated.

Keywords: chronic diseases, digitalization, patient-centeredness, patient empowerment, patient engagement

Procedia PDF Downloads 91

Authors: Rozafa Shala

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Development of preschool education in Kosovo has passed through several periods. The period after the 1999 war was very intensive period when preschool education started to change. Step-by-step program was one of the programs which were very well extended during the period after the 1999 war until now. The aim of this study is to present the impact of the step-by-step program in the preschool education. This research is based on the hypothesis that: Step-by-step program continues to be present with its elements, in all other programs that the teachers can use. For data collection a questionnaire is constructed which was distributed to 25 teachers of preschool education who work in public preschool institutions. All the teachers have finished the training for step by step program. To support the data from the questionnaire a focus group is also organized with whom the critical issues of the program were discussed. From the results obtained we can conclude that the step-by-step program has a very strong impact in the preschool level. Many specific elements such as: circle time, weather calendar, environment inside the class, portfolios and many other elements are present in most of the preschool classes. The teacher's approach also has many elements of the step-by-step program.

Keywords: preschool education, step-by-step program, impact, teachers

Procedia PDF Downloads 332

Authors: Jill Villarreal, Kristalyn Cooksey, Kai Lloyd, Daniel Ha

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Little research has been conducted to examine college students' reading attitudes, including students' perceptions of reading behaviors and reading abilities. This is problematic, as reading assigned course material is a critical component to an undergraduate student's academic success. For this study, flyers were electronically disseminated to instructors at 24 public and 10 private U.S. institutions in “Reading-Intensive Departments” including Psychology, Sociology, Education, Business, and Communications. We requested the online survey be completed as an in-class activity during the fall 2019 and spring 2020 semesters. All participants voluntarily completed the questionnaire anonymously. Of the participants, 280 self-identified their race as Black and 280 self-identified their race as White. Of the participants, 177 self-identified their gender as Male and 383 self-identified their Gender as Female. Participants ranged in age from 18-24. Factor analysis found four dimensions resulting from the questions regarding reading. The first we interpret as “Reading Proficiency”, accounted for 19% of the variability. The second dimension was “Reading Anxiety” (15%), the third was “Textbook Reading Ability” (9%), and the fourth was “Reading Enjoyment” (8%). Linear models on each of these dimensions revealed no effect of Age, Gender, Race, or Income on “Reading proficiency”. The linear model of “Reading Anxiety” showed a significant effect of race (p = 0.02), with higher anxiety in white students, as well as higher reading anxiety in female students (p < 0.001). The model of “Textbook Reading Ability” found a significant effect of race (p < 0.001), with higher textbook problems in white students. The model of “Reading Enjoyment” showed significant effects of race (p = 0.013) with more enjoyment for white students, gender (p = 0.001) with higher enjoyment for female students, and age (p = 0.033) with older students showing higher enjoyment. These findings suggest that gender, age, and race are important factors in many aspects of college students' reading attitudes. Further research will investigate possible causes for these differences. In addition, the effectiveness of college-level programs to reduce reading anxiety, promote the reading of textbooks, and foster a love of reading will be assessed.

Keywords: age, college, gender, race, reading

Procedia PDF Downloads 132

Authors: Seungsik Yu, Minho Kang

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As the threat of terrorism to nuclear facilities is increasing globally after the attacks of September 11, we are striving to recognize the physical protection system and strengthen the emergency response system. Since 2015, Korea has implemented physical protection security exercise for nuclear facilities. The exercise should be carried out with full cooperation between the operator and response forces. Performance testing of the physical protection system should include appropriate exercises, for example, force-on-force exercises, to determine if the response forces can provide an effective and timely response to prevent sabotage. Significant deficiencies and actions taken should be reported as stipulated by the competent authority. The IAEA(International Atomic Energy Agency) is also preparing force-on-force exercise program documents to support exercise of member states. Currently, ROK(Republic of Korea) is implementing exercise on the force-on-force exercise evaluation system which is developed by itself for the nuclear power plant, and it is necessary to establish the exercise procedure considering the use of the force-on-force exercise evaluation system. The purpose of this study is to establish the work procedures of the three major organizations related to the force-on-force exercise of nuclear power plants in ROK, which conduct exercise using force-on-force exercise evaluation system. The three major organizations are composed of licensee, KINAC (Korea Institute of Nuclear Nonproliferation and Control), and the NSSC(Nuclear Safety and Security Commission). Major activities are as follows. First, the licensee establishes and conducts an exercise plan, and when recommendations are derived from the result of the exercise, it prepares and carries out a force-on-force result report including a plan for implementation of the recommendations. Other detailed tasks include consultation with surrounding units for adversary, interviews with exercise participants, support for document evaluation, and self-training to improve the familiarity of the MILES (Multiple Integrated Laser Engagement System). Second, KINAC establishes a force-on-force exercise plan review report and reviews the force-on-force exercise plan report established by licensee. KINAC evaluate force-on-force exercise using exercise evaluation system and prepare training evaluation report. Other detailed tasks include MILES training, adversary consultation, management of exercise evaluation systems, and analysis of exercise evaluation results. Finally, the NSSC decides whether or not to approve the force-on-force exercise and makes a correction request to the nuclear facility based on the exercise results. The most important part of ROK's force-on-force exercise system is the analysis through the exercise evaluation system implemented by KINAC after the exercise. The analytical method proceeds in the order of collecting data from the exercise evaluation system and analyzing the collected data. The exercise application process of the exercise evaluation system introduced in ROK in 2016 will be concretely set up, and a system will be established to provide objective and consistent conclusions between exercise sessions. Based on the conclusions drawn up, the ultimate goal is to complement the physical protection system of licensee so that the system makes licensee respond effectively and timely against sabotage or unauthorized removal of nuclear materials.

Keywords: Force-on-Force exercise, nuclear power plant, physical protection, sabotage, unauthorized removal

Procedia PDF Downloads 131

Authors: Azadeh Bashiri

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Introduction: In order to better designing of electronic health record system in Iran, integration of health information systems based on a common language must be done to interpret and exchange this information with this system is required. Background: This study, provides a conceptual model of radiology reporting system using unified modeling language. The proposed model can solve the problem of integration this information system with electronic health record system. By using this model and design its service based, easily connect to electronic health record in Iran and facilitate transfer radiology report data. Methods: This is a cross-sectional study that was conducted in 2013. The student community was 22 experts that working at the Imaging Center in Imam Khomeini Hospital in Tehran and the sample was accorded with the community. Research tool was a questionnaire that prepared by the researcher to determine the information requirements. Content validity and test-retest method was used to measure validity and reliability of questioner respectively. Data analyzed with average index, using SPSS. Also, Visual Paradigm software was used to design a conceptual model. Result: Based on the requirements assessment of experts and related texts, administrative, demographic and clinical data and radiological examination results and if the anesthesia procedure performed, anesthesia data suggested as minimum data set for radiology report and based it class diagram designed. Also by identifying radiology reporting system process, use case was drawn. Conclusion: According to the application of radiology reports in electronic health record system for diagnosing and managing of clinical problem of the patient, provide the conceptual Model for radiology reporting system; in order to systematically design it, the problem of data sharing between these systems and electronic health records system would eliminate.

Keywords: structured radiology report, information needs, minimum data set, electronic health record system in Iran

Procedia PDF Downloads 239

Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors by Latour. The learning conditions are found to be distinguished by broad complexity characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation

Procedia PDF Downloads 353

Authors: Anyia Nduka, Aslan Bin Amad Senin, Ayu Azrin Binti Abdul Aziz

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Telemedicine is a rapidly developing discipline with enormous promise for better healthcare results for patients. To meet the demands of patients and the healthcare sector, medical providers must be proficient in telemedicine and also need government funding for infrastructure and core competencies. In this study, we surveyed general hospitals in Kuala Lumpur and Selangor to investigate patient’s impressions of both the positive and negative aspects of government funding for telemedicine and its level of acceptance. This survey was conducted in accordance with the Diffusion of Innovations (DOI) hypothesis; the survey instruments were designed through a Google Form and distributed to patients and every member of the medical team. The findings suggested a framework for categorizing patients' levels of technology use and acceptability, which provided practical consequences for healthcare. We therefore recommend the increase in technical assistance and government-backed funding of telemedicine by bolstering the entire system.

Keywords: technology acceptance, quality assurance, digital transformation, cost management.

Procedia PDF Downloads 55

Authors: Pudji Astuti, C. P. C. Putro, C. M. Airin, L. Sjahfirdi, S. Widiyanto, H. Maheshwari

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Stress of slaughter animals starting long before until at the time of process of slaughtering which cause misery and decrease of meat quality. Meanwhile, determination of animal stress using hormonal such as cortisol is expensive and less practical so that portable stress indicator for cows based on Fourier Transform Infrared Spectroscopy (FTIR) must be provided. The aims of this research are to find out the comparison process of slaughter between Rope Casting Local (RCL) and Restraining Box Method (RBM) by measuring of cortisol and wavelength in FTIR methods. Thirty two of male Ongole crossbred cattle were used in this experiment. Blood sampling was taken from jugular vein when they were rested and repeated when slaughtered. All of blood samples were centrifuged at 3000 rpm for 20 minutes to get serum, and then divided into two parts for cortisol assayed using ELISA and for measuring the wavelength using FTIR. The serum then measured at the wavelength between 4000-400 cm-1 using MB3000 FTIR. Band data absorption in wavelength of FTIR is analyzed descriptively by using FTIR Horizon MBTM. For RCL, average of serum cortisol when the animals rested were 11.47 ± 4.88 ng/mL, when the time of slaughter were 23.27 ± 7.84 ng/mL. For RBM, level of cortisol when rested animals were 13.67 ± 3.41 ng/mL and 53.47 ± 20.25 ng/mL during the slaughter. Based on student t-Test, there were significantly different between RBM and RCL methods when beef cattle were slaughtered (P < 0.05), but no significantly different when animals were rested (P > 0.05). Result of FTIR with the various of wavelength such as methyl group (=CH3) 2986cm-1, methylene (=CH2) 2827 cm-1, hydroxyl (-OH) 3371 cm-1, carbonyl (ketones) (C=O) 1636 cm-1, carboxyl (COO-1) 1408 cm-1, glucosa 1057 cm-1, urea 1011 cm-1have been obtained. It can be concluded that the RCL slaughtered method is better than the RBM method based on the increase of cortisol as an indicator of stress in beef cattle (P<0.05). FTIR is really possible to be used as stub of stress tool due to differentiate of resting and slaughter condition by recognizing the increase of absorption and the separation of component group at the wavelength.

Keywords: cows, cortisol, FTIR, RBM, RCL, stress indicator

Procedia PDF Downloads 626

Authors: I. Teotónio, C.O. Cruz, C.M. Silva, M. Manso

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Diverse stakeholders show different concerns when choosing green roof systems. Also, green roof solutions vary in their cost and performance. Therefore, decision-makers continually face the difficult task of balancing benefits against green roofs costs. Decision analysis methods, as multicriteria analysis, can be used when the decision‑making process includes different perspectives, multiple objectives, and uncertainty. The present study adopts a multicriteria decision model to evaluate the installation of green roofs in buildings, determining the solution with the best trade-off between costs and benefits in agreement with the preferences of the users/investors. This methodology was applied to a real decision problem, assessing the preferences between different green roof systems in an existing building in Lisbon. This approach supports the decision-making process on green roofs and enables robust and informed decisions on urban planning while optimizing buildings retrofitting.

Keywords: decision making, green roofs, investors preferences, multicriteria analysis, sustainable development

Procedia PDF Downloads 167

Authors: Ryan Villafuerte Lansangan

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Assessing students’ understanding in the microscopic level of an abstract subject like chemistry poses a challenge to teachers. Literature reveals that the use of representations serves as an essential avenue of measuring the extent of understanding in the discipline as an alternative to traditional assessment methods. This undertaking explored the representational competence profile of high school students from the University of Santo Tomas High School in understanding selected chemical principles and correlate this with their academic profile in chemistry based on their performance in the academic achievement examination in chemistry administered by the Center for Education Measurement (CEM). The common misconceptions of the students on the selected chemistry principles based on their representations were taken into consideration as well as the students’ views regarding their understanding of the role of chemical representations in their learning. The students’ level of representation task instrument consisting of the main lessons in chemistry with a corresponding scoring guide was prepared and utilized in the study. The study revealed that most of the students under study are unanimously rated as Level 2 (symbolic level) in terms of their representational competence in understanding the selected chemical principles through the use of chemical representations. Alternative misrepresentations were most observed on the students’ representations on chemical bonding concepts while the concept of chemical equation appeared to be the most comprehensible topic in chemistry for the students. Data implies that teachers’ representations play an important role in helping the student understand the concept in a microscopic level. Results also showed that the academic achievement in the chemistry of the students based on the standardized CEM examination has a significant association with the students’ representational competence. In addition, the students’ responses on the students’ views in chemical representations questionnaire evidently showed a good understanding of what a chemical representation or a mental model is by drawing a negative response that these tools should be an exact replica. Moreover, the students confirmed a greater appreciation that chemical representations are explanatory tools.

Keywords: chemical representations, representational competence, academic profile in chemistry, secondary students

Procedia PDF Downloads 388

Authors: Yuanjin Liu

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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

Procedia PDF Downloads 61

Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

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Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: convolutional neural network, lithology, prediction of reservoir, seismic attributes

Procedia PDF Downloads 162

Authors: Omnia F. Elkommos

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In the course of teaching stylistics to undergraduate students of the Department of English Language and Literature, Faculty of Arts and Humanities, the linguistic tool kit of theories comes in handy and useful for the better understanding of the different literary genres: Poetry, drama, and short stories. In the present paper, a model of teaching of stylistics is compiled and suggested. It is a collaborative group project technique for use in the undergraduate diverse specialisms (Literature, Linguistics and Translation tracks) class. Students initially are introduced to the different linguistic tools and theories suitable for each literary genre. The second step is to apply these linguistic tools to texts. Students are required to watch videos performing the poems or play, for example, and search the net for interpretations of the texts by other authorities. They should be using a template (prepared by the researcher) that has guided questions leading students along in their analysis. Finally, a practical analysis would be written up using the practical analysis essay template (also prepared by the researcher). As per collaborative learning, all the steps include activities that are student-centered addressing differentiation and considering their three different specialisms. In the process of selecting the proper tools, the actual application and analysis discussion, students are given tasks that request their collaboration. They also work in small groups and the groups collaborate in seminars and group discussions. At the end of the course/module, students present their work also collaboratively and reflect and comment on their learning experience. The module/course uses a drama play that lends itself to the task: ‘The Bond’ by Amy Lowell and Robert Frost. The project results in an interpretation of its theme, characterization and plot. The linguistic tools are drawn from pragmatics, and discourse analysis among others.

Keywords: applied linguistic theories, collaborative learning, cooperative principle, discourse analysis, drama analysis, group project, online acting performance, pragmatics, speech act theory, stylistics, technology enhanced learning

Procedia PDF Downloads 155

Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

Procedia PDF Downloads 524

Authors: Min Hae Song, Jooyong Park

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Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests. Multiple-choice tests (MC) are efficient in automatic grading, however structural problems of multiple-choice tests allow students to find the correct answer from options even though they do not know the answer. A computerized modified multiple-choice testing system (CMMT) was developed using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. This study was conducted to find out whether penalizing for wrong answers in CMMT could lower random guessing. In this study, we checked whether students knew the answers by having them respond to the short-answer tests before choosing the given options in CMMT or MC format. Ninety-four students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: two conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. In the low penalty condition, the penalty rate was the probability of getting the correct answer by random guessing. In the high penalty condition, students were penalized at twice the percentage of the low penalty condition. The results showed that the number of no response was significantly higher for the CMMT format and the number of random guesses was significantly lower for the CMMT format. There were no significant between the two penalty conditions. This result may be due to the fact that the actual score difference between the two conditions was too small. In the discussion, the possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed.

Keywords: computerized modified multiple choice test format, multiple-choice test format, penalizing, test format

Procedia PDF Downloads 157

Authors: Benjawan Tipprachaban

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This research aims to investigate mistakes in translation, particularly from Thai to English, which cause translation problems for undergraduate students in Thailand. The researcher had the non-English major students of Suratthani Rajabhat University as samples. The data were collected by having 27 non-English major students translate 50 Thai sentences into English. After the translation, lots of mistakes were found and the researcher categorized them into 3 main types which were the grammatical mistake, the usage mistake, and the spelling mistake. However, this research is currently in the process of analyzing the data and shall be completed in August. The researcher, nevertheless, predicts that, of all the mistakes, the grammatical mistake will principally be made, the usage mistake and the spelling one respectively, which will support the researcher’s hypothesizes, i.e. 1) the grammatical mistake, mainly caused by language transfer, essentially leads to considerable translation problems; 2) the usage mistake is another critical problem that causes translation problems; 3) basic knowledge in Thai to English translation of undergraduate students in Thailand is at low level.

Keywords: English, language, Thai, translation

Procedia PDF Downloads 446

Authors: Wikanda Boonma, Jang Hyunmi

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Smart tourism applications (STAs) play an important role in tourism to enhance the quality tourism experience and add value to tourists with accurate information, better decision support, greater time-saving, and providing more personalized information to meet tourists’ expectations. This paper intends to develop and investigate the effect of smart tourism applications on memorable tourism experiences in enhancing tourist satisfaction and destination loyalty. Questionnaires were distributed to tourists who are traveling in Bangkok, Thailand. A structural equation method was used to find the relationship among smart tourism technology attributes, the perceived value of the STAs, memorable tourism experience, tourist satisfaction, and destination loyalty. The findings of this study provide insight into the critical role of smart tourism applications, which create chances for smart tourism development. Additionally, some theoretical and managerial implications were derived from the findings.

Keywords: smart tourism applications, memorable tourism experience, tourist satisfaction, destination loyalty

Procedia PDF Downloads 86

Authors: Henriette van Rensburg, Betty Adcock

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Concern about the lack of knowledge of quality teaching and teacher retention in rural and remote areas of Australia, has caused academics to improve pre-service teachers’ understanding of this problem. The participants in this study were forty students enrolled in an undergraduate educational course (EDO3341 Teaching in rural and remote communities) at the University of Southern Queensland in Toowoomba in 2012. This study involved an innovative case-based teaching approach in order to broaden their generally under-informed understanding of teaching in a rural and remote area. Three themes have been identified through analysing students’ critical reflections: learning expertise, case-based learning support and authentic learning. The outcomes identified the changes in pre-service teachers’ understanding after they have deepened their knowledge of the realities of teaching in rural and remote areas.

Keywords: rural and remote education, case based teaching, innovative education approach, higher education

Procedia PDF Downloads 480

Authors: Fred Mageto

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A great number of children in mainstream schools across Kenya are currently living with emotional, behavioural difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioural difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Kenya find classroom behaviour problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with emotional and behavioural difficulties (EBD). The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: teachers, children, learning, emotional and behaviour difficulties

Procedia PDF Downloads 139

Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

Procedia PDF Downloads 86

Authors: Roman J. Jedrzejczyk, Damian K. Chlebda, Anna Dziedzicka, Rafal Wazny, Agnieszka Domka, Maciej Sitarz, Przemyslaw J. Jodlowski

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The aim of this study was to obtain antimicrobial material based on thin zirconium dioxide coatings on structured reactors doped with metal nanoparticles using the sonochemical sol-gel method. As a result, dense, uniform zirconium dioxide films were obtained on the kanthal sheets which can be used as support materials in antimicrobial converters with sophisticated shapes. The material was characterised by physicochemical methods, such as AFM, SEM, EDX, XRF, XRD, XPS and in situ Raman and DRIFT spectroscopy. In terms of antimicrobial activity, the material was tested by ATP/AMP method using model microbes isolated from the real systems. The results show that the material can be potentially used in the market as a good candidate for active package and as active bulkheads of climatic systems. The mechanical tests showed that the developed method is an efficient way to obtain durable converters with high antimicrobial activity against fungi and bacteria.

Keywords: antimicrobial properties, kanthal steel, nanocomposite, zirconium oxide

Procedia PDF Downloads 186

Authors: Luigina Mortari, Alessia Bevilacqua, Roberta Silva

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The experience presented in this paper aims to understand how educational research can support the introduction and optimization of teaching innovations in legal education. In this increasingly complex context, a strong need to introduce paths aimed at acquiring not only professional knowledge and skills but also transversal such as reflective, critical, and problem-solving skills emerges. Through a peer observation intertwined with an analysis of discursive practices, researchers and the teacher worked together through a process of participatory and transformative accompaniment whose objective was to promote the active participation and engagement of students in learning processes, an element indispensable to work in the more specific direction of strengthening key competences. This reflective faculty development path led the teacher to activate metacognitive processes, becoming thus aware of the strengths and areas of improvement of his teaching innovation.

Keywords: legal education, teaching innovation, peer observation, discursive analysis, faculty development

Procedia PDF Downloads 148

Authors: Renu Tomar, Hitendra K. Malik, Raj P. Dahiya

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Similar to the sound waves in air, plasmas support the propagation of ion waves, which evolve into the solitary structures when the effect of non linearity and dispersion are balanced. The ion acoustic solitary waves have been investigated in details in homogeneous plasmas, inhomogeneous plasmas, and magnetized plasmas. The ion acoustic solitary waves are also found to reflect from a density gradient or boundary present in the plasma after propagating. Another interesting feature of the solitary waves is their collision. In the present work, we carry out analytical calculations for the head-on collision of solitary waves in a magnetized plasma which has dust grains in addition to the ions and electrons. For this, we employ Poincar´e-Lighthill-Kuo (PLK) method. To lowest nonlinear order, the problem of colliding solitary waves leads to KdV (modified KdV) equations and also yields the phase shifts that occur in the interaction. These calculations are accomplished for the uniform and nonuniform plasmas, and the results on the soliton properties are discussed in detail.

Keywords: inhomogeneous magnetized plasma, dust charging, soliton collisions, magnetized plasma

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Authors: Surita Maini, Sanjay Dhanka

Abstract:

Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Mona M. Salem, Khaled S. Al-Hagla, Hany M. Ayad

Abstract:

The concept of urban metabolism has increasingly been employed in a diverse range of disciplines as a mean to analyze and theorize the city. Urban ecology has a particular focus on the implications of applying the metabolism concept to the urban realm. This approach has been developed by a few researchers, though it has rarely if ever been used in policy development for city planning. The aim of this research is to use ecologically informed urban planning interventions to increase the sustainability of urban metabolism; with special focus on land stock as a most important city resource by developing a system dynamic based DSS. This model identifies two critical management strategy variables for the Strategic Urban Plan Alexandria SUP 2032. As a result, this comprehensive and precise quantitative approach is needed to monitor, measure, evaluate and observe dynamic urban changes working as a decision support system (DSS) for policy making.

Keywords: ecology, land resource, LULCC, management, metabolism, model, scenarios, system dynamics, urban development

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Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

Abstract:

Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Irina-Emily Hansen, Ola Jon Mork

Abstract:

The European economic growth strategy and supporting it framework for research and innovation highlight the importance of nurturing new open innovation in order to strengthen Europe’s competitiveness. One of the main approaches to enhance innovation in European society is the Triple Helix model that centres on science- industry collaboration where the universities are assigned the managerial role. In spite of the defined collaboration strategy, the collaboration between academics and in-dustry in Europe has still many challenges. Many of them are explained by culture difference: academic culture aims towards scientific knowledge, while businesses are oriented towards pro-duction and profitable results; also execution of collaborative projects is seen differently by part-ners involved. That proves that traditional management strategies applied to collaboration between researchers and businesses are not effective. There is a need for dynamic strategies that can support the interaction between researchers and industry intensifying knowledge co-creation and contributing to development of national innovation system (NIS) by incorporating individual, organizational and inter-organizational learning. In order to find a good subject to follow, the researchers of a given paper have investigated one of the most rapidly developing knowledge-based, innovation society, Singapore. Singapore does not dispose much land- or sea- resources that normally provide income for any country. Therefore, Singapore was forced to think differently and build society on resources that are available: talented people and knowledge. Singapore has during the last twenty years developed attracting high rated university camps, research institutions and leading industrial companies from all over the world. This article elucidates and elaborates Singapore’s national innovation strategies from Knowledge Management perspective. The research is done on the variety of organizations that enable and support knowledge development in this state: governmental research and development (R&D) centers in universities, private talent incubators for entrepreneurs, and industrial companies with own R&D departments. The research methods are based on presentations, documents, and visits at a number of universities, research institutes, innovation parks, governmental institutions, industrial companies and innovation exhibitions in Singapore. In addition, a literature review of science articles is made regarding the topic. The first finding is that objectives of collaboration between researchers, entrepreneurs and industry in Singapore correspond primary goals of the state: knowledge- and economy growth. There are common objectives for all stakeholders on all national levels. The second finding is that Singapore has enabled system on a national level that supports innovation the entire way from fostering or capturing the new knowledge, providing knowledge exchange and co-creation to application of it in real-life. The conclusion is that innovation means not only new idea, but also the enabling mechanism for its execution and the marked-oriented approach in order that new knowledge can be absorbed in society. The future research can be done with regards to application of Singapore knowledge management strategy in innovation to European countries.

Keywords: knowledge management strategy, national innovation system, research industry and business collaboration, knowledge enabling

Procedia PDF Downloads 168