Search results for: pre-service teachers’ attitude towards learning

Authors: Sylvester Akpah, Selasi Vondee

Abstract:

Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

Procedia PDF Downloads 131

Authors: Yulan Wu

Abstract:

With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

Procedia PDF Downloads 74

Authors: I. Schiller, D. Morsomme, A. Remacle

Abstract:

Children’s ability to process spoken language develops until the late teenage years. At school, where efficient spoken language processing is key to academic achievement, listening conditions are often unfavorable. High background noise and poor teacher’s voice represent typical sources of interference. It can be assumed that these factors particularly affect primary school children, because their language and literacy skills are still low. While it is generally accepted that background noise and impaired voice impede spoken language processing, there is an increasing need for analyzing impacts within specific linguistic areas. Against this background, the aim of the study was to investigate the effect of speech-shaped noise and imitated dysphonic voice on first-grade primary school children’s speech perception and sentence comprehension. Via headphones, 5 to 6-year-old children, recruited within the French-speaking community of Belgium, listened to and performed a minimal-pair discrimination task and a sentence-picture matching task. Stimuli were randomly presented according to four experimental conditions: (1) normal voice / no noise, (2) normal voice / noise, (3) impaired voice / no noise, and (4) impaired voice / noise. The primary outcome measure was task score. How did performance vary with respect to listening condition? Preliminary results will be presented with respect to speech perception and sentence comprehension and carefully interpreted in the light of past findings. This study helps to support our understanding of children’s language processing skills under adverse conditions. Results shall serve as a starting point for probing new measures to optimize children’s learning environment.

Keywords: impaired voice, sentence comprehension, speech perception, speech-shaped noise, spoken language processing

Procedia PDF Downloads 175

Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

Abstract:

Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: electrochemical, endocrine disruptors, microscopy, nanoparticles, sensors

Procedia PDF Downloads 266

Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

Abstract:

Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

Procedia PDF Downloads 24

Authors: Israa A. Qari

Abstract:

Learning to request in a foreign language is a key ability within pragmatics language teaching. This paper examines how requests are taught in English Unlimited Book 3 (Cambridge University Press), an EFL textbook series employed by King Abdulaziz University in Jeddah, Saudi Arabia to teach advanced foundation year students English. The focus of analysis is the evaluation of the request linguistic strategies present in the textbook, frequency of the use of these strategies, and the contextual information provided on the use of these linguistic forms. The researcher collected all the linguistic forms which consisted of the request speech act and divided them into levels employing the CCSARP request coding manual. Findings demonstrated that simple and commonly employed request strategies are introduced. Looking closely at the exercises throughout the chapters, it was noticeable that the book exclusively employed the most direct form of requesting (the imperative) when giving learners instructions: e.g. listen, write, ask, answer, read, look, complete, choose, talk, think, etc. The book also made use of some other request strategies such as ‘hedged performatives’ and ‘query preparatory’. However, it was also found that many strategies were not dealt with in the book, specifically strategies with combined functions (e.g. possibility, ability). On a sociopragmatic level, a strong focus was found to exist on standard situations in which relations between the requester and requestee are clear. In general, contextual information was communicated implicitly only. The textbook did not seem to differentiate between formal and informal request contexts (register) which might consequently impel students to overgeneralize. The paper closes with some recommendations for textbook and curriculum designers. Findings are also contrasted with previous results from similar body of research on EFL requests.

Keywords: EFL, requests, saudi, speech acts, textbook evaluation

Procedia PDF Downloads 127

Authors: Hui Liu, Xiaozan Wang, Jiarong Zhong, Ziming Shao

Abstract:

Introduction: Related research shows that students don’t concentrate on teacher’s speaking in the classroom. The d2 attention test is a time-limited test about selective attention. The d2 attention test can be used to evaluate individual selective attention. Purpose: To use the d2 attention test tool to measure the difference between the attention level of the experimental class and the control class before and after Brain-Break and to explore the effect of Brain-Break in the classroom on students' selective attention. Methods: According to the principle of no difference in pre-test data, two classes in the fourth- grade of Shenzhen Longhua Central Primary School were selected. After 20 minutes of class in the third class in the morning and the third class in the afternoon, about 3-minute Brain-Break intervention was performed in the experimental class for 10 weeks. The normal class in the control class did not intervene. Before and after the experiment, the d2 attention test tool was used to test the attention level of the two-class students. The paired sample t-test and independent sample t-test in SPSS 23.0 was used to test the change in the attention level of the two-class classes around 10 weeks. This article only presents results with significant differences. Results: The independent sample t-test results showed that after ten-week of Brain-Break, the missed errors (E1 t = -2.165 p = 0.042), concentration performance (CP t = 1.866 p = 0.05), and the degree of omissions (Epercent t = -2.375 p = 0.029) in experimental class showed significant differences compared with control class. The students’ error level decreased and the concentration increased. Conclusions: Adding Brain-Break interventions in the classroom can effectively improve the attention level of fourth-grade primary school students to a certain extent, especially can improve the concentration of attention and decrease the error rate in the tasks. The new sport's learning model is worth promoting

Keywords: cultural class, micromotor, attention, D2 test

Procedia PDF Downloads 119

Authors: Hirokatsu Kawashima

Abstract:

One important element of teaching/learning listening is intensive listening such as listening for precise sounds, words, grammatical, and semantic units. Several classroom-based investigations have been conducted to explore the usefulness of auditory recognition of phonological, grammatical and semantic errors in such a context. The current study reports the results of one such investigation, which targeted auditory recognition of phonological, grammatical, and semantic errors at the sentence level. 56 Japanese EFL learners participated in this investigation, in which their recognition performance of phonological, grammatical and semantic errors was measured on a 9-point scale by learners’ self-evaluation from the perspective of 1) two types of similar English sound (vowel and consonant minimal pair words), 2) two types of sentence word order (verb phrase-based and noun phrase-based word orders), and 3) two types of semantic consistency (verb-purpose and verb-place agreements), respectively, and their general listening proficiency was examined using standardized tests. A number of findings have been made about the interactive relationships between the three types of auditory error recognition and general listening proficiency. Analyses based on the OPLS (Orthogonal Projections to Latent Structure) regression model have disclosed, for example, that the three types of auditory error recognition are linked in a non-linear way: the highest explanatory power for general listening proficiency may be attained when quadratic interactions between auditory recognition of errors related to vowel minimal pair words and that of errors related to noun phrase-based word order are embraced (R2=.33, p=.01).

Keywords: auditory error recognition, intensive listening, interaction, investigation

Procedia PDF Downloads 500

Authors: Kazuki Kamada, Haruka Yamashita

Abstract:

In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

Procedia PDF Downloads 127

Authors: Andrew Kanzunguze, Lusayo Mwabumba, Jason K. Gilbertson, Dominic B. Gondwe, George Z. Nxumayo

Abstract:

Knowledge about the spatio-temporal distribution of invasive plants in protected areas provides a base from which hypotheses explaining proliferation of plant invasions can be made alongside development of relevant invasive plant monitoring programs. The aim of this study was to investigate the spatio-temporal distribution of bracken fern on the grassland plateau of Nyika National Park over the past 30 years (1986-2016) as well as to determine the current extent of the invasion. Remote sensing, machine learning, and statistical modelling techniques (object-based image analysis, image classification and linear regression analysis) in geographical information systems were used to determine both the spatial and temporal distribution of bracken fern in the study area. Results have revealed that bracken fern has been increasing coverage on the Nyika plateau at an estimated annual rate of 87.3 hectares since 1986. This translates to an estimated net increase of 2,573.1 hectares, which was recorded from 1,788.1 hectares (1986) to 4,361.9 hectares (2016). As of 2017 bracken fern covered 20,940.7 hectares, approximately 14.3% of the entire grassland plateau. Additionally, it was observed that the fern was distributed most densely around Chelinda camp (on the central plateau) as well as in forest verges and roadsides across the plateau. Based on these results it is recommended that Ecological Niche Modelling approaches be employed to (i) isolate the most important factors influencing bracken fern proliferation as well as (ii) identify and prioritize areas requiring immediate control interventions so as to minimize bracken fern proliferation in Nyika National Park.

Keywords: bracken fern, image classification, Landsat-8, Nyika National Park, spatio-temporal distribution

Procedia PDF Downloads 169

Authors: Rozi Laskaraki, Argyris Karapetsas, Aikaterini Karapetsa

Abstract:

This paper is focused on the efficacy of a rehabilitation program based on musical activities, implied to a group of school-aged dyslexic children. Objective: The purpose of this study was to investigate the efficacy of auditory training including musical exercises in children with developmental dyslexia (DD). Participants and Methods: 45 third-, and fourth-grade students with DD and a matched control group (n=45) were involved in this study. In the beginning, students participated in a clinical assessment, including both electrophysiological (i.e., event related potentials (ERPs) esp.P300 waveform) and neuropsychological tests, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Initial assessment’s results confirmed statistically significant lower performance for children with DD, compared to that of the typical readers. After clinical assessment, a subgroup of children with dyslexia was submitted to a music auditory training program, conducted in 45-minute training sessions, once a week, for twenty weeks. The program included structured and digitized musical activities involving pitch, rhythm, melody and tempo perception and discrimination as well as auditory sequencing. After the intervention period, children underwent a new recording of ERPs. Results: The electrophysiological results revealed that children had similar P300 latency values to that of the controls, after the remediation program; thus children overcame their deficits. Conclusion: The outcomes of the current study suggest that ERPs is a valid clinical tool in neuropsychological assessment settings and dyslexia can be ameliorated through music auditory training.

Keywords: dyslexia, event related potentials, learning disabilities, music, rehabilitation

Procedia PDF Downloads 139

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

Abstract:

In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: scalable architectures, sustainability, application design, disruptive technology, machine learning and natural language processing, AI, social media platform, cloud computing, advanced networking and storage devices, advanced monitoring and metering infrastructure, climate change

Procedia PDF Downloads 73

Authors: Nurwina Anuar, Aswad Anuar

Abstract:

Imagery is a popular mental technique used by athletes and coaches to improve learning and performance. It has been widely investigated and beneficial in the sports context. However, the imagery application in equestrian sport has been understudied. Thus, the effectiveness of imagery should encompass the application in the equestrian sport to ensure its application covert all sports. Unlike most sports (e.g., football, badminton, tennis, ski) which are both mental and physical are dependent solely upon human decision and response, equestrian sports involves the interaction of human-horse collaboration to success in the equestrian tasks. This study aims to investigate the effect of PETTLEP imagery on equestrian jumping tasks, motivation and imagery ability. It was hypothesized that the use of PETTLEP imagery intervention will significantly increase in the skill equestrian jumping tasks. It was also hypothesized that riders’ imagery ability and motivation will increase across phases. The participants were skilled riders with less to no imagery experience. A single-subject ABA design was employed. The study was occurred over five week’s period at Universiti Teknologi Malaysia Equestrian Park. Imagery ability was measured using the Sport Imagery Assessment Questionnaires (SIAQ), the motivational measured based on the Motivational imagery ability measure for Sport (MIAMS). The effectiveness of the PETTLEP imagery intervention on show jumping tasks were evaluated by the professional equine rider on the observational scale. Results demonstrated the improvement on all equestrian jumping tasks for the most participants from baseline to intervention. Result shows the improvement on imagery ability and participants’ motivations after the PETTLEP imagery intervention. Implication of the present study include underlining the impact of PETTLEP imagery on equestrian jumping tasks. The result extends the previous research on the effectiveness of PETTLEP imagery in the sports context that involves interaction and collaboration between human and horse.

Keywords: PETTLEP imagery, imagery ability, equestrian, equestrian jumping tasks

Procedia PDF Downloads 190

Authors: Kariman Abdelaziz Ahmed Ali Hamzawy

Abstract:

Amidst the growing global challenges facing communities, from climate change to educational gaps, sustainable community education has emerged as a vital tool for ensuring comprehensive and enduring development. This research aims to explore effective strategies for sustainable community education that can lead to long-term impacts on local communities. The study begins by defining the concept of sustainable education within a community context and reviews the current literature on the topic. It then presents case studies from various communities around the world where sustainable educational strategies have been successfully implemented. These case studies illustrate how sustainable education can enhance community engagement, build local capacities, and improve quality of life in sustainable ways. The findings from these studies are analyzed to identify the key factors contributing to the success of sustainable educational programs. These factors include partnerships between different sectors (governmental, private, and community), the innovative use of technology, and the adaptation of educational curricula to meet the unique needs of the community. The research also offers practical recommendations on designing and implementing sustainable educational programs, emphasizing the integration of formal and informal education, promoting lifelong learning, and developing local resources. It addresses potential challenges and ways to overcome them to ensure the long-term sustainability of these programs. In conclusion, the research provides a future vision of the role of sustainable education in building resilient and prosperous communities and highlights the importance of investing in education as a key driver of sustainable development. This study contributes to the ongoing discussion on achieving lasting impact through sustainable community education and offers a practical framework for stakeholders to adopt and implement these strategies.

Keywords: sustainable education, community education, Community engagement, local capacity building, educational technology

Procedia PDF Downloads 27

Authors: Dilini Bodhinayaka, Aunsha Sajeewanie Rubasinghe

Abstract:

The library of the University of Kelaniya plays a significant role in supporting the academic work of the university. As at July, 2016 the library of the University of Kelaniya comprised of 250301 printed books, 2157 CD-ROMs, 1203 theses and 800 non-book materials. Furthermore, the library is subscribed to about 60 local journals, access to over 12,500 full text academic journals and around 100,000 e-books. The library provides the services and resources that support in teaching, doing research and learning. On the other hand, undergraduate students have adopted and continued to use the online information retrieval for their academic and research work. This study aims to compare the usage of internet and the usage of library among undergraduates in the faculties of Humanities, Social Sciences, Science and Commerce & Management in the University of Kelaniya. Also, the research attempts to determine the factors of enthusiasm or the disinterest in the students in using library and Internet. All the undergraduate students in the University (8440 students at the time of the study) were taken as the population of the study and the sample of 15% was selected out of the population using stratified sampling method. A total of 1266 questionnaires were distributed among undergraduates of the above mentioned faculties. The qualitative data were analyzed using Descriptive Statistical Method. Findings, of the study indicated that undergraduate students of the faculties of Humanities, Social Sciences, Science and Commerce & Management use both the library and the internet to fulfill their information needs. But, the students in the faculty of Science and Commerce & Management use the internet sources more than the library. The undergraduates in the faculties of Humanities and Social Sciences frequently use the university library than the internet. Although, majority agreed that the internet is the most preferred source of information they have no an adequate awareness about the available internet resources in the E-library of the University of Kelaniya.

Keywords: university libraries, University of Kelaniya, online resources, undergraduates in Sri Lanka

Procedia PDF Downloads 231

Authors: David de Oliveira Costa, Miguel Ângelo Lellis Moreira, Carlos Francisco Simões Gomes, Daniel Augusto de Moura Pereira, Marcos dos Santos

Abstract:

Strategic management is a fundamental process for global companies that intend to remain competitive in an increasingly dynamic and complex market. To do so, it is necessary to maintain alignment with their principles and values. The Balanced Scorecard (BSC) proposes to ensure that the overall business performance is based on different perspectives (financial, customer, internal processes, and learning and growth). However, relying solely on the BSC may not be enough to ensure the success of strategic management. It is essential that companies also evaluate and prioritize strategic projects that need to be implemented to ensure they are aligned with the business vision and contribute to achieving established goals and objectives. In this context, the proposition involves the incorporation of the SAPEVO-M multicriteria method to indicate the degree of relevance between different perspectives. Thus, the strategic objectives linked to these perspectives have greater weight in the classification of structural projects. Additionally, it is proposed to apply the concept of the Impact & Probability Matrix (I&PM) to structure and ensure that strategic projects are evaluated according to their relevance and impact on the business. By structuring the business's strategic management in this way, alignment and prioritization of projects and actions related to strategic planning are ensured. This ensures that resources are directed towards the most relevant and impactful initiatives. Therefore, the objective of this article is to present the proposal for integrating the BSC methodology, the SAPEVO-M multicriteria method, and the prioritization matrix to establish a concrete weighting of strategic planning and obtain coherence in defining strategic projects aligned with the business vision. This ensures a robust decision-making support process.

Keywords: MCDA process, prioritization problematic, corporate strategy, multicriteria method

Procedia PDF Downloads 63

Authors: Pooja Jain

Abstract:

Art education is often ignored in syllabus of developing countries like India and in educational planning for development but now days Indian Art with a global recognition is becoming an integral part of the education at all levels. The term art, widely used in all parts of the modern world, carried varied significance in India as its meaning was continuously being extended, covering the many varieties of creative expression such as painting, sculpture, commercial art, design, poetry, music, dance, and architecture. Over the last 100 years Indian artists of all forms have evolved a wide variety of expressive styles. With the recommendations and initiatives by Government of India, Art Education has subsequently gained pace at the school level as a mandatory subject for all making a path way for students with a creative bend of mind. This paper investigates curriculum in various schools of the country at secondary and senior secondary levels along with some eminent institutions running the program. Findings depicted the role of art education and justified its importance primarily with commercial art being perceived to be essential for students learning skills for economic gain in their career ahead. With so many art colleges spread across India, emerging artists and designers are being trained and are creating art of infinite variety and style and have opened up many career avenues. Commercial Art being a plethora of artistic expressions has confidently come of age wherein a creative perception is mixed with an introspective imagination to bring out multi faceted career options with a significant future enveloped in art. Visual arts in education thus is an expanding field of result assured research.

Keywords: modern art, commercial art, introspective imagination, career

Procedia PDF Downloads 177

Authors: Wilfred Jeyatheese Jeyaraj

Abstract:

Education is a key determinant of future success, and every person deserves non-discriminant access to information for educational inevitabilities in any case. Analysing and understanding complex information is a crucial learning tool, especially for students. In order to compete equally with sighted students, visually impaired students require the unhinged access to access to all the available information resources. When the education of visually impaired students comes to a focal point, it can be stated that visually impaired students encounter several obstacles and barriers before they enter the university and during their time there as students. These obstacles and barriers are spread across technical, organizational and social arenas. This study reveals the possible approaches to absorb and benefit from the information provided by the Sri Lankan University Libraries for visually impaired students. Purposive sampling technique was used to select sample visually impaired students attached to the Sri Lankan National universities. There are 07 National universities which accommodate the visually impaired students and with the identified data, they were selected for this study and 80 visually impaired students were selected as the sample group. Descriptive type survey method was used to collect data. Structured questionnaires, interviews and direct observation were used as research instruments. As far as the Sri Lankan context spread is concerned, visually impaired students are able to finish their courses through their own determination to overcome the barriers they encounter on their way to graduation, through moral and practical support from their own friends and very often through a high level of creativity. According to the findings there are no specially trained university librarians to serve visually impaired users and less number of assistive technology equipment are available at present. This paper enables all university libraries in Sri Lanka to be informed about the social isolation of visually compromised students at the Sri Lankan universities and focuses on the rectification issues by considering their distinct case for interaction.

Keywords: information access, Sri Lanka, university libraries, visual impairment

Procedia PDF Downloads 223

Authors: Tayyaba Azim, Bibi Amina

Abstract:

The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

Procedia PDF Downloads 137

Authors: Paul D. Facey, Claire Morgan

Abstract:

Speech anxiety is thought to be deep-seated within the human evolutionary lineage.As a result, almost all people display high levels of anxiety when asked to communicate in front of an audience.However, proficiency in oral communication is considered as an essential skill for a graduate career and significant emphasis is placed on developing these skills in many degree programs.Because of this, many degree schemes incorporate some form of assessed dialogic presentation. Yet, a student’s anxiety over public speaking, especially if severe, can be so great that at worst it can cause the student to withdraw from their study. This study investigated how students perceive their own levels of anxiety when faced with public speaking using the Personal Report of Public Speaking Anxiety (PRPSA) questionnaire developed by McCroskey. Additionally, students were asked to provide examples of adjustments that could be implemented that they felt would alleviate some/all of their anxiety. The results of the study indicated that the majority of the students experienced a moderate level of anxiety. However, further analysis showed that of those who were in the moderate anxiety’ group, 43% fell into the higher range suggesting that overall more students experience higher levels of anxiety when faced with public speaking than maybe first envisaged. Thus, it is essential that steps are taken to address student anxiety in order that students engage with presentations, are motivated and encouraged and do not avoid such assignments. The feedback from our students indicated a need to implement systematic desensitization programs where students learn to overcome their anxiety through a series of sessions that gradually increase their anxiety levels. Furthermore, these sessions should be run in parallel with skills sessions in order for students to be better prepared and allow self-reflection and self-analysis.This study highlights the paucity of these sessions on many degree schemes and suggests that they should form an integral part of a students’ early academic learning.

Keywords: student anxiety, communication anxiety, public speaking, higher education, desensitisation

Procedia PDF Downloads 232

Authors: Dilek Saritas Atalar, Cansu Alsancak Akbulut, İrem Metin Orta, Feyza Yön, Zeynep Yenen, Joan Grusec

Abstract:

Objective: The aim of this study was to develop semi-structured Domains of Socialization Interview and its coding manual and to test their psychometric properties. Domains of Socialization Interview was designed to assess maternal awareness regarding effective parenting in five socialization domains (protection, mutual reciprocity, control, guided learning, and group participation) within the framework of the domains-of-socialization approach. Method: A series of two studies were conducted to develop and validate the interview and its coding manual. The pilot study, sampled 13 mothers of preschool-aged children, was conducted to develop the assessment tools and to test their function and clarity. Participants of the main study were 82 Turkish mothers (Xage = 34.25, SD = 3.53) who have children aged between 35-76 months (Xage = 50.75, SD = 11.24). Mothers filled in a questionnaire package including Coping with Children’s Negative Emotions Questionnaire, Social Competence and Behavior Evaluation-30, Child Rearing Questionnaire, and Two Dimensional Social Desirability Questionnaire. Afterward, interviews were conducted online by a single interviewer. Interviews were rated independently by two graduate students based on the coding manual. Results: The relationships of the awareness of effective parenting scores to the other measures demonstrate convergent, discriminant, and predictive validity of the coding manual. Intra-class correlation coefficient estimates were ranged between 0.82 and 0.90, showing high interrater reliability of the coding manual. Conclusion: Taken as a whole, the results of these studies demonstrate the validity and reliability of a new and useful interview to measure maternal awareness regarding effective parenting within the framework of the domains-of-socialization approach.

Keywords: domains of socialization, parenting, interview, assessment

Procedia PDF Downloads 173

Authors: Casey Keenan Joiner, Shayna Tayloe

Abstract:

Classical voice training for the novice singer has long relied on the guidance and instruction of vocalise collections, such as those written and compiled by Marchesi, Lütgen, Vaccai, and Lamperti. These vocalise collections purport to encourage healthy vocal habits and instill technical longevity in both aspiring and established singers, though their scope has long been somewhat confined to the classical idiom. For pedagogues and students specializing in other vocal genres, such as musical theatre and CCM (contemporary commercial music,) low-impact and pertinent vocal training aids are in short supply, and much of the suggested literature derives from classical methodology. While the tenants of healthy vocal production remain ubiquitous, specific stylistic needs and technical emphases differ from genre to genre and may require a specified extension of vocal acuity. As musical theatre continues to grow in popularity at both the professional and collegiate levels, the need for specialized training grows as well. Pedagogical literature geared specifically towards musical theatre (MT) singing and vocal production, while relatively uncommon, is readily accessible to the contemporary educator. Practitioners such as Norman Spivey, Mary Saunders Barton, Claudia Friedlander, Wendy Leborgne, and Marci Rosenberg continue to publish relevant research in the field of musical theatre voice pedagogy and have successfully identified many common MT vocal faults, their subsequent diagnoses, and their eventual corrections. Where classical methodology would suggest specific vocalises or training exercises to maintain corrected vocal posture following successful fault diagnosis, musical theatre finds itself without a relevant body of work towards which to transition. By analyzing the existing vocalise literature by means of a specialized set of parameters, including but not limited to melodic variation, rhythmic complexity, vowel utilization, and technical targeting, we have composed a set of vocalises meant specifically to address the training and conditioning of adult musical theatre voices. These vocalises target many pedagogical tenants in the musical theatre genre, including but not limited to thyroarytenoid-dominant production, twang resonance, lateral vowel formation, and “belt-mix.” By implementing these vocalises in the musical theatre voice studio, pedagogues can efficiently communicate proper musical theatre vocal posture and kinesthetic connection to their students, regardless of age or level of experience. The composition of these vocalises serves MT pedagogues on both a technical level as well as a sociological one. MT is a relative newcomer on the collegiate stage and the academization of musical theatre methodologies has been a slow and arduous process. The conflation of classical and MT techniques and training methods has long plagued the world of voice pedagogy and teachers often find themselves in positions of “cross-training,” that is, teaching students of both genres in one combined voice studio. As MT continues to establish itself on academic platforms worldwide, genre-specific literature and focused studies are both rare and invaluable. To ensure that modern students receive exacting and definitive training in their chosen fields, it becomes increasingly necessary for genres such as musical theatre to boast specified literature and a collection of musical theatre-specific vocalises only aids in this effort. This collection of musical theatre vocalises is the first of its kind and provides genre-specific studios with a basis upon which to grow healthy, balanced voices built for the harsh conditions of the modern theatre stage.

Keywords: voice pedagogy, targeted methodology, musical theatre, singing

Procedia PDF Downloads 148

Authors: Laurent Bellemare

Abstract:

After the showcase of traditional Indonesian performing arts at the Vancouver Expo 1986, Canadian universities inherited sets of Indonesian gamelan orchestras and soon began offering courses for music students interested in learning these diverse traditions. Among them, Université de Montréal was offered two sets of Balinese orchestras, a novelty that allowed a community of Montreal gamelan enthusiasts to form and engage with this music. A few generations later, a large body of archives have amassed, framing the history of this niche community’s achievements. This data, scattered in public and private archive collections, comes in various formats: Digital Audio Tape, audio cassettes, Video Home System videotape, digital files, photos, reel-to-reel audiotape, posters, concert programs, letters, TV shows, reports and more. Attempting to study these documents in order to unearth a chronology of gamelan in Montreal has proven to be challenging since no suitable platform for preservation, storage, and research currently exists. These files are, therefore, hard to find due to their decentralized locations. Additionally, most of the documents in older formats have yet to be digitized. In the case of recent digital files, such as pictures or rehearsal recordings, their locations can be even messier and their quantity overwhelming. Aside from the basic issue of choosing a suitable repository platform, questions of legal rights and methodology arise. For posterity, these documents should nonetheless be digitized, organized, and stored in an easily accessible online repository. This paper aims to underline the various challenges encountered in the early stages of such a project as well as to suggest ways of overcoming the obstacles to a thorough archival investigation.

Keywords: archival work, archives, Balinese gamelan, Canada, Gamelan, Indonesia, Javanese gamelan, Montreal

Procedia PDF Downloads 108

Authors: Madhuri S. Ghate, Rahul P. Chavhan, Shriya S. Nahar

Abstract:

Learning objective: •To describe Magnetic Resonance Imaging (MRI) imaging appearances of typical and atypical uterine fibroids with emphasis on differentiating it from other similar conditions. •To classify uterine fibroids according to International Federation of Gynecology and Obstetrics (FIGO) Sub-classifications system and emphasis on its clinical significance. •To show cases with atypical imaging appearances atypical fibroids Material and methods: MRI of Pelvis had been performed in symptomatic women of child bearing age group on 1.5T and 3T MRI using T1, T2, STIR, FAT SAT, DWI sequences. Contrast was administered when degeneration was suspected. Imaging appearances of Atypical fibroids and various degenerations in fibroids were studied. Fibroids were classified using FIGO Sub-classification system. Its impact on surgical decision making and clinical outcome were also studied qualitatively. Results: Intramural fibroids were most common (14 patients), subserosal 7 patients, submucosal 5 patients . 6 patients were having multiple fibroids. 7 were having atypical fibroids. (1 hyaline degeneration, 1 cystic degeneration, 1 fatty, 1 necrosis and hemorrhage, 1 red degeneration, 1 calcification, 1 unusual large bilobed growth). Fibroids were classified using FIGO system. In uterus conservative surgeries, the lesser was the degree of myometrial invasion of fibroid, better was the fertility outcome. Conclusion: Relationship of fibroid with mucosal and serosal layers is important in the management of symptomatic fibroid cases. Risk to fertility involved in uterus conservative surgeries in women of child bearing age group depends on the extent of myometrial invasion of fibroids. FIGO system provides better insight into the degree of myometrial invasion. Knowledge about the atypical appearances of fibroids is important to avoid diagnostic confusion and untoward treatment.

Keywords: degeneration, FIGO sub-classification, MRI pelvis, uterine fibroids

Procedia PDF Downloads 74

Authors: Sharda Kumari, Saiman Shetty

Abstract:

Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

Procedia PDF Downloads 91

Authors: Ruby Jean Hornsby

Abstract:

In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

Procedia PDF Downloads 94

Authors: Mitansha, Suzanne Wilkinson, Regan Potangaroa

Abstract:

The built environment is designed, maintained, operated, and decommissioned by construction organisations, which play a significant role in providing physical resources and rebuilding infrastructures during major crises and disasters. It is evident that enhancing the resilience of construction organisations allows better responding ability and speedy recovery from disasters and acts as a boon for the nation in the face of significant disruptions. As individuals are the integral component of any organisation, hence, individual resilience is considered a critical aspect, which may boost organisational resilience of construction sector. It has been observed that individual resilience is indirectly supported by organisation’s citizenship behaviour, job performance, and career success. Not only this, it also tends to hold a directly proportional relation with job satisfaction, physical and emotional well-being affected by organisation’s work culture, whereas the resilience of organisation increases as a result of positive adaption, growth and collective learning of the employees as an entity. Moreover, indicators like Situation awareness in staff and crisis related issues, effective vulnerability management, organisational leadership and culture ensured by approachable, encouraging and people-oriented leaders, are prominent for achieving organisational resilience. It, thus, becomes perceptible that both, organisational and individual resiliencies have the potential to influence each other. Consequently, it arises a major question that how these characteristics are associated and tend to behave with respect to each other The study, thus, aims to explore the overlapping dimensions of organisational and individual resilience to determine the impact boundaries. The research methodology of the paper would be based on systematic literature review specifically focused on the resilience of construction industry. This would provide a direct comparison of characteristics influencing individual and organisational resilience and will present the most significant indicators of individual resilience, that can eventually help to enhance the resilience of construction organisations amidst any disaster or crisis.

Keywords: construction industry, individual resilience, organizational resilience, overlapping dimension

Procedia PDF Downloads 91

Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

Procedia PDF Downloads 51

Authors: Bahadır Erişti

Abstract:

Values are the behavioral procedures of society based communication and interaction process that includes social and cultural backgrounds. The policy of learning and teaching in higher education is oriented towards constructing knowledge and skills, based on theorist framework of cognitive and psychomotor aspects. This approach makes people not to develop generosity, empathy, affection, solidarity, justice, equality and so on. But the sensorial gains of education system provide the integrity of society interaction. This situation carries out the necessity of values education’s in higher education. The current study aims to consider values education from the viewpoint of students in higher education. Within the framework of the current study, an open ended survey based scenario of higher education students was conducted with the students’ social, cognitive, affective and moral developments. In line with this purpose, the following situations of the higher education system were addressed based on the higher education students’ viewpoint: The views of higher education students’ regarding values that are tried to be gained at the higher education system; The higher education students’ suggestions regarding values education at the higher education system; The views of the higher education students’ regarding values that are imposed at the higher education system. In this study, descriptive qualitative research method was used. The study group of the research is composed of 20 higher education postgraduate students at Curriculum and Instruction Department of Educational Sciences at Anadolu University. An open-ended survey was applied for the purpose of collecting qualitative data. As a result of the study, value preferences, value judgments and value systems of the higher education students were constructed on prioritizes based on social, cultural and economic backgrounds and statues. Multi-dimensional process of value education in higher education need to be constructed on higher education-community-cultural background cooperation. Thus, the act of judgement upon values between higher education students based on the survey seems to be inherent in the system of education itself. The present study highlights the students’ value priorities and importance of values in higher education. If the purpose of the higher education system gains on values, it is possible to enable society to promote humanity.

Keywords: higher education, value, values education, values in higher education

Procedia PDF Downloads 324

Authors: G. Ravindranath, S. Savitha

Abstract:

This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

Procedia PDF Downloads 353