Search results for: college student learning experience

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 55

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

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Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

Procedia PDF Downloads 153

Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

Procedia PDF Downloads 217

Authors: Joyce K. Anastasi, Bernadette Capili

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Community Engagement Strategies to Assist with the Development of an RCT Among People Living with HIV Our research team focuses on developing and testing protocols to manage chronic symptoms. For many years, our team designed and implemented symptom management studies for people living with HIV (PLWH). We identify symptoms that are not curative and are not adequately controlled by conventional therapies. As an exemplar, we describe how we successfully engaged PLWH in developing and refining our research feasibility protocol for distal sensory peripheral neuropathy (DSP) associated with HIV. With input from PLWH with DSP, our research received National Institutes of Health (NIH) research funding support. Significance: DSP is one of the most common neurologic complications in HIV. It is estimated that DSP affects 21% to 50% of PLWH. The pathogenesis of DSP in HIV is complex and unclear. Proposed mechanisms include cytokine dysregulation, viral protein-produced neurotoxicity, and mitochondrial dysfunction associated with antiretroviral medications. There are no FDA-approved treatments for DSP in HIV. Purpose: Aims: 1) to explore the impact of DSP on the lives of PLWH, 2) to identify patients’ perspectives on successful treatments for DSP, 3) to identify interventions considered feasible and sensitive to the needs of PLWH with DSP, and 4) to obtain participant input for protocol/study design. Description of Process: We conducted a needs assessment with PLWH with DSP. From our needs assessment, we learned from the patients’ perspective detailed descriptions of their symptoms; physical functioning with DSP; self-care remedies tried, and desired interventions. We also asked about protocol scheduling, instrument clarity, study compensation, study-related burdens, and willingness to participate in a randomized controlled trial (RCT) with a placebo and a waitlist group. Implications: We incorporated many of the suggestions learned from the need assessment. We developed and completed a feasibility study that provided us with invaluable information that informed subsequent NIH-funded studies. In addition to our extensive clinical and research experience working with PLWH, learning from the patient perspective helped in developing our protocol and promoting a successful plan for recruitment and retention of study participants.

Keywords: clinical trial development, peripheral neuropathy, traditional medicine, HIV, AIDS

Procedia PDF Downloads 73

Authors: Shanshan Zhou, Massimo Battaglia

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Identity plays a critical role when an organization faces disasters. Individuals reflect on their working identities and identify themselves with the group and the organization, which facilitate collective sensemaking under crisis situations and enable coordinated actions to respond to and recover from disasters. In addition, an organization’s identity links it to its regional community, which fosters the mobilization of resources and contributes to rapid recovery. However, identity is also problematic for disaster prevention because of its persistence. An organization’s ego-defenses system prohibits the rethink of its identity and a rigid identity obstructs disaster prevention. This research aims to tackle the ‘problem’ of identity by study in-depth a case of an Italian multi–utility which experienced the 2012 Northern Italy earthquakes. Collecting data from 11 interviews with top managers and key players in the local community and archived materials, we find that the earthquakes triggered the rethink of the organization’s identity, which got reinforced afterward. This research highlighted the importance of identity in disaster response and recovery. More importantly, it explored the solution of overcoming the barrier of ego-defense that is to transform the organization into a learning organization which constantly rethinks its identity.

Keywords: community identity, disaster, identity, organizational learning

Procedia PDF Downloads 705

Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

Procedia PDF Downloads 62

Authors: Jerome D. Donovan

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The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

Procedia PDF Downloads 61

Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

Procedia PDF Downloads 160

Authors: Steve Apell

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Transit-oriented development (TOD) is a popular intervention for local governments endeavoring to reduce auto-dependency and the adverse effects of sprawl. At the same time, American households such as the millennial generation, are shifting their residential preferences from the suburbs to the central city. These changes have intensified demand for TOD housing which generates high rents. This leads to displacement of low-income, transit-dependent households by more affluent middle class families. Critics argue that, the effectiveness of TOD might be compromised as newer affluent residents drive more and use transit less. However, there has not been a comprehensive study to test this hypothesis. Using census data ( 1990 – 2012) from six metropolitans areas, this research investigated if block groups within one-mile radius of TOD are gentrifying. Our findings reveal that the price of housing and number of college graduates, increased more in TODs compared to the metropolitan area. Similarly, the percentage of immigrants increased in TOD, while those of blacks and whites declined. Most importantly, TOD residents generally commuted less by car, while transit use increased in some metropolitan areas. TOD in the south of the United States registered higher cost of housing and less transit use. These findings have significant implications for the future of equitable and sustainable transportation policy.

Keywords: commuting, equity, gentrification, mode choice, transit oriented development

Procedia PDF Downloads 354

Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

Procedia PDF Downloads 417

Authors: Bhrugesh Radadiya, Jaydeep Shah

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In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

Procedia PDF Downloads 709

Authors: Christopher J. Johnston

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This paper presents the finding of a research study in which novice (first and second year) elementary teachers (grades Kindergarten – six) evaluated various mathematics Virtual Manipulatives, websites, and Applets (tools) for use in mathematics instruction. Participants identified the criteria they used for evaluating these types of resources and provided recommendations for or against five pre-selected tools. During the study, participants participated in three data collection activities: (1) A brief Likert-scale survey which gathered information about their attitudes toward technology use; (2) An identification of criteria for evaluating technology tools; and (3) A review of five pre-selected technology tools in light of their self-identified criteria. Data were analyzed qualitatively using four theoretical categories (codes): Software Features (41%), Mathematics (26%), Learning (22%), and Motivation (11%). These four theoretical categories were then grouped into two broad categories: Content and Instruction (Mathematics and Learning), and Surface Features (Software Features and Motivation). These combined, broad categories suggest novice teachers place roughly the same weight on pedagogical features as they do technological features. Implications for mathematics teacher educators are discussed, and suggestions for future research are provided.

Keywords: mathematics education, novice teachers, technology, virtual manipulatives

Procedia PDF Downloads 113

Authors: Salha Mohamed Hussain

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As part of the review on the Malay Language curriculum and pedagogy in Singapore conducted in 2010, some recommendations were made to nurture active learners who are able to use the Malay Language efficiently in their daily lives. In response to the review, a new Malay Language teaching and learning package for primary school, called CEKAP (Cungkil – Elicit; Eksplorasi – Exploration; Komunikasi – Communication; Aplikasi – Application; Penilaian – Assessment), was developed from 2012 and implemented for Primary 1 in all primary schools from 2015. Resources developed in this package include the text book, activity book, teacher’s guide, big books, small readers, picture cards, flash cards, a game kit and Information and Communication Technology (ICT) resources. The development of the CEKAP package is continuous until 2020. This paper will look at a model incorporated in the development of the teaching materials in the new Malay Language Curriculum for Primary Schools and the rationale for each phase of development to ensure that the resources meet the needs of every pupil in the teaching and learning of Malay Language in the primary schools. This paper will also focus on the preliminary findings of the effectiveness of the model based on the feedback given by members of the working and steering committees. These members are academicians and educators who were appointed by the Ministry of Education to provide professional input on the soundness of pedagogical approach proposed in the revised syllabus and to make recommendations on the content of the new instructional materials. Quantitative data is derived from the interviews held with these members to gather their input on the model. Preliminary findings showed that the members provided positive feedback on the model and that the comprehensive process has helped to develop good and effective instructional materials for the schools. Some recommendations were also gathered from the interview sessions. This research hopes to provide useful information to those involved in the planning of materials development for teaching and learning.

Keywords: Malay language, materials development, model, primary school

Procedia PDF Downloads 94

Authors: Happy Kumar Das, Md. Shahriar Shafiq

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This paper portrays an assumed change in the primary teacher education program in Bangladesh. An initiative has been taken with a vision to ensure an integrated approach to developing trainee teachers’ knowledge and understanding about learning at a deeper level, and with that aim, the Diploma in Primary Education (DPEd) program replaces the Certificate-in-Education (C-in-Ed) program in Bangladeshi context for primary teachers. The stated professional values of the existing program such as ‘learner-centered’, ‘reflective’ approach to pedagogy tend to contradict the practice exemplified through the delivery mechanism. To address the challenges, through the main two components (i) Training Institute-based learning and (ii) School-based learning, the new program tends to cover knowledge and value that underpin the actual practice of teaching. These two components are given approximately equal weighting within the program in terms of both time, content and assessment as the integration seeks to combine theoretical knowledge with practical knowledge and vice versa. The curriculum emphasizes a balance between the taught modules and the components of the practicum. For example, the theories of formative and summative assessment techniques are elaborated through focused reflection on case studies as well as observation and teaching practice in the classroom. The key ideology that is reflected through this newly developed program is teacher’s belief in ‘holistic education’ that can lead to creating opportunities for skills development in all three (Cognitive, Social and Affective) domains simultaneously. The proposed teacher education program aims to address these areas of generic skill development alongside subject-specific learning outcomes. An exploratory study has been designed in this regard where 7 Primary Teachers’ Training Institutes (PTIs) in 7 divisions of Bangladesh was used for experimenting DPEd program. The analysis was done based on document analysis, periodical monitoring report and empirical data gathered from the experimental PTIs. The findings of the study revealed that the intervention brought positive change in teachers’ professional beliefs, attitude and skills along with improvement of school environment. Teachers in training schools work together for collective professional development where they support each other through lesson study, action research, reflective journals, group sharing and so on. Although the DPEd program addresses the above mentioned factors, one of the challenges of the proposed program is the issue of existing capacity and capabilities of the PTIs towards its effective implementation.

Keywords: Bangladesh, effective implementation, primary teacher education, reflective approach

Procedia PDF Downloads 201

Authors: Banaz Sdiq Abdulla

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Four local species (Allium sativum, Capsicum annum, Anethum graveolens, and Ocimum basilicum) were evaluated in the laboratory of Biolog Department, College of Education, for their ability to protect stored rice from the infection by weevil Sitophilus oryzae. Aqueous extracts of the plant species were applied as direct admixture of three concentrations levels of 1%, 2.5%, and 5% (W/V) to assess for mortality, adult emergence, and repellency and weight losses. The results showed that Al. sativum extracts was the most effective as it gave the highest mortality (90%)at 5% concentration followed by Capsicum annum (80%) on the 4th day post treatment, the result showed that the plant extract of different concentrations exhibited different level of reduction in adult emergence and different repellency of adults of Sitophilus oryzae. Allium sativum recorded the lowest mean number of adult emergence (8) followed by Capsicum annum (10) at 5% concentration, while Capsicum annum was found to be revealed complete repellent agent (100%) repellency on the 6th hours against Sitophilus oryzae followed by Allium sativum and Anethum graveolens (81.8%). There was a significant (P>0.05) reduction in the weight lossed by the weevils with less damaged recorded on grain treated with Allium sativum and Capsicum annum (1.6%) and (2.3%) respectively.

Keywords: plant extraction, rice, protectant, pest

Procedia PDF Downloads 413

Authors: Shivangi Agrawal, Hsiu-I Ting

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Entrepreneurship is an essential source of economic growth and a prominent factor influencing socio-economic development. Entrepreneurship education educates and enhances entrepreneurial activity. This study aims to understand current trends in entrepreneurship education and evaluate the effectiveness of diverse entrepreneurship education programs. An increasing number of universities offer entrepreneurship education courses to create and successfully continue entrepreneurial ventures. Despite the prevalence of entrepreneurship education, research studies lack inconsistency about the effectiveness of entrepreneurship education to promote and develop entrepreneurship. Strategies to develop entrepreneurial attitudes and intentions among individuals are hindered by a lack of understanding of entrepreneurs' educational purposes, components, methodology, and resources required. Lack of adequate entrepreneurship education has been linked with low self-efficacy and lack of entrepreneurial intent. Moreover, in the age of digitisation and during the COVID-19 pandemic, digital learning platforms (e.g., online entrepreneurship education courses and programs) and other digital tools (e.g., digital game-based entrepreneurship education) have become more relevant to entrepreneurship education. This paper contributes to the continuation of academic literature in entrepreneurship education by evaluating and assessing current trends in entrepreneurship education programs, leading to better understanding to reduce gaps between entrepreneurial development requirements and higher education institutions.

Keywords: entrepreneurship education, digital technologies, academic entrepreneurship, COVID-19

Procedia PDF Downloads 232

Authors: Sultan Ayoub Meo

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Environmental pollution is a highly challenging global concern of the 21st century and is a major cause of various communicable and non-communicable diseases. We investigate the impact of air pollution on "lung function, fractional exhaled nitric oxide, and cognitive function"in a group of one hundred young students studying in a traffic-polluted school. The students wereselected based on their age, gender, height, weight, and ethnicity. After the clinical history, one hundred students were recruited from the schoolnear and away from the polluted areas. The lung and cognitive functions were recorded. The results revealed that lung and cognitive function parameters were reduced in groups of students studying in a school located in a traffic-polluted area compared to thosestudying in a schoolsituated away from the traffic-polluted area. Environmental pollution impairs students' lung and cognitive functions studying in schools located within traffic-polluted areas. The health officials and policymakers establish strategies to minimize environmental pollution and its allied health hazards. Prof. Sultan Ayoub Meo, MD, Ph.D Professor, Department of Physiology, College of Medicine, King Saud University, Saudi Arabia Email. [email protected] / [email protected]

Keywords: environmental pOllution, lung physiology, cognitive functions, air pollution

Procedia PDF Downloads 101

Authors: Vinay P., Srinivas K. S.

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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

Procedia PDF Downloads 174

Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

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This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

Procedia PDF Downloads 320

Authors: T. Moody, E. Mitchell, T. Dang, A. Barry, T. Proshan, S. Andrisse, V. Odero-Marah

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Women’s prison and reentry programs are focused primarily on reducing recidivism but neglect how an individual’s intersecting identities influence their risk of violence and ways that histories of gender-based violence (GBV) must be addressed for these women to recover from traumas. Light To Life (LTL) and From Prison Cells to Ph.D. (P2P) Womxn’s Cohort program recognizes this need; providing national gender-responsive programming (GRP), and trauma-informed programming to justice-impacted survivors through digital resources, leadership opportunities, educational workshops, and healing justice approaches for positive health outcomes. Through the support of a community-university partnership (CUP), a comparative evaluation study is being conducted among intimate-partner violence (IPV) survivors with histories of incarceration who have or have not participated in the cohort. The objectives of the partnership are to provide mutually beneficial training and consultation for evaluating GRP through a rigorously tested research methodology. This collaborative applies a rigorous methodology of semi-structured interviews with an intervention and control group to evaluate the impact of LTL’s programming in the P2P Womxn’s Cohort. The CUP is essential to achieve the expected results of the project. It will measure primary outcomes, including participants' level of engagement and satisfaction with programming, reduction in attitudes that accept violence in relationships, and increase in interpersonal and intrapersonal skills that lead to healthy relationships. This community-based approach will provide opportunities to evaluate the effectiveness of the program. The results addressed in the hypothesis will provide learning lessons to improve this program, to scale it up, and apply it to other similarly affected populations. The partnership experience and anticipated outcomes contribute to the knowledge in women’s health and criminal justice by fostering public awareness on the importance of developing new partnerships and fostering CUP to establish a framework to the leveraging of partnerships for social impact available to academic institutions.

Keywords: Community-university partnership, gender-responsive programming, incarceration, intimate-partner violence, POC, women

Procedia PDF Downloads 46

Authors: Tarik Elaujali

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This study examines a new media effective theory was developed by the author, it is called ‘The Effervescent Disk Theory’ (EDT). The theory main goal is to affect the unaffected audience who are either not exposing to a particular message or do not show interest in it. EDT suggest melting down messages that means to be affected within the media materials which are selected willingly by the audience themselves. A certain set of procedures to test EDT hypotheses were taken and illustrated in this study. A sample of 342 respondents (males & females) was collected from Tripoli University in Libya during the academic year 2013-2014. The designated sample is representing students who were failing to pass the English module for beginners’. This study aims to change the students’ negative notion about the importance of learning English, and to put their new idea into action. The theory seeks to affect audience cognition, emotions, and behaviors. EDT was applied in the present study alongside the media dependency theory. EDT hypotheses were confirmed, study results denoted that 73.6 percentage of the students responded positively and passed their English exam for beginners after being exposed selectively to their favorite TV program that contains a dissolved messages about the importance and vitality of learning English language.

Keywords: effervescent disk theory, selective exposure, media dependency, Libyan students

Procedia PDF Downloads 229

Authors: Dorothy Ebere Adimora

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The study investigated the predictive power of home environment and peer pressure on disruptive behaviour and risky sexual behaviour of Secondary School Class Two Adolescents in Enugu State, Nigeria. The design of the study is a cross sectional survey of correlational study. The study was carried out in the six Education zones in Enugu state, Nigeria. Enugu State is divided into six education zones, namely Agbani, Awgu, Enugu, Nsukka, Obollo-Afor and Udi. The population for the study was all the 31,680 senior secondary class two adolescents in 285 secondary schools in Enugu State, Nigeria in 2014/2015 academic session. The target population was students in SSS.2 senior secondary class two. They constitute one-sixth of the entire student population in the state. The sample of the study was 528, a multi stage sampling technique was employed to draw the sample. Four research questions and four null hypotheses guided the study. The instruments for data collection were an interview session and a structured questionnaire of four clusters, they are; home environment, peer pressure, risky sexual behaviour and disruptive behaviour disorder questionnaires. The instruments were validated by 3 experts, two in psychology and one in measurement and Evaluation in Faculty of Education, University of Nigeria, Nsukka. The reliability coefficient of the instruments was ascertained by subjection to field trial. The adolescents were asked to complete the questionnaire on their home environment, peer pressure, disruptive behaviour disorder and risky sexual behaviours. The risky sexual behaviours were ascertained based on interview conducted on their actual sexual practice within the past 12 months. The research questions were analyzed using Pearson r and R-square, while the hypotheses were tested using ANOVA and multiple regression analysis at 0.05 level of significance. The results of this survey revealed that the adolescents are sexually active in very young ages. The mean age at sexual debut for the adolescents covered in this survey is a pointer to the fact that some of them started engaging in sexual activities long ago. It was also found that the adolescents engage in disruptive behaviour as a result of their poor home environment factors and association with negative peers. Based on the findings, it was recommended that the adolescents should be exposed to enhanced home environment such as parents’ responsiveness, organization of the environment, availability of appropriate learning materials, opportunities for daily stimulation and to offer a proper guidance to these adolescents to avoid negative peer influence which could result in risky sexual behaviour and disruptive behaviour disorder.

Keywords: parenting, peer group, adolescents, sexuality, conduct disorder

Procedia PDF Downloads 458

Authors: Mehran Memari, Bita Asadi

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Second language (L2) classrooms in academic contexts usually consist of learners with diverse L2 proficiency levels. One solution for managing such heterogeneous classes and addressing individual needs of students is to improve learner autonomy by using technological innovations such as blogging. The focus of this study is on investigating the effects of blogging on improving the quality of Iranian university students' writings. For this aim, twenty-six Iranian university students participated in the study. Students in the experimental group (n=13) were required to blog daily while the students in the control group (n=13) were asked to write a daily schedule using paper and pencil. After a 3-month period of instruction, the five last writings of the students from both groups were rated by two experienced raters. Also, students' attitudes toward the traditional method and blogging were surveyed using a questionnaire and a semi-structured interview. The research results showed evidences in favor of the students who used blogging in their writing program. Also, although students in the experimental group found blogging more demanding than the traditional method, they showed an overall positive attitude toward the use of blogging as a way of improving their writing skills. The findings of the study have implications for the incorporation of computer-assisted learning in L2 academic contexts.

Keywords: blogging, computer-assisted learning, paper and pencil, writing

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Authors: Sangeeta Rai

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International education is Australia’s third largest export with significant revenue flowing to the economy in all state and territory jurisdictions. International students make significant economic, social and cultural contributions to all communities in which they are studying and often working. Among these international students are those from Nepal, who continue to seek Australian higher education in increasing numbers. This paper reports on findings from a literature review that highlights the gap in knowledge of the pedagogical issues that may need addressing in teaching Nepalese students in the higher education sector in Australia. Nepalese students bring to their studies a rich culture shaped by their country’s turbulent political and poor economic conditions. These factors may further contribute to their endeavors to seek education abroad to better themselves and their situation. This cohort of students faces various challenges undertaking their studies in Australia that may be due to factors including language, learning styles and engagement with peers. Hence, this paper highlights the importance of these students on Australian shores and forms the basis for further study on the issues and challenges that they face and those that need to be addressed by Australian educators.

Keywords: Nepalese students in Australia, challenges and coping mechanisms of Nepalese students, international students in Australia, socio-cultural background of Nepalese students

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Authors: Alice Civera, Mattia Cattaneo, Michele Meoli, Stefano Paleari

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Despite the fact that more equal access to higher education has been an objective public policy for several decades, little is known about the effectiveness of alternative means for achieving such goal. Indeed, nowadays, high level of graduate population can be observed both in countries with the high and low level of fees, or high and low level of public expenditure in higher education. This paper surveys the extant literature providing some background on the economic concepts of the higher education market, and reviews key determinants of demand and supply. A theoretical model of aggregate demand and supply of higher education is derived, with the aim to facilitate the understanding of the challenges in today’s higher education systems, as well as the opportunities for development. The model is validated on some exemplary case studies describing the different relationship between the level of public investment and levels of graduate population and helps to derive general implications. In addition, using a two-stage least squares model, we build a macroeconomic model of supply and demand for European higher education. The model allows interpreting policies shifting either the supply or the demand for higher education, and allows taking into consideration contextual conditions with the aim of comparing divergent policies under a common framework. Results show that the same policy objective (i.e., increasing graduate population) can be obtained by shifting either the demand function (i.e., by strengthening student aid) or the supply function (i.e., by directly supporting higher education institutions). Under this theoretical perspective, the level of tuition fees is irrelevant, and empirically we can observe high levels of graduate population in both countries with high (i.e., the UK) or low (i.e., Germany) levels of tuition fees. In practice, this model provides a conceptual framework to help better understanding what are the external conditions that need to be considered, when planning a policy for increasing graduate population. Extrapolating a policy from results in different countries, under this perspective, is a poor solution when contingent factors are not addressed. The second implication of this conceptual framework is that policies addressing the supply or the demand function needs to address different contingencies. In other words, a government aiming at increasing graduate population needs to implement complementary policies, designing them according to the side of the market that is interested. For example, a ‘supply-driven’ intervention, through the direct financial support of higher education institutions, needs to address the issue of institutions’ moral hazard, by creating incentives to supply higher education services in efficient conditions. By contrast, a ‘demand-driven’ policy, providing student aids, need to tackle the students’ moral hazard, by creating an incentive to responsible behavior.

Keywords: graduates, higher education, higher education policies, tuition fees

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Authors: Kafeero Frank

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This study aimed at developing a frame work for open source software adoption in an institution of higher learning in Uganda, with the case of KIU as a study area. There were mainly four research questions based on; individual staff interaction with open source software forum, perceived FOSS characteristics, organizational characteristics and external characteristics as factors that affect open source software adoption. The researcher used causal-correlation research design to study effects of these variables on open source software adoption. A quantitative approach was used in this study with self-administered questionnaire on a purposively and randomly sampled sample of university ICT staff. Resultant data was analyzed using means, correlation coefficients and multivariate multiple regression analysis as statistical tools. The study reveals that individual staff interaction with open source software forum and perceived FOSS characteristics were the primary factors that significantly affect FOSS adoption while organizational and external factors were secondary with no significant effect but significant correlation to open source software adoption. It was concluded that for effective open source software adoption to occur there must be more effort on primary factors with subsequent reinforcement of secondary factors to fulfill the primary factors and adoption of open source software. Lastly recommendations were made in line with conclusions for coming up with Kyambogo University frame work for open source software adoption in institutions of higher learning. Areas of further research recommended include; Stakeholders’ analysis of open source software adoption in Uganda; Challenges and way forward. Evaluation of Kyambogo University frame work for open source software adoption in institutions of higher learning. Framework development for cloud computing adoption in Ugandan universities. Framework for FOSS development in Uganda IT industry

Keywords: open source software., organisational characteristics, external characteristics, cloud computing adoption

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Authors: Ayşen Bakioğlu, Gökçen Seyra Çakır

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This study aims to explore how research assistants who work in project teams experience team member autonomy and how they reconcile team member autonomy with team collaboration. The study utilizes snowball sampling. 20 research assistants who work the faculties of education in Marmara University and Yıldız Technical University have been interviewed. The analysis of data involves a content analysis MAXQDAPlus 11 which is a qualitative data analysis software is used as the data analysis tool. According to the findings of this study, emerging themes include team norm formation, team coordination management, the role of individual tasks in team collaboration, leadership distribution. According to the findings, interviewees experience team norm formation process in terms of processes, which pertain to task fulfillment, and processes, which pertain to the regulation of team dynamics. Team norm formation process instills a sense of responsibility amongst individual team members. Apart from that, the interviewees’ responses indicate that the realization of the obligation to work in a team contributes to the team norm formation process. The participants indicate that individual expectations are taken into consideration during the coordination of the team. The supervisor of the project team also has a crucial role in maintaining team collaboration. Coordination problems arise when an individual team member does not relate his/her academic field with the research topic of the project team. The findings indicate that the leadership distribution in the project teams involves two leadership processes: leadership distribution which is based on the processes that focus on individual team members and leadership distribution which is based on the processes that focus on team interaction. Apart from that, individual tasks serve as a facilitator of collaboration amongst team members. Interviewees also indicate that individual tasks also facilitate the expression of individuality.

Keywords: project teams in higher education, research assistant teams, team collaboration, team member autonomy

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Authors: Chandra Shekhar Majumder, Md. Shamsul Haque, Khondaker Anower Hossain, Md. Rafiqul Islam

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Introduction: Ocular helminths are parasites that infect the eye or its adnexa. They can be either motile worms or sessile worms that form cysts. These parasites require two hosts for their life cycle, a definite host (usually a human) and an intermediate host (usually an insect). While there have been reports of ocular helminths infecting various structures of the eye, including the anterior chamber and subconjunctival space, there is no previous record of such a case involving the lens. Research Aim: The aim of this case report is to present a rare case of ocular helminth infection in the lens and to contribute to the understanding of this unusual site of infection. Methodology: This study is a case report, presenting the details and findings of an 80-year-old retired policeman who presented with severe pain, redness, and vision loss in the left eye. The patient had a history of diabetes mellitus and hypertension. The examination revealed the presence of a thread-like helminth in the lens. The patient underwent treatment and follow-up, and the helminth specimen was sent for identification to the department of Parasitology. Case report: An 80-year-old retired policeman attended the OPD, Faridpur Medical College Hospital with the complaints of severe pain, redness and gross dimness of vision of the left eye for 5 days. He had a history of diabetes mellitus and hypertension for 3 years. On examination, L/E visual acuity was PL only, moderate ciliary congestion, KP 2+, cells 2+ and posterior synechia from 5 to 7 O’clock position was found. Lens was opaque. A thread like helminth was found under the anterior of the lens. The worm was moving and changing its position during examination. On examination of R/E, visual acuity was 6/36 unaided, 6/18 with pinhole. There was lental opacity. Slit-lamp and fundus examination were within normal limit. Patient was admitted in Faridpur Medical College Hospital. Diabetes mellitus was controlled with insulin. ICCE with PI was done on the same day of admission under depomedrol coverage. The helminth was recovered from the lens. It was thread like, about 5 to 6 mm in length, 1 mm in width and pinkish in colour. The patient followed up after 7 days, VA was HM, mild ciliary congestion, few KPs and cells were present. Media was hazy due to vitreous opacity. The worm was sent to the department of Parasitology, NIPSOM, Dhaka for identification. Findings: The findings of this case report highlight the presence of a helminth in the lens, which has not been previously reported. The helminth was successfully removed from the lens, but the patient experienced complications such as anterior uveitis and vitreous opacity. The exact mechanism by which the helminth enters the lens remains unclear. Theoretical Importance: This case report contributes to the existing literature on ocular helminth infections by reporting a unique case involving the lens. It highlights the need for further research to understand the pathogenesis and mechanism of entry of helminths in the lens. Data Collection and Analysis Procedures: The data for this case report were collected through clinical examination and medical records of the patient. The findings were described and presented in a descriptive manner. No statistical analysis was conducted. Question Addressed: This case report addresses the question of whether ocular helminth infections can occur in the lens, which has not been previously reported. Conclusion: To the best of our knowledge, this is the first reported case of ocular helminth infection in the lens. The presence of the helminth in the lens raises interesting questions regarding its pathogenesis and entry mechanism. Further study and research are needed to explore these aspects. Ophthalmologists and parasitologists should be aware of the possibility of ocular helminth infections in unusual sites like the lens.

Keywords: ocular, helminth, unsual site, lens

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Authors: Matthew Edmunds, Andrew Hunter, Clare Littlewood, Wisha Gul, Gabriel Heppenstall-Harris, Thomas Humphries

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Background: Revision courses for medical students undertaking their final examinations are commonplace throughout the UK. Traditionally these take the form of a series of lectures over multiple weeks or a single day of intensive lectures. The COVID-19 pandemic, however, has required medical educators to create new teaching formats to ensure they adhere to social distancing requirements. It has provided an unexpected opportunity to accelerate the development of students proficiency in the use of ‘technology-enabled communication platforms’, as mandated in the 2018 GMC Outcomes of Graduates. Recent advances in technology have made distance learning possible, whilst also providing novel and more engaging learning opportunities for students. Foundation Year 2 doctors at Aintree University Hospital developed an online series of videos to help prepare medical students in the North West and byond for their final medical school examinations. Method: Eight hour-long videos covering the key topics in medicine and surgery were posted on the Peer Learning Liverpool Youtube channel. These videos were created using new technology such as the screen and audio recording platform, Loom. Each video compromised at least 20 single best answer (SBA) questions, in keeping with the format in most medical school finals. Explanations of the answers were provided, and additional important material was covered. Students were able to ask questions by commenting on the videos, with the authors replying as soon as possible. Feedback was collated using an online Google form. Results: An average of 327 people viewed each video, with 113 students filling in the feedback form. 65.5% of respondents were within one month of their final medical school examinations. The average rating for how well prepared the students felt for their finals was 6.21/10 prior to the course and 8.01/10 after the course. A paired t-test demonstrated a mean increase of 1.80 (95% CI 1.66-1.93). Overall, 98.2% said the online format worked well or very well, and 99.1% would recommend the course to a peer. Conclusions: Based on the feedback received, the online revision course was successful both in terms of preparing students for their final examinations, and with regards to how well the online format worked. Free-text qualitative feedback highlighted advantages such as; students could learn at their own pace, revisit key concepts important to them, and practice exam style questions via the case-based format. Limitations identified included inconsistent audiovisual quality, and requests for a live online Q&A session following the conclusion of the course. This course will be relaunched later in the year with increased opportunities for students to access live feedback. The success of this online course has shown the roll that technology can play in medical education. As well as providing novel teaching modes, online learning allows students to access resources that otherwise would not be available locally, and ensure that they do not miss out on teaching that was previously provided face to face, in the current climate of social distancing.

Keywords: COVID-19 pandemic, Medical School, Online learning, Revision course

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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