Search results for: teaching and learning English
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9113

Search results for: teaching and learning English

2663 Adoption of Digital Storytelling Tool to Teach 21st Century Skills by Malaysian Pre-service Teachers

Authors: Siti Aisyah binti Jumpaan

Abstract:

21ˢᵗ century skills (PAK-21) integration has made its way into Malaysian curriculum when Ministry of Education introduce its implementation since 2016. This study was conducted to explore pre-service teachers’ readiness in integrating 21st century skills in the classroom via the digital storytelling (DST) method and to find gaps between theory and practice that can be integral towards pre-service teachers’ professional growth. Qualitative research method was used in this research involving six respondents who were selected using a purposive sampling method. Their response from interviews and lesson plan analysis were analysed using narrative analysis. The findings showed that pre-service teachers showed a moderate level of readiness in integrating 21st century skills using DST. Pre-service teachers demonstrated high level of preparedness in writing their lesson plan, but their interview revealed that they faced struggles in implementation due to several factors, such as lack of technology and failure to obtain students’ participation. This study further strengthens the need for specialised curriculum for pre-service teachers in teaching 21st century skills via DST.

Keywords: digital storytelling, 21ˢᵗ century skills, preservice teachers, teacher training

Procedia PDF Downloads 76
2662 Using the Smith-Waterman Algorithm to Extract Features in the Classification of Obesity Status

Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

Procedia PDF Downloads 283
2661 The Role of Social Isolation and Its Relevance Towards the Intersex Condition for Policy Management of Inclusive Education

Authors: Hamza Iftikhar

Abstract:

The intersex person’s social isolation condition is the leading concern in inclusive educational practices. It provides for the relevance of intersex communities with the influence of social isolation on their education and well-being. Given the underlying concern, this paper stresses the isolation-free condition of the intersex community by facilitating inclusive education. The Atkinson and Shiffrin Model and Behaviorism-Based Intersex Theory supports inclusive education by extending the desire for the significant management of stereotypes, quality teaching, parental beliefs, expressions, physique, and intersex attribution. The reducing role of social isolation for inclusive education is analyzed using the qualitative research method. The semi-structured interview research instrument is used for the data collection from the Ministry of Human Rights, Educational Institutions, and inter-sex Representatives. The results show that managing directors and heads of educational institutions frame policy management for the free social isolation of intersex persons, which is relevant through inclusive education. The implication of this paper is to provide a better social condition for intersex persons towards inclusive education through effective policy management.

Keywords: social isolation, inter-sex, relevance, inclusive education, policy management

Procedia PDF Downloads 80
2660 Data and Model-based Metamodels for Prediction of Performance of Extended Hollo-Bolt Connections

Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

Abstract:

Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

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2659 Recognizing Human Actions by Multi-Layer Growing Grid Architecture

Authors: Z. Gharaee

Abstract:

Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

Procedia PDF Downloads 148
2658 Contemporary Matter on Communication and Information Education: Technological Lack

Authors: Sedat Cereci

Abstract:

This study investigates character of communication, evaluates communication and information need of people, handles relation between communication and contemporary technology, and emphasizes technological lack on communication education in many societies. To get information and communication are of main needs of people and people developed different instruments and technics to learn and to communicate in the past. Because of social need, communication became social matter and governments contributed facilities of communication and set communication places for people to meet and to communicate. Industrial Revolution and technological developments also contributed communication technics and proved numerous technological facilities for communication. Education in the world also use developed technology in any department and communication education especially necessities high technological facilities in schools. Many high schools and universities have communication departments and most of them use contemporary technological facilities, but they are not sufficient. Communication departments in educational organizations in Turkey have computer classrooms, monitors, cameras, microphones, telephones, different softwares, and others. However, despite all this, technological facilities and teaching methods are not sufficient because of contemporary developments. Technology develops rapidly due to hopes of people and technological facilities in education cannot catch developments and people always hope more.

Keywords: information, communication education, technology, technological lack, contemporary conditions, technics

Procedia PDF Downloads 302
2657 Crack Growth Life Prediction of a Fighter Aircraft Wing Splice Joint Under Spectrum Loading Using Random Forest Regression and Artificial Neural Networks with Hyperparameter Optimization

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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2656 Shaking the Iceberg: Metaphoric Shifting and Loss in the German Translations of 'The Sun Also Rises'

Authors: Christopher Dick

Abstract:

While the translation of 'literal language' poses numerous challenges for the translator, the translation of 'figurative language' creates even more complicated issues. It has been only in the last several decades that scholars have attempted to propose theories of figurative language translation, including metaphor translation. Even less work has applied these theories to metaphoric translation in literary texts. And almost no work has linked an analysis of metaphors in translation with the recent scholarship on conceptual metaphors. A study of literature in translation must not only examine the inevitable shifts that occur as specific metaphors move from source language to target language but also analyze the ways in which these shifts impact conceptual metaphors and, ultimately, the text as a whole. Doing so contributes to on-going efforts to bridge the sometimes wide gulf between considerations of content and form in literary studies. This paper attempts to add to the body of scholarly literature on metaphor translation and the function of metaphor in a literary text. Specifically, the study examines the metaphoric expressions in Hemingway’s The Sun Also Rises. First, the issue of Hemingway and metaphor is addressed. Next, the study examines the specific metaphors in the original novel in English and the German translations, first in Annemarie Horschitz’s 1928 German version and then in the recent Werner Schmitz 2013 translation. Hemingway’s metaphors, far from being random occurrences of figurative language, are linguistic manifestations of deeper conceptual metaphors that are central to an interpretation of the text. By examining the modifications that are made to these original metaphoric expressions as they are translated into German, one can begin to appreciate the shifts involved with metaphor translation. The translation of Hemingway’s metaphors into German represents significant metaphoric loss and shifting that subsequently shakes the important conceptual metaphors in the novel.

Keywords: Hemingway, Conceptual Metaphor, Translation, Stylistics

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2655 Effects of Allowance for Corporate Equity on the Financing Choices of Belgian Small and Medium-Sized Enterprises in a Crisis Context

Authors: O. Colot, M. Croquet, L. Cultrera, Y. Fandja Collince

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The objective of our research is to evaluate the impact of the allowance for corporate equity (ACE) on the financial structure of Belgian SME in order to highlight the potential existence of a fiscal leverage. To limit the biases linked to the rationing of the capital further to the financial crisis, we compare first the dynamic evolution of the financial structure of the Belgian firms over the period 2006-2015 by focusing on three sub-periods: 2006-2008, 2009-2012 and 2013-2015. We give then an international size to this comparison by including SMEs from countries adjoining Belgium (France, Germany, Netherlands and the United Kingdom) and within which there is no ACE. This comparison allows better understanding the fiscal advantage linked to the ACE of firms evolving in a relatively unstable economic environment further to the financial crisis of 2008. This research is relevant given the economic and political context in which Belgium operates and the very uncertain future of the Belgian ACE. The originality of this research is twofold: the long study period and the consideration of the effects of the financial and economic crisis on the financing structure of Belgian SMEs. The results of this research, even though they confirm the existence of a positive fiscal leverage for the tax deduction for venture capital on the financing structure of Belgian SMEs, do not allow the extent of this leverage to be clearly quantified. The comparative evolution of financing structures over the period 2006-2015 of Belgian, French, German, Dutch and English SMEs shows a strong similarity in the overall evolution of their financing.

Keywords: allowance for corporate equity, Belgium, financial structure, small and medium sized firms

Procedia PDF Downloads 190
2654 Optimization of Bills Assignment to Different Skill-Levels of Data Entry Operators in a Business Process Outsourcing Industry

Authors: M. S. Maglasang, S. O. Palacio, L. P. Ogdoc

Abstract:

Business Process Outsourcing has been one of the fastest growing and emerging industry in the Philippines today. Unlike most of the contact service centers, more popularly known as "call centers", The BPO Industry’s primary outsourced service is performing audits of the global clients' logistics. As a service industry, manpower is considered as the most important yet the most expensive resource in the company. Because of this, there is a need to maximize the human resources so people are effectively and efficiently utilized. The main purpose of the study is to optimize the current manpower resources through effective distribution and assignment of different types of bills to the different skill-level of data entry operators. The assignment model parameters include the average observed time matrix gathered from through time study, which incorporates the learning curve concept. Subsequently, a simulation model was made to duplicate the arrival rate of demand which includes the different batches and types of bill per day. Next, a mathematical linear programming model was formulated. Its objective is to minimize direct labor cost per bill by allocating the different types of bills to the different skill-levels of operators. Finally, a hypothesis test was done to validate the model, comparing the actual and simulated results. The analysis of results revealed that the there’s low utilization of effective capacity because of its failure to determine the product-mix, skill-mix, and simulated demand as model parameters. Moreover, failure to consider the effects of learning curve leads to overestimation of labor needs. From 107 current number of operators, the proposed model gives a result of 79 operators. This results to an increase of utilization of effective capacity to 14.94%. It is recommended that the excess 28 operators would be reallocated to the other areas of the department. Finally, a manpower capacity planning model is also recommended in support to management’s decisions on what to do when the current capacity would reach its limit with the expected increasing demand.

Keywords: optimization modelling, linear programming, simulation, time and motion study, capacity planning

Procedia PDF Downloads 499
2653 The Effects of Evidence-Based Nursing Training and Consultation Program on Self-Efficacy and Outcome Expectancy of Evidence-Based Practice among Nurses

Authors: Yea-Pyng Lin

Abstract:

Evidence-based nursing (EBN) can improve quality of patient care and reduce medical expenses. Development of training and consultation program according to nurses’ needs and difficulties is essential to promote their competence and self-efficacy in EBN. However, limited research evaluated the effects of EBN program on EBN self-efficacy among nurses. This study aimed to evaluate the effects of an EBN consultation program on self-efficacy and outcome expectancy of evidence-based practice (EBP) among nurses. A two-group pretest-posttest quasi-experimental design was used. A purposive sample of full-time nurses was recruited from a hospital. Experimental group (n=28) received the EBN consultation program including 18-hour EBN training courses, hand-on practices and group discussion by faculty mentors. Control group (n=33) received regular in-service education with no EBN program. All participants received baseline and post-test assessment using Chinese version of Self-Efficacy in EBP scale (SE-EBP) and Outcome Expectancy for EBP scale (OE-EBP). After receiving EBN consultation program, experimental group’s posttest scores of SE-EBP (t=-4.98, p<0.001) and OE-SEP (t=-3.65, p=0.001) were significantly higher than those of the pretests. By controlling the age and years of nursing work experience, the experimental group‘s SE-EBP(F=10.47, p=0.002) and OE-SEP(F=9.53, p=0.003) scores were significantly improved compared to those of the control group. EBN program focus on hand-on practice and group discussion by faculty mentors in addition to EBN training courses can improve EBP self-efficacy and outcome expectancy among nurses. EBN program focus on English literature reading, database searching, and appraisal practice according to nurses’ needs and difficulties can promote implementation of EBN.

Keywords: evidence-based nursing, evidence-based practice, consultation program, self-efficacy, outcome expectancy

Procedia PDF Downloads 492
2652 The Study of Formal and Semantic Errors of Lexis by Persian EFL Learners

Authors: Mohammad J. Rezai, Fereshteh Davarpanah

Abstract:

Producing a text in a language which is not one’s mother tongue can be a demanding task for language learners. Examining lexical errors committed by EFL learners is a challenging area of investigation which can shed light on the process of second language acquisition. Despite the considerable number of investigations into grammatical errors, few studies have tackled formal and semantic errors of lexis committed by EFL learners. The current study aimed at examining Persian learners’ formal and semantic errors of lexis in English. To this end, 60 students at three different proficiency levels were asked to write on 10 different topics in 10 separate sessions. Finally, 600 essays written by Persian EFL learners were collected, acting as the corpus of the study. An error taxonomy comprising formal and semantic errors was selected to analyze the corpus. The formal category covered misselection and misformation errors, while the semantic errors were classified into lexical, collocational and lexicogrammatical categories. Each category was further classified into subcategories depending on the identified errors. The results showed that there were 2583 errors in the corpus of 9600 words, among which, 2030 formal errors and 553 semantic errors were identified. The most frequent errors in the corpus included formal error commitment (78.6%), which were more prevalent at the advanced level (42.4%). The semantic errors (21.4%) were more frequent at the low intermediate level (40.5%). Among formal errors of lexis, the highest number of errors was devoted to misformation errors (98%), while misselection errors constituted 2% of the errors. Additionally, no significant differences were observed among the three semantic error subcategories, namely collocational, lexical choice and lexicogrammatical. The results of the study can shed light on the challenges faced by EFL learners in the second language acquisition process.

Keywords: collocational errors, lexical errors, Persian EFL learners, semantic errors

Procedia PDF Downloads 127
2651 Distributed Framework for Pothole Detection and Monitoring Using Federated Learning

Authors: Ezil Sam Leni, Shalen S.

Abstract:

Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.

Keywords: federated Learning, pothole detection, distributed framework, federated averaging

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2650 Balance Rigor, Relevance and Socio-Emotional Learning in Math

Authors: Abimbola Akintounde

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Supporting the social and emotional needs of young adolescents has become an emergent concern for schools around the world. Yet educators remain in a dilemma regarding the optimum approach for integrating social and emotional learning (SEL) into their content area instruction. The purpose of this study was to explore the perception of secondary students regarding their schoolwide SEL interventions. Twenty-four International Baccalaureate students in a final year mathematics course at an American Public Secondary School near Washington D. C. were randomly selected for participation in this study via an online electronic survey. The participants in this study used Likert-scale items to rate the effectiveness of the socio-emotional and character development programs being implemented at their schools. Respondents also ranked their preferred mode of delivery of social and emotional support programs. About 71% of the teenagers surveyed preferred SEL support rendered via interactive team-building activities and games, 42% of the high school students in the study ranked focus group discussions as their preferred format for SEL interventions, while only 13% of the respondents in the study regarded lectures and presentations as their preferred mode of SEL delivery. About one-fourth of the study participants agreed that explicit instruction was critical to enhancing students’ wellness, 79% agreed that SEL programs should foster less teacher talk, while 88% of the students indicated that student engagement was critical to their mental health. Eighty percent of the teenagers surveyed decried that the focus of their school-wide social and emotional programs was poorly prioritized. About two-thirds of the students agreed that social justice and equity issues should be embedded in their schools’ advisory programs. More than half of the respondents agitated for strategies for managing stress and their school workload. About 54% of the respondents also clamored for SEL programs that reinforce emotion regulation and coping strategies for anxiety. Based on the findings of this study, recommendations were proffered for best practices in the design and implementation of effective learner-friendly social and emotional development interventions.

Keywords: SEL, math anxiety, student support, emotion regulation, social awareness, self awareness, self management, relationship building

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2649 BERT-Based Chinese Coreference Resolution

Authors: Li Xiaoge, Wang Chaodong

Abstract:

We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

Procedia PDF Downloads 194
2648 Translation and Validation of the Pediatric Quality of Life Inventory for Children in Pakistani Context

Authors: Nazia Mustafa, Aneela Maqsood

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Pediatric Quality of Life Inventory is the most widely used instrument for assessing children and adolescent health-related quality of life and has shown excellent markers of reliability and validity. The current study was carried out with the objectives of translation and cross-language validation along with the determination of factor Structure and psychometric properties of the Urdu version. It was administered on 154 Primary School Children with age range 10 to12 years (M= 10.86, S.D = 0.62); including boys (n=92) and girls (n = 62). The sample was recruited from two randomly selected schools from the Rawalpindi district of Pakistan. Results of the pilot phase revealed that the instrument had good reliability (Urdu Version α = 0.798; English Version α = 0.795) as well as test-retest correlation coefficients over a period of 15 days (r = 0.85). Exploratory factor analysis (EFA) resulted in three factorial structures; Social/School Functioning (k = 8), Psychological Functioning (k = 7) and Physical Functioning (k = 6) considered suitable for our sample instead of four factors. Bartlett's test of sphericity showed inter-correlation between variables. However, factor loadings for items 22 and 23 of the School Functioning subscale were problematic. The model was fit to the data after their removal with Cronbach’s Alpha Reliability coefficient of the scale (k = 21) as 0.87 and for subscales as 0.75, 0.77 and 0.73 for Social/School Scale, Psychological subscale and Physical subscale, respectively. These results supported the feasibility and reliability of the Urdu version of the Pediatric Quality of Life Inventory as a reliable and effective tool for the measurement of quality of life among Pediatrics Pakistani population.

Keywords: primary school children, paediatric quality of life, exploratory factor analysis, Pakistan

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2647 Comparison between XGBoost, LightGBM and CatBoost Using a Home Credit Dataset

Authors: Essam Al Daoud

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Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

Procedia PDF Downloads 152
2646 Comparison of Cognitive Load in Virtual Reality and Conventional Simulation-Based Training: A Randomized Controlled Trial

Authors: Michael Wagner, Philipp Steinbauer, Andrea Katharina Lietz, Alexander Hoffelner, Johannes Fessler

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Background: Cardiopulmonary resuscitations are stressful situations in which vital decisions must be made within seconds. Lack of routine due to the infrequency of pediatric emergencies can lead to serious medical and communication errors. Virtual reality can fundamentally change the way simulation training is conducted in the future. It appears to be a useful learning tool for technical and non-technical skills. It is important to investigate the use of VR in providing a strong sense of presence within simulations. Methods: In this randomized study, we will enroll doctors and medical students from the Medical University of Vienna, who will receive learning material regarding the resuscitation of a one-year-old child. The study will be conducted in three phases. In the first phase, 20 physicians and 20 medical students from the Medical University of Vienna will be included. They will perform simulation-based training with a standardized scenario of a critically ill child with a hypovolemic shock. The main goal of this phase is to establish a baseline for the following two phases to generate comparative values regarding cognitive load and stress. In phase 2 and 3, the same participants will perform the same scenario in a VR setting. In both settings, on three set points of progression, one of three predefined events is triggered. For each event, three different stress levels (easy, medium, difficult) will be defined. Stress and cognitive load will be analyzed using the NASA Task Load Index, eye-tracking parameters, and heart rate. Subsequently, these values will be compared between VR training and traditional simulation-based training. Hypothesis: We hypothesize that the VR training and the traditional training groups will not differ in physiological response (cognitive load, heart rate, and heart rate variability). We further assume that virtual reality training can be used as cost-efficient additional training. Objectives: The aim of this study is to measure cognitive load and stress level during a real-life simulation training and compare it with VR training in order to show that VR training evokes the same physiological response and cognitive load as real-life simulation training.

Keywords: virtual reality, cognitive load, simulation, adaptive virtual reality training

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2645 The First Japanese-Japanese Dictionary for Non-Japanese Using the Defining Vocabulary

Authors: Minoru Moriguchi

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This research introduces the concept of a monolingual Japanese dictionary for non-native speakers of Japanese, whose temporal title is Dictionary of Contemporary Japanese for Advanced Learners (DCJAL). As the language market is very small compared with English, a monolingual Japanese dictionary for non-native speakers, containing sufficient entries, has not been published yet. In such a dictionary environment, Japanese-language learners are using bilingual dictionaries or monolingual Japanese dictionaries for Japanese people. This research started in 2017, as a project team which consists of four Japanese and two non-native speakers, all of whom are linguists of the Japanese language. The team has been trying to propose the concept of a monolingual dictionary for non-native speakers of Japanese and to provide the entry list, the definition samples, the list of defining vocabulary, and the writing manual. As the result of seven-year research, DCJAL has come to have 28,060 head words, 539 entry examples, 4,598-word defining vocabulary, and the writing manual. First, the number of the entry was determined as about 30,000, based on an experimental method using existing six dictionaries. To make the entry list satisfying this number, words suitable for DCJAL were extracted from the Tsukuba corpus of the Japanese language, and later the entry list was adjusted according to the experience as Japanese instructor. Among the head words of the entry list, 539 words were selected and added with lexicographical information such as proficiency level, pronunciation, writing system (hiragana, katakana, kanji, or alphabet), definition, example sentences, idiomatic expression, synonyms, antonyms, grammatical information, sociolinguistic information, and etymology. While writing the definition of the above 539 words, the list of the defining vocabulary was constructed, based on frequent vocabulary used in a Japanese monolingual dictionary. Although the concept of DCJAL has been almost perfected, it may need some more adjustment, and the research is continued.

Keywords: monolingual dictionary, the Japanese language, non-native speaker of Japanese, defining vocabulary

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2644 Evaluating Effects of Health and Physical Maintenance on Academic Competencies of University Teachers in Pakistan

Authors: Muhammad Badar Habib, Muhammad Shakir, Asif Ali, Muhammad Zia ul Haq

Abstract:

Purpose of the research is to examine the university teachers’ health and physical activities regarding their academic competencies. Major objectives of this piece research were (a) to identify health problems of teachers at university level that affects academic competencies of university teachers and (b) to evaluate educational betterment through physical balance. This research is descriptive in nature and questionnaire was used as source of collecting data. Population of the present research comprises teachers, professors and professionals teaching in the universities of Pakistan. 580 university teachers were selected as a population of the study. Random sampling technique was used to identify recipients. Data was feed and filter in Ms-Excel. In the light of the analysis of the study following findings were drawn out. This study found that the university teachers in Pakistan do not adopt proper physical exercise program. They were less interested to burn their extra calories and face diseases such as cramping, contraction of the muscles, diabetics and stomach diseases. This study recommends that seminars/workshops may be held by University establishment; to develop overall awareness among the teachers.

Keywords: evaluating effects of health and physical maintenance, academic competencies, university teachers, Pakistan

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2643 Human Kinetics Education and the Computer Operations, Effects and Merits

Authors: Kehinde Adeyeye Adelabu

Abstract:

Computer applications has completely revolutionized the way of life of people which does not exclude the field of sport education. There are computer technologies which help to enhance teaching in every field of education. Invention of computers has done great to the field of education. This study was therefore carried out to examine the effects and merits of computer operations in Human Kinetics Education and Sports. The study was able to identify the component of computer, uses of computer in Human Kinetics education (sports), computer applications in some branches of human kinetics education. A qualitative research method was employed by the author in gathering experts’ views and used to analyze the effects and merits of computer applications in the field of human kinetics education. No experiment was performed in the cause of carrying out the study. The source of information for the study was text-books, journal, articles, past project reports, internet i.e. Google search engine. Computer has significantly helped to improve Education (Human Kinetic), it has complemented the basic physical fitness testing and gave a more scientific basis to the testing. The use of the software and packages has made cost projections, database applications, inventory control, management of events, word processing, electronic mailing and record keeping easier than the pasts.

Keywords: application, computer operation, education, human kinetics

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2642 Educating Children Who Are Deaf and Hearing Impaired in Southern Africa: Challenges and Triumphs

Authors: Emma Louise McKinney

Abstract:

There is a global move to integrate children who are Deaf and Hearing Impaired into regular classrooms with their hearing peers with an inclusive education framework. This paper examines the current education situation for children who are Deaf and Hearing Impaired in South Africa, Madagascar, Malawi, Zimbabwe, and Namibia. Qualitative data for this paper was obtained from the author’s experiences working as the Southern African Education Advisor for an international organization funding disability projects. It examines some of the challenges facing these children and their teachers relating to education. Challenges include cultural stigma relating to disability and deafness, a lack of hearing screening and early identification of deafness, schools in rural areas, special schools, specialist teacher training, equipment, understanding of how to implement policy, support, appropriate teaching methodologies, and sign language training and proficiency. On the other hand, in spite of the challenges some teachers are able to provide quality education to children who are Deaf and Hearing Impaired. This paper examines both the challenges as well as what teachers are doing to overcome these.

Keywords: education of children who are deaf and hearing impaired, Southern African experiences, challenges, triumphs

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2641 Comparison of Existing Predictor and Development of Computational Method for S- Palmitoylation Site Identification in Arabidopsis Thaliana

Authors: Ayesha Sanjana Kawser Parsha

Abstract:

S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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2640 The Importance of Student Feedback in Development of Virtual Engineering Laboratories

Authors: A. A. Altalbe, N. W Bergmann

Abstract:

There has been significant recent interest in on-line learning, as well as considerable work on developing technologies for virtual laboratories for engineering students. After reviewing the state-of-the-art of virtual laboratories, this paper steps back from the technology issues to look in more detail at the pedagogical issues surrounding virtual laboratories, and examines the role of gathering student feedback in the development of such laboratories. The main contribution of the paper is a set of student surveys before and after a prototype deployment of a simulation laboratory tool, and the resulting analysis which leads to some tentative guidelines for the design of virtual engineering laboratories.

Keywords: engineering education, elearning, electrical engineering, virtual laboratories

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2639 Snapchat’s Scanning Feature

Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

Abstract:

The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

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2638 Smart Sensor Data to Predict Machine Performance with IoT-Based Machine Learning and Artificial Intelligence

Authors: C. J. Rossouw, T. I. van Niekerk

Abstract:

The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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2637 Presenting Internals of Networks Using Bare Machine Technology

Authors: Joel Weymouth, Ramesh K. Karne, Alexander L. Wijesinha

Abstract:

Bare Machine Internet is part of the Bare Machine Computing (BMC) paradigm. It is used in programming application ns to run directly on a device. It is software that runs directly against the hardware using CPU, Memory, and I/O. The software application runs without an Operating System and resident mass storage. An important part of the BMC paradigm is the Bare Machine Internet. It utilizes an Application Development model software that interfaces directly with the hardware on a network server and file server. Because it is “bare,” it is a powerful teaching and research tool that can readily display the internals of the network protocols, software, and hardware of the applications running on the Bare Server. It was also demonstrated that the bare server was accessible by laptop and by smartphone/android. The purpose was to show the further practicality of Bare Internet in Computer Engineering and Computer Science Education and Research. It was also to show that an undergraduate student could take advantage of a bare server with any device and any browser at any release version connected to the internet. This paper presents the Bare Web Server as an educational tool. We will discuss possible applications of this paradigm.

Keywords: bare machine computing, online research, network technology, visualizing network internals

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2636 Why Do We Need Hierachical Linear Models?

Authors: Mustafa Aydın, Ali Murat Sunbul

Abstract:

Hierarchical or nested data structures usually are seen in many research areas. Especially, in the field of education, if we examine most of the studies, we can see the nested structures. Students in classes, classes in schools, schools in cities and cities in regions are similar nested structures. In a hierarchical structure, students being in the same class, sharing the same physical conditions and similar experiences and learning from the same teachers, they demonstrate similar behaviors between them rather than the students in other classes.

Keywords: hierarchical linear modeling, nested data, hierarchical structure, data structure

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2635 Revisiting Domestication and Foreignisation Methods: Translating the Quran by the Hybrid Approach

Authors: Aladdin Al-Tarawneh

Abstract:

The Quran, as it is the sacred book of Islam and considered the literal word of God (Allah) in Arabic, is highly translated into many languages; however, the foreignising or the literal approach excessively stains the quality and discredits the final product in the eyes of its receptors. Such an approach fails to capture the intended meaning of the Quran and to communicate it in any language. Therefore, this study is conducted to propose a different approach that seeks involving other ones according to a hybrid model. Indeed, this study challenges the binary adherence that is highly used in Translation Studies (TS) in general and in the translation of the Quran in particular. Drawing on the genuine fact that the Quran can be communicated in any language in terms of meaning, and the translation is not sacred; this paper approaches the translation of the Quran by blending different methods like domestication or foreignisation in a systematic way, avoiding the binary choice made by many translators. To reach this aim, the paper has a conceptual part that seeks to elucidate and clarify the main methods employed in TS, and criticise and modify them to propose the new hybrid approach (the hybrid model) for translating the Quran – that is, the deductive method. To support and validate the outcome of the previous part, a comparative model is employed in order to highlight the differences between the suggested translation and other widely used ones – that is, the inductive method. By applying this methodology, the paper proves that there is a deficiency of communicating the original meaning of the Quran in light of the foreignising approach. In conclusion, the paper suggests producing a Quran translation has to take into account the adoption of many techniques to express the meaning of the Quran as understood in the original, and to offer this understanding in English in the most native-like manner to serve the intended target readers.

Keywords: Quran translation, hybrid approach, domestication, foreignization, hybrid model

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2634 Cultural Heritage Education in Preschools: Preschool Teachers' Perspectives

Authors: Yasemin Yücesan, Gabriela Portugal, Maria Figueiredo

Abstract:

This paper presents a part of an ongoing study on preschool teachers' perspectives and pedagogical practices regarding cultural heritage education. Accordingly, this study is based on a quantitative survey. The study area is Türkiye, and the research participants are preschool teachers actively teaching in preschool education institutions. It is necessary to encourage children to understand the past and cultural heritage values at an early age. Moreover, raising awareness of cultural heritage in preschool children is crucial for recognising and preserving this heritage. Therefore, it is very important to provide people with cultural heritage knowledge at an early age, as the preschool period is a key factor in raising awareness of this issue. In the preschool education programme implemented in Türkiye, it is stated that cultural heritage education is important in early childhood and should be included in the programme. However, although it is stated that cultural heritage education should be included in the preschool education programme, it is not clearly stated which subjects will be included in the programme and what kind of practices will be carried out. Therefore, this study examines the perspectives and pedagogical practices of preschool teachers working in preschool education institutions toward cultural heritage education.

Keywords: cultural heritage, early childhood education, pedagogical practices, preschool teacher

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