Search results for: indiana university dataset
Commenced in January 2007
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Edition: International
Paper Count: 5292

Search results for: indiana university dataset

4842 Knowing Where the Learning is a Shift from Summative to Formative Assessment

Authors: Eric Ho

Abstract:

Pedagogical approaches in Asia nowadays are imported from the West. In Confucian Heritage Culture (CHC), however, there is a dichotomy between the perceived benefits of Western pedagogies and the real classroom practices in Chinese societies. The success of Hong Kong students in large-scale international assessments has proved that both the strengths of both Western pedagogies and CHC educational approaches should be integrated for the sake of the students. University students aim to equip themselves with employability skills upon graduation. Formative assessments allow students to receive detailed, positive, and timely feedback and they can identify their strengths and weaknesses before they start working. However, there remains a question of whether university year 1 students who come from an examination-driven secondary education background are ready to respond to more formative assessments. The findings show that year 1 students are less concerned about competition in the university and more open to new teaching approaches that will allow them to improve as professionals in their major study areas.

Keywords: formative assessment, higher education, learning styles, Confucian heritage cultures

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4841 African Folklore for Critical Self-Reflection, Reflective Dialogue, and Resultant Attitudinal and Behaviour Change: University Students’ Experiences

Authors: T. M. Buthelezi, E. O. Olagundoye, R. G. L. Cele

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This article argues that whilst African folklore has mainly been used for entertainment, it also has an educational value that has power to change young people’s attitudes and behavior. The paper is informed by the findings from the data that was generated from 154 university students who were coming from diverse backgrounds. The qualitative data was thematically analysed. Referring to the six steps of the behaviour change model, we found that African Folklore provides relevant cultural knowledge and instills values that enable young people to engage on self-reflection that eventually leads them towards attitudinal changes and behaviour modification. Using the transformative learning theory, we argue that African Folklore in itself is a pedagogical strategy that integrates cultural knowledge, values with entertainment elements concisely enough to take the young people through a transformative phase which encompasses psychological, convictional and life-style adaptation. During data production stage all ethical considerations were observed including obtaining gatekeeper’s permission letter and ethical clearance certificate from the Ethics Committee of the University. The paper recommends that African Folklore approach should be incorporated into the school curriculum particularly in life skills education with aims to change behaviour.

Keywords: African folklore, young people, attitudinal, behavior change, university students

Procedia PDF Downloads 249
4840 The Impact of Basic TRIZ Training on Psychological Flexibility among University Students

Authors: Bakr M. Saeid

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Psychological flexibility is a basic ability that allows people to adapt to a changing, difficult world. TRIZ is a Theory of Solving Inventive Problems that has many applications in both science & technology and creativity development; this research aimed to investigate the impact of basic TRIZ training on psychological flexibility among university students. The research sample included (30) university students divided into two groups: experimental group (n=15) and control group (n=15). The Psychological Flexibility Questionnaire (PFQ) was conducted in the pre-test and post-test on the experimental and control group, as the study treatment was applied to the experimental group only. Data were analyzed statistically by the Mann-Whitney test and Wilcoxon z test; results showed the effectiveness of the TRIZ training program on the development of psychological flexibility and its five factors. Results were interpreted, recommendations were presented.

Keywords: psychological flexibility, TRIZ, positive perception of change, self as flexible and innovative, perception of reality

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4839 Challenges Associated with Recruitment of Professional Doctorate Degree Holders into Ghanaian Universities

Authors: Joseph E. Cobbinah, Abigail A. Aryeh-Adjei

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Over the years, entry into the academia in any Ghanaian university requires an advanced research degree, more preferably traditional doctorate (PhD or DPhil). It is however argued that PhD is more research intensive, so since university teaching involves a lot of research, those having traditional doctorate have good research background to teach in a university and are thus recruited as lecturers. However, in the last ten years, a reasonable number of academics enter Ghanaian universities with professional doctorate degrees, which hitherto was considered to be only suitable for industry, because it gives individuals with just basic research skills needed for professional practice, unlike the traditional PhD which is research intensive degree. Currently, there are a reasonable number of professional doctorate degree holders with qualifications like DBA, EdD, PsychD, DPharm, EngD, among others in various departments in many Ghanaian universities. Maybe, because such degree holders also use the title Dr, some university authorities put them at par with their counterparts with traditional doctorate, although some lecturers with PhD seem to look down upon those with traditional doctorate degrees and this has created some tension amongst those academics. This makes their promotions and holding of university academic positions very problematic in some ways. This paper therefore seeks to investigate the types of professional doctorate degree holders working as lecturers in some selected universities in Ghana and the challenges associated with their recruitment, acceptability and proper integration into universities’ teaching and learning. The paper adopted qualitative research methodology. In all, respondents from three state-owned and privately owned universities were involved in the study. Administrators, lecturers, heads of departments and deans of faculty were interviewed to assess the challenges associated with the recruitment of professional doctorate degree holders and any problems they face in the departments they work. It became evident that, although some lecturers enter the academia with professional doctorate degrees, their counterparts seem not to give them the recognition and respect they deserve. Although there is little or no evidence that professional doctorate degree holders are under performing, recruiting professional doctorate degree holders does not only become a challenge, but also their progression into the university’s promotion ladder become very slow compared to their counterparts with traditional PhD degrees.

Keywords: professional doctorate, academia, lecturers, Ghanaian universities, orate

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4838 Attitudes of the Staff in the Faculty of Science and Technology towards the E-Office Documentary System of the Faculty of Science and Technology, Suan Sunandha Rajabhat University

Authors: Narinee Sophatsathit, Yuwadee Nitutorn

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The purpose of this study was to investigate the attitudes of the staff in the Faculty of Science and Technology towards the e-office documentary system of the Faculty of Science and Technology, Suan Sunandha Rajabhat University. The subjects of this study included 98 staffs of the Faculty of Science and Technology, Suan Sunandha Rajabhat University. Questionnaires were used to ask the attitude of the staffs towards the implementation of e-office system. The results showed that most of the users of e-office are female with the age between 31-40 years old, master degree of education and in the academic positions. They have working experiences between 1-5 years and reported the time of using e-office between 8:30-12:30 during the weekday with the frequency of 3-5 times/day. Most of them reported their opinions on the e-office at high level (x=3.84) and problems and obstacles in using e-office at high level, as well (x=3.63).

Keywords: attitudes, e-office, staff, documentary system

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4837 The Use of Boosted Multivariate Trees in Medical Decision-Making for Repeated Measurements

Authors: Ebru Turgal, Beyza Doganay Erdogan

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Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

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4836 An Accurate Brain Tumor Segmentation for High Graded Glioma Using Deep Learning

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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4835 Body Mass Index and Dietary Habits among Nursing College Students Living in the University Residence in Kirkuk City, Iraq

Authors: Jenan Shakoor

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Obesity prevalence is increasing worldwide. University life is a challenging period especially for students who have to leave their familiar surroundings and settle in a new environment. The current study aimed to assess the diet and exercise habits and their association with body mass index (BMI) among nursing college students living at Kirkuk University residence. This was a descriptive study. A non-probability (purposive) sample of 101 students living in Kirkuk University residence was recruited during the period from the 15th November 2015 to the 5th May 2016. A questionnaire was constructed for the purpose of the study which consisted of four parts: the demographic characteristics of the study sample, eating habits, eating at college and healthy habits. The data were collected by interviewing the study sample and the weight and height were measured by a trained researcher at the college. Descriptive statistical analysis was undertaken. Data were prepared, organized and entered into the computer file; the Statistical Package for Social Science (SPSS 20) was used for data analysis. A p value≤ 0.05 was accepted as statistical significant. A total of 63 (62.4%) of the sample were aged20-21with a mean age of 22.1 (SD±0.653). A third of the sample 38 (37.6%) were from level four at college, 67 (66.3%) were female and 46 45.5% of participants were from a middle socio-economic status. 14 (13.9%) of the study sample were overweight (BMI =25-29.9kg/m2) and 6 (5.9%) were obese (BMI≥30kg/m2) compared to 73 (72.3%) were of normal weight (BMI =18.5-24.9kg/m2). With regard to eating habits and exercise, 42 (41.6%) of the students rarely ate breakfast, 79 (78.2%) eat lunch at university residence, 77 (78.2%) of the students reported rarely doing exercise and 62 (61.4%) of them were sleeping for less than eight hours. No significant association was found between the variables age, sex, level of college and socio-economic status and BMI, while there was a significant association between eating lunch at university and BMI (p =0.03). No significant association was found between eating habits, healthy habits and BMI. The prevalence of overweight and obesity among the study sample was 19.8% with female students being more obese than males. Further studies are needed to identify BMI among residence students in other colleges and increasing the awareness of undergraduate students to healthy food habits.

Keywords: body mass index, diet, obesity, university residence

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4834 Research on the Transformation of Bottom Space in the Teaching Area of Zijingang Campus, Zhejiang University

Authors: Jia Xu

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There is a lot of bottom space in the teaching area of Zijingang Campus of Zhejiang University, which benefits to the ventilation, heat dissipation, circulation, partition of quiet and noisy areas and diversification of spaces. Hangzhou is hot in summer but cold in winter, so teachers and students spend much less time in the bottom space of buildings in winter than in summer. Recently, depending on the teachers and students’ proposals, the school transformed the bottom space in the teaching area to provide space for relaxing, chatting and staying in winter. Surveying and analyzing the existing ways to transform, the paper researches deeply on the transformation projects of bottom space in the teaching buildings. It is believed that this paper can be a salutary lesson to make the bottom space in the teaching areas of universities richer and bring more diverse activities for teachers and students.

Keywords: bottom space, teaching area, transformation, Zijingang Campus of Zhejiang University

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4833 Linguistic Attitudes and Language Learning Needs of Heritage Language Learners of Spanish in the United States

Authors: Sheryl Bernardo-Hinesley

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Heritage language learners are students who have been raised in a home where a minority language is spoken, who speaks or merely understand the minority heritage language, but to some degree are bilingual in the majority and the heritage language. In view of the rising university enrollment by Hispanics in the United States who have chosen to study Spanish, university language programs are currently faced with challenges of accommodating the language needs of heritage language learners of Spanish. The present study investigates the heritage language perception and language attitudes by heritage language learners of Spanish, as well as their classroom language learning experiences and needs. In order to carry out the study, a qualitative survey was used to gather data from university students. Analysis of students' responses indicates that heritage learners are motivated to learn the heritage language. In relation to the aspects of focus of a language course for heritage learners, results show that the aspects of interest are accent marks and spelling, grammatical accuracy, vocabulary, writing, reading, and culture.

Keywords: heritage language learners, language acquisition, linguistic attitudes, Spanish in the US

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4832 From Teaching Methods to Learning Styles: Toward Humanizing Education and Building Rapport with Students at Sultan Qaboos University

Authors: Mounir Ben Zid

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The controversy over the most effective teaching method to facilitate the increase of a student's knowledge has remained a frustration for poetry teachers at Sultan Qaboos University in Oman for the last ten years. Scholars and educationists have pursued answers to this question, and tremendous effort has been marshalled to discover the optimum teaching strategy, with little success. The present study stems from this perpetual frustration among teachers of poetry and the dispute about the repertoire of teaching methods. It attempts to shed light on an alternative direction which, it is believed, has received less scholarly attention than deserved. It emphasizes the need to create a democratic and human atmosphere of learning, arouses students' genuine interest, provides students with aesthetic pleasure, and enable them to appreciate and enjoy the beauty and musicality of words in poems. More important, this teaching-learning style should aim to secure rapport with students, invite teachers to inspire the passion and love of poetry in their students and help them not to lose the sense of wonder and enthusiasm that should be in the forefront of enjoying poetry. Hence, it is the need of the time that, after they have an interest, feeling and desire for poetry, university students can move to heavier tasks and discussions about poetry and how to further understand and analyze what is being portrayed. It is timely that the pendulum swung in support of the humanization of education and building rapport with students at Sultan Qaboos University.

Keywords: education, humanization, learning style, Rapport

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4831 An Improved K-Means Algorithm for Gene Expression Data Clustering

Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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4830 Clustering Categorical Data Using the K-Means Algorithm and the Attribute’s Relative Frequency

Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: clustering, unsupervised learning, pattern recognition, categorical datasets, knowledge discovery, k-means

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4829 The Persistent English Language Gap between the Direct Entry and Foundation Program University Students: Empirical Evidence from the UAE

Authors: Eda Orhun

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This paper studies the IELTS exit scores of Emirati university students before graduation and specifically compares the IELTS exit performance of the English foundation program (FP) students to direct entry (DE) students. Direct entry (DE) students are the students who were able to directly start with the undergraduate program without the need to attend English foundation program courses as they were able to prove a sufficient level of English at the university admittance. The results clearly show that the gap that existed already between these two groups of students at the start does not seem to disappear at the end of university studies, as DE students’ IELTS exit scores are significantly higher compared to FP students. Further work of a regression analysis exhibits that GPA and CMATH scores do have a positive and significant effect on IELTS exit scores. In addition, while the College of Education students are found to have the lowest performance in every sub-section of the IELTS exam across colleges, students of the College of Humanities and Social Sciences and the College of Natural and Health Sciences seem to have the best reading skills. Another important determinant of IELTS exit scores is found to be the English level of students at inception. With these results, the study offers important policy implications regarding the public education system of the UAE and sheds light on the main roots of the problem.

Keywords: English proficiency, higher education, IELTS exit scores, English foundation program, United Arab Emirates

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4828 Public Relations for the Faculty of Management Science in Suan Sunandha Rajabhat University

Authors: Narong Anurak

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The objectives of this research were to investigate the knowledge and understanding of public relations principles for public relations officials of the office of the faculty of management science in Ratjabhat Suan Sunandha University and to determine the approach of public relations for the Office of Faculty of Management Science.  The questionnaire was utilized as a tool to collect data. Statistics utilized included frequency, percentage, mean, standard deviation, and regression analysis. The results of the research showed that the public relations officials misunderstood on public relations principles. The lack of the perception in media of the target groups both in-house and outside caused the misunderstanding on the roles, mission, and responsibilities. It would be beneficial to public relations division and other divisions of the office of the faculty of management science to be trained and obtained more knowledge and skills on the public relations to support the public relations work for the organization.

Keywords: faculty of management science, preparation in media, public relations, Suan Sunandha Rajabhat University

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4827 Neural Network and Support Vector Machine for Prediction of Foot Disorders Based on Foot Analysis

Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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4826 Exploring the Association between Race and Attitudes toward Physician-Assisted Death; An Analysis of the Gss Dataset

Authors: Seini G. Kaufusi

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Background. Physician-assisted death (PAD) has and continues to be a controversial issue in the U.S. Dying with dignity statutes exists in 9 U.S. jurisdictions that permit competent adults diagnosed with a terminal illness and given a prognosis of 6 month or less to live to request medication to hasten death. Robust advocacy for and against PAD influences policy, and opinions vary. Aim. This study aims to explore the association between race and the attitudes toward physician-assisted death in the U.S. Methods. Data for this study derives from the General Social Survey (GSS) dataset, a national survey conducted by the National Opinion Research Center (NORC) that focuses on the opinions and values of American’s. A cross-sectional design and probability sample from the 2018 data set was used to randomly select respondents. Results. The results indicated that race is significantly associated with attitudes towards physician-assisted death. The level of significance suggests a strong positive association, and the direction indicated that Black and Other racial groups have higher rates of positive decision about PAD. Conclusion. Although attitudes towards PAD varied, Black and other racial groups had favorable decisions for PAD. Further research is crucial in the continuous debate on PAD and understanding the influences of predictors for or against PAD.

Keywords: attitudes, euthanasia, physician-assisted death, race

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4825 A Selection Approach: Discriminative Model for Nominal Attributes-Based Distance Measures

Authors: Fang Gong

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Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.

Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor

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4824 A Quantitative Study of Blackboard Utilisation at a University of Technology in South Africa

Authors: Lawrence Meda, Christopher Dumas, Moses Moyo, Zayd Waghid

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As a result of some schools embracing technology to enhance students’ learning experiences in the digital era, the Faculty of Education at a University of Technology in South Africa has mandated lecturers to scale up their utilisation of technology in their teaching. Lecturers have been challenged to utilise the institution’s Learning Management System - Blackboard among other technologies - to adequately prepare trainee teachers to be able to teach competently in schools. The purpose of this study is to investigate the extent to which lecturers are utilising Blackboard to enhance their teaching. The study will be conducted using a quantitative approach, and its paradigmatic position will be positivist. The study will be done as a case study of the university’s Faculty of Education. Data will be extracted from all 100 lecturers’ Blackboard sites according to their respective modules, and it will be analysed using the four pillars of Blackboard as a conceptual framework. It is presumed that there is an imbalance on the lecturers’ utilisation of the four pillars of Blackboard as the majority use it as a content dumping site.

Keywords: blackboard, digital, education, technology

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4823 Heuristic Classification of Hydrophone Recordings

Authors: Daniel M. Wolff, Patricia Gray, Rafael de la Parra Venegas

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An unsupervised machine listening system is constructed and applied to a dataset of 17,195 30-second marine hydrophone recordings. The system is then heuristically supplemented with anecdotal listening, contextual recording information, and supervised learning techniques to reduce the number of false positives. Features for classification are assembled by extracting the following data from each of the audio files: the spectral centroid, root-mean-squared values for each frequency band of a 10-octave filter bank, and mel-frequency cepstral coefficients in 5-second frames. In this way both time- and frequency-domain information are contained in the features to be passed to a clustering algorithm. Classification is performed using the k-means algorithm and then a k-nearest neighbors search. Different values of k are experimented with, in addition to different combinations of the available feature sets. Hypothesized class labels are 'primarily anthrophony' and 'primarily biophony', where the best class result conforming to the former label has 104 members after heuristic pruning. This demonstrates how a large audio dataset has been made more tractable with machine learning techniques, forming the foundation of a framework designed to acoustically monitor and gauge biological and anthropogenic activity in a marine environment.

Keywords: anthrophony, hydrophone, k-means, machine learning

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4822 The Socio-Culturals Factors Hindering Female Sport Participation, in the Centre for Biokinetics, Recreation and Sport Science, University of Venda

Authors: P. Mambanga, Goon, L. O. Amusa

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The purpose of the study was to investigate the socio-cultural factors hindering sport participation among female students in the Centre for Biokinetics, Recreation and Sport Science, University of Venda. A descriptive survey of 100 female student selected by simple random sampling was used and utilises the close ended questionnaire designed in a likert format was use for data collection. Face and content validity was employed in which the supervisor went through the instrument and correct and accept it thus checking the validity of the instrument. The test-retest approach was used to test the reliability of the instrument. Ethical considerations were ensured and confidentiality respected. Data was collected and presented in tables and results interpreted. Chi square which is a measure of non-parametric investigation was employed in order to analyse the observed and expected scores, with the probability value was set at 0.05 levels of significance on a two-tailed test of the hypotheses formulated for the study. Findings of the study established significant socio-cultural factors that hinder female sport participation among female students in the Centre for Biokinetics, Recreation and Sport Science. The study concluded that the low level participation of female students at the University of Venda might be as a result of socio-cultural factors.

Keywords: female students, sport participation, University of Venda, biokinetic

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4821 The Experience of the Prosthetics Program in Palestine Arab American University as Model

Authors: Ahmad Dawabsheh

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The prosthetics program is an international program, found in honorable respectable universities. This program like other programs was found to serve several reasons, The most important reason is humanity, humanity free of conflict, religion, race, or war, but rather focuses on the humanitarian issue. This is what encouraged me to study this topic to help people, especially the poor in the world. The researcher will distribute a questionnaire to the faculty members and students of the department to measure the knowledge and importance of this program from the practical and theoretical sides of the local community. The researcher used the analytical method to study the subject. The research will attempt to answer the questions: What is the student's knowledge of this program? How important is this program to society?. The research aims to know the Palestinian society's need for this program. The research also aims to know the extent of students' knowledge of recent developments and new innovations in prosthetics around the world. What does the university offer to students in addition to theoretical courses?

Keywords: prosthetics, Arab American University, analytical method, questionnair

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4820 Gait Biometric for Person Re-Identification

Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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4819 Public-Public Partnership and Tourism Development Strategy: The Case of Municipality of Gazi Baba in Macedonia

Authors: Dejan Metodijeski, Elizabeta Mitreva, Nako Taskov, Oliver Filiposki

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Tourism development strategies are an important link in the tourism policy that is used to make its management better and easier. A public-public partnership (PUP) is a partnership between two or more public authorities or between a public authority and any non-profit organization with the goal of providing services and facilities or transferring technical skills. The paper presents this kind of partnership between two public authorities in Macedonia, the Municipality of Gazi Baba on one hand, and the University of Goce Delcev on the other. The main idea of this partnership is the development of a tourism strategy for the Municipality of Gazi Baba by the University on one side, and on the other, the construction of a mini park in the court of the University by the Municipality. This paper presents the causes and analyzes the procedures relating to this partnership and the methodology of the tourism development strategy. It contains a relevant literature review related to PUPs and tourism development strategy. The results and benefits of this partnership are presented with figures.

Keywords: public-public partnership, tourism development strategy, municipality of Gazi Baba, Macedonia

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4818 Developing a Research Culture in the Faculty of Engineering and Information Technology at the Central University of Technology, Free State: Implications for Knowledge Management

Authors: Mpho Agnes Mbeo, Patient Rambe

Abstract:

The thirteenth year of the Central University of Technology, Free State’s (CUT) transition from a vocational and professional training orientation institution (i.e. a technikon) into a university with a strong research focus has neither been a smooth nor an easy one. At the heart of this transition was the need to transform the psychological faculties of academic and research staffs compliment who were accustomed to training graduates for industrial placement. The lack of a culture of research that fully embraces a strong ethos of conducting world-class research needed to be addressed. The induction and socialisation of academic staff into the development and execution of cutting-edge research also required the provision of research support and the creation of a conducive academic environment for research, both for emerging and non-research active academics. Drawing on ten cases, comprising four heads of departments, three prolific established researchers, and three emerging researchers, this study explores the challenges faced in establishing a strong research culture at the university. Furthermore, it gives an account of the extent to which the current research interventions have addressed the perceivably “missing research culture”, and the implications of these interventions for knowledge management. Evidence suggests that the endowment of an ideal institutional research environment (comprising strong internet networks, persistent connectivity on and off campus), research peer mentorship, and growing publication outputs should be matched by a coherent research incentive culture and strong research leadership. This is critical to building new knowledge and entrenching knowledge management founded on communities of practice and scholarly networking through the documentation and communication of research findings. The study concludes that the multiple policy documents set for the different domains of research may be creating pressure on researchers to engage research activities and increase output at the expense of research quality.

Keywords: Central University of Technology, performance, publication, research culture, university

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4817 FLIME - Fast Low Light Image Enhancement for Real-Time Video

Authors: Vinay P., Srinivas K. S.

Abstract:

Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

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4816 On Enabling Miner Self-Rescue with In-Mine Robots using Real-Time Object Detection with Thermal Images

Authors: Cyrus Addy, Venkata Sriram Siddhardh Nadendla, Kwame Awuah-Offei

Abstract:

Surface robots in modern underground mine rescue operations suffer from several limitations in enabling a prompt self-rescue. Therefore, the possibility of designing and deploying in-mine robots to expedite miner self-rescue can have a transformative impact on miner safety. These in-mine robots for miner self-rescue can be envisioned to carry out diverse tasks such as object detection, autonomous navigation, and payload delivery. Specifically, this paper investigates the challenges in the design of object detection algorithms for in-mine robots using thermal images, especially to detect people in real-time. A total of 125 thermal images were collected in the Missouri S&T Experimental Mine with the help of student volunteers using the FLIR TG 297 infrared camera, which were pre-processed into training and validation datasets with 100 and 25 images, respectively. Three state-of-the-art, pre-trained real-time object detection models, namely YOLOv5, YOLO-FIRI, and YOLOv8, were considered and re-trained using transfer learning techniques on the training dataset. On the validation dataset, the re-trained YOLOv8 outperforms the re-trained versions of both YOLOv5, and YOLO-FIRI.

Keywords: miner self-rescue, object detection, underground mine, YOLO

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4815 Integrating Wound Location Data with Deep Learning for Improved Wound Classification

Authors: Mouli Banga, Chaya Ravindra

Abstract:

Wound classification is a crucial step in wound diagnosis. An effective classifier can aid wound specialists in identifying wound types with reduced financial and time investments, facilitating the determination of optimal treatment procedures. This study presents a deep neural network-based based classifier that leverages wound images and their corresponding locations to categorize wounds into various classes, such as diabetic, pressure, surgical, and venous ulcers. By incorporating a developed body map, the process of tagging wound locations is significantly enhanced, providing healthcare specialists with a more efficient tool for wound analysis. We conducted a comparative analysis between two prominent convolutional neural network models, ResNet50 and MobileNetV2, utilizing a dataset of 730 images. Our findings reveal that the RestNet50 outperforms MovileNetV2, achieving an accuracy of approximately 90%, compared to MobileNetV2’s 83%. This disparity highlights the superior capability of ResNet50 in the context of this dataset. The results underscore the potential of integrating deep learning with spatial data to improve the precision and efficiency of wound diagnosis, ultimately contributing to better patient outcomes and reducing healthcare costs.

Keywords: wound classification, MobileNetV2, ResNet50, multimodel

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4814 Application of an Educational Program for Al Jouf University Students regarding Scientific Writing and Presentation Skills

Authors: Fatma Abdel Moneim Al Tawil

Abstract:

This study was undertaken to evaluate an educational program regarding scientific writing and presentation skills among university students. This interventional study used a one-group, pretest/posttest design and was conducted in Al Jouf University among four colleges in Saudi Arabia. Baseline students’ assessment was conducted for developing educational program. Interventional, one group, pretest/posttest study was designed to evaluate the effectiveness of the educational program. Three parts evaluation sheet with total scores of 30 was used for 113 students for the development of the program and 52 students for test pretest phase. Wilcoxon signed ranks showed statistically significant improvement in the combined overall program skills score from a median of 56.7 pre to a median of 86.7 post, (z = 6.231, p < 0.001). When compared to preprogram intervention, post interventions 51.9 % of students achieve excellent performance. While pre intervention no students (0.0 %) achieve this score. Regarding to scientific writing skills, Wilcoxon signed ranks showed statistically significant improvement in the score from a median of 60 pre to a median of 90 post, (z = 6.122, p < 0.001). None of students had excellent performance changed to 73.1%. Regarding to oral presentation skills, Wilcoxon signed ranks showed statistically significant improvement in the score from a median of 50 pre to a median of 80 post, (z = 6.153, p < 0.001). None of students had excellent performance changed to 48.1%. Such educational program needs to be incorporated into classroom delivery of the students’ curriculum. Scientific writing skills book needed to be developed to be recommended as a basic educational strategy for all university faculties.

Keywords: scientific writing, presentation skills, university students, educational program

Procedia PDF Downloads 436
4813 Archive's Accessibility of University Archive: Case Study at Universitas Gadjah Mada Archives

Authors: Berlian Eka Kurnia, Mohamad Very Setiawan, Rahmat Fadhli

Abstract:

Archives play an important role in organization’s continuity, especially related to the learning activities in the past. Archive management is considered accessible when the archive can be used when needed. University archive can support research activities for institutions, besides, archive management services also have to pay attention to the accessibility that became a barometer of how easy users get the data or information from an archive, use and understand it. This study identifies about the accessibility of archive services at the Universitas Gadjah Mada, with case study method. Universitas Gadjah Mada archives not only provide a service to the academicians, but also for public. Universitas Gadjah Mada archive can be traced online and offline. Online searching archives can be acceessed through an application “SIKS” and offline searching can be accessed by "finding aids" printed. Although Universitas Gadjah Mada Archives has its own procedures to access the archive directly, but they also remain guided by National Archive of Indonesia.

Keywords: archival institution, university archive, archive’s accessibility, archive management

Procedia PDF Downloads 306