Search results for: online training
2340 The Communication Between Visual Aesthetic Criteria of Product with User Experience and Social Sustainability: A Study of Street Furniture
Authors: Hassan Sadeghi Naeini, Mozhgan Sabzehparvar, Mahdiye Jafarnezhad, Neda Brumandi, Mohammad Parsa Sabzehparvar
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This study aims to discover the relationship between the factors of aesthetics, user experience, and social sustainability concerning the design of street furniture and the impact of these factors on the emotional arousal of citizens to encourage and make them prefer to use street furniture. The method used in this research included extracting indicators related to each of the factors of aesthetics, user experience, and social sustainability from the articles and then selecting indicators related to the purpose of the research in consultation with industrial design experts and architects. Finally, 9 variables for aesthetics, 7 variables for user experience, and 5 variables for evaluating social sustainability were selected. To identify the effect of each of these factors on street furniture and to recognize their relationship with each other. A 10-scale prioritization questionnaire, from 1, the least amount of importance, to 10, the most amount of importance, was answered by architects and industrial designers on the “Pors Line” online platform for three consecutive weeks, and a total of 82 people answered the questionnaire. The results showed that by using aesthetic factors in the design of street furniture and having a positive impact on users’ experience of using the product, we could expect the occurrence of behavioral factors, such as creating constructive interaction and product acceptance so that the satisfaction of the user in the use of street furniture and optimal interaction in the urban environment is formed, followed by that, the requirements of social sustainability will be met.Keywords: visual aesthetic, user experience, social sustainability, street furniture
Procedia PDF Downloads 952339 Towards Kurdish Internet Linguistics: A Case Study on the Impact of Social Media on Kurdish Language
Authors: Karwan K. Abdalrahman
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Due to the impacts of the internet and social media, new words and expressions enter the Kurdish language, and a number of familiarized words get new meanings. The case is especially true when the technique of transliteration is taken into consideration. Through transliteration, a number of selected words widely used on social media are entering the Kurdish media discourse. In addition, a selected number of Kurdish words get new cultural and psychological meanings. The significance of this study is to delve into the process of word formation in the Kurdish language and explore how new words and expressions are formed by social media users and got public recognition. First, the study investigates the English words that enter the Kurdish language through different social media platforms. All of these words are transliterated and are used in spoken and written discourses. Second, there are a specific number of Kurdish words that got new meanings in social media. As for these words, there are psychological and cultural factors that make people use these expressions for specific political reasons. It can be argued that they have an indirect political message along with their new linguistic usages. This is a qualitative study analyzing video content that was published in the last two years on social media platforms, including Facebook and YouTube. The collected data was analyzed based on the themes discussed above. The findings of the research can be summarized as follows: the widely used transliterated words have entered both the spoken and written discourses. Authors in online and offline newspapers, TV presenters, literary writers, columnists are using these new expressions in their writings. As for the Kurdish words with new meanings, they are also widely used for psychological, cultural, and political reasons.Keywords: Kurdish language, social media, new meanings, transliteration, vocabulary
Procedia PDF Downloads 1812338 Research on the Status Quo and Countermeasures of Professional Development of Engineering Teachers in China
Authors: Wang Xiu Xiu
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The professional development of engineering teachers in universities is the key to the construction of outstanding engineers in China, which is related to the quality and prospects of the entire engineering education. This study investigated 2789 teachers' professional development in different regions of China, which outlines the current situation of the professional development of engineering teachers from three perspectives: professional development needs, professional development methods and professional development effects. Data results show that engineering teachers have the strongest demand for the improvement of subject knowledge and teaching ability. Engineering faculty with 0-5 years of teaching experience, under 35 years of age and a doctorate degree have the strongest demand for development. The frequency of engineering teachers' participation in various professional development activities is low, especially in school-enterprise cooperation-related activities. There are significant differences in the participation frequency of professional development activities among engineering faculty with different teaching ages, ages, professional titles, degrees and administrative positions in schools. The professional development of engineering faculty has been improved to a certain extent and is positively affected by professional development needs and participation in professional development. In this regard, we can constantly improve the professional development system of engineering teachers from three aspects: training on demand, stimulating motivation, and optimizing resource allocation, to enhance the professional development level of engineering teachers.Keywords: engineering teachers in universities, professional development, status quo, countermeasures
Procedia PDF Downloads 192337 The Impact of Equine-Assisted Therapy on Occupational Engagement for Children with Intellectual and/or Developmental Disabilities: From the Perspectives of the Children and Their Caregivers
Authors: Morgan Dempsey, Sam Lewis, Maggie Pierce, Alex Goodman
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This research investigates the impact of equine-assisted therapy programs on occupational engagement for children with intellectual and developmental disabilities. There is a general lack of evidence for equine-based services for this population, so this research aims to decrease gaps in the current literature. To gain comprehensive insight, data will be collected from both the child and their caregiver. This study takes a qualitative approach utilizing online surveys and in-person guided interviews. The participants are individuals ages 4-17 with a diagnosed intellectual or developmental disability who are currently participating in a PATH int. certified equine-assisted therapy program. Also, caregivers of individuals who meet this criterion are included. This study decreases gaps in the literature by providing comprehensive data regarding the impacts of these services on occupational engagement. The addressed domains are physical, behavioral, emotional, and social functioning, as well as overall activity engagement and impacts in everyday life. With a better understanding of how equine-assisted therapy affects relevant outcomes for children with disabilities, an increased number of occupational therapists can implement these uniquely effective services while adhering to standards of evidence-based practice. Ultimately, this research strives to contribute to generalizable data in occupational therapy by supporting the implementation of equine-assisted services for children with intellectual and/or developmental disabilities and their caregivers/families.Keywords: occupational therapy, pediatric, rehabilitation, hippotherapy
Procedia PDF Downloads 362336 Geopolitical Implications and the Role of LinkedIn in the Russo-Ukrainian War: A Comprehensive Analysis of Social Media in Crisis Situations
Authors: Amber Brittain-Hale
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This research investigates the evolving role of social media in crisis situations by employing discourse analysis methodology and honing in on the Russo-Ukrainian War, particularly Ukraine's use of LinkedIn. The study posits that social media platforms, such as LinkedIn, play a crucial role in shaping communication, disseminating information, and influencing geopolitical strategies during conflicts. Focusing on Ukraine's official state account on LinkedIn and analyzing its posts and interactions, the research aims to unveil discourse dynamics in high-stakes scenarios and provide valuable insights for leaders navigating complex global challenges. A comprehensive analysis of the data will contribute to a deeper understanding of the tactics adopted by political leaders in managing communication, the bidirectional nature of discourse provided by online social networks, and the rapid advancement of technology that has led to the growing significance of social media platforms in crisis situations. Through this approach, the geopolitical factors that influenced the country's social media strategy during the Russo-Ukrainian War will be illuminated, offering a broader perspective on the role of social media in such challenging times. Ultimately, the study seeks to uncover lessons that can be drawn from Ukraine's LinkedIn approach, informing future strategies for utilizing social media during crises and advancing the understanding of how social media can be harnessed to address intricate global issues.Keywords: russo-ukrainian war, social media, crisis, discourse analysis
Procedia PDF Downloads 1162335 E-Marketing Strategy a Competitive Advantage among Commercial Bank Branches in Bauchi State
Authors: Sagir Abubakar
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The electronic means of transaction has provided an opportunity especially for commercial banks to entice more customers that will subsequently boost their return on investment. It moves them from traditional marketing into digital marketing and gives them a competitive advantage over others in the same industry. The paper, therefore, examined the competitive advantage of the electronic marketing strategy among commercial banks branches in Bauchi state. The main objective of the study was to determine the impact of e-marketing strategy as a competitive advantage among commercial banks branches in Bauchi state and to evaluate the level of enlightenment campaign offered by the commercial banks branches to their customers on e-marketing. The study obtained data from the staff of the five (s) selected banks branches as the respondents to answer the questionnaire. The research is a quantitative research, where the data where obtained using questionnaire. 100 questionnaires were distributed and analyzed using SPSS’s regression analysis. The research among other findings discovered that the e-marketing has led to a significant improvement in the banking industry and is expected to continue because of the improvement in the ICT sector. It was also found out that most customers are not aware of the electronic products offered by commercial banks branches in Bauchi state. Some of factors affecting the adoption of e-marketing by banks as indicated from the findings include: top management commitment, government policy on ICT and availability of ICT personnel. The study recommended that commercial banks branches should engage in enlightenment campaign about the existing of their e- products/services, management should place an incentive in order to raise the interest of customers to patronize the products/services online.Keywords: e-marketing strategy, competitive advantage, banks, Bauchi State
Procedia PDF Downloads 4802334 Diabetes Diagnosis Model Using Rough Set and K- Nearest Neighbor Classifier
Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho
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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.Keywords: classifier algorithm, diabetes, diagnostic model, machine learning
Procedia PDF Downloads 3362333 Effective Stacking of Deep Neural Models for Automated Object Recognition in Retail Stores
Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay
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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition
Procedia PDF Downloads 1572332 The Mediation Role of Loneliness in the Relationship between Interpersonal Trust and Empathy
Authors: Ghazal Doostmohammadi, Susan Rahimzadeh
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Aim: This research aimed to investigate the relationship between empathy and interpersonal trust and recognize the mediating role of loneliness between them in both genders. Methods: With a correlational descriptive design, 192 university students (130 female and 62 male) responded to the questionnaires on “empathy quotient,” “loneliness,” and “interpersonal trust” tests. These tests were designed and validated by experts in the field. Data were analysed using Pearson correlation and path analysis, which is a statistical technique that uses standard linear regression equations to determine the degree of conformity of a theoretical causal model with reality. Results: The data analysis showed that there was no significant correlation between interpersonal trust, both with loneliness (t=0.169) and empathy (t=0.186), while there was a significant negative correlation (t=0.359) between empathy and loneliness. This means that there is an inverse correlation between empathy and loneliness. The path analysis confirmed the hypothesis of the research about the mediating role of loneliness between empathy and interpersonal trust. But gender did not play a role in this relationship. Conclusion: As an outcome, clinical professionals and education trainers should pay more attention to interpersonal trust as a basic need and try to recreate and shape it to prevent people's social breakdown, and on the other hand, self-disclosure training (especially in Men), expression of feelings and courage should be given double importance to prevent the consequences of loneliness.Keywords: empathy, loneliness, interpersonal trust, gender
Procedia PDF Downloads 842331 Academic Achievement Differences in Grandiose and Vulnerable Narcissists and the Mediating Effects of Self-Esteem and Self-Efficacy
Authors: Amber Dummett, Efstathia Tzemou
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Narcissism is a personality trait characterized by selfishness, entitlement, and superiority. Narcissism is split into two subtypes, grandiose narcissism (GN) and vulnerable narcissism (VN). Grandiose narcissists are extraverted and arrogant, while vulnerable narcissists are introverted and insecure. This study investigates the psychological mechanisms that lead to differences in academic achievement (AA) between grandiose and vulnerable narcissists, specifically the mediating effects of self-esteem and self-efficacy. While narcissism is considered to be a negative trait, one of the Dark Triads, GN, has been found to have some benefits; therefore, this study considers if better AA is one of them. Moreover, further research into VN is essential to fully compare and contrast it with GN. We hypothesize that grandiose narcissists achieve higher marks due to having high self-esteem and self-efficacy. In comparison, we hypothesize that vulnerable narcissists underperform and achieve lower marks due to having low self-esteem and self-efficacy. Two online surveys were distributed to undergraduate university students. The first was a collection of scales measuring the mentioned dimensions and semester one AA, and the second investigated end of year AA. Sequential mediation analyses were conducted using the gathered data. Our analysis shows that neither self-esteem nor self-efficacy mediates the relationship between GN and AA. GN positively predicts self-esteem but has no relationship with self-efficacy. Self-esteem does not mediate the relationship between VN and AA. VN has a negative indirect effect on AA via self-efficacy, and VN negatively predicts self-esteem. Self-efficacy positively predicts AA. GN does not affect AA through the mediation of self-esteem and then self-efficacy, and neither does VN in this way. Overall, having grandiose or vulnerable narcissistic traits does not affect students’ AA. However, being highly efficacious does lead to academic success; therefore, universities should employ methods to improve the self-efficacy of their students.Keywords: academic achievement, grandiose narcissism, self-efficacy, self-esteem, vulnerable narcissism
Procedia PDF Downloads 1962330 An Investigation of the Association between Pathological Personality Dimensions and Emotion Dysregulation among Virtual Network Users: The Mediating Role of Cyberchondria Behaviors
Authors: Mehdi Destani, Asghar Heydari
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Objective: The present study aimed to investigate the association between pathological personality dimensions and emotion dysregulation through the mediating role of Cyberchondria behaviors among users of virtual networks. Materials and methods: A descriptive–correlational research method was used in this study, and the statistical population consisted of all people active on social network sites in 2020. The sample size was 300 people who were selected through Convenience Sampling. Data collection was carried out in a survey method using online questionnaires, including the "Difficulties in Emotion Regulation Scale" (DERS), Personality Inventory for DSM-5 Brief Form (PID-5-BF), and Cyberchondria Severity Scale Brief Form (CSS-12). Data analysis was conducted using Pearson's Correlation Coefficient and Structural Equation Modeling (SEM). Findings: Findings suggested that pathological personality dimensions and Cyberchondria behaviors have a positive and significant association with emotion dysregulation (p<0.001). The presented model had a good fit with the data. The variable “pathological personality dimensions” with an overall effect (p<0.001, β=0.658), a direct effect (p<0.001, β=0.528), and an indirect mediating effect through Cyberchondria Behaviors (p<.001), β=0.130), accounted for emotion dysregulation among virtual network users. Conclusion: The research findings showed a necessity to pay attention to the pathological personality dimensions as a determining variable and Cyberchondria behaviors as a mediator in the vulnerability of users of social network sites to emotion dysregulation.Keywords: cyberchondria, emotion dysregulation, pathological personality dimensions, social networks
Procedia PDF Downloads 1042329 Effects of E-Learning Mode of Instruction and Conventional Mode of Instruction on Student’s Achievement in English Language in Senior Secondary Schools, Ibadan Municipal, Nigeria
Authors: Ibode Osa Felix
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The use of e-Learning is presently intensified in the academic world following the outbreak of the Covid-19 pandemic in early 2020. Hitherto, e-learning had made its debut in teaching and learning many years ago when it emerged as an aspect of Computer Based Teaching, but never before has its patronage become so important and popular as currently obtains. Previous studies revealed that there is an ongoing debate among researchers on the efficacy of the E-learning mode of instruction over the traditional teaching method. Therefore, the study examined the effect of E-learning and Conventional Mode of Instruction on Students Achievement in the English Language. The study is a quasi-experimental study in which 230 students, from three public secondary schools, were selected through a simple random sampling technique. Three instruments were developed, namely, E-learning Instructional Guide (ELIG), Conventional Method of Instructional Guide (CMIG), and English Language Achievement Test (ELAT). The result revealed that students taught through the conventional method had better results than students taught online. The result also shows that girls taught with the conventional method of teaching performed better than boys in the English Language. The study, therefore, recommended that effort should be made by the educational authorities in Nigeria to provide internet facilities to enhance practices among learners and provide electricity to power e-learning equipment in the secondary schools. This will boost e-learning practices among teachers and students and consequently overtake conventional method of teaching in due course.Keywords: e-learning, conventional method of teaching, achievement in english, electricity
Procedia PDF Downloads 1702328 Experience Level and Adoption of Interpretation Strategies by Iranian Interpreters
Authors: Niloofar Fathizaviyehkord
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Just as two hands cannot make a good boxer, knowing two or more languages cannot make a skillful interpreter. Interpreting, either consecutive or simultaneous, is a cognitively demanding task requiring not only linguistic and discourse knowledge but also strategic competence. Moreover, experience level can play a very crucial role in the strategies interpreters may employ since translation and interpretation quality is a matter of experience, besides other factors, as well. With regard to the significance of strategic competence, this study investigated what strategies are mainly employed by interpreters, what strategies are employed more frequently, and whether experience level can affect the choice of strategies by interpreters or not. To collect the necessary data, the first retrospective interviews were held with 20 interpreters experienced more or less in simultaneous and consecutive interpretation to see what strategies other than those classified in the literature are employed by interpreters. Then, several classifications of strategies in literature were merged with those emerging from the retrospective interviews to come up with a comprehensive questionnaire on interpreting strategies. After seeking five experts’ opinions regarding the wording/content of the questionnaire, it was given to 60 interpreters. The statistical analysis of the questionnaire data and experience level through ANOVA showed experience level could affect the choice of strategies. This study closes with the theoretical/practical implications of the findings for interpreter training.Keywords: experience level, consecutive and simultaneous, interpretation strategies, translation
Procedia PDF Downloads 1382327 An Entropy Based Novel Algorithm for Internal Attack Detection in Wireless Sensor Network
Authors: Muhammad R. Ahmed, Mohammed Aseeri
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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.Keywords: internal attack, wireless sensor network, network security, entropy
Procedia PDF Downloads 4552326 Schoolwide Implementation of Schema-Based Instruction for Mathematical Problem Solving: An Action Research Investigation
Authors: Sara J. Mills, Sally Howell
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The field of special education has long struggled to bridge the research to practice gap. There is ample evidence from research of effective strategies for students with special needs, but these strategies are not routinely implemented in schools in ways that yield positive results for students. In recent years, the field of special education has turned its focus to implementation science. That is, discovering effective methods of implementing evidence-based practices in school settings. Teacher training is a critical factor in implementation. This study aimed to successfully implement Schema-Based Instruction (SBI) for math problem solving in four classrooms in a special primary school serving students with language deficits, including students with Autism Spectrum Disorders (ASD) and Intellectual Disabilities (ID). Using an action research design that allowed for adjustments and modification to be made over the year-long study, two cohorts of teachers across the school were trained and supported in six-week learning cycles to implement SBI in their classrooms. The learning cycles included a one-day training followed by six weeks of one-on-one or team coaching and three fortnightly cohort group meetings. After the first cohort of teachers completed the learning cycle, modifications and adjustments were made to lesson materials in an attempt to improve their effectiveness with the second cohort. Fourteen teachers participated in the study, including master special educators (n=3), special education instructors (n=5), and classroom assistants (n=6). Thirty-one students participated in the study (21 boys and 10 girls), ranging in age from 5 to 12 years (M = 9 years). Twenty-one students had a diagnosis of ASD, 20 had a diagnosis of mild or moderate ID, with 13 of these students having both ASD and ID. The remaining students had diagnosed language disorders. To evaluate the effectiveness of the implementation approach, both student and teacher data was collected. Student data included pre- and post-tests of math word problem solving. Teacher data included fidelity of treatment checklists and pre-post surveys of teacher attitudes and efficacy for teaching problem solving. Finally, artifacts were collected throughout the learning cycle. Results from cohort 1 and cohort 2 revealed similar outcomes. Students improved in the number of word problems they answered correctly and in the number of problem-solving steps completed independently. Fidelity of treatment data showed that teachers implemented SBI with acceptable levels of fidelity (M = 86%). Teachers also reported increases in the amount of time spent teaching problem solving, their confidence in teaching problem solving and their perception of students’ ability to solve math word problems. The artifacts collected during instruction indicated that teachers made modifications to allow their students to access the materials and to show what they knew. These findings are in line with research that shows student learning can improve when teacher professional development is provided over an extended period of time, actively involves teachers, and utilizes a variety of learning methods in classroom contexts. Further research is needed to evaluate whether these gains in teacher instruction and student achievement can be maintained over time once the professional development is completed.Keywords: implementation science, mathematics problem solving, research-to-practice gap, schema based instruction
Procedia PDF Downloads 1252325 Multi-Spectral Deep Learning Models for Forest Fire Detection
Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani
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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection
Procedia PDF Downloads 2412324 Prediction of the Crustal Deformation of Volcán - Nevado Del RUíz in the Year 2020 Using Tropomi Tropospheric Information, Dinsar Technique, and Neural Networks
Authors: Juan Sebastián Hernández
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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR
Procedia PDF Downloads 1032323 The Search of Possibility of Running Six Sigma Process in It Education Center
Authors: Mohammad Amini, Aliakbar Alijarahi
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This research that is collected and title as ‘ the search of possibility of running six sigma process in IT education center ‘ goals to test possibility of running the six sigma process and using in IT education center system. This process is a good method that is used for reducing process, errors. To evaluate running off six sigma in the IT education center, some variables relevant to this process is selected. These variables are: - The amount of support from organization master boss to process. - The current specialty. - The ability of training system for compensating reduction. - The amount of match between current culture whit six sigma culture . - The amount of current quality by comparing whit quality gain from running six sigma. For evaluation these variables we select four question and to gain the answers, we set a questionnaire from with 28 question and distribute it in our typical society. Since, our working environment is a very competition, and organization needs to decree the errors to minimum, otherwise it lasts their customers. The questionnaire from is given to 55 persons, they were filled and returned by 50 persons, after analyzing the forms these results is gained: - IT education center needs to use and run this system (six sigma) for improving their process qualities. - The most factors need to run the six sigma exist in the IT education center, but there is a need to support.Keywords: education, customer, self-action, quality, continuous improvement process
Procedia PDF Downloads 3402322 Role of Social Media in Imparting Climate Change through Diffusion of Innovation
Authors: Zahra Ali Abbasi, Syed Muhammad Saqib Saleem
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This research explores the relationship between social media and awareness about climate change amongst the university students of Lahore, Pakistan. The aim is to understand how the people of Pakistan perceive climate change, especially on the social media. A deductive and quantitative method is applied on the research to find out the awareness of climate change in the people using social media. For this purpose, a survey method is used, to analyze the response from 167 online respondents through stratified random sampling technique. The relation between multiple variables including awareness about important climatic events like Paris agreement, GreenTube, Smog in Lahore, Floods in Pakistan and other eminent incidents of climate change and social media are calculated by analyzing social media as a source to impart information about climate change. The results show that as people get aware of climate change, they post about different national and international events/incidents of climate which reveal a significant relationship between respondents' awareness about climate change and their posting and sharing of content about climate change. Another test indicates that respondents’ post/share/comment (impart) information about climate change when there is a shift in the climate both globally and nationally. However, the significance of both these correlations has been found to be negligible. Social media being an independent platform holds greater influencing power, hence, as consumers of the environment the users hold the responsibility of producing and sharing content at a global platform about climate. However, matters of politics, economy and religion seem to have overshadowed the significance of climate.Keywords: climate change, diffusion of innovation, environment, social media, Pakistan
Procedia PDF Downloads 1962321 China’s Participation in WorldSkills Competition for 14 Years: Experience, Problems and Prospects
Authors: Wang Di, Luo Shengqiang, Chen Yanjie
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Vocational skill competition is an effective means to test and improve the quality of engineering education personnel training and provides a high-level practice platform for practical teaching in engineering education. Since China participated in the WorldSkills Competition in 2011, it has achieved very good results in the past 14 years. This study provides a group portrait of China's participation in the WorldSkills Competition, including competitors, competition managers and, Chinese laborers, etc. Meanwhile, through in-depth research on the basic process of launching the WorldSkills Competition in China, the experience and main problems of China's participation in skills competition are summarized. Including China's remarkable practices in institutional mechanisms, team management, promoting world skills development, and boosting social equity and gender equality, it puts forward specific ideas for developing countries to strengthen engineering education and participate in skills competitions. Centering on the value concept of a community with a shared future for mankind proposed by China, we envision how to reinforce skills development in China and take concrete actions to support the United Nations Sustainable Development Goals (SDGs).Keywords: WorldSkills competition, engineering education, TVET, Chinese experience
Procedia PDF Downloads 112320 Application of Principle Component Analysis for Classification of Random Doppler-Radar Targets during the Surveillance Operations
Authors: G. C. Tikkiwal, Mukesh Upadhyay
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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp
Procedia PDF Downloads 3462319 Quasi-Photon Monte Carlo on Radiative Heat Transfer: An Importance Sampling and Learning Approach
Authors: Utkarsh A. Mishra, Ankit Bansal
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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks
Procedia PDF Downloads 2232318 Describing Professional Purchasers' Performance Applying the 'Big Five Inventory': Findings from a Survey in Austria
Authors: Volker Koch, Sigrid Swobodnik, Bernd M. Zunk
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The success of companies on globalized markets is significantly influenced by the performance of purchasing departments and, of course, the individuals employed as professional purchasers. Nonetheless, this is generally accepted in practice, in literature as well as in empirical research, only insufficient attention was given to the assessment of this relationship between the personality of professional purchasers and their individual performance. This paper aims to describe the relationship against the background of the 'Big Five Inventory'. Based on the five dimensions of a personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) a research model was designed. The research model divides the individual performance of professional purchasers into two major dimensions: operational and strategic. The operational dimension consists of the items 'cost', 'quality delivery' and 'flexibility'; the strategic dimension comprises the positions 'innovation', 'supplier satisfaction' as wells as 'purchasing and supply management integration in the organization'. To test the research model, a survey study was performed, and an online questionnaire was sent out to purchasing professionals in Austrian companies. The data collected from 78 responses was used to test the research model applying a group comparison. The comparison points out that there is (i) an influence of the purchasers’ personality on the individual performance of professional purchasers and (ii) a link between purchasers’ personality to a high or a low individual performance of professional purchasers. The findings of this study may help human resource managers during staff recruitment processes to identify the 'right performing personality' for an operational and/or a strategic position in purchasing departments.Keywords: big five inventory, individual performance, personality, purchasing professionals
Procedia PDF Downloads 1702317 Shear Strength Evaluation of Ultra-High-Performance Concrete Flexural Members Using Adaptive Neuro-Fuzzy System
Authors: Minsu Kim, Hae-Chang Cho, Jae Hoon Chung, Inwook Heo, Kang Su Kim
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For safe design of the UHPC flexural members, accurate estimations of their shear strengths are very important. However, since the shear strengths are significantly affected by various factors such as tensile strength of concrete, shear span to depth ratio, volume ratio of steel fiber, and steel fiber factor, the accurate estimations of their shear strengths are very challenging. In this study, therefore, the Adaptive Neuro-Fuzzy System (ANFIS), which has been widely used to solve many complex problems in engineering fields, was introduced to estimate the shear strengths of UHPC flexural members. A total of 32 experimental results has been collected from previous studies for training of the ANFIS algorithm, and the well-trained ANFIS algorithm provided good estimations on the shear strengths of the UHPC test specimens. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(NRF-2016R1A2B2010277).Keywords: ultra-high-performance concrete, ANFIS, shear strength, flexural member
Procedia PDF Downloads 1882316 The Development of Portable Application Software for Cardiovascular Fitness Norms of NDUM Cadet Students
Authors: Mohar Kassim, Hardy Azmir, Rahmat Sholihin Mokhtar
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The purpose of this study is to build portable application software to determine the level of cardiovascular fitness for cadet students of the National Defence University of Malaysia (NDUM). Fitness in the context of this study refers to physical fitness, specifically the cardiovascular endurance level test battery in the form of a 2.4 km run test for UPNM cadet students. This run test will be conducted to measure, test, and evaluate the performance of UPNM cadet students. All the run test results can be recorded electronically inside the portable software and will later be able to show the level of cardiovascular fitness of every cadet student according to age and gender. This software can also calculate the body mass index (BMI). Normative survey method will be used in this study through the analysis of the 2.4 km run test results. The run test scores will be classified in interval and ratio scales. Based on the findings of this study, portable application software will produced. The software will be able to directly assist the Military Training Academy (ALK), Malaysian Armed Forces (ATM), and other relevant agencies in determining the level of cardiovascular fitness among their staff. The test can be done electronically and on portable mode. The next step to be taken is to have this application patented.Keywords: development, software, application, portable, fitness norms, cardiovascular endurance
Procedia PDF Downloads 5492315 Hydro-Gravimetric Ann Model for Prediction of Groundwater Level
Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar
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Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.Keywords: machine learning, hydro-gravimetry, ground water level, predictive model
Procedia PDF Downloads 1272314 Thai Perception on Litecoin Value
Authors: Toby Gibbs, Suwaree Yordchim
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This research analyzes factors affecting the success of Litecoin Value within Thailand and develops a guideline for self-reliance for effective business implementation. Samples in this study included 119 people through surveys. The results revealed four main factors affecting the success as follows: 1) Future Career training should be pursued in applied Litecoin development. 2) Didn't grasp the concept of a digital currency or see the benefit of a digital currency. 3) There is a great need to educate the next generation of learners on the benefits of Litecoin within the community. 4) A great majority didn't know what Litecoin was. The guideline for self-reliance planning consisted of 4 aspects: 1) Development planning: by arranging meet up groups to conduct further education on Litecoin and share solutions on adoption into every day usage. Local communities need to develop awareness of the usefulness of Litecoin and share the value of Litecoin among friends and family. 2) Computer Science and Business Management staff should develop skills to expand on the benefits of Litecoin within their departments. 3) Further research should be pursued on how Litecoin Value can improve business and tourism within Thailand. 4) Local communities should focus on developing Litecoin awareness by encouraging street vendors to accept Litecoin as another form of payment for services rendered.Keywords: litecoin, mining, confirmations, payment method
Procedia PDF Downloads 1842313 Effects of Clinical Practice Guideline on Knowledge and Preventive Practices of Nursing Personnel and Incidences of Ventilator-associated Pneumonia Thailand
Authors: Phawida Wattanasoonthorn
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Ventilator-associated pneumonia is a serious infection found to be among the top three infections in the hospital. To investigate the effects of clinical practice guideline on knowledge and preventive practices of nursing personnel, and incidences of ventilator-associated pneumonia. A pre-post quasi-experimental study on 17 professional nurses, and 123 ventilator-associated pneumonia patients admitted to the surgical intensive care unit, and the accident and surgical ward of Songkhla Hospital from October 2013 to January 2014. The study found that after using the clinical practice guideline, the subjects’ median score increased from 16.00 to 19.00. The increase in practicing correctly was from 66.01 percent to 79.03 percent with the statistical significance level of .05, and the incidences of ventilator-associated pneumonia decreased by 5.00 percent. The results of this study revealed that the use of the clinical practice guideline helped increase knowledge and practice skill of nursing personnel, and decrease incidences of ventilator-associated pneumonia. Thus, nursing personnel should be encouraged, reminded and promoted to continue using the practice guideline through various means including training, providing knowledge, giving feedback, and putting up posters to remind them of practicing correctly and sustainably.Keywords: Clinical Practice Guideline, knowledge, Preventive Ventilator, Pneumonia
Procedia PDF Downloads 4102312 Towards a Successful Implementation of ICT in Education : Analyzing Teacher Practices and Perceptions
Authors: Azzeddine Atibi, Lamalif latifa, Khadija El Kababi, Salim Ahmed, Mohamed Radid
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This study analyzes the integration of Information and Communication Technologies (ICT) in modern education, where these tools have become essential. Due to the rapid emergence of new technologies and their increasing adoption in education, it is important to understand how teachers use and perceive these tools. The study pursues three objectives : examining current teacher practices regarding ICT, evaluating their impact on student skills and engagement, and making recommendations for better integration of ICT in education. The study's methodology is based on a quantitative approach, using a questionnaire administered to a sample of 104 teachers. This questionnaire, rigorously validated to ensure its reliability, gathers representative data on perceptions and challenges related to the use of ICT. The results show widespread adoption of ICT by teachers, with the majority reporting an improvement in student skills due to these technologies. However, opinions diverge on their impact on student engagement : some teachers note an increase in engagement, while others remain skeptical. Persistent challenges include insufficient technological infrastructure and the need for ongoing training. The recommendations highlight the importance of improving infrastructures and supporting the professional development of teachers to optimize the integration of ICT.Keywords: ICT, education, teaching practices, teacher perceptions, continuing education
Procedia PDF Downloads 332311 Testing Nature Based Solutions for Air Quality Improvement: Aveiro Case Study
Authors: A. Ascenso, C. Silveira, B. Augusto, S. Rafael, S. Coelho, J. Ferreira, A. Monteiro, P. Roebeling, A. I. Miranda
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Innovative nature-based solutions (NBSs) can provide answers to the challenges that urban areas are currently facing due to urban densification and extreme weather conditions. The effects of NBSs are recognized and include improved quality of life, mental and physical health and improvement of air quality, among others. Part of the work developed in the scope of the UNaLab project, which aims to guide cities in developing and implementing their own co-creative NBSs, intends to assess the impacts of NBSs on air quality, using Eindhoven city as a case study. The state-of-the-art online air quality modelling system WRF-CHEM was applied to simulate meteorological and concentration fields over the study area with a spatial resolution of 1 km2 for the year 2015. The baseline simulation (without NBSs) was validated by comparing the model results with monitored data retrieved from the Eindhoven air quality database, showing an adequate model performance. In addition, land use changes were applied in a set of simulations to assess the effects of different types of NBSs. Finally, these simulations were compared with the baseline scenario and the impacts of the NBSs were assessed. Reductions on pollutant concentrations, namely for NOx and PM, were found after the application of the NBSs in the Eindhoven study area. The present work is particularly important to support public planners and decision makers in understanding the effects of their actions and planning more sustainable cities for the future.Keywords: air quality, modelling approach, nature based solutions, urban area
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