Search results for: learning motion patterns

Authors: Kumar Vikas

Abstract:

Education is to be anticipated for Human resource development and then national development. However, in most of the developing countries, due to the inadequacy of resources it is almost unattainable to educate all of their citizens through on-campus teaching. Huge amount of money is necessary to establish the infrastructure for on-campus teaching which is out of the reach of the developing countries. In these circumstances, to educate their huge inhabitants the developing countries are to depend on open learning and distance education system. However, a question still stands: can the educators dissimulate knowledge to the learners smoothly through this new system of education? Some recent research shows that the graduates of the open and distance learning institutions in the developing countries are treated as second-grade graduates. This paper aims to identify the challenges or barriers in the development of distance and Open learning system in India and suggest possible alternatives may be followed to overcome the barriers.

Keywords: barriers, distance education, developing countries, motivation, alternative solutions

Procedia PDF Downloads 242

Authors: M. Eskandarighadi, C. R. McGann

Abstract:

It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

Procedia PDF Downloads 148

Authors: Suruchi

Abstract:

This study aims to examine the spatial and temporal patterns of fog occurrences across Czech Republic. It utilizes satellite imagery and other data sources to achieve this goal. The main objective is to understand the role of fog in atmospheric deposition processes and its potential impact on the environment and ecosystems. Through satellite image analysis, the study will identify and categorize different types of fog, including radiation fog, orographic fog, and mountain fog. Fog detection algorithms and cloud type products will be evaluated to assess the frequency and distribution of fog events throughout the Czech Republic. Furthermore, the regions covered by fog will be classified based on their fog type and associated pollution levels. This will provide insights into the variability in fog characteristics and its implications for atmospheric deposition. Spatial analysis techniques will be used to pinpoint areas prone to frequent fog events and evaluate their pollution levels. Statistical methods will be employed to analyze patterns in fog occurrence over time and its connection with environmental factors. The ultimate goal of this research is to offer fresh perspectives on fog's role in atmospheric deposition processes, enhancing our understanding of its environmental significance and informing future research and environmental management initiatives.

Keywords: pollution, GIS, FOG, satellie, atmospheric deposition

Procedia PDF Downloads 9

Authors: Sandra Thompson, Paul Dervan

Abstract:

Ireland’s first Technological University (TU Dublin) was established on 1st January 2019, and its creation is an exciting new milestone in Irish Higher Education. TU Dublin is now Ireland’s biggest University supporting 29,000 students across three campuses with 3,500 staff. The University aspires to create work-ready graduates who are socially responsible, open-minded global thinkers who are ambitious to change the world for the better. As graduates, they will be enterprising and daring in all their endeavors, ready to play their part in transforming the future. Feedback from Irish employers and students coupled with evidence from other authoritative sources such as the World Economic Forum points to a need for greater focus on the development of students’ employability skills as they prepare for today’s work environment. Moreover, with an increased focus on Universal Design for Learning (UDL) and inclusiveness, there is recognition that students are more than a numeric grade value. Robust grading systems have been developed to track a student’s performance around discipline knowledge but there is little or no global consensus on a definition of transversal skills nor on a unified framework to assess transversal skills. Education and industry sectors are often assessing one or two skills, and some are developing their own frameworks to capture the learner’s achievement in this area. Technological University Dublin (TU Dublin) have discovered and implemented a framework to allow students to develop, assess and record their transversal skills using transformative learning theory. The model implemented is an adaptation of Student Transformative Learning Record - STLR which originated in the University of Central Oklahoma (UCO). The purpose of this paper therefore, is to examine the views of students, staff and employers in the context of deploying a Transformative Learning model within the University to assess transversal skills. It will examine the initial impact the transformative learning model is having socially, personally and on the University as an organization. Crucially also, to identify lessons learned from the deployment in order to assist other Universities and Higher Education Institutes who may be considering a focused adoption of Transformative Learning to meet the challenge of preparing students for today’s work environment.

Keywords: assessing transversal skills, higher education, transformative learning, students

Procedia PDF Downloads 125

Authors: Bashaiar Alsanaa

Abstract:

Never has a revolution influenced all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aims to fill the void of research conducted around that topic. The study explores teachers’ acceptance of incorporating communication technologies in higher education in Kuwait. Teachers’ responses to survey questions present an overview of the e-learning experience in this country, and draw a framework through which implications and suggestions for future research can be discussed to better serve the advancement of e-education in developing countries.

Keywords: communication technologies, E-learning, Kuwait, social media

Procedia PDF Downloads 278

Authors: Bashaiar Alsana

Abstract:

Never has a revolution influenced all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aims to fill the void of research conducted around that topic. The study explores teachers’ acceptance of incorporating communication technologies in higher education in Kuwait. Teachers’ responses to survey questions present an overview of the e-learning experience in this country, and draw a framework through which implications and suggestions for future research can be discussed to better serve the advancement of e-education in developing countries.

Keywords: communication technologies, e-learning, Kuwait, social media

Procedia PDF Downloads 255

Authors: Siti Ayu Ningsih

Abstract:

This study aims to find the differences outcomes in learning reading comprehension with text and film as media on Indonesian Language for foreign speaker (BIPA) learning at intermediate level. By using quantitative and qualitative research methods, the respondent of this study is a single respondent from D'Royal Morocco Integrative Islamic School in grade nine from secondary level. Quantitative method used to calculate the learning outcomes that have been given the appropriate action cycle, whereas qualitative method used to translate the findings derived from quantitative methods to be described. The technique used in this study is the observation techniques and testing work. Based on the research, it is known that the use of the text media is more effective than the film for intermediate level of Indonesian Language for foreign speaker learner. This is because, when using film the learner does not have enough time to take note the difficult vocabulary and don't have enough time to look for the meaning of the vocabulary from the dictionary. While the use of media texts shows the better effectiveness because it does not require additional time to take note the difficult words. For the words that are difficult or strange, the learner can immediately find its meaning from the dictionary. The presence of the text is also very helpful for Indonesian Language for foreign speaker learner to find the answers according to the questions more easily. By matching the vocabulary of the question into the text references.

Keywords: Indonesian language for foreign speaker, learning outcome, media, reading comprehension

Procedia PDF Downloads 194

Authors: Ming-Juei Chang, Hui-Ing Ma, Tsung-Hsueh Lu

Abstract:

Introduction: Because of the advance of medical care (e.g., ventilation techniques and gastrostomy feeding), more and more children with CP can live to adulthood. However, little is known about the use of health care services from children to adults who have CP. The patterns of utilization of ambulatory care are heavily influenced by insurance coverage and primary care gatekeeper regulation. The purpose of this study was to examine patterns of ambulatory care utilization among individuals with CP in Taiwan, a country with universal coverage and no gatekeeper regulation. Methods: A representative sample of one million patients (about 1/23 of total population) covered by Taiwan’s National Health Insurance was used to analyze the ambulatory care utilization in individuals with CP. Data were analyzed by 3 different age groups (children, youth and adults) during 2000 to 2003. Participants were identified by the presence of CP diagnosis made by pediatricians or physicians of physical and rehabilitation medicine and stated at least three times in claims data. Results: Annual rates of outpatient physician visits were 31680 for children, 16492 for youth, and 28617 for adults with CP (per 1000 persons). Individuals with CP received over 50% of their outpatient care from hospital outpatient department. Higher use of specialist physician services was found in children (54.7%) than in the other two age groups (28.4% in youth and 18.8% in adults). Diseases of respiratory system were the most frequent diagnoses for visits in both children and youth with CP. Diseases of the circulatory system were the main reasons (24.3%) that adults with CP visited hospital outpatient care department or clinics. Conclusion: This study showed different patterns of ambulatory care utilization among different age groups. It appears that youth and adults with CP continue to have complex health issues and rely heavily on the health care system. Additional studies are needed to determine the factors which influence ambulatory care utilization among individuals with CP.

Keywords: cerebral palsy, health services, lifespan, universal coverage

Procedia PDF Downloads 373

Authors: Jorn Meyer, Stefan Sturmer

Abstract:

The assessment of attachment patterns in toddlers and adults has been well researched, and valid diagnostic methods (e.g., Strange Situation Test, Adult Attachment Interview) are applicable. For middle and late childhood, on the other hand, there are only few validated methods available so far. For the Child Attachment Interview (CAI) promising validation studies from English-speaking countries are available, but so far a comprehensive study on the validity of a German sample is lacking. Within the scope of a longitudinal project, the results of the first point of measurement are reported in this study. A German-language version of the CAI was carried out with 111 primary school children (56% female; age: M = 8.34, SD = 0.49). In relation to psychometric quality criteria, parameters on interrater reliability, construct validity and discriminant, and convergent validity are reported. Analyses of the correlations between attachment patterns and internalizing and externalizing behavior problems from parent and teacher reports are presented. The implications for the German-language assessment of attachment in middle and late childhood in research and individual case diagnostics, e.g., in the context of conducting expert evaluation reports for family courts, are discussed.

Keywords: attachment, attachment assessment, developmental psychology, longitudinal study

Procedia PDF Downloads 232

Authors: Chia Wei Lim, Ning Yan

Abstract:

The subject of reactor design, dealing with the transformation of chemical feedstocks into more valuable products, constitutes the central idea of chemical engineering. Despite its importance, the way it is taught to chemical engineering undergraduates has stayed virtually the same over the past several decades, even as the chemical industry increasingly leans towards the use of software for the design and daily monitoring of chemical plants. As such, there has been a widening learning gap as chemical engineering graduates transition from university to the industry since they are not exposed to effective platforms that relate the fundamental concepts taught during lectures to industrial applications. While the success of technology enhanced learning (TEL) has been demonstrated in various chemical engineering subjects, TELs in the teaching of reactor design appears to focus on the simulation of reactor processes, as opposed to arguably more important ideas such as the selection and optimization of reactor configuration for different types of reactions. This presents an opportunity for us to utilize the readily available easy-to-use MATLAB App platform to create an educational tool to aid the learning of fundamental concepts of reactor design and to link these concepts to the industrial context. Here, interactive software for the learning of reactor design has been developed to narrow the learning gap experienced by chemical engineering undergraduates. Dubbed the ReactorDesign App, it enables students to design reactors involving complex design equations for industrial applications without being overly focused on the tedious mathematical steps. With the aid of extensive visualization features, the concepts covered during lectures are explicitly utilized, allowing students to understand how these fundamental concepts are applied in the industrial context and equipping them for their careers. In addition, the software leverages the easily accessible MATLAB App platform to encourage self-directed learning. It is useful for reinforcing concepts taught, complementing homework assignments, and aiding exam revision. Accordingly, students are able to identify any lapses in understanding and clarify them accordingly. In terms of the topics covered, the app incorporates the design of different types of isothermal and non-isothermal reactors, in line with the lecture content and industrial relevance. The main features include the design of single reactors, such as batch reactors (BR), continuously stirred tank reactors (CSTR), plug flow reactors (PFR), and recycle reactors (RR), as well as multiple reactors consisting of any combination of ideal reactors. A version of the app, together with some guiding questions to aid explorative learning, was released to the undergraduates taking the reactor design module. A survey was conducted to assess its effectiveness, and an overwhelmingly positive response was received, with 89% of the respondents agreeing or strongly agreeing that the app has “helped [them] with understanding the unit” and 87% of the respondents agreeing or strongly agreeing that the app “offers learning flexibility”, compared to the conventional lecture-tutorial learning framework. In conclusion, the interactive ReactorDesign App has been developed to encourage self-directed explorative learning of the subject and demonstrate the industrial applications of the taught design concepts.

Keywords: explorative learning, reactor design, self-directed learning, technology enhanced learning

Procedia PDF Downloads 90

Authors: Diego Aguirre, Olac Fuentes

Abstract:

In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

Procedia PDF Downloads 128

Authors: Kartikey Gupta

Abstract:

Global warming and environmental degradation are at their peak today, with the years after 2000A.D. giving way to 15 hottest years in terms of average temperatures. In India, much of the standard temperature measuring equipment are located in ‘developed’ urban areas, hence showing us an incomplete picture in terms of the climate across many rural areas, which comprises most of the landmass. This study showcases data studied by the author since 3 years at Vatsalya’s Children’s village, in outskirts of Jaipur, Rajasthan, India; in the midst of semi-arid topography, where consistently huge temperature differences of up to 15.8 degrees Celsius from local Jaipur weather only 30 kilometers away, are stunning yet scary at the same time, encouraging analysis of where the natural climatic pattern is heading due to rapid unrestricted urbanization. Record-breaking data presented in this project enforces the need to discuss causes and recovery techniques. This research further explores how and to what extent we are causing phenomenal disturbances in the natural meteorological pattern by urban growth. Detailed data observations using a standardized ambient weather station at study site and comparing it with closest airport weather data, evaluating the patterns and differences, show striking differences in temperatures, wind patterns and even rainfall quantity, especially during high-pressure zone days. Winter-time lows dip to 8 degrees below freezing with heavy frost and ice, while only 30 kms away minimum figures barely touch single-digit temperatures. Human activity is having an unprecedented effect on climatic patterns in record-breaking trends, which is a warning of what may follow in the next 15-25 years for the next generation living in cities, and a serious exploration into possible solutions is a must.

Keywords: climate change, meteorology, urban heat island, urbanization

Procedia PDF Downloads 81

Authors: Lillian Musila, Valerie Oundo, Daniel Erwin, Willie Sang

Abstract:

Staphylococcus aureus infections are a major cause of nosocomial infections in Kenya. Methicillin resistant S. aureus (MRSA) infections are a significant burden to public health and are associated with considerable morbidity and mortality. At a hospital in Western Kenya two clusters of MRSA cases emerged within short periods of time. In this study we explored whether these clusters represented a nosocomial outbreak by characterizing the isolates using phenotypic and molecular assays and examining epidemiological data to identify possible transmission patterns. Specimens from the site of infection of the subjects were collected, cultured and S. aureus isolates identified phenotypically and confirmed by APIStaph™. MRSA were identified by cefoxitin disk screening per CLSI guidelines. MRSA were further characterized based on their antibiotic susceptibility patterns and spa gene typing. Characteristics of cases with MRSA isolates were compared with those with MSSA isolated around the same time period. Two cases of MRSA infection were identified in the two week period between 21 April and 4 May 2015. A further 2 MRSA isolates were identified on the same day on 7 September 2015. The antibiotic resistance patterns of the two MRSA isolates in the 1st cluster of cases were different suggesting that these were distinct isolates. One isolate had spa type t2029 and the other had a novel spa type. The 2 isolates were obtained from urine and an open skin wound. In the 2nd cluster of MRSA isolates, the antibiotic susceptibility patterns were similar but isolates had different spa types: one was t037 and the other a novel spa type different from the novel MRSA spa type in the first cluster. Both cases in the second cluster were admitted into the hospital but one infection was community- and the other hospital-acquired. Only one of the four MRSA cases was classified as an HAI from an infection acquired post-operatively. When compared to other S. aureus strains isolated within the same time period from the same hospital only one spa type t2029 was found in both MRSA and non-MRSA strains. None of the cases infected with MRSA in the two clusters shared any common epidemiological characteristic such as age, sex or known risk factors for MRSA such as prolonged hospitalization or institutionalization. These data suggest that the observed MRSA clusters were multi strain clusters and not an outbreak of a single strain. There was no clear relationship between the isolates by spa type suggesting that no transmission was occurring within the hospital between these cluster cases but rather that the majority of the MRSA strains were circulating in the community. There was high diversity of spa types among the MRSA strains with none of the isolates sharing spa types. Identification of disease clusters in space and time is critical for immediate infection control action and patient management. Spa gene typing is a rapid way of confirming or ruling out MRSA outbreaks so that costly interventions are applied only when necessary.

Keywords: cluster, Kenya, MRSA, spa typing

Procedia PDF Downloads 324

Authors: Sherrene Bogle, Verlia Bogle, Tyrone Anderson

Abstract:

In recent years, organizations have become increasingly interested in the possibility of analyzing social media as a means of gaining meaningful feedback about their products and services. The aspect based sentiment analysis approach is used to predict the sentiment for Twitter datasets for Digicel and Lime, the main mobile companies in Jamaica, using supervised learning classification techniques. The results indicate an average of 82.2 percent accuracy in classifying tweets when comparing three separate classification algorithms against the purported baseline of 70 percent and an average root mean squared error of 0.31. These results indicate that the analysis of sentiment on social media in order to gain customer feedback can be a viable solution for mobile companies looking to improve business performance.

Keywords: machine learning, sentiment analysis, social media, supervised learning

Procedia PDF Downloads 434

Authors: Prashant Verma

Abstract:

Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

Procedia PDF Downloads 137

Authors: Tauhidur Rahman, Kasturi Bhuyan

Abstract:

In the present paper, Ground Response Analysis at the Rukni irrigation project has been thoroughly investigated. Surface level seismic hazard is mainly used by the practical Engineers for designing the important structures. Surface level seismic hazard can be obtained accounting the soil factor. Structures on soft soil will show more ground shaking than the structure located on a hard soil. The Surface level ground motion depends on the type of soil. Density and shear wave velocity is different for different types of soil. The intensity of the soil amplification depends on the density and shear wave velocity of the soil. Rukni irrigation project is located in the North Eastern region of India, near the Dauki fault (550 Km length) which has already produced earthquakes of magnitude (Mw= 8.5) in the past. There is a probability of a similar type of earthquake occuring in the future. There are several faults also located around the project site. There are 765 recorded strong ground motion time histories available for the region. These data are used to determine the soil amplification factor by incorporation of the engineering properties of soil. With this in view, three of soil bore holes have been studied at the project site up to a depth of 30 m. It has been observed that in Soil bore hole 1, the shear wave velocity vary from 99.44 m/s to 239.28 m/s. For Soil Bore Hole No 2 and 3, shear wave velocity vary from 93.24 m/s to 241.39 m/s and 93.24m/s to 243.01 m/s. In the present work, surface level seismic hazard at the project site has been calculated based on the Probabilistic seismic hazard approach accounting the soil factor.

Keywords: Ground Response Analysis, shear wave velocity, soil amplification, surface level seismic hazard

Procedia PDF Downloads 547

Authors: Robin Ferguson

Abstract:

The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

Procedia PDF Downloads 75

Authors: Ulriikka Savela-Huovinen, Hanni Muukkonen, Auli Toom

Abstract:

The development of workplace as a learning environment has been emphasized in research field of workplace learning. The prior literature on sensory performance emphasized the individual’s competences as assessor, while the competences in the collaborative interactional and knowledge creation practices as workplace learning method are not often mentioned. In the present study aims to find out what kinds of competences and contexts are central when assessor conducts food sensory evaluation in authentic professional context. The aim was to answer the following questions: first, what kinds of competences does sensory evaluation require according to assessors? And second, what kinds of contexts for sensory evaluation do assessors report? Altogether thirteen assessors from three Finnish food companies were interviewed by using semi-structural thematic interviews to map practices and development intentions as well as to explicate already established practices. The qualitative data were analyzed by following the principles of abductive and inductive content analysis. Analysis phases were combined and their results were considered together as a cross-analysis. When evaluated independently required competences were perception, knowledge of specific domains and methods and cognitive skills e.g. memory. Altogether, 42% of analysis units described individual evaluation contexts, 53% of analysis units described collaborative interactional contexts, and 5% of analysis units described collaborative knowledge creation contexts. Related to collaboration, analysis reviewed learning, sharing and reviewing both external and in-house consumer feedback, developing methods to moderate small-panel evaluation and developing product vocabulary collectively between the assessors. Knowledge creation contexts individualized from daily practices especially in cases product defects were sought and discussed. The study findings contribute to the explanation that sensory assessors learn extensively from one another in the collaborative interactional and knowledge creation context. Assessors learning and abilities to work collaboratively in the interactional and knowledge creation contexts need to be ensured in the development of the expertise.

Keywords: assessor, collaboration, competences, contexts, learning and practices, sensory evaluation

Procedia PDF Downloads 234

Authors: Nidhal Azawi

Abstract:

Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

Procedia PDF Downloads 110

Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

Abstract:

Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

Procedia PDF Downloads 162

Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

Abstract:

The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

Procedia PDF Downloads 79

Authors: Mehwish Asghar

Abstract:

Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

Procedia PDF Downloads 219

Authors: Abigaba Sophia

Abstract:

Artificial intelligence (AI) has transformed the education sector by revolutionizing educational frameworks by providing new opportunities and innovative advanced platforms for language translation during the teaching and learning process. In today's education sector, the primary key to scholarly communication is language; therefore, translation between different languages becomes vital in the process of communication. KIU-T being an International University, admits students from different nations speaking different languages, and English is the official language; some students find it hard to grasp a word during teaching and learning. This paper explores the practical aspect of using artificial intelligence technologies in an advanced language translation manner during teaching and learning. The impact of this technology is reflected in the education strategies to equip students with the necessary knowledge and skills for professional activity in the best way they understand. The researcher evaluated the demand for this practice since students have to apply the knowledge they acquire in their native language to their countries in the best way they understand. The main objective is to improve student's language competence and lay a solid foundation for their future professional development. A descriptive-analytic approach was deemed best for the study to investigate the phenomena of language translation intelligence alongside Microsoft Office during the teaching and learning process. The study analysed the responses of 345 students from different academic programs. Based on the findings, the researcher recommends using the artificial intelligence language translation technique during teaching, and this requires the wisdom of human content designers and educational experts. Lecturers and students will be trained in the basic knowledge of this technique to improve the effectiveness of teaching and learning to meet the student’s needs.

Keywords: artificial intelligence, language translation technique, teaching and learning process, Microsoft Office

Procedia PDF Downloads 73

Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

Abstract:

As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

Procedia PDF Downloads 636

Authors: Saurabh Kumar

Abstract:

In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.

Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth

Procedia PDF Downloads 14

Authors: Yi-Hung Ho, Chih-Wei Wang, Chih-Hsien Chen, Chih-Han Chang

Abstract:

Unilateral laminotomy and bilateral laminotomies were successful decompressions methods for managing spinal stenosis that numerous studies have reported. Thus, unilateral laminotomy was rated technically much more demanding than bilateral laminotomies, whereas the bilateral laminotomies were associated with a positive benefit to reduce more complications. There were including incidental durotomy, increased radicular deficit, and epidural hematoma. However, no relative biomechanical analysis for evaluating spinal instability treated with unilateral and bilateral laminotomies. Therefore, the purpose of this study was to compare the outcomes of different decompressions methods by experimental and finite element analysis. Three porcine lumbar spines were biomechanically evaluated for their range of motion, and the results were compared following unilateral or bilateral laminotomies. The experimental protocol included flexion and extension in the following procedures: intact, unilateral, and bilateral laminotomies (L2–L5). The specimens in this study were tested in flexion (8 Nm) and extension (6 Nm) of pure moment. Spinal segment kinematic data was captured by using the motion tracking system. A 3D finite element lumbar spine model (L1-S1) containing vertebral body, discs, and ligaments were constructed. This model was used to simulate the situation of treating unilateral and bilateral laminotomies at L3-L4 and L4-L5. The bottom surface of S1 vertebral body was fully geometrically constrained in this study. A 10 Nm pure moment also applied on the top surface of L1 vertebral body to drive lumbar doing different motion, such as flexion and extension. The experimental results showed that in the flexion, the ROMs (±standard deviation) of L3–L4 were 1.35±0.23, 1.34±0.67, and 1.66±0.07 degrees of the intact, unilateral, and bilateral laminotomies, respectively. The ROMs of L4–L5 were 4.35±0.29, 4.06±0.87, and 4.2±0.32 degrees, respectively. No statistical significance was observed in these three groups (P>0.05). In the extension, the ROMs of L3–L4 were 0.89±0.16, 1.69±0.08, and 1.73±0.13 degrees, respectively. In the L4-L5, the ROMs were 1.4±0.12, 2.44±0.26, and 2.5±0.29 degrees, respectively. Significant differences were observed among all trials, except between the unilateral and bilateral laminotomy groups. At the simulation results portion, the similar results were discovered with the experiment. No significant differences were found at L4-L5 both flexion and extension in each group. Only 0.02 and 0.04 degrees variation were observed during flexion and extension between the unilateral and bilateral laminotomy groups. In conclusions, the present results by finite element analysis and experimental reveal that no significant differences were observed during flexion and extension between unilateral and bilateral laminotomies in short-term follow-up. From a biomechanical point of view, bilateral laminotomies seem to exhibit a similar stability as unilateral laminotomy. In clinical practice, the bilateral laminotomies are likely to reduce technical difficulties and prevent perioperative complications; this study proved this benefit through biomechanical analysis. The results may provide some recommendations for surgeons to make the final decision.

Keywords: unilateral laminotomy, bilateral laminotomies, spinal stenosis, finite element analysis

Procedia PDF Downloads 396

Authors: Terence Soule, Tami Al Ghamdi

Abstract:

To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

Procedia PDF Downloads 135

Authors: Husain A. Murad, Ali A. Dashti, Ali Al-Kandari

Abstract:

The outbreak of Coronavirus during the Spring semester of 2020 brought new challenges for the teaching of vocational mass communication courses at universities in Kuwait. Using the Media Richness Theory (MRT), this study examines the response of 252 university students on mass communication programs. A questionnaire regarding their perceptions and preferences concerning modes of instruction on vocational courses online, focusing on the four factors of MRT: immediacy of feedback, capacity to include personal focus, conveyance of multiple cues, and variety of language. The outcomes show that immediacy of feedback predicted all criterion variables: suitability of distance learning (DL) for teaching vocational courses, sentiments of students toward DL, perceptions of easiness of evaluation of DL coursework, and the possibility of retaking DL courses. Capacity to include personal focus was another positive predictor of the criterion variables. It predicted students’ sentiments toward DL and the possibility of retaking DL courses. The outcomes are discussed in relation to implications for using DL, as well as constructing an agenda for DL research.

Keywords: distance learning, media richness theory, traditional learning, vocational media courses

Procedia PDF Downloads 69

Authors: Sudheer Dhume, T. Prasad

Abstract:

There are distinct signs of Business Education losing its sheen. It is more so in developing countries. One of the reasons is the value addition at the end of 2 year MBA program is not matching with the requirements of present times and expectations of the students. In this backdrop, Pedagogy Innovation has become prerequisite for making our MBA programs relevant and useful. This paper is the description and analysis of innovative Action Learning pedagogical approach adopted by a group of faculty members at NITIE Mumbai. It not only promotes multidisciplinary research but also enhances integration of the functional areas skillsets in the students. The paper discusses the theoretical bases of this pedagogy and evaluates the effectiveness of it vis-à-vis conventional pedagogical tools. The evaluation research using Bloom’s taxonomy framework showed that this blended method of Business Education is much superior as compared to conventional pedagogy.

Keywords: action learning, blooms taxonomy, business education, innovation, pedagogy

Procedia PDF Downloads 265

Authors: Katherine Karayianis

Abstract:

Children with Attention Deficit Hyperactivity Disorder (ADHD) have trouble learning in traditional classrooms. These children miss out on important developmental opportunities in school, which leads to challenges starting in early childhood, and these problems persist throughout their adult lives. Despite receiving supplemental support in school, children with ADHD still perform below their non-ADHD peers. Thus, there is a great need to find better ways of facilitating learning in children with ADHD. Evidence has shown that children with ADHD learn best through interactive engagement, but this is not always possible in schools, given classroom restraints and the large student-to-teacher ratio. Redesigning classrooms may not be feasible, so informal learning opportunities provide a possible alternative. One popular informal learning opportunity is educational TV shows like Sesame Street. These types of educational shows can teach children foundational skills taught in pre-K and early elementary school. One downside to these shows is the lack of interactive dialogue between the TV characters and the child viewers. Pseudo-interaction is often deployed, but the benefits are limited if the characters can neither understand nor contingently respond to the child. AI technology has become extremely advanced and is now popular in many electronic devices that both children and adults have access to. AI has been successfully used to create interactive dialogue in children’s educational TV shows, and results show that this enhances children’s learning and engagement, especially when children perceive the character as a reliable teacher. It is likely that children with ADHD, whose minds may otherwise wander, may especially benefit from this type of interactive technology, possibly to a greater extent depending on their perception of the animated dialogic agent. To investigate this issue, I have begun examining the moderating role of inattention among children’s learning from an educational TV show with different types of dialogic interactions. Preliminary results have shown that when character interactions are neither immediate nor accurate, children who are more easily distracted will have greater difficulty learning from the show, but contingent interactions with a TV character seem to buffer these negative effects of distractibility by keeping the child engaged. To extend this line of work, the moderating role of the child’s perception of the dialogic agent as a reliable teacher will be examined in the association between children’s attention and the type of dialogic interaction in the TV show. As such, the current study will investigate this moderated moderation.

Keywords: attention, dialogic TV, informal learning, educational TV, perception of teacher

Procedia PDF Downloads 74