Search results for: language learning

Authors: Patricia Silva, Iolanda Costa Galinha, Cristina Costa-Lobo

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The present research aims to evaluate, in the context of formal learning, the influence of affections, through subjective well-being, as well as the influence of personality, in the metacognition levels. There are few studies that analyze the influence of affection and personality on metacognition. The sample of this study consists of 300 Portuguese adolescents, male and female, aged between 15 and 17 years. The main variables of this study are affections, personality, ascertained through neuroticism and extraversion, and metacognition, namely the knowledge of cognition and the regulation of cognition. Initially, the sociodemographic questionnaire was constructed and administered to characterize the sample in its variables. To evaluate the affective experience in adolescents was administered PANAS-N, that is a measure of self-assessment of positive and negative affectivity in children and adolescents. To evaluate the personality, in its variables extroversion and neuroticism, the NEO-FFI was applied. The Metacognitive Awareness Inventory, MAI, was used to assess knowledge of cognition and regulation of cognition. The data analysis was performed using the statistical software IBM SPSS 22.0. After analyzing and discussing the results, a set of theoretical interdisciplinary reflection, between the sciences of education and psychology, is concretized, contributing to the reflection on psychoeducational intervention, opening the way for future studies.

Keywords: affections, personality, metacognition, psychoeducational intervention

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Authors: Ismial A. Raji, Blessing Egbezieme Oladejo, Babatunde Kasim Oladele

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The study investigated the influence of leadership succession and tenure on goal attainment in the University of Ibadan. Leadership styles, tenure politics, organization succession, leadership succession, goal attainment in terms of research, teaching and public services were considered. The study adopted a descriptive survey design. The population of the study was 250 consisting 90 academic staff, 100 Senior Non-Teaching Staff and 60 Junior Non-Teaching Staff. Questionnaire was the instrument used to collect data. The instrument reliability coefficient was 0.88. Data collected were analysed with descriptive statistics. The result revealed that a significant relationship exist between leadership succession, tenure and goal attainment (r= .648, 0.466 and 0.479p< .0.5) Also, There was no statistical significant interaction between the effects of leadership tenure and leadership succession on goal attainment, F (38, 131) = 1.356, p = .104. The main influence of the independent variables on goal attainment were significant at F (24, 131) = 1.682, p=.034 and F (26, 131) = 2.182, p=.002. The study concluded that leadership succession and tenure are key factors for goal attainment in the University of Ibadan. The study recommended that an effective leadership succession and tenure processes should be maintained and sustained by higher institutions of learning.

Keywords: leadership tenure, style, succession, institutional goal

Procedia PDF Downloads 262

Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

Procedia PDF Downloads 119

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

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Authors: Xinchen Zhu

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In the history of Chinese-language film, female stars’ acting is connected with issues of national ideology, consumerism, and sexual politics. In the 1980s, Taiwan entered a period of ‘soft authoritarianism’ in which the economy prospered politics became more democratic, and mass culture became more diverse. Film censorship was more flexible and sexual scenes were increasingly shown on screen. Female stars’ bodies were eroticized and commercialized through sexual and nude scenes and, by challenging conservative film censorship and social taboos, became the focus of mass media. This article will explore how discourses in mass media constructed the erotic images of female stars and, conversely, impacted film censorship, filmmakers and film actresses in 1980s’ Taiwan. This article will regard the eroticized female film stars’ acting as a ‘field’ of internal interaction and continuous reproduction, where the ideology of male dominance and voices of female film stars conflict with each other. Based on textual analysis of female stars’ sexual acting and the debate in mass media, the argument is that the eroticized female bodies were gazed upon on and off the screen. In the discourses of mass media, the artistry of actresses’ erotic acting was not only ignored, devalued and delegitimized, these stars were also labelled as ‘undressed star’ or ‘nude star’ and construed as victims of the film industry. However, the female stars were able to speak through mass media platforms, emphasizing their efforts in erotic acting and highlighting modern female subjectivity.

Keywords: sexual scenes, Taiwan female stars, erotic acting, discourses in mass media, female subjectivity

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Authors: Satien Janpla, Radasa Pojard

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The objective of this study is to study bachelor's degree students’ satisfaction towards the course of Science Project based on education quality assurance. It is a case study of the Faculty of Science and Technology, Suan Sunandha Rajabhat University. The findings can be used as a guideline for analysis and revision of the content and the teaching/learning process of the subject. Moreover, other interesting factors such as teaching method can be developed based on education quality assurance. Population in this study included 267 students in year 3 and year 4 of the Faculty of Science and Technology, Suan Sunandha Rajabhat University who registered in the subject of Science Project in semester 1/2556. The research tool was a questionnaire and the research statistics included arithmetic mean and SD. The results showed that the study of bachelor degree students’ satisfaction towards the subject of Science Project based on education quality assurance reported high satisfaction with the average of 3.51. Students from different departments showed no difference in their satisfaction.

Keywords: satisfaction, science project subject, education quality assurance, students

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Ya-Hsuan Wang

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This project of intercultural education aimed to explore pluricultural people’s interpretation and evaluation of the transnational community in Taiwan. Based on transnationalism and transculturalism, this study concerns the human right issues for immigrants and pluricultural people. Research participants as immigrants in Taiwan were asked about their typical thinking styles in the transnational community, their cultural integration in terms of transnational behaviors, and their collective memory of the transnational community. Interview questions included what key factors were involved in their identity negotiation, what roles the transnational community and collective memory would be for their identity negotiation and what were the positive or negative aspects impacting cross-border identity. Based on the experiences of pluricultural people and transnational communities, this project expected to enhance the depth and width of developing transcultural knowledge in textbook reform on History in K-12 schools. It is to transform cross-border identity into knowledge embedded with local culture in response to globalization and localization. The purpose of this paper is to portrait the cross-cultural practice of transnational community for Taiwan’s immigrants. It is to report their external socio-cultural expectation of ethnic economics, to understand their internal life course of national identity, and to clarify transnational community in relation to their cross-border identity. In conclusion, the cross-cultural practice of transnational community combined the external contexts such as ethnic economic interaction among transnational communities, social report and ethnic industry, and the internal contexts such as ethnic identity, language use, and collective memory in ethnic history.

Keywords: cross-cultural practice, immigrants, pluricultural people, transnational community

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: Chi-Cheng Cheng, Che-Hsin Lin, Yu-Jen Wang, Chua-Chin Wang

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The project-oriented capstone course has become a required element for most engineering educational units. It is not only because the capstone course is an important criterion for international accreditation of engineering degree programs under Washington Accord, but also the capstone course provides an opportunity for students to apply what they have learned in their school years to actual engineering problems. Nevertheless, most project-oriented capstone courses are conducted with one single project for all students or teams. In other words, students work to reach the same or similar goals by coming up with different layouts and approaches. It appears not suitable for a multidisciplinary engineering department. Therefore, a one-year multidisciplinary project-oriented capstone course was designed for the junior year of the undergraduate program. About one-half of faculty members in the department needs to be involved in generating as many projects as possible to meet different students' interests and specialties. Project achievement has to be displayed and demonstrated in the annual exposition and competition at the end of this course. Significant success in attracting attention and hardworking of students on projects was witnessed for the past two pilot years. Analysis of course evaluation demonstrates positive impact on all perspectives despite of slightly negative influence due to poor communication and collaboration between students and their project supervisors.

Keywords: Capstone course, CDIO, engineering education, project-oriented learning

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Giovana Nunes Inocêncio

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The professional and technological education (EPT) plays a pivotal role in equipping students for specialized careers, and it is imperative to establish a framework for efficient data exchange among educational institutions. The primary focus of this article is to address the pressing need for document interoperability within the context of EPT. The challenges, motivations, and benefits of implementing interoperability standards for digital educational documents are thoroughly explored. These documents include EPT completion certificates, academic records, and curricula. In conjunction with the prior abstract, it is evident that the intersection of IT governance and interoperability standards holds the key to transforming the landscape of technical education in Brazil. IT governance provides the strategic framework for effective data management, aligning with educational objectives, ensuring compliance, and managing risks. By adopting interoperability standards, the technical education sector in Brazil can facilitate data exchange, enhance data security, and promote international recognition of qualifications. The utilization of the XML (Extensible Markup Language) standard further strengthens the foundation for structured data exchange, fostering efficient communication, standardization of curricula, and enhancing educational materials. The IT governance, interoperability standards, and data management critical role in driving the quality, efficiency, and security of technical education. The adoption of these standards fosters transparency, stakeholder coordination, and regulatory compliance, ultimately empowering the technical education sector to meet the dynamic demands of the 21st century.

Keywords: interoperability, education, standards, governance

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 386

Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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Authors: Ivy Jeralyn T. Andres, Eva B. Macugay

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Using a descriptive research design utilizing the Research and Development (R&D) methodology, this study focused on the development of Reproductive Health Education (RHE) Toolkit for Science Teachers that provides a guide in teaching reproductive health. Based on the findings, the teacher-respondents identified nine topics that can be included in the development of the RHE toolkit. The topics included are The Male Reproductive System, The Female Reproductive System, The Roles of Hormones in Male and Female Reproductive System, Menstrual Cycle, Fertilization, Pregnancy and Childbirth, Breastfeeding, Human Reproductive and Developmental Concerns and Reproductive Health Management and Diseases. The developed RHE Toolkit is remarked as very highly valid and very highly acceptable learning material. The validators and evaluators acknowledged the developed RHE toolkit as clear, creative, and academically useful supplemental material for educating reproductive health. Moreover, it follows the principles of SMART objectives, factual, timely, and relevant content for both learners and the community as a whole. Science teachers should employ the RHE Toolkit in teaching reproductive health education into their respective classes. It is also suggested that the developed RHE toolkit can be implemented to elementary pupils and the community, particularly in rural areas.

Keywords: reproductive health education, toolkit, science teachers, supplemental material

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Authors: Latif Yanar, Muharrem Kaçan

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In this study, an Analytic Hierarchy Process and Analytic Network Process Decision Support System (DSS) model for determination of a navy base place in another country is proposed together with a decision support software (DESTEC 1.0) developed using C Sharp programming language. The proposed software also has the ability of performing the fuzzy models (Fuzzy AHP and Fuzzy ANP) of the proposed DSS to cope with the ambiguous and linguistic nature of the model. The AHP and ANP model, for a decision support for selecting the best place among the alternatives, including the criteria and alternatives, is developed and solved by the experts from Turkish Navy and Turkish academicians related to international relations branches of the universities in Turkey. Also, the questionnaires used for weighting of the criteria and the alternatives are filled by these experts.Some of our alternatives are: economic and political stability of the third country, the effect of another super power in that country, historical relations, security in that country, social facilities in the city in which the base will be built, the transportation security and difficulty from a main city that have an airport to the city will have the base etc. Over 20 criteria like these are determined which are categorized in social, political, economic and military aspects. As a result all the criteria and three alternatives are evaluated by different people who have background and experience to weight the criteria and alternatives as it must be in AHP and ANP evaluation system. The alternatives got their degrees all between 0 – 1 and the total is 1. At the end the DSS advices one of the alternatives as the best one to the decision maker according to the developed model and the evaluations of the experts.

Keywords: analytic hierarchical process, analytic network process, fuzzy logic, naval base place selection, multiple criteria decision making

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Authors: Cynthia A. Gallardo, Kelly S. Hall, Kristopher Garza, Linda Challoo, Mais Nijim

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Dual-enrollment programs have become more prevalent in college and high school settings. Also known as early college programs, dual-enrollment programs help students acquire a head start in earning college credit for post-secondary studies. The number and percentage of high school students who take college courses while in high school is growing. However, little is known about how dual-enrolled students fare. The classroom environment is important to learning. This study compares dually enrolled high school students who take courses that yield college credit either within their high school or at some other location. Mann-Whitney U was the statistical test used. Mean proportions were compared for each of the five standard letter grades earned across the state of Texas. Results indicated that students earn similar passing A, B, and C grades when they take dual-enrollment courses at their high school location but are more likely to fail if they take dual-enrollment courses at non-high school locations. Implications of results are that student success rate of dual-enrollment college courses may have a significant difference between the locations and student performance.

Keywords: educational leadership, dual-enrollment, student performance, college

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Authors: K. R. Mukuna

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Teachers are faced many challenges in the South African rural schools such as stress, depression, lack of resources, poor working relationships, inflexible curriculum etc. These could affect their wellbeing and effectiveness at the workplace. As a result, the study had a significance in the teacher’s lives, and community due teachers worked under conditions that are unfavourable to perform their jobs effectively. Despite these conditions, they still managed to do their jobs and the community is uplifted. However, this study aimed to explore factors that enable teachers to cope with workplace adversities at a rural school district in the Free State Province. It adopted a qualitative case study as a research design. Semi-structured interviews and colleges had employed as tools to collect data. Ten participants (n=10; 5 males and 5 females) were selected through purposive and convenience sampling. All participants selected from a South African rural school. Sesotho culture was their home language, and most of them had 5 years of teaching experiences. The thematic findings revealed that they developed abilities to cope with and adjust to the social and cultural environment. These included self-efficacy, developing problem-solving skills, awareness of strengths and asserts, self-managing of emotions, and self-confidence. This study concluded that these psychosocial factors contributed to coping with teacher’s diversities, and effectively stabilized their wellbeing in the schools.

Keywords: psychosocial factors, teachers counselling, teacher stress, workplace adversity, rural school, teachers’ wellbeing, teachers’ resilience, teachers’ self-efficacy, social interaction

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Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh

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Protection system is an essential feature of the electrical system which helps in detection and removal of faults. Protection system consists of many subsystems like relays, circuit breakers, instrument transformers, auxiliary DC system, auxiliary relays etc. Although the fundamental protective and relay operating concepts are similar throughout the world, there are very significant differences in their implementation. These differences arise through different traditions, operating philosophies, experiences and national standards. Protection system mis-operation due to problem in one or more of its subsystem or inadequate knowledge of numerical relay settings and configuration are very common throughout the world. Protection system mis-operation leads to unstable and unreliable grid operation. In this paper we will discuss about the fundamental concepts of protective relaying and the reasons for protection system mis-operation due to one or more of its subsystems. Many real-world case studies of protection system mis-operation from Indian power sector are discussed in detail in this paper.

Keywords: auxiliary trip relays, bus zone, check zone, CT saturation, dead zone protection, DC ground faults, DMT, DR, end fault protection, instrument transformer, SOTF, STUB

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Authors: H. K. V. Narayan

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This study was conducted at Tata Memorial Hospital (TMH), Mumbai, India. The study was to evaluate the impact of adapting Smart Card (SC) for clinical and business transactions in order to reduce Lead times and to enforce business rules of the hospital. The objective for implementing the Smart Card was to improve the patient perception of quality in terms of structures process and outcomes and also to improve the productivity of the Institution. The Smart Card was implemented in phases from 2011 and integrated with the Hospital Information System (HIS/EMR). The implementation was a learning curve for all the stake holders as software obviated the need to use hardcopies of transactions. The acceptability to the stake holders was challenge in change management. The study assessed the impact 3 years into the implementation and the observed trends have suggested that it has decreased the lead times for services and increased the no of transactions and thereby the productivity. Patients who used to complain of multiple queues and cumbersome transactions now compliment the administration for effective use of Information and Communication Technology.

Keywords: smart card, high availability of health care information, reduction in potential medical errors due to elimination of transcription errors, reduction in no of queues, increased transactions, augmentation of revenue

Procedia PDF Downloads 287

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Kldiashvili Ekaterina, Burduli Archil, Ghortlishvili Gocha

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Introduction – Medical information system (MIS) is at the heart of information technology (IT) implementation policies in healthcare systems around the world. Different architecture and application models of MIS are developed. Despite of obvious advantages and benefits, application of MIS in everyday practice is slow. Objective - On the background of analysis of the existing models of MIS in Georgia has been created a multi-user web-based approach. This presentation will present the architecture of the system and its application for image based second opinion consultations. Methods – The MIS has been created with .Net technology and SQL database architecture. It realizes local (intranet) and remote (internet) access to the system and management of databases. The MIS is fully operational approach, which is successfully used for medical data registration and management as well as for creation, editing and maintenance of the electronic medical records (EMR). Five hundred Georgian language electronic medical records from the cervical screening activity illustrated by images were selected for second opinion consultations. Results – The primary goal of the MIS is patient management. However, the system can be successfully applied for image based second opinion consultations. Discussion – The ideal of healthcare in the information age must be to create a situation where healthcare professionals spend more time creating knowledge from medical information and less time managing medical information. The application of easily available and adaptable technology and improvement of the infrastructure conditions is the basis for eHealth applications. Conclusion - The MIS is perspective and actual technology solution. It can be successfully and effectively used for image based second opinion consultations.

Keywords: digital images, medical information system, second opinion consultations, electronic medical record

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Authors: Daud Abdia, Aqsa Shamim, Farhan Tabassum

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In order to achieve specific goals, basketball players have to use different skills to enhance their motivation, one such skill is deliberate practice. The aim of this study was to explore the relationship between deliberate practice of dribbling and self-regulatory behavior of male basketball players. For this purpose, a sample of 108 basketball players using stratified sampling was taken from public and private sector universities. Sample was divided into two groups that are experimental (n=54) and control group (n=54) using comparative experimental design. Experimental group was involved in the training of deliberate practice of dribbling for 5 weeks. Amounts of weekly practice activity and Self-Regulation of Learning Self-Report Scale (SRL-SRS) were used for self-regulatory behavior to collect data after the deliberate practice. The reliability of amounts of weekly practice activity was found to be 0.852, whereas SRL-SRS was found to be 0.890. The results of the study indicated a strong positive correlation between deliberate practice of dribbling and self-regulatory behavior (r=0.755, n=54, p=.000). Whereas, paired sample t-test; t(53)=1.37, p < 0.005 shows statistically significant improvement in the self-regulatory behavior after the training program of deliberate practice from 3.02 ± 0.64m to 3.21 ± 0.75m (p < 0.005). It was concluded that in order to enhance the self-regulatory behavior of basketball players we should work on the deliberate practice of the players.

Keywords: self-regulatory behavior, deliberate practice, dribbling, basketball

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Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

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New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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Authors: Leonardo C. Pacheco-Londoño, Nataly J. Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta, Elkin Navarro, Gustavo Aroca-Martínez, Karin Rondón-Payares, Samuel P. Hernández-Rivera

Abstract:

In our Life Science Research Center of the University Simon Bolivar (LSRC), one of the focuses is the diagnosis and prognosis of different diseases; we have been implementing the use of gold nanoparticles (Au-NPs) for various biomedical applications. In this case, Au-NPs were used for Surface-Enhanced Raman Spectroscopy (SERS) in different diseases' diagnostics, such as Lupus Nephritis (LN), hypertension (H), preeclampsia (PC), and others. This methodology is proposed for the diagnosis of each disease. First, good signals of the different metabolites by SERS were obtained through a mixture of urine samples and Au-NPs. Second, PLS-DA models based on SERS spectra to discriminate each disease were able to differentiate between sick and healthy patients with different diseases. Finally, the sensibility and specificity for the different models were determined in the order of 0.9. On the other hand, a second methodology was developed using machine learning models from all data of the different diseases, and, as a result, a discriminant spectral map of the diseases was generated. These studies were possible thanks to joint research between two university research centers and two health sector entities, and the patient samples were treated with ethical rigor and their consent.

Keywords: SERS, Raman, PLS-DA, diseases

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Authors: Mohammad Ali Alavidoost, Hossein Bozorgian

Abstract:

Criterion-referenced tests (CRTs) are designed to measure student performance against a fixed set of predetermined criteria or learning standards. The reliability of such tests cannot be based on internal reliability. Threshold loss agreement is one way to calculate the reliability of CRTs. However, the selection of master and non-master in such agreement is determined by the threshold point. The problem is if the threshold point witnesses a minute change, the selection of master and non-master may have a drastic change, leading to the change in reliability results. Therefore, in this study, the Fuzzy logic approach is employed as a remedial procedure for data analysis to obviate the threshold point problem. Forty-one Iranian students were selected; the participants were all between 20 and 30 years old. A quantitative approach was used to address the research questions. In doing so, a quasi-experimental design was utilized since the selection of the participants was not randomized. Based on the Fuzzy logic approach, the threshold point would be more stable during the analysis, resulting in rather constant reliability results and more precise assessment.

Keywords: criterion-referenced tests, threshold loss agreement, threshold point, fuzzy logic approach

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Authors: Pichamon Chansuchai

Abstract:

This paper studied the expanding market opportunity palm oil ASEAN community: case study of Choomporn Palm Oil Cooperative as qualitative research. The purpose is to study and analyze expanding and linking the liberalization of trade in palm oil products under the terms of cooperation and ASEAN countries. Collection data were collected using participatory observation, in-depth interviews, focus groups, government officials, palm oil cooperative, entrepreneurs and farmers to exchange opinions. The study found that of major competitors is Indonesia and Malaysia which as ASEAM members countries has the potential to produce over Thailand. Thailand government must have a policy to increase the competitiveness of the palm oil Thailand. Using grants from the Free Trade Area fund should add value to agricultural products, palm oil and the development of standard products to meet the needs of the member countries. And creating a learning center of the palm oil sector can transfer knowledge, development of palm species, solution process from planting to harvest care privatization process. And the development of palm oil in order to expand market opportunities for Thailand's palm oil has the potential to be competitive in the neighboring countries and the region.

Keywords: palm oil, market, cooperative, ASEAN

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Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

Procedia PDF Downloads 148