Search results for: open and distant learning programme

Authors: Selvia Arokiya Mary

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Introduction: Worldwide, breast cancer comprises 10.4% of all cancer incidence among women. In 2004, breast cancer caused 519,000 deaths worldwide (7% of cancer deaths; almost 1% of all deaths). Many women who undergo breast surgery suffer from ill-defined pain syndromes. STATEMENT OF THE PROBLEM: A study to assess the effectiveness of twin therapeutic approaches on certain bio-physiological parameters in breast cancer patients after breast surgery at selected hospital, Chennai. Objectives: This study is to 1. assess the level of certain biophysiological parameters in women after mastectomy. 2. assess the effectiveness of twin therapeutic approaches on certain biophysiological parameters in women after mastectomy. 3. correlate the practice of twin therapeutic approaches with certain biophysiological parameters. 4. associate the selected demographic variables with certain biophysiological parameters in women after mastectomy Research Design and Method: Pre experimental research design was used. Fifty women were selected by using convenient sampling technique at government general hospital, Chennai. Results: The Level of pain shows, in the study group 49(98%) of them had moderate in the pre test and after the intervention all of them had mild pain in the post test. In relation to level of shoulder function before the intervention shows that in the study group 49(98%) of them had movement towards gravity and after intervention 24 (48%) of them had movement against gravity maximum resistance. There was a significant reduction in pain and shoulder stiffness level at a ‘P’ level of < 0.001. There was a negative correlation between the pranayama practice and the level of pain, there was a positive correlation between the arm exercise practice and the level of shoulder function. There was no significant association between demographic and clinical variables with the level of pain and shoulder function in the study. Hypothesis: There is a significant difference in level of pain and shoulder function among women following breast surgery who receive pranayama & arm exercise programme. The pranayama had effect in terms of reduction of pain, arm exercise programme had effect in prevention of arm stiffness among post operative women following breast surgery. Thus the stated hypothesis was accepted. Conclusion: On the basis of the findings of the present study there was Advancing age related to increasing risk of breast cancer, level of pain also the type of surgery was associated with level of pain and shoulder function, There fore it is to be concluded that the study participants may get benefited by practice of pranayama and arm exercise program.

Keywords: biophysiological parameters breast surgery, lumpectomy , mastectomy, radical mastectomy, twin therapeutic approach, pranayama, arm exercise

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Authors: Maha Wiss, Wael Khreich

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Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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Authors: Linnea Stenliden

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

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

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Authors: Mamani Acurio Alex, Aguilar Alonso Igor

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The lack of interest and the lack of motivation are related. The lack of both in school generates serious problems such as school dropout or a low level of learning. Augmented reality has been very useful in different areas, and in this research, it was implemented in the area of education. Information necessary for the correct development of this mobile application with augmented reality was searched using six different research repositories. It was concluded that the application must be immersive, attractive, and fun for students, and the necessary technologies for its construction were defined.

Keywords: augmented reality, Vuforia, school interest, learning

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Authors: Aiydh Aljeddani, Fran Martin

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Sustainable human development is an essential component of a sustainable economic, social and environmental development. Addressing sustainable learning only through the addition of new teaching methods, or embedding certain approaches, is not sufficient on its own to support the goals of sustainable human development. This research project seeks to explore how the process of redesigning the current principles of curriculum based on the concept of sustainable learning could contribute to preparing a citizen who could later contribute towards sustainable human development. Multiple qualitative methodologies were employed in order to achieve the aim of this study. The main research methods were teachers’ field notes, artefacts, informal interviews (unstructured interview), a passive participant observation, a mini nominal group technique (NGT), a weekly diary, and weekly meeting. The study revealed that the integration of a curriculum for sustainable development, in addition to the use of innovative teaching approaches, highly valued by students and teachers in social studies’ sessions. This was due to the fact that it created a positive atmosphere for interaction and aroused both teachers and students’ interest. The content of the new curriculum also contributed to increasing students’ sense of shared responsibility through involving them in thinking about solutions for some global issues. This was carried out through addressing these issues through the concept of sustainable development and the theory of Thinking Activity in a Social Context (TASC). Students had interacted with sustainable development sessions intellectually and they also practically applied it through designing projects and cut-outs. Ongoing meetings and workshops to develop work between both the researcher and the teachers, and by the teachers themselves, played a vital role in implementing the new curriculum. The participation of teachers in the development of the project through working papers, exchanging experiences and introducing amendments to the students' environment was also critical in the process of implementing the new curriculum. Finally, the concept of sustainable learning can contribute to the learning outcomes much better than the current curriculum and it can better develop the learning objectives in educational institutions.

Keywords: redesigning, social studies and citizenship education curriculum, sustainable learning, thinking activity in a social context

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Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Yuh-Jen Wu, Chun-Min Lin

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Homophonic words are common in Mandarin Chinese which belongs to the tonal language family. Using homophonic cues to study foreign languages is one of the learning techniques of mnemonics that can aid the retention and retrieval of information in the human memory. When learning difficult foreign words, some learners transpose them with words in a language they are familiar with to build an association and strengthen working memory. These phonological clues are beneficial means for novice language learners. In the classroom, if mnemonic skills are used at the appropriate time in the instructional sequence, it may achieve their maximum effectiveness. For Chinese-speaking students, proper use of Chinese-English homophonic word pairs may help them learn difficult vocabulary. In this study, a database program is developed by employing Visual Basic. The database contains two corpora, one with Chinese lexical items and the other with English ones. The Chinese corpus contains 59,053 Chinese words that were collected by a web crawler. The pronunciations of this group of words are compared with words in an English corpus based on WordNet, a lexical database for the English language. Words in both databases with similar pronunciation chunks and batches are detected. A total of approximately 1,000 Chinese lexical items are located in the preliminary comparison. These homophonic word pairs can serve as a valuable tool to assist Chinese-speaking students in learning and memorizing new English vocabulary.

Keywords: Chinese, corpus, English, homophonic words, vocabulary

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Authors: Paulomi Polly Burey, Mark Lynch

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It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

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Authors: Ya-Ting Carolyn Yang, Ping-Han Cheng, Shi-Hui Gilbert Chang, Terry Yuan-Fang Chen, Chih-Chieh Li

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Nanotechnology is widely applied in various areas so professionals in the related fields have to know more than nano knowledge. In the study, we focus on adopting ICT-assisted PBL in college general education to foster professionals who possess multiple abilities. The research adopted a pretest and posttest quasi-experimental design. The control group received traditional instruction, and the experimental group received ICT-assisted PBL instruction. Descriptive statistics will be used to describe the means, standard deviations, and adjusted means for the tests between the two groups. Next, analysis of covariance (ANCOVA) will be used to compare the final results of the two research groups after 6 weeks of instruction. Statistics gathered in the end of the research can be used to make contrasts. Therefore, we will see how different teaching strategies can improve students’ understanding about nanotechnology and learning skills.

Keywords: nanotechnology, science education, project-based learning, information and communication technology

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Authors: Robert Jesiolowski, Monique Jesiolowski

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Today more than ever before, we have access to new technologies which provide unforeseen opportunities for educators to pursue in online education. It starts with an idea, but that needs to be coupled with the right team of experts willing to take big risks and put in the hard work to build something different. An instructional design team was empowered to reimagine an Introduction to Sociology university course as a Game-Based Learning (GBL) experience utilizing cutting edge Virtual Reality (VR) technology. The result was a collaborative process that resulted in a type of learning based in Game theory, Method of Loci, and VR Immersion Simulations to promote deeper retention of core concepts. The team deconstructed the way that university courses operated, in order to rebuild the educational process in a whole learner-centric manner. In addition to a review of the build process, this paper will explore the results of in-course surveys completed by student participants.

Keywords: higher education, innovation, virtual reality, game-based learning, loci method

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Authors: Eugene Allevato

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Developing a responsible personal worldview is central to sustainable development, but achieving quality education to promote transformative learning for sustainability is thus far, poorly understood. Most programs involving education for sustainable development rely on changing behavior, rather than attitudes. The emphasis is on the scientific and utilitarian aspect of sustainability with negligible importance on the intrinsic value of nature. Campus sustainability projects include building sustainable gardens and implementing energy-efficient upgrades, instead of focusing on educating for sustainable development through exploration of students’ values and beliefs. Even though green technology adoption maybe the right thing to do, most schools are not targeting the root cause of the environmental crisis; they are just providing palliative measures. This study explores the under-examined factors that lead to pro-environmental behavior by investigating the environmental perceptions of both college business students and personnel of green organizations. A mixed research approach of qualitative, based on structured interviews, and quantitative instruments was developed including 30 college-level students’ interviews and 40 green organization staff members involved in sustainable activities. The interviews were tape-recorded and transcribed for analysis. Categorization of the responses to the open‐ended questions was conducted with the purpose of identifying the main types of factors influencing attitudes and correlating with behaviors. Overall the findings of this study indicated a lack of appreciation for nature, and inability to understand interconnectedness and apply critical thinking. The results of the survey conducted on undergraduate students indicated that the responses of business and liberal arts students by independent t-test were significantly different, with a p‐value of 0.03. While liberal arts students showed an understanding of human interdependence with nature and its delicate balance, business students seemed to believe that humans were meant to rule over the rest of nature. This result was quite intriguing from the perspective that business students will be defining markets, influencing society, controlling and managing businesses that supposedly, in the face of climate change, shall implement sustainable activities. These alarming results led to the focus on green businesses in order to better understand their motivation to engage in sustainable activities. Additionally, a probit model revealed that childhood exposure to nature has a significantly positive impact in pro-environmental attitudes to most of the New Ecological Paradigm scales. Based on these findings, this paper discusses educators including Socrates, John Dewey and Paulo Freire in the implementation of eco-pedagogy and transformative learning following a curriculum with emphasis on critical and systems thinking, which are deemed to be key ingredients in quality education for sustainable development.

Keywords: eco-pedagogy, environmental behavior, quality education for sustainable development, transformative learning

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Authors: Edgardo V. Gubatanga Jr., Mark Joshua Salvacion

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Most aerial LiDAR systems have accompanying aerial cameras in order to capture not only the terrain of the surveyed area but also its true-color appearance. However, the presence of atmospheric clouds, poor lighting conditions, and aerial camera problems during an aerial survey may cause absence of aerial photographs. These leave areas having terrain information but lacking aerial photographs. Intensity images can be derived from LiDAR data but they are only grayscale images. A deep learning model is developed to create a complex function in a form of a deep neural network relating the pixel values of LiDAR-derived intensity images and true-color images. This complex function can then be used to predict the true-color images of a certain area using intensity images from LiDAR data. The predicted true-color images do not necessarily need to be accurate compared to the real world. They are only intended to look realistic so that they can be used as base maps.

Keywords: aerial LiDAR, colorization, deep learning, intensity images

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Authors: James Purnama, Riri Fitri Sari

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

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

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Henriette van Rensburg, Betty Adcock

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

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

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Authors: Temple Probyne Abali

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Port Harcourt, Rivers State in the Niger Delta region of Nigeria is bedeviled by the phenomenon of climatechange, posing threat to food security and livelihood. This study examined a 4 decadel (1980-2020) trend of climate change as well as its socio-economic impact on food security in the region. Furthermore, to achieve sustainable food security and livelihood amidst the phenomenon, the study adopted the World Bank Assisted Third National Fadama Development Programme approach. The data source for climate change involved secondary data from Nigeria Meteorological Agency (NIMET). Consequently, the results for climate change over the 4decade period were displayed in tables, charts and maps for the expected changes. Data sources on socio-economic impact of food security and livelihood were acquired through questionnairedesign. A purposive random sampling technique was used in selecting 5 coastal communities inthe region known for viable economic potentials for agricultural development and the resultswere analyzed using Analysis of Variance (ANOVA). The Participatory Rural Appraisal (PRA) technique of the World Bank for needs assessment wasadopted in selecting 5 agricultural sub-project proposals/activities based on groups’ commoneconomic interest from a total of 1,000 farmers each drawn from the 5 communities of differentage groups including men, women, youths and the vulnerable. Based on the farmers’ sub-projectinterests, the various groups’ Strength, Weakness, Opportunities and Threats (SWOT), Problem Listing Matrix, Skill Gap Analysis as well as EIAson their sub-project proposals/activities were analyzed with substantialMonitoring and Evaluation (M & E), using the Specific, Measurable, Attribute, Reliable and Time bound (SMART)approach. Based on the findings from the PRA technique, the farmers recorded considerableincreaseinincomeofover200%withinthe5yearprojectplan(2008-2013).Thestudyrecommends capacity building and advisory services on this PRA innovation. By so doing, there would be a sustainable increase in agricultural production and assured food security in an environmental friendly manner, in line with the United Nation’s Sustainable Development Goals(SDGs).

Keywords: climate change, food security, fadama, world bank, agriculture, sdgs

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Authors: Eszter Kulcsar, Agnes Takacs, Gabriella B. Kiss, Peter Prakfalvi

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The Karancs Mountain is part of the Miocene Inner Carpathian Volcanic Belt and is located in N-NE Hungary, along the Hungarian-Slovakian border. The 14 Ma old andesitic-dacitic units are surrounded by Oligocene sedimentary units (sandstone, siltstone). The host rocks of the mineralisation are siliceous and/or argillaceous volcanic units, quartz veins, hydrothermal breccia, and strongly silicified vuggy rocks, found in the various altered volcanic units. The hydrothermal breccia consists of highly silicified vuggy quartz clasts in quartz matrix. The hydrothermal alteration of the host units shows structural control at the deeper levels. The main ore minerals are galena, pyrite, marcasite, sphalerite, hematite, magnetite, arsenopyrite, anglesite and argentite The mineralisation was first mentioned in 1944 and the first exploration took place between 1961 and 1962 in the area. The first ore geological studies were performed between 1984-1985. The exploration programme was limited only to surface sampling; no drilling programme was performed. Petrographical and preliminary fluid inclusion studies were performed on calcite samples from a galena-bearing vein. Despite the early discovery of the mineralisation, no detailed description is available, thus its size, characteristics, and origin have remained unknown. The aim of this study is to examine the mineralisation, describe the characteristics in detail and to test the possible gold content of the various quartz veins and breccias. Finally, we also investigate the potential relation of the hydrothermal mineralisation to the surrounding similar mineralisations with similar ages (e.g. W-Mátra Mountains in Hungary, Banska Bystrica, Banska Stiavnica in Slovakia) in order to place the mineralisation within the volcanic-hydrothermal evolution of the Miocene Inner Carpathian Belt. As first steps, the study includes field mapping, traditional petrological and ore microscopy; X-ray diffraction analysis; SEM-EDS and EMPA studies on ore minerals, to obtain mineral chemical information. Fluid inclusion petrography and microthermometry and micro-Raman-spectroscopy studies are also planned on quartz-hosted inclusions to investigate the physical and chemical properties of the ore-forming fluid.

Keywords: epithermal, Karancs Mountain, Hungary, Miocene Inner Carpathian volcanic belt, polimetallic ore deposit

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Rosa M. Gambier, Jennifer L. Carlson

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In order to revitalize the science curriculum for botany courses for non-science majors, we have introduced the use of the medicinal plants into a first-year botany course. We have connected the use of scientific method, scientific inquiry and active learning in the classroom with the study of Western Traditional Medical Botany. The students have researched models of Botanical medicine and have designed a sustainable medicinal plants garden using native medicinal plants from the northeast. Through the semester, the students have researched their chosen species, planted seeds in the college greenhouse, collected germination ratios, growth ratios and have successfully produced a beginners medicinal plant garden. Phase II of the project will be to tie in SCCCs community outreach goals by involving the public in the expanded development of the garden as a way of sharing learning about medicinal plants and traditional medicine outside the classroom.

Keywords: medicinal plant garden, botany curriculum, active learning, community outreach

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Authors: Feyza Daloglu

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This paper scrutinizes the Ottoman years of Wasif Jawharriyeh’s memoir, The Storyteller of Jerusalem, within the framework of citadinite, employed by the Open Jerusalem Project. Open Jerusalem Project uses the term citadinite to describe “the dynamic identity relationship city dwellers have with each other and their urban environment.” While Jerusalem and Jerusalemite identity have usually been analyzed within religious, national, or colonial frameworks, citadinite offers a fresh perspective by turning its lens to the urban identity of its citizens in the 19th and 20th centuries to overcome the shortcomings of usual frameworks. Wasif Jawharriyeh is a proud Jerusalemite and a Greek Orthodox Arab, who spent his childhood and teenage years under the Ottoman Empire. His memoir reveals a great deal of urbanity and a strong sense of Jerusalemite identity which appears to be favored over other forms of identities - Arab, Christian - in the late empire years. Through citadinite, this paper aims to discuss aspects of Jerusalemite identity and key points of urban life in the late Ottoman holy city with the guidance of a very lively and social Ottoman citizen and at that time a young musician, Wasif Jawharriyeh.

Keywords: arab memoir, cityscape, jerusalem identity, ottoman city, urban life

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Authors: Mehrnoosh Mirzaei

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Children are among the most vulnerable at the occurrence of natural disasters such as earthquakes. Most of the management and measures which are considered for both before and during an earthquake are neither suitable nor efficient for this age group and cannot be applied. On the other hand, due to their age, it is hard to educate and train children to learn and understand the concept of earthquake risk mitigation as matters like earthquake prevention and safe places during an earthquake are not easily perceived. To our knowledge, children’s awareness of such concepts via their own world with the help of games is the best training method in this case. In this article, the researcher has tried to consider the child an active element before and during the earthquake. With training, provided by adults before the incidence of an earthquake, the child has the ability to learn disaster risk reduction (DRR). The focus of this research is on learning risk reduction behavior and regarding children as an individual element. The information of this article has been gathered from library resources, observations and the drawings of 10 children aged 5 whose subject was their conceptual definition of an earthquake who were asked to illustrate their conceptual definition of an earthquake; the results of 20 questionnaires filled in by preschoolers along with information gathered by interviewing them. The design of the suitable educational game, appropriate for the needs of this age group, has been made based on the theory of design with help of the user and the priority of children’s learning needs. The final result is a package of a game which is comprised of a learning table and matching cards showing sign marks for safe and unsafe places which introduce the safe behaviors and safe locations before and during the earthquake. These educational games can be used both in group contexts in kindergartens and on an individual basis at home, and they help in earthquake risk reduction.

Keywords: disaster education, earthquake sign marks, learning table, matching card, risk reduction behavior

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Authors: M. Rodionov, Z. Dedovets

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This article discusses ways to implement a differentiated approach to developing academic motivation for mathematical studies which relies on defining the primary structural characteristics of motivation. The following characteristics are considered: features of realization of cognitive activity, meaning-making characteristics, level of generalization and consistency of knowledge acquired by personal experience. The assessment of the present level of individual student understanding of each component of academic motivation is the basis for defining the relevant educational strategy for its further development.

Keywords: learning activity, mathematics, motivation, student

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Authors: Salah Algabli

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As online learning takes center stage; Arabic language instructors face the imperative to adapt their practices for the digital realm. This study investigates the experiences of online Arabic instructors to unveil the pedagogical opportunities and challenges this format presents. Utilizing a transcendental phenomenological approach with 15 diverse participants, the research shines a light on the unique realities of online language teaching at the university level, specifically in the United States. The study proposes theoretical and practical solutions to maximize the benefits of online language learning while mitigating its challenges. Recommendations cater to instructors, researchers, and program coordinators, paving the way for enhancing the quality of online Arabic language education. The findings highlight the need for pedagogical approaches tailored to the online environment, ultimately shaping a future where both instructors and learners thrive in this digital landscape.

Keywords: online Arabic language learning, pedagogical opportunities and challenges, online Arabic teachers, online language instruction, digital pedagogy

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Authors: Shaila Rana, Wasim Alhamdani

Abstract:

Effective cybersecurity learning relies on an engaging, interactive, and entertaining activity that fosters positive learning outcomes. VR cybersecurity training may promote these aforementioned variables. However, a methodological approach and framework have not yet been created to allow trainers and educators to employ VR cybersecurity training methods to promote positive learning outcomes to the author’s best knowledge. Thus, this paper aims to create an approach that cybersecurity trainers can follow to create a VR cybersecurity training module. This methodology utilizes concepts from other cybersecurity training frameworks, such as NICE and CyTrONE. Other cybersecurity training frameworks do not incorporate the use of VR. VR training proposes unique challenges that cannot be addressed in current cybersecurity training frameworks. Subsequently, this ontology utilizes concepts unique to developing VR training to create a relevant methodology for creating VR cybersecurity training modules. The outcome of this research is to create a methodology that is relevant and useful for designing VR cybersecurity training modules.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training, ontology

Procedia PDF Downloads 269

Authors: Uche Joyce Ogbonda, Yingchun Ji, Paul Coates

Abstract:

The proximity of schools to gas flaring sites and the use of simple ventilation systems in school buildings with currently no regulation or laid down blueprint during design and construction in an environment prone to adverse environmental hazards caused by the continuous exploration of oil in the Niger Delta is worrisome. Although a wide health implication has been associated with inhalation of poor air, its effect on the performance of schoolchildren and staffs is poorly understood. Thus, the aim of this research is to explore from professionals around the region the issues surrounding the provision of clean air indoors even though, most developed and developing world are advancing in newer systems and technologies for clean indoor air. This study adopts both qualitative and quantitative approach using both open-ended and semi- structured interview techniques. This paper finds that indoor air quality is not considered during design, selection, and construction of schools. Analysis showed that rather than consider the health effect associated with the inhalation of ambient air by schoolchildren who spend 80% of their active time in schools due to the use of simple open windows and doors as source of breathable air. Advanced ventilation systems were therefore recommended to ensure supplying clean air for school buildings.

Keywords: air quality, gas flare, health implication, schools, ventilation system

Procedia PDF Downloads 286

Authors: J. Bartnicka, J. A. Piedrabuena, R. Portilla, L. Moyano - Cuevas, J. B. Pagador, P. Augat, J. Tokarczyk, F. M. Sánchez Margallo

Abstract:

Orthopaedic surgeries are characterized by a high degree of complexity. This is reflected by four main groups of resources: 1) surgical team which is consisted of people with different competencies, educational backgrounds and positions; 2) information and knowledge about medical and technical aspects of surgery; 3) medical equipment including surgical tools and materials; 4) space infrastructure which is important from an operating room layout point of view. These all components must be integrated and build a homogeneous organism for achieving an efficient and ergonomically correct surgical workflow. Taking this as a background, there was formulated a concept of international project, called “Online Vocational Training course on ergonomics for orthopaedic Minimally Invasive” (Train4OrthoMIS), which aim is to develop an e-learning tool available in 4 languages (English, Spanish, Polish and German). In the article, there is presented the first project research outcomes focused on three aspects: 1) ergonomic needs of surgeons who work in hospitals around different European countries, 2) the concept of structure of e-learning course, 3) the definition of tools and methods for knowledge assessment adjusted to users’ expectation. The methodology was based on the expert panels and two types of surveys: 1) on training needs, 2) on evaluation and self-assessment preferences. The major findings of the study allowed describing the subjects of four training modules and learning sessions. According to peoples’ opinion there were defined most expected test methods which are single choice test and right after quizzes: “True or False” and “Link elements”. The first project outcomes confirmed the necessity of creating a universal training tool for orthopaedic surgeons regardless of the country in which they work. Because of limited time that surgeons have, the e-learning course should be strictly adjusted to their expectation in order to be useful.

Keywords: international e-learning, ergonomics, orthopaedic surgery, Train4OrthoMIS

Procedia PDF Downloads 169

Authors: Cristian Crespo

Abstract:

Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

Procedia PDF Downloads 188

Authors: B. K. Manjunatha Goud, Aruna Chanu Oinam

Abstract:

The undergraduate medical curriculum is oriented towards training the students to undertake the responsibilities of a physician. During the training period, adequate emphasis is placed on inculcating logical and scientific habits of thought; clarity of expression and independence of judgment; and ability to collect and analyze information and to correlate them. At Ras Al Khaimah Medical and Health Sciences University (RAKMHSU), Biochemistry a basic medical science subject is taught in the 1st year of 5 years medical course with vertical interdisciplinary interaction with all subjects, which needs to be taught and learned adequately by the students to be related to clinical case or clinical problem in medicine and future diagnostics so that they can practice confidently and skillfully in the community. Based on these facts study was done to know the extent of usage of library resources by the students and the impact of study materials on their preparation for examination. It was a comparative cross sectional study included 100 and 80 1st and 2nd-year students who had successfully completed Biochemistry course. The purpose of the study was explained to all students [participants]. Information was collected on a pre-designed, pre-tested and self-administered questionnaire. The questionnaire was validated by the senior faculties and pre tested on students who were not involved in the study. The study results showed that 80.30% and 93.15% of 1st and 2nd year students have the clear idea of course outline given in course handout or study guide. We also found a statistically significant number of students agreed that they were benefited from the practical session and writing notes in the class hour. A high percentage of students [50% and 62.02%] disagreed that that reading only the handouts is enough for their examination as compared to other students. The study also showed that only 35% and 41% of students visited the library on daily basis for the learning process, around 65% of students were using lecture notes and text books as a tool for learning and to understand the subject and 45% and 53% of students used the library resources (recommended text books) compared to online sources before the examinations. The results presented here show that students perceived that e-learning resources like power point presentations along with text book reading using SQ4R technique had made a positive impact on various aspects of their learning in Biochemistry. The use of library by students has overall positive impact on learning process especially in medical field enhances the outcome, and medical students are better equipped to treat the patient. But it’s also true that use of library use has been in decline which will impact the knowledge aspects and outcome. In conclusion, a student has to be taught how to use the library as learning tool apart from lecture handouts.

Keywords: medical education, learning resources, study guide, biochemistry

Procedia PDF Downloads 170