Search results for: onsite and online learning

Authors: Ibrahima Diallo

Abstract:

The literature on teacher education foregrounds reflection as an important aspect of professional practice. Reflection for a teacher consists in critically analysing and evaluating retrospectively a lesson to see what worked, what did not work, and how to improve it for the future. Now, many teacher education programmes worldwide consider the ability to reflect as one of the hallmarks of an effective educator. However, in some context like Senegal, reflection has not been given due consideration in teacher education programmes. In contexts where it has been in the education landscape for some time now, reflection is mostly depicted as an individual written activity and many teacher trainees have become disenchanted by the repeated enactments of this task that is solely intended to satisfy course requirements. This has resulted in whitewashing weaknesses or even ‘faking’ reflection. Besides, the “one-size-fits-all” approach of reflection could not flourish because how reflection impacts on practice is still unproven. Therefore, reflective practice needs to be contextualised and made more thought-provoking through dialogue and by using classroom data. There is also a need to highlight change brought in teachers’ practice through reflection. So, this study introduces reflection in a new context and aims to show evidenced change in novice EFL teachers’ practice through dialogic data-led reflection. The purpose of this study is also to contribute to the scarce literature on reflection in sub-Saharan Africa by bringing new perspectives on contextualised teacher-led reflection. Eight novice EFL teachers participated in this qualitative longitudinal study, and data have been gathered online through post-lesson reflection recordings and lesson videos for a period of four months. Then, the data have been thematically analysed using NVivo to systematically organize and manage the large amount of data. The analysis followed the six steps approach to thematic analysis. Major themes related to teachers’ classroom practice and their conception of reflection emerged from the analysis of the data. The results showed that post-lesson reflection with a peer can help novice EFL teachers gained more awareness on their classroom practice. Dialogic reflection also helped them evaluate their lessons and seek for improvement. The analysis of the data also gave insight on teachers’ conception of reflection in an EFL context. It was found that teachers were more engaged in reflection when using their lesson video recordings. Change in teaching behaviour as a result of reflection was evidenced by the analysis of the lesson video recordings. This study has shown that video-stimulated reflection is practical form of professional development that can be embedded in teachers’ professional life.

Keywords: novice EFL teachers, practice, professional development, video-stimulated reflection

Procedia PDF Downloads 87

Authors: Chuen-arom Janthimachai-amorn, Chirawadee Harnrittha

Abstract:

This study aims to identify the factors facilitating the knowledge management to develop the graduate study programs to achieve success and to identify the approaches in developing the graduate study programs in the Rajbhat Suansunantha University. The 10 respondents were the administrators, the faculty, and the personnel of its Graduate School. The research methodology was based on Pla-too Model of the Knowledge Management Institute (KMI) by allocating the knowledge indicators, the knowledge creation and search, knowledge systematization, knowledge processing and filtering, knowledge access, knowledge sharing and exchanges and learning. The results revealed that major success factors were knowledge indicators, evident knowledge management planning, knowledge exchange and strong solidarity of the team and systematic and tenacious access of knowledge. The approaches allowing the researchers to critically develop the graduate study programs were the environmental data analyses, the local needs and general situations, data analyses of the previous programs, cost analyses of the resources, and the identification of the structure and the purposes to develop the new programs.

Keywords: program development, knowledge management, graduate study programs, Rajbhat Suansunantha University

Procedia PDF Downloads 297

Authors: Ardak Myrzabekova

Abstract:

Sentinel epidemiological surveillance (SES) of severe acute respiratory infections (SARI) was introduced in the Republic of Kazakhstan in 2008. The purpose of this study was to analyze SES of flu among SARI patients in the Republic of Kazakhstan during last two flu seasons. Comparative analysis was conducted of SARI morbidity during 40 – 23 weeks of 2014/2015 (season 2014) and 2015/2016 (season 2015) in online base (http:\\ses.dec.kz). In the database during season 2014 were 1,398 SARI patients and 1,985 patients during season 2015. Individual data (clinical, epidemiological and laboratory) of SARI cases were collected based on the questionnaire and were put into the flu electronic system. The studied population was residents of the Republic of Kazakhstan who addressed for medical help in 24 sentinel in-patient clinics in 9 sentinel regions of the country. Swabs from nose and throat were taken for laboratory testing from SARI patients who met the standard case definition. The samples were examined in virology labs of sentinel regions using PCR and 'AmpliSens' test systems made in Russia. The first positive results for flu during season 2014 were obtained on 48 week, during season 2015 – on 46 week. The increase of the number of hospitalized SARI patients was observed during 42 week of 2015 – 01 week of 2016, and during 03 - 06 weeks of 2016, with fluctuating SARI incidence rate from 171 to 444 per 1,000 hospitalized. The highest SARI incidence rate during season 2014 were observed during 01 - 03 weeks of 2015: from 389 to 466 per 1,000 hospitalized. Patients admitted to the ICU during season 2015 were 3.0% (60) SARI patients, compared to 2.7% (38) in 2014 (p=0.3), obtaining oxygen therapy 1.0% (21) compared to 0.3% (5), accordingly, (р=0.009); with shortness of breath 74.8% (1,486) compared to 72.6% (1,015), (р=0.07); with impairment of consciousness 1.0% (21) compared to 0.6% (9), (р=0.11); with muscle pain 19.3% (384) compared to 13.6% (191), (р < 0.001); with joint pain 13.3% (265) compared to 9.3% (131), (p < 0.001). During season 2015 the prevailing subtype of flu А was А/Н1N1-09, it was observed mainly in the age group 30-64: 32.5% (169/520). During season 2014 flu А/Н3N2 was observed mainly in the age group 15-29: 43.6% (106/243). Among children under 14 flu А/Н1N1-09 during season 2015 was 37.3% (194/520), during season 2014 flu А/Н3N2 – 34.9% (85/243). Earlier beginning of the flu season was noted in 2015-2016 and a longer period of hospitalization of SARI patients, with high SARI morbidity rates, unlike season 2014-2015. Season 2015-2016 was characterized by prevailing circulation of virus of flu А/Н1N1-09, mainly in the age group 30-64, and also among children under 14. During season 2014-2015 the virus circulating in the country was А/Н3N2, which was observed mainly in the age group 15-29 and among children under 14.

Keywords: flu, electronic system, sentinel epidemiological surveillance, severe acute respiratory infections

Procedia PDF Downloads 212

Authors: Alaa Alrakaf, Sk. Md. Mizanur Rahman

Abstract:

Since the last two decades’ Arabic natural language processing (ANLP) has become increasingly much more important. One of the key issues related to ANLP is ambiguity. In Arabic language different pronunciation of one word may have a different meaning. Furthermore, ambiguity also has an impact on the effectiveness and efficiency of Machine Translation (MT). The issue of ambiguity has limited the usefulness and accuracy of the translation from Arabic to English. The lack of Arabic resources makes ambiguity problem more complicated. Additionally, the orthographic level of representation cannot specify the exact meaning of the word. This paper looked at the diacritics of Arabic language and used them to disambiguate a word. The proposed approach of word sense disambiguation used Diacritizer application to Diacritize Arabic text then found the most accurate sense of an ambiguous word using Naïve Bayes Classifier. Our Experimental study proves that using Arabic Diacritics with Naïve Bayes Classifier enhances the accuracy of choosing the appropriate sense by 23% and also decreases the ambiguity in machine translation.

Keywords: Arabic natural language processing, machine learning, machine translation, Naive bayes classifier, word sense disambiguation

Procedia PDF Downloads 345

Authors: Shyam Mehraaj, Samanthi E. R. Siriwardana, Shehara A. K. G. H., Wanigasinghe N. T., Wandana R. A. K., Wedage C. V.

Abstract:

A presentation is a critical tool for conveying not just spoken information but also a wide spectrum of human emotions. The single most effective thing to make the presentation successful is to practice it beforehand. Preparing for a presentation has been shown to be essential for improving emotional control, intonation and prosody, pronunciation, and vocabulary, as well as the quality of the presentation slides. As a result, practicing has become one of the most critical parts of giving a good presentation. In this research, the main focus is to analyze the audio, video, and slides of the presentation uploaded by the presenters. This proposed solution is based on the Natural Language Processing and Computer Vision techniques to cater to the requirement for the presenter to do a presentation beforehand using a mobile responsive web application. The proposed system will assist in practicing the presentation beforehand by identifying the presenters’ emotions, body language, tonality, prosody, pronunciations and vocabulary, and presentation slides quality. Overall, the system will give a rating and feedback to the presenter about the performance so that the presenters’ can improve their presentation skills.

Keywords: presentation, self-evaluation, natural learning processing, computer vision

Procedia PDF Downloads 109

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 260

Authors: Maria Wendy Mendoza-Solomo

Abstract:

The study assessed the level of understanding of catholic doctrines in relation to the way of life of Ignatian graduates of Ateneo de Naga University (ADNU). It was conducted to find out if ADNU is successful in leading their students to a deeper moral understanding of the world centered on Jesus Christ through their curriculum, academic programs, activities and practices. This study further evaluated if their graduates live out their Catholic commitment to Christ in their current way of life. It also determined the factors that affected their level of understanding of Catholic doctrines and their current way of life. The descriptive, qualitative, evaluative and correlational analyses determined the level of understanding of the Catholic doctrines and the current way of life of 390 graduates. It also correlated the level of understanding to moral life and worship. The factors that affected the graduates’ level of understanding and their current way of life were measured. A researcher-made instrument was distributed to the respondents either using the traditional way or the online survey to reach out graduates across the globe. Major findings were (1) The weighted mean of graduates’ level of understanding of Catholic doctrines was 4.63. (2) Along moral life, 4.07 while along worship, 3.83. (3) The Catholic doctrines and moral life had Pearson r value of 0.79. The doctrines and worship, 0.87; and worship and moral life, 0.89. (4) The understanding of the doctrines was affected highly by the teacher factor with 4.09 mean. The moral life and worship were affected highly by the teacher and technological factors both ranked 1.5 (4.04). (5) Along Catholic doctrines, the teacher factor had 0.90 r value; and environmental, -0.40. Along moral life, teacher had r value of -0.30; technological (-0.92), socio-economic (-0.93), political (-0.83), and environmental (-0.90). Along worship, the teacher had 0.36 Pearson r value, technological and socio-economic (-0.78), political (-0.73) and environmental (-0.72). Major conclusions were: (1) Graduates had very high level of understanding of the Catholic doctrines as summarized in the Creed which is grounded in the Sacred Scriptures. (2) They live out this Catholic commitment to Christ by obeying the Commandments very extensively but needed more participation in religious and parish activities. They have overwhelming spirituality and religiosity in terms of receiving of sacraments and sacramental practices except reading the Bible and reflecting on its passages. (3) The graduates’ level of understanding of the Catholic doctrines had very strong correlation with their current way of life. (4) Teacher, socio-economic, technological, environmental, and political factors significantly affected their understanding of the Catholic doctrines and their current way of life. (5) The teacher factor had very strong relationship with the doctrines; technological and political, weak; environmental, moderate; and socio-economic, very weak relationship. The teacher factor had weak relationship but the other factors had very strong relationship with moral life and strong relationship with worship.

Keywords: Catholic doctrines, Ignatian graduates, relationship, way of life

Procedia PDF Downloads 337

Authors: Navid Mirzaei Varzeghani, Mahmoud Saffarzadeh, Ali Naderan, Amirhossein Taheri

Abstract:

Countries are progressing, and the world's busiest airports see year-on-year increases in travel demand. Passenger acceptability of an airport depends on the airport's appeals, which may include one of these routes between the city and the airport, as well as the facilities to reach them. One of the critical roles of transportation planners is to predict future transportation demand so that an integrated, multi-purpose system can be provided and diverse modes of transportation (rail, air, and land) can be delivered to a destination like an airport. In this study, 356 questionnaires were filled out in person over six days. First, the attraction of business and non-business trips was studied using data and a linear regression model. Lower travel costs, a range of ages more significant than 55, and other factors are essential for business trips. Non-business travelers, on the other hand, have prioritized using personal vehicles to get to the airport and ensuring convenient access to the airport. Business travelers are also less price-sensitive than non-business travelers regarding airport travel. Furthermore, carrying additional luggage (for example, more than one suitcase per person) undoubtedly decreases the attractiveness of public transit. Afterward, based on the manner and purpose of the trip, the locations with the highest trip generation to the airport were identified. The most famous district in Tehran was District 2, with 23 visits, while the most popular mode of transportation was an online taxi, with 12 trips from that location. Then, significant variables in separation and behavior of travel methods to access the airport were investigated for all systems. In this scenario, the most crucial factor is the time it takes to get to the airport, followed by the method's user-friendliness as a component of passenger preference. It has also been demonstrated that enhancing public transportation trip times reduces private transportation's market share, including taxicabs. Based on the responses of personal and semi-public vehicles, the desire of passengers to approach the airport via public transportation systems was explored to enhance present techniques and develop new strategies for providing the most efficient modes of transportation. Using the binary model, it was clear that business travelers and people who had already driven to the airport were the least likely to change.

Keywords: multimodal transportation, demand modeling, travel behavior, statistical models

Procedia PDF Downloads 156

Authors: Xian Xie, Qinghua Fang

Abstract:

This study used quantitative and qualitative methods to explore the characteristics of flipped classroom’s influence on classroom environment of college English reading, writing, and translating, and to summarize and reflect on the teaching characteristics of college English Reading, writing, and translating. The results of the study indicated that after the flipped classroom applied to reading, writing, and translating, students’ performance was improved to a certain extent, the classroom environment was improved to some extent, students of the flipped classroom are generally satisfied with the classroom environment; students showed a certain degree of individual differences to the degree of cooperation, participation, self-responsibility, task-orientation, and the teacher leadership and innovation. The study indicated that the implementation of flipped classroom teaching mode can optimize College English reading, writing, and translating classroom environment and realize target－learner as the center in foreign language teaching and learning, but bring a greater challenge to teachers.

Keywords: classroom environment, college English reading, writing and translating, individual differences, flipped classroom

Procedia PDF Downloads 252

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 58

Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

Abstract:

The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

Procedia PDF Downloads 158

Authors: Dinesh Khanduja, Pardeep Kumar Sharma

Abstract:

Education as the most important resource in any country has multiplying effects on all facets of development in a society. The new social realities, particularly, the interplay between democratization of education; unprecedented developments in the IT sector; emergence of knowledge society, liberalization of economy, and globalization have greatly influenced the educational process of all nations. This turbulence entails upon education to undergo dramatic changes to keep up with the new expectations. Growth of entrepreneurship among Indian women is highly important for empowering them and this is highly essential for the socio-economic development of a society. Unfortunately, in India, there is poor acceptance of entrepreneurship among women as unfounded myths and fears restrain them to be enterprising. To remove these inhibitions, the education system needs to be re-engineered to make entrepreneurship more acceptable. This paper empirically analyses the results of a survey done on around 500 female graduates in North India to measure and evaluate various entrepreneurial traits present in them. A formative model has been devised in this context, which should improve the teaching-learning process in our education system, which can lead to a sustainable growth of women entrepreneurship in India.

Keywords: women empowerment, entrepreneurship, education system, women entrepreneurship, sustainable development

Procedia PDF Downloads 334

Authors: Mikkel Snorre Wilms Boysen

Abstract:

From a theoretical perspective, expertise is generally considered a precondition for creativity. The assumption is that an individual needs to master the common and accepted rules and techniques within a certain knowledge-domain in order to create something new and valuable. However, real life cases, and a limited amount of empirical studies, demonstrate that this assumption may be overly simple. In this article, this question is explored through a number of semi-experimental case studies conducted within the fields of music, technology, and youth culture. The studies indicate that, in various ways, expertise plays an important part in creative processes. However, the case studies also indicate that expertise sometimes leads to an entrenched perspective, in the sense that knowledge and experience may work as a path into the well-known rather than into the unknown. In this article, these issues are explored with reference to different theoretical approaches to creativity and learning, including actor-network theory, the theory of blind variation and selective retention, and Csikszentmihalyi’s system model. Finally, some educational aspects and implications of this are discussed.

Keywords: creativity, expertise , education, technology

Procedia PDF Downloads 310

Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

Abstract:

Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

Procedia PDF Downloads 75

Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

Abstract:

As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

Procedia PDF Downloads 153

Authors: Aisulu Tileukulova, Zhexebay Dauren

Abstract:

Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

Procedia PDF Downloads 333

Authors: L. Meers, L. Contalbrigo, V. Stevens, O. Ulitina, S. Laufer, W. E. Samuels, S. Normando

Abstract:

Since the COVID-19 pandemic started, there has been concern that domestic animals may help spread SARS-Cov-2. This concern also greatly affected human-animal interaction projects such as animal-assisted interventions (AAI). As a result, institutions and AAI practitioners developed new safety protocols and procedures to control the spread of the SARS-Cov-2 virus during AAI sessions and to guarantee safety for their clients and animals. However, little is known yet about the impact on animals' needs and the possible welfare issues due to these lifestyle adaptions. Fifteen therapists in Flanders, Belgium, who were currently conducting canine-assisted interventions, conducted unstructured observations on how their dogs' (11 mixed breeds, 3 Labradors, 1 terrier aged 2 – 12 years) behaviors changed due to institutional COVID-19 safety protocols. Most (80%) of the respondents reported that their dogs showed sniffing or sneezing after smelling disinfected areas. Two (13%) dogs responded with vomiting and gagging, and three (20%) dogs urinated over disinfected areas. All protocols advise social distancing between participants and animals. When held back, eight (53%) dogs showed self-calming behaviors. Respondents reported that most (73%) dogs responded with flight reactions when seeing humans wearing facial masks. When practitioners threw their used masks in open dustbins, five (33%) dogs tried to take them out with their mouths and play with them; two (13%) Labradors tried to eat them. Taking the dogs' temperatures was the most frequently (53%) used method to supervise their health. However, all dogs showed behaviors as ducking the tail, trying to escape, or biting the animal handler during this procedure. We interpret these results to suggest that dogs tended to react with stress and confusion to the changes in AAI practices they're part of. The health and safety protocols that institutions used were largely borne from recommendations made to protect humans. The participating practitioners appeared to use their knowledge of dog behavior and safety to modify them as best they could—but with more significant concern directed towards the other humans. Given their inter-relatedness and mutual importance for welfare, we advocate for integrated human and animal health and welfare assessments and protocols to provide a framework for "One health" approaches in animal-assisted interventions.

Keywords: animal-assisted therapy, COVID-19 protocol, one health, welfare

Procedia PDF Downloads 189

Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

Abstract:

In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

Procedia PDF Downloads 344

Authors: Memory Ranga, Phillip Pretorious

Abstract:

The South African Government has invested a lot of money in Information Technology Governance (ITG) within the Government departments. The ITG framework was spearheaded by the Department of Public Service and Administration (DPSA). This led to the development of a governing ITG DPSA framework and later the Government Wide Enterprise Architecture (GWEA) Framework for assisting the departments to implement ITG. In addition to this, the government departments have adopted the Information Systems Audit and Control Association (ISACA) Control Objectives for Information and Related Technology (COBIT) for ITG processes. Despite all these available frameworks, departments fail to fully capitalise and improve the ITG processes mainly as these are too generic and difficult to apply for specific governance needs. There has been less research done to evaluate the progress on ITG initiatives within the government departments. This paper aims to evaluate the existing ITG frameworks within selected government departments in South Africa. A quantitative research approach was used in this study. Data was collected through an online questionnaire targeting ICT Managers and Directors from government departments. The study is undertaken within a case study and only the Eastern Cape Province was selected for the research. Document review mainly on ITG framework and best practices was also used. Data was analysed using the Google Analytic tools and SPSS. A one–sample Chi-Squared Test was used to verity the evaluation findings. Findings show that there is evidence that the current guiding National governance framework (DPSA) is out dated and does not accommodate the new changes in other governance frameworks. The Eastern Cape Government Departments have spent huge amount of money on ITG but not yet able to identify the benefits of the ITG initiatives. The guiding framework is rigid and does to address some of the departmental needs making it difficult to be flexible and apply the DPSA framework. Furthermore, despite the large budget on ITG, the departments still find themselves with many challenges and unable to improve some of the processes and services. All the engaged Eastern Cape departments have adopted the COBIT framework, but none has been conducting COBIT maturity Assessment which is a functionality of COBIT. There is evidence of too many the ITG frameworks and underutilisation of these frameworks. The study provides a comprehensive evaluation of the ITG frameworks that have been adopted by the South African Government Departments in the Eastern Cape Province. The evaluation guides and recommends the government departments to rethink and adopt ITG frameworks that could be customised to accommodate their needs. The adoption and application of ITG by government departments should assist in better governance and service delivery to the citizens.

Keywords: information technology governance, COBIT, evaluate, framework, governance, DPSA framework

Procedia PDF Downloads 107

Authors: M. Rodionov, N. Sharapova, Z. Dedovets

Abstract:

The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.

Keywords: education, methodological approaches, teacher, secondary school

Procedia PDF Downloads 158

Authors: Greeshma Sharma, Sushil Chandra, Vijander Singh, Alok Prakash Mittal

Abstract:

Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory.

Keywords: memory, planning navigational ability, virtual reality

Procedia PDF Downloads 317

Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

Abstract:

This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

Procedia PDF Downloads 182

Authors: Xinyu Zhang, Olga Torres-Hostench

Abstract:

This article presents a comparative study evaluating and comparing the quality of machine translation (MT) output of Chinese gastronomy nomenclature. Chinese gastronomic culture is experiencing an increased international acknowledgment nowadays. The nomenclature of Chinese gastronomy not only reflects a specific aspect of culture, but it is related to other areas of society such as philosophy, traditional medicine, etc. Chinese dish names are composed of several types of cultural references, such as ingredients, colors, flavors, culinary techniques, cooking utensils, toponyms, anthroponyms, metaphors, historical tales, among others. These cultural references act as one of the biggest difficulties in translation, in which the use of translation techniques is usually required. Regarding the lack of Chinese food-related translation studies, especially in Chinese-Spanish translation, and the current massive use of MT, the quality of the MT output of Chinese dish names is questioned. Fifty Chinese dish names with different types of cultural components were selected in order to complete this study. First, all of these dish names were translated by three different MT tools (Google Translate, Baidu Translate and Bing Translator). Second, a questionnaire was designed and completed by 12 Chinese online users (Chinese graduates of a Hispanic Philology major) in order to find out user preferences regarding the collected MT output. Finally, human translation techniques were observed and analyzed to identify what translation techniques would be observed more often in the preferred MT proposals. The result reveals that the MT output of the Chinese gastronomy nomenclature is not of high quality. It would be recommended not to trust the MT in occasions like restaurant menus, TV culinary shows, etc. However, the MT output could be used as an aid for tourists to have a general idea of a dish (the main ingredients, for example). Literal translation turned out to be the most observed technique, followed by borrowing, generalization and adaptation, while amplification, particularization and transposition were infrequently observed. Possibly because that the MT engines at present are limited to relate equivalent terms and offer literal translations without taking into account the whole context meaning of the dish name, which is essential to the application of those less observed techniques. This could give insight into the post-editing of the Chinese dish name translation. By observing and analyzing translation techniques in the proposals of the machine translators, the post-editors could better decide which techniques to apply in each case so as to correct mistakes and improve the quality of the translation.

Keywords: Chinese dish names, cultural references, machine translation, translation techniques

Procedia PDF Downloads 123

Authors: Wongwarit Nipitwittaya

Abstract:

The objectives of this research is bringing folk song with the teaching of Western music were to examine to investigate, to compare, develop the skill, technique, knowledge of Thai folk song and to preserve folk song of Thailand to be known more widely also learn Thai culture from Thai folk song. Study by bringing Thailand folk song is widely known for learning with Western music in course brass performance. Bringing the melody of Thai folk music and changing patterns to western music notes for appropriate on brass performance. A sample was selected from brass students, using research by assessment of knowledge from test after used Thai folk song lesson. The lesson focus for scales and key signature in western music by divided into two groups, the one study by used research tools and another one used simple lesson and a collection of research until testing. The results of the study were as follows: 1. There are good development skill form research method 2. Sound recognition can be even better. The study was a qualitative research and data collection by observation.

Keywords: Thai folk song, brass instrument, key signature, western music

Procedia PDF Downloads 660

Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

Abstract:

Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

Procedia PDF Downloads 171

Authors: Camille Alexis-Garsee, Nicola Payne

Abstract:

One consequence of the pandemic has been the debilitating health impact that some people experience over a longer period of time, known as long-COVID. This has been predominately researched in adults; however, there is emerging evidence on the effects of long-COVID in children. Research has indicated over half of children who contracted COVID-19 experienced persistent symptoms four months after a confirmed diagnosis. There is little research on the impact of this on children and their families. This study aimed to explore the experiences of children with long-COVID, to enable further understanding of the impacts and needs within this group. Semi-structured interviews, facilitated by children’s drawings, were conducted with 15 children (aged 9-16, 9 females). Inductive thematic analysis was used to analyze the data. The findings tell a story of loss, change and of resilience. Many children were unable to engage in normal daily activities and were unable to attend school, however, all employed self-management techniques to cope with symptoms and were positive for the future. Four main themes were identified: (1) Education challenges: although some schools tried to accommodate the child’s new limitations with provision of flexi-attendance, online classes and a reduced timetable, children struggled to keep up with their schoolwork and needed more support; (2) Disrupted relationships: children felt socially isolated; they were forced to give up co and extra-curricular activities, were no longer in contact with friendship groups and missed out on key experiences with friends and family; (3) Diverse health-related challenges: children’s symptoms affected daily functioning but were also triggers for changes in thoughts and mood; (4) Coping and resilience: children actively engaged in symptom management and were able to ‘self-pace’ and/or employ distraction activities to cope. They were also focused on living a ‘normal’ life and looked to the future with great positivity. A key challenge of the long-term effects of COVID is recognizing and treating the illness in children and the subsequent impact on multiple aspects of their lives. Even though children described feeling disconnected in many ways, their life goals were still important. A multi-faceted approach is needed for management of this illness, with a focus on helping these children successfully reintegrate into society and achieve their dreams.

Keywords: children’s illness experience, COVID-19, long-COVID in children, long-COVID kids, qualitative research

Procedia PDF Downloads 51

Authors: Sanjay Adhikesaven

Abstract:

Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

Procedia PDF Downloads 93

Authors: Danny Mwangi, Collins Oduor Ondiek

Abstract:

Mass mobility is one of the most important characteristics of every industrialized civilization. Man must travel about in order to fulfill his commitment to putting food on his table. As a result, movement is an important part of human life. Man must travel from one place to another. This is a natural trait of humans, according to elementary science. Variables in human mobility have arisen as a result of technological advancements over time. Public transit is one of these modes of transportation. When it comes to reducing safety-related risks in the public transport system, awareness is crucial. So much so even when it comes to public transportation in Kenya. Having a system that can be able to keep users updated with real-time traffic updates on the route, they are on and also have the ability to rate drivers after a trip could go a long way in improving safety on Kenyan roads. What this proposed system is intended to accomplish is to reduce occurrences of reckless driving and give matatu drivers the feeling that they are accountable to someone and more so have the incentive to be better drivers who are motivated to follow the law and have passenger safety as a priority. The research was conducted, and the findings show that 95.2% of respondents were not satisfied with the current safety measures in the Kenyan public transport sector. This means that the chances for this system to be accepted in the market are high because it addresses a key issue. 98.8% of the respondents were of the opinion that the implementation of the proposed system would significantly increase safety measures in the public transport sector. During the research, it was clear that the main challenge 77.1% of the respondents face when using public transport is that there is no way to monitor driver safety performance, and 68.7% of the respondent believed the widespread use of unroadworthy public transit vehicles contributed to the lack of safety when using public transport. However, 77.1% of the respondents expect the benefit of creating a sense of accountability for the drivers, and 74.7% of the respondents expect the benefit of increased passenger safety. 63.9% believe that with the implementation of the system, there will be the benefit of monitoring driver performance. This shows that with the implementation of the proposed system, it will be possible to make a lot of progress in terms of making Kenyan roads safer when using public transit. According to the findings, it is recommended that this proposed public transportation safety awareness system be implemented as it will be able to address matatu passengers' safety concerns while also encouraging matatu drivers to drive more carefully. As a result, it's a project with a chance of becoming viable, marketable, and feasible.

Keywords: public safety, public transportation, accountable driving, safe transportation

Procedia PDF Downloads 84

Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman

Abstract:

Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.

Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model

Procedia PDF Downloads 63

Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

Abstract:

This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

Procedia PDF Downloads 135