Search results for: collaborative learning approach

Authors: Neliswa Dyosi

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Purpose - Using an integrated Technology-Organization-Environment (TOE) framework and the model of technology appropriation (MTA) as a theoretical lens, this interpretive qualitative study seeks to understand and explain the factors that influence the appropriation, non-appropriation, and disappropriation of bitcoin as a payment method by South African retailers. Design/methodology/approach –The study adopts the interpretivist philosophical paradigm. Multiple case studies will be adopted as a research strategy. For data collection, the study follows a qualitative approach. Qualitative data will be collected from the six retailers in various industries. Semi-structured interviews and documents will be used as the data collection techniques. Purposive and snowballing sampling techniques will be used to identify participants within the organizations. Data will be analyzed using thematic analysis. Originality/value - Using the deduction approach, the study seeks to provide a descriptive and explanatory contribution to theory. The study contributes to theory development by integrating the MTA and TOE frameworks as a means to understand technology adoption behaviors of organizations, in this case, retailers. This is also the first study that looks at an integrated approach of the Technology-Organization-Environment (TOE) framework and the MTA framework to understand the adoption and use of a payment method. South Africa is ranked amongst the top ten countries in the world on cryptocurrency adoption. There is, however, still a dearth of literature on the current state of adoption and usage of bitcoin as a payment method in South Africa. The study will contribute to the existing literature as bitcoin cryptocurrency is gaining popularity as an alternative payment method across the globe.

Keywords: cryptocurrency, bitcoin, payment methods, blockchain, appropriation, online retailers, TOE framework, disappropriation, non-appropriation

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Authors: Adhinarayanan Venkatasubramanian

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For design of high speed digital circuit wave pipeline is the best approach this can be operated at higher operating frequencies by adjusting clock periods and skews so as latch the o/p of combinational logic circuit at the stable period. In this paper, there are two methods are proposed in automation task one is BIST (Built in self test) and second method is Reconfigurable technique. For the above two approaches dedicated AND gate (multiplier) by applying wave pipeline technique. BIST approach is implemented by Xilinx Spartan-II device. In reconfigurable technique done by ASIC. From the results, wave pipeline circuits are faster than nonpipeline circuit and area, power dissipation are reduced by reconfigurable technique.

Keywords: SOC, wave-pipelining, FPGA, self-testing, reconfigurable, ASIC

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Authors: Bimal Raj Regmi, Cassandra Star

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Climate change adaptation is now the priority of many Least Developed Countries (LDCs). The country governments in LDCs are designing institutional and financing architecture to implement adaptation programmes. Nepal has introduced the concept of Local Adaptation Plan of Action (LAPA) to facilitate adaptation at the local level. However, there is lack of clarity and ambiguity on whether or not LAPA can be effective means to reach to the most vulnerable. This research paper aims to generate evidences to assess the applicability and significance of LAPA. The study used a case study approach and relied on data gathered from field studies carried out in Pyuthan and Nawalparasi district of Nepal. The findings show that LAPA has potentials to link the community based adaptation with national adaptation initiatives and thus act as middle range approach to adaptation planning. However, the current scale of LAPA and its approaches to planning and delivery are constraints by socio-economic and governance barriers. This research paper argue that the in order to address the constraints a more flexible and co-management approach to LAPA is needed.

Keywords: community based adaptation, local adaptation, co-management, climate change

Procedia PDF Downloads 243

Authors: Pimpisa Rattanadilok Na Phuket

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This research study aims to examine: 1) teaching competency of the native English-speaking teacher (NEST) 2) the English language learning achievement of Thai students, and 3) students’ perceptions toward their NEST. The population considered in this research was a group of 39 undergraduate students of the academic year 2013. The tools consisted of a questionnaire employed to measure the level of competency of NEST, pre-test and post-test used to examine the students’ achievement on English pronunciation, and an interview used to discover how participants perceived their NEST. The data was statistically analysed as percentage, mean, standard deviation and One-sample-t-test. In addition, the data collected by interviews was qualitatively analyzed. The research study found that the level of teaching competency of native speaker teachers of English was mostly low, the English pronunciation achievement of students had increased significantly at the level of 0.5, and the students’ perception toward NEST is combined. The students perceived their NEST as an English expertise, but they felt that NEST had not recognized students' linguistic difficulty and cultural differences.

Keywords: competency, native English-speaking teacher (NET), English teaching, learning achievement

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Authors: Chan Ka Lok Sobel

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The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

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Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

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Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability

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Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: May Newisar, Richard Kingston, Philip Black

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Heritage-led regeneration developments have been considered as one of the cornerstones of the economic and social revival of historic towns and cities in the UK. However, this approach has proved its deficiency within the development of Liverpool World Heritage site. This is due to the conflict between sustaining the tangible and intangible values as well as achieving the aimed economic developments. Accordingly, the development of such areas is influenced by a top-down approach which considers heritage as consumable experience and urban regeneration as the economic development for it. This neglects the heritage sites characteristics and values as well as the design criteria for public open spaces that overlap with the heritage sites. Currently, knowledge regarding the relationship between the physical built environment of the heritage sites including the intangible values and the design development of the public open spaces is limited. Public open spaces have been studied from different perspectives such as increasing walkability, a source of social cohesion, provide a good quality of life as well as understanding users’ perception. While heritage sites have been discussed heavily on how to maintain the physical environment, understanding the courses of threats and how to be protected. In addition to users’ experiences and motivations of visiting such areas. Furthermore, new approaches tried to overcome the gap such as the historic urban landscape approach. This approach is focusing on the entire human environment with all its tangible and intangible qualities. However, this research aims to understand the relationship between the heritage sites and public open spaces and how the overlap of the design and development of both could be used as a quality to enhance the heritage sites and improve users’ experience. A meaning-making approach will be used in order to understand and articulate how the development of Liverpool World Heritage site and its value could influence and shape the design of public open space Pier Head in order to attract a different level of tourists to be used as a tool for economic development. Consequently, this will help in bridging the gap between the planning and conservation areas’ policies through an understanding of how flexible is the system in order to adopt alternative approaches for the design and development strategies for those areas.

Keywords: historic urban landscape, environmental psychology, urban governance, identity

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Authors: Muzaffar Hussain

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Requests strategies are considered as a part of the speech acts, which are frequently used in everyday communication. Each language provides speech acts to the speakers; therefore, the selection of appropriate form seems more culture-specific rather than language. The present paper investigates the gender-based difference in the use of request strategies by native speakers of Urdu/Punjabi male and female who are learning English as a second language. The data for the present study were collected from 68 graduate students, who are learning English as an L2 in Pakistan. They were given an online close-ended questionnaire, based on Discourse Completion Test (DCT). After analyzing the data, it was found that the L1 male Urdu/Punjabi speakers were inclined to use more direct request strategies while the female Urdu/Punjabi speakers used indirect request strategies. This paper also found that in some situations female participants used more direct strategies than male participants. The present study concludes that the use of request strategies is influenced by culture, social status, and power distribution in a society.

Keywords: gender variation, request strategies, face-threatening, second language pragmatics, language competence

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

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The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: prediction model, sensitivity analysis, simulation method, USMLE

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Authors: Kamaludeen Samaila, Khashyaullah Abdulfattah, Fahimi Ahmad Bin Amir

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The study was conducted to examine the relationship between selected factors (performance expectancy, effort expectancy, social influence and facilitating condition) and students’ intention to use the learning management system (LMS), as well as investigating the factors predicting students’ intention to use the LMS. The study was specifically conducted at the Faculty of Educational Study of University Putra Malaysia. Questionnaires were distributed to 277 respondents using a random sampling technique. SPSS Version 22 was employed in analyzing the data; the findings of this study indicated that performance expectancy (r = .69, p < .01), effort expectancy (r=.60, p < .01), social influence (r = .61, p < .01), and facilitating condition (r=.42, p < .01), were significantly related to students’ intention to use the LMS. In addition, the result also revealed that performance expectancy (β = .436, p < .05), social influence (β=.232, p < .05), and effort expectancy (β = .193, p < .05) were strong predictors of students’ intention to use the LMS. The analysis further indicated that (R2) is 0.054 which means that 54% of variation in the dependent variable is explained by the entire predictor variables entered into the regression model. Understanding the factors that affect students’ intention to use the LMS could help the lecturers, LMS managers and university management to develop the policies that may attract students to use the LMS.

Keywords: LMS, postgraduate students, PutraBlas, students’ intention, UPM, UTAUT model

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Authors: Hamed Seddighi Khavidak

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Voluntary work has a lot of economic and social benefits for a country, but the economic value is ignored because it is voluntary. The aim of this study is reviewing Monetary Value of Voluntary Work methods and comparing opportunity cost method and replacement cost method both in theory and in practice. Beside monetary value, in this study, we discuss cost-benefit analysis of health and safety plan in the New Year that conducted by young volunteers of Red Crescent society of Iran. Method: We discussed eight methods for monetary value of voluntary work including: Alternative-Employment Wage Approach, Leisure-Adjusted OCA, Volunteer Judgment OCA, Replacement Wage Approach, Volunteer Judgment RWA, Supervisor Judgment RWA, Cost of Counterpart Goods and Services and Beneficiary Judgment. Also, for cost benefit analysis we drew on 'value audit and volunteer investment' (VIVA) technique that is used widely in voluntary organizations like international federation of Red Cross and Red Crescent societies. Findings: In this study, using replacement cost approach, voluntary work by 1034 youth volunteers was valued 938000000 Riyals and using Replacement Wage Approach it was valued 2268713232 Riyals. Moreover, Yazd Red Crescent Society spent 212800000 Riyals on food and other costs for these volunteers. Discussion and conclusion: In this study, using cost benefit analysis method that is Volunteer Investment and Value Audit (VIVA), VIVA rate showed that for every Riyal that the Red Crescent Society invested in the health and safety of New Year's travelers in its volunteer project, four Riyals returned, and using the wage replacement approach, 11 Riyals returned. Therefore, New Year's travelers health and safety project were successful and economically, it was worthwhile for the Red Crescent Society because the output was much bigger than the input costs.

Keywords: voluntary work, monetary value, youth, red crescent society

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

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Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

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Authors: Elham A. Alsadoon, Hamadah B. Alsadoon

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Educators try to design learning environments that are preferred by their students. With the wide-spread adoption of cell phones surpassing any other technology, educators should not fail to invest in the power of such technology. This study aimed to explore the current use of cell phones in education among Saudi students in Saudi universities and how students perceive such use. Data was collected from 237 students at King Saud University. Descriptive analysis was used to analyze the data. A T-test for independent groups was used to examine whether there was a significant difference between males and females in their perception of using cell phones in education. Findings suggested that students have a positive attitude toward the use of cell phones in education. The most accepted use was for sending notification to students, which has already been experienced through the Twasel system provided by King Saud University. This electronic system allows instructors to easily send any SMS or email to their students. The use of cell phone applications came in the second rank of using cell phones in education. Students have already experienced the benefits of having these applications handy wherever they go. On the other hand, they did not perceive using cell phones for assessment as practical educational usage. No gender difference was detected in terms of students’ perceptions toward using cell phones in education.

Keywords: cell phone, mobile learning, educational sciences, education

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Authors: Guillaume Morin-Duponchelle, Ahmed Nait Chabane, Benoit Zerr, Pierre Schoesetters

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Industrial inspection can be achieved through robotic systems, allowing visual and chemical servoing. A popular scheme for visual servo-controlled robotic is the image-based servoing sys-tems. In this paper, an approach of visual and chemical servoing of a hexapod robot using a visual and chemical Jacobian matrix are proposed. The basic idea behind the visual Jacobian matrix is modeling the differential relationship between the camera system and the robotic control system to detect and track accurately points of interest in confined environments. This approach allows the robot to easily detect and navigates to the QR code or seeks a gas source localization using surge cast algorithm. To track the QR code target, a visual servoing based on Jacobian matrix is used. For chemical servoing, three gas sensors are embedded on the hexapod. A Jacobian matrix applied to the gas concentration measurements allows estimating the direction of the main gas source. The effectiveness of the proposed scheme is first demonstrated on simulation. Finally, a hexapod prototype is designed and built and the experimental validation of the approach is presented and discussed.

Keywords: chemical servoing, hexapod robot, Jacobian matrix, visual servoing, navigation

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Authors: Twarakavi Venkata Suresh Kumar, Sailaja Kumar, B. Eswara Reddy

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In a world of tremendous technical developments, effective and efficient higher education has always been a major challenge. The rising number of educational institutions have made it mandatory for healthy competitions among the institutions. To evaluate the qualitative competence of these educations institutions in engineering and technology and related disciplines, an efficient assessment technique in internal and external quality has to be followed. To achieve this, the curriculum is to be developed into courses, and each course has to be presented in the form teaching lesson plan consisting of topics and session outcome known as Course Outcomes (COs), that easily map into different Programme Outcomes (POs). The major objective of these methodologies is to provide quality technical education to its students. Detailed clear weightage in CO-PO mapping helps in proper measurable COs and to devise the POs attainment is an important issue. This ensures in assisting the achievement of the POs with proper weightage to POs, and also improves the successive curriculum development. In this paper, we presented a methodology for mapping CO and PO considering the key elements supported by each PO. This approach is useful in evaluating the attainment of POs which is based on the attainment of COs using the existing data from students' marks taken from various test items. Such direct assessment tools are used to measure the degree to which each student has achieved each course learning outcome by the completion of the course. Hence, these results are also useful in measuring the PO attainment for improving the programme vision and mission.

Keywords: attainment, course outcomes, programme outcomes, educational institutions

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Sophia Hayes, Kenny L. Liang, Sahil Sharma, Austin Shema, Mahmoud Bader, Mohamed Elbarkouky

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Despite being one of the most significant economic contributors of the country, Canada’s construction industry is lagging behind other sectors when it comes to labor productivity improvements. The construction industry is very collaborative as a general contractor, will hire trade contractors to perform most of a project’s work; meaning low productivity from one contractor can have a domino effect on the shared success of a project. To address this issue and encourage trade contractors to improve their productivity tracking methods, an investigative study was done on the productivity views and tracking methods of various trade contractors. Additionally, an in-depth review was done on four standard tracking methods used in the construction industry: cost codes, benchmarking, the job productivity measurement (JPM) standard, and WorkFace Planning (WFP). The four tracking methods were used as a baseline in comparing the trade contractors’ responses, determining gaps within their current tracking methods, and for making improvement recommendations. 15 interviews were conducted with different trades to analyze how contractors value productivity. The results of these analyses indicated that there seem to be gaps within the construction industry when it comes to an understanding of the purpose and value in productivity tracking. The trade contractors also shared their current productivity tracking systems; which were then compared to the four standard tracking methods used in the construction industry. Gaps were identified in their various tracking methods and using a framework; recommendations were made based on the type of trade on how to improve how they track productivity.

Keywords: labor productivity, productivity tracking methods, trade contractors, construction

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Authors: Laxman Budhathoki, Lal Bahadur Shrestha, K. C. Laxman

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Hundreds of people are being lost their life by flood disaster in Nepal every year. Community-based disaster management committee has formed to formulate the disaster management plan including the component of EWS like EWS tower, rain gauge station, flood gauge station, culverts, boats, ropes, life jackets, a communication mechanism, emergency shelter, Spur, dykes, dam, evacuation route, emergency dry food management etc. Now EWS become a successful tool to decrease the human casualty from 13 to 0 every year in Rapti River of Chitwan District.

Keywords: disaster risk reduction, early warning system, flood, participatory approach

Procedia PDF Downloads 339

Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Ebrahim Alrashed, Yousef Rafique

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Mobile devices have drastically changed the way we do things on the move. They are being extremely relied on to perform tasks that are analogous to desktop computer capability. There has been a rapid increase of computational power on these devices; however, battery technology is still the bottleneck of evolution. The primary modern approach day approach to tackle this issue is offloading computation to the cloud, proving to be latency expensive and requiring high network bandwidth. In this paper, we explore efforts to perform barter-based mobile-to-mobile offloading. We present define a protocol and present an architecture to facilitate the development of such a system. We further highlight the deployment and security challenges.

Keywords: computational offloading, power conservation, cloud, sandboxing

Procedia PDF Downloads 375

Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Mirza Waseem Abbas, Syed Danish Raza

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For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

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Authors: Franklin Uakhemen Ajogbor

Abstract:

The issue of the English sentence has remained controversial from Traditional Grammar to modern linguistics. The English sentence occupies the highest rank in the hierarchy of grammatical units. Its consideration is therefore very necessary in learning English as a second language. Unfortunately, divergent views by grammarians on the concept of the English sentence have generated much controversy. There seems not to be a unanimous agreement on what actually constitute a sentence. Some schools of thought believe that a sentence must have a subject and a predicate while some believe that it should not. The types of sentence according to structure are also not devoid of controversy as the views of several linguists have not been properly harmonized. Findings have shown that serious effort and attention have not been paid by previous linguists to clear these ambiguities as it has a negative implication in the learning and teaching of English language. The variations on the concept of the English sentence have become particularly worrisome as a result of the widening patronage of English as a global language. The paper is therefore interested in the investigation of this controversy and suggesting a solution to the problem. In doing this, data was collected from students and scholars that show lack of uniformity in what a sentence is. Using the Systemic Functional Model as theoretical framework, the paper launches into the views held by these various schools of thought with the aim of reconciling these divergent views and also an attempt to open up further research on what actually constitute a sentence.

Keywords: traditional grammar, linguistics, controversy, sentence, grammatical units

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Authors: Zhang Xingnan, Huang Jingjia, Feng Yue, Burra Venkata Durga Kumar

Abstract:

This paper proposes a comprehensive approach to mitigate ROP (Return-Oriented Programming) attacks by combining internal operating system protection mechanisms and hardware-assisted techniques. Through extensive literature review, we identify the effectiveness of ASLR (Address Space Layout Randomization) and LBR (Last Branch Record) in preventing ROP attacks. We present a process involving buffer overflow detection, hardware-assisted ROP attack detection, and the use of Turing detection technology to monitor control flow behavior. We envision a specialized tool that views and analyzes the last branch record, compares control flow with a baseline, and outputs differences in natural language. This tool offers a graphical interface, facilitating the prevention and detection of ROP attacks. The proposed approach and tool provide practical solutions for enhancing software security.

Keywords: operating system, ROP attacks, returning-oriented programming attacks, ASLR, LBR, CFI, DEP, code randomization, hardware-assisted CFI

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Authors: Fernanda Mary R. G. Da Silva, Adriana C. F. Mozzambani, Marcelo F. Mello

Abstract:

Introduction: Sexual assault against children and adolescents is a public health problem with serious consequences on their quality of life, especially for those who develop post-traumatic stress disorder (PTSD). The broad literature in this research area points to greater losses in verbal learning, explicit memory, speed of information processing, attention and executive functioning in PTSD. Objective: To compare the neuropsychological functions of adolescents from 14 to 17 years of age, victims of sexual violence with PTSD with those of healthy controls. Methodology: Application of a neuropsychological battery composed of the following subtests: WASI vocabulary and matrix reasoning; Digit subtests (WISC-IV); verbal auditory learning test RAVLT; Spatial Span subtest of the WMS - III scale; abbreviated version of the Wisconsin test; concentrated attention test - D2; prospective memory subtest of the NEUPSILIN scale; five-digit test - FDT and the Stroop test (Trenerry version) in adolescents with a history of sexual violence in the previous six months, referred to the Prove (Violence Care and Research Program of the Federal University of São Paulo), for further treatment. Results: The results showed a deficit in the word coding process in the RAVLT test, with impairment in A3 (p = 0.004) and A4 (p = 0.016) measures, which compromises the verbal learning process (p = 0.010) and the verbal recognition memory (p = 0.012), seeming to present a worse performance in the acquisition of verbal information that depends on the support of the attentional system. A worse performance was found in list B (p = 0.047), a lower priming effect p = 0.026, that is, lower evocation index of the initial words presented and less perseveration (p = 0.002), repeated words. Therefore, there seems to be a failure in the creation of strategies that help the mnemonic process of retention of the verbal information necessary for learning. Sustained attention was found to be impaired, with greater loss of setting in the Wisconsin test (p = 0.023), a lower rate of correct responses in stage C of the Stroop test (p = 0.023) and, consequently, a higher index of erroneous responses in C of the Stroop test (p = 0.023), besides more type II errors in the D2 test (p = 0.008). A higher incidence of total errors was observed in the reading stage of the FDT test p = 0.002, which suggests fatigue in the execution of the task. Performance is compromised in executive functions in the cognitive flexibility ability, suggesting a higher index of total errors in the alternating step of the FDT test (p = 0.009), as well as a greater number of persevering errors in the Wisconsin test (p = 0.004). Conclusion: The data from this study suggest that sexual violence and PTSD cause significant impairment in the neuropsychological functions of adolescents, evidencing risk to quality of life in stages that are fundamental for the development of learning and cognition.

Keywords: adolescents, neuropsychological functions, PTSD, sexual violence

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Authors: Abid Kousay

Abstract:

Appeared and developed essentially in large companies and multinationals, Talent Management (TM) in Small and Medium-Sized Enterprises (SMEs) has remained an under-explored subject till today. Although the literature on TM in the Anglo-Saxon context is developing, it remains monopolized in non-European contexts, especially in France. Therefore, this article aims to address these shortcomings through contributing to TM issues by adopting a multilevel approach holding the goal of reaching a global holistic vision of interactions between various levels while applying TM. A qualitative research study carried out within 12 SMEs in France, built on the methodological perspective of grounded theory, will be used in order to go beyond description, to generate or discover a theory or even a unified theoretical explanation. Our theoretical contributions are the results of the grounded theory, the fruit of context considerations and the dynamic of the multilevel approach. We aim firstly to determine the perception of talent and TM in SMEs. Secondly, we formalize TM in SME through the empowerment of all 3 levels in the organization (individual, collective, and organizational). And we generate a multilevel dynamic system model, highlighting the institutionalization dimension in SMEs and the managerial conviction characterized by the domination of the leader’s role. Thirdly, this first study sheds light on the importance of rigorous implementation of TM in SMEs in France by directing CEO and HR and TM managers to focus on elements that upstream TM implementation and influence the system internally. Indeed, our systematic multilevel approach policy reminds them of the importance of strategic alignment while translating TM policy into strategies and practices in SMEs.

Keywords: French context, multilevel approach, talent management, , TM system

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