Search results for: online learning activities

Authors: Mariam Mojally, Randa Abdou, Wisal Bokhari, Sultan Sab, Mohammed Dawoud, Amjad Albohy

Abstract:

Secondary metabolites produced by endophytes are an excellent source of biologically active compounds. In our current study, we evaluated terezine E and 14-hydroxyterezine D for binding to the active site of histone deacetylase (PDB ID: 4CBT) and matrix metalloproteinase 9 (PDB ID: 4H3X) by molecular docking using AutoDock Vina software after having tested their cytotoxic activities on three cell lines (human ductal breast epithelial tumor cells (T47D)-HCC1937), human hepatocarcinoma cell line (HepG2)-HB8065), and human colorectal carcinoma cells (HCT-116)-TCP1006, purchased from ATCC, USA)). Additionally, their antimicrobial activities were investigated, and their minimum inhibitory concentration (MIC) values were determined against P. notatum and S. aureus by the broth microdilution method. Higher cytotoxicity was observed for terezine E against all tested cell lines compared to 14-hydroxyterezine D. Molecular docking results supported the high cytotoxicity of terezine E and showed higher binding affinity with 4CBT with an energy score of 9 kcal/mol. Terezine E showed higher antibacterial and antifungal activities than 14-hydroxyrerezine D: MIC values were 15.45 and 21.73 mg/mL against S. aureus and 8.61 and 11.54 mg/mL against P. notatum, respectively

Keywords: Terezine E, 14-Hydroxyterezine D, cytotoxicity, antimicrobial activity, molecular docking

Procedia PDF Downloads 76

Authors: Joshua Osondu

Abstract:

This research explores how Artificial Intelligence (AI) can be utilized as a policy response to address teaching and learning (TL) issues in education in Ghana. The dual (AI and human) instructor model is used as a theoretical framework to examine how AI can be employed to improve teaching and learning processes and to equip learners with the necessary skills in the emerging AI society. A qualitative research design was employed to assess the impact of AI on various TL issues, such as teacher workloads, a lack of qualified educators, low academic performance, unequal access to education and educational resources, a lack of participation in learning, and poor access and participation based on gender, place of origin, and disability. The study concludes that AI can be an effective policy response to TL issues in Ghana, as it has the potential to increase students’ participation in learning, increase access to quality education, reduce teacher workloads, and provide more personalized instruction. The findings of this study are significant for filling in the gaps in AI research in Ghana and other developing countries and for motivating the government and educational institutions to implement AI in TL, as this would ensure quality, access, and participation in education and help Ghana industrialize.

Keywords: artificial intelligence, teacher, learner, students, policy response

Procedia PDF Downloads 93

Authors: Gassem Alfaleh

Abstract:

In Strict liability, a person can be held liable for any harm resulting from certain actions or activities without any mistake. The liability is strict because a person can be liable when he or she commits any harm with or without his intention. The duty owed is the duty to avoid causing the plaintiff any harm. However, “strict liability is imposed at the International level by two types of treaties, namely those limited to giving internal effect to treaty provisions and those that impose responsibilities on states. The basic principle of strict liability is that there is a liability on the operator or the state (when the act concerned is attributable to the state) for damage inflicted without there being a need to prove unlawful behavior”. In international human rights law, strict liability can exist when a defendant is in legal jeopardy by virtue of an internationally wrongful act, without any accompanying intent or mental state. When the defendant engages in an abnormally dangerous activity against the environment, he will be held liable for any harm it causes, even if he was not at fault. The paper will focus on these activities under international human rights law. First, the paper will define important terms in the first section of the paper. Second, it will focus on state and non-state actors in terms of strict liability. Then, the paper will cover three major areas in which states should be liable for hazardous activities: (1) nuclear energy, (2) maritime pollution, (3) Space Law, and (4) other hazardous activities which damage the environment.

Keywords: human rights, law, legal, absolute

Procedia PDF Downloads 149

Authors: P. Daniels, T. Adonis, P. September-Brown, R. Comalie

Abstract:

The community engagement unit at the University of the Western Cape was tasked with establishing a community engagement database. The database would store information of all community engagement projects related to the university. The wealth of knowledge obtained from the various disciplines would be used to facilitate interdisciplinary collaboration within the university, as well as facilitating community university partnership opportunities. The purpose of this qualitative study was to explore electronic data collection through the development of a database. Two types of electronic data collection platforms were used, namely online questionnaire and email. The semi structured questionnaire was used to collect data related to community engagement projects from different faculties and departments at the university. There are many benefits for using an electronic data collection platform, such as reduction of costs and time, ease in reaching large numbers of potential respondents, and the possibility of providing anonymity to participants. Despite all the advantages of using the electronic platform, there were as many challenges, as depicted in our findings. The findings suggest that certain barriers existed by using an electronic platform for data collection, even though it was in an academic environment, where knowledge and resources were in abundance. One of the challenges experienced in this process was the lack of dissemination of information via email to staff within faculties. The actual online software used for the questionnaire had its own limitations, such as only being able to access the questionnaire from the same electronic device. In a few cases, academics only completed the questionnaire after a telephonic prompt or face to face meeting about "Is higher education in South Africa ready to embrace electronic platform in data collection?"

Keywords: community engagement, database, data collection, electronic platform, electronic tools, knowledge sharing, university

Procedia PDF Downloads 265

Authors: Christine K. Ormsbee, Jeremy S. Robinson

Abstract:

Teacher quality is important for United States universities. It impacts student achievement, program and degree progress, and even retention. While course instructors are still the primary designers and deliverers of instruction in U.S. higher education classrooms, students have become better and more vocal consumers of instruction. They are capable of identifying what instructors do that facilitates their learning or, conversely, what instructors do that makes learning more difficult. Instructors can use students as resources as they design and implement their courses. Students have become more aware of their own learning preferences and processes and can articulate those. While it is not necessarily possible or likely that an instructor can address the widely varying differences in learning preferences represented by a large class of students, it is possible for them to employ general instructional supports that help students understand clearly the instructor's study expectations, identify critical content, efficiently commit content to memory, and develop new skills. Those learning supports include reading guides, test study guides, and other instructor-developed tasks that organize learning for students, hold them accountable for the content, and prepare them to use that material in simulated and real situations. When U.S. university teaching and learning support staff work with instructors to help them identify areas of their teaching to improve, a key part of that assistance includes talking to the instructor member's students. Students are asked to explain what the instructor does that helps them learn, what the instructor does that impedes their learning, and what they wish the instructor would do. Not surprisingly, students are very specific in what they see as helpful learning supports for them. Moreover, they also identify impediments to their success, viewing those as the instructor creating unnecessary barriers to learning. A qualitative survey was developed to provide undergraduate students the opportunity to identify instructor behaviors and/or practices that they thought helped students learn and those behaviors and practices that were perceived as hindrances to student success. That information is used to help instructors implement more student-focused learning supports that facilitate student achievement. In this session, data shared from the survey will focus on supportive instructor behaviors identified by undergraduate students in an institution located in the southwest United States and those behaviors that students perceive as creating unnecessary barriers to their academic success.

Keywords: effective teaching, pedagogy, student engagement, instructional design

Procedia PDF Downloads 89

Authors: Muhammad Fajar Suardi, Fathimatufzzahra, Dela Isnaini Sendra

Abstract:

Learning is an activity that has been used to do, especially for a student or academics. But a handful of people have not been using and maximizing their brains work and some also do not know a good brain work time in capturing the lessons, so that knowledge is absorbed is also less than the maximum. Indonesia Memory Sports Council (IMSC) is an institution which is engaged in the performance of the brain and the development of effective learning methods by using several techniques that can be used in considering the lessons and knowledge to grasp well, including: loci method, substitution method, and chain method. This study aims to determine the techniques and benefits of using the method given in learning and memorization by applying memory techniques taught by Indonesia Memory Sports Council (IMSC) to students and the difference if not using this method. This research uses quantitative research with survey method addressed to students of Indonesian Memory Sports Council (IMSC). The results of this study indicate that learn, understand and remember the lesson using the techniques of memory which is taught in Indonesia Memory Sport Council is very effective and faster to absorb the lesson than learning without using the techniques of memory, and this affects the academic achievement of students in each educational institution.

Keywords: chain method, Indonesia memory sports council, loci method, substitution method

Procedia PDF Downloads 291

Authors: Kimberley Kennedy

Abstract:

The major findings of this study discuss the importance of understanding and applying Systems thinking concepts to ensure an effective Project-Based Learning environment. A pilot project study of a major pedagogical change was conducted over a five year period with the goal to give students real world, hands-on learning experiences and the opportunity to apply what they had learned over the past two years of their business program. The first two weeks of the fifteen week semester utilized teaching methods of lectures, guest speakers and design thinking workshops to prepare students for the project work. For the remaining thirteen weeks of the semester, the students worked with actual business owners and clients on projects and challenges. The first three years of the five year study focused on student feedback to ensure a quality learning experience and continuous improvement process was developed. The final two years of the study, examined the conceptual understanding and perception of learning and teaching by faculty using Project-Based Learning pedagogy as compared to lectures and more traditional teaching methods was performed. Relevant literature was reviewed and data collected from program faculty participants who completed pre-and post-semester interviews and surveys over a two year period. Systems thinking concepts were applied to better understand the challenges for faculty using Project-Based Learning pedagogy as compared to more traditional teaching methods. Factors such as instructor and student fatigue, motivation, quality of work and enthusiasm were explored to better understand how to provide faculty with effective support and resources when using Project-Based Learning pedagogy as the main teaching method. This study provides value by presenting generalizable, foundational knowledge by offering suggestions for practical solutions to assure student and teacher engagement in Project-Based Learning courses.

Keywords: continuous improvement, project-based learning, systems thinking, teacher engagement

Procedia PDF Downloads 122

Authors: Karen V. Lee

Abstract:

The background and significance of this study involves research about a music teacher discovering how language development and learning can help her overcome harmful and lasting consequences from sexual violence. Education about intervention resources from language development that helps her cope with consequences influencing her career as teacher. Basic methodology involves the qualitative method of research as theoretical framework where the author is drawn into a deep storied reflection about political issues surrounding teachers who need to overcome social, psychological, and health risk behaviors from violence. Sub-themes involve available education from learning resources to ensure teachers receive social, emotional, physical, spiritual, and intervention resources that evoke visceral, emotional responses from the audience. Major findings share how language development and learning provide helpful resources to victims of violence. It is hoped the research dramatizes an episodic yet incomplete story that highlights the circumstances surrounding the protagonist’s life. In conclusion, the research has a reflexive storied framework that embraces harmful and lasting consequences from sexual violence. The reflexive story of the sensory experience critically seeks verisimilitude by evoking lifelike and believable feelings from others. Thus, the scholarly importance of using language development and learning for intervention resources can provide transformative aspects that contribute to social change. Overall, the circumstance surrounding the story about sexual violence is not uncommon in society. Language development and learning supports the moral mission to help teachers overcome sexual violence that socially impacts their professional lives as victims.

Keywords: intervention, language development and learning, sexual violence, story

Procedia PDF Downloads 334

Authors: Elena Puica

Abstract:

This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

Procedia PDF Downloads 117

Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

Abstract:

In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

Procedia PDF Downloads 293

Authors: Nooraisah Katmon, Hartini Jaafar, Hazianti Abdul Halim, Jessnor Elmy Mat Jizat

Abstract:

Our study empirically examines the effect of student activities on Facebook and religion on academic performance. We extend prior research in this area in a number of ways. First, given the paucity of the research in this area particularly from the Asian context, we provide the evidence from developing country like Malaysia. Second, our sample drawn from Sultan Idris Education University in Malaysia, where graduates from these universities are unique since they are expected to be able to work in both education and industry environment, and presumed to play significant roles in shaping the development of future student’s intellectual at the Malaysian secondary school and Malaysian economy in general. Third, we control for religiosity aspect when examining the association between Facebook and academic performance, something that has been predominantly neglected by the prior studies. Fourth, unlike prior studies that circulating around the Christian sphere in measuring religiosity, we provide evidence from the Islamic perspective where the act of worships and practices are much more comprehensive rather than the Christian counterparts. Fifth, we examine whether Facebook activities and religiosity are complementary or substitutive each other in improving student’s academic performance. Our sample comprise of 60 undergraduates. Our result exhibit that students with high number of friends on facebook and frequent engagement on facebook activities, such as sharing links, send message, posting photo, tagging video as well as spending long hours on facebook generally are associated with lower academic performance. Our results also reported that student’s engagement in religious activities promotes better academic performance. When we examine the potential interaction effect between facebook and religiosity, our result revealed that religiosity is effective in reducing student’s interest on facebook, hence lead to better academic achievement. In other words, religious student will be less interested in joining activities on facebook and make them more perform than their counterparts. Our findings from this study should be able to assist the university management in shaping university policies and curriculum to regulate and manage student’s activities in order to enhance overall student’s quality. Moreover, the findings from this study are also of use to the policy maker such as Malaysian Communication and Multimedia Commissions to regulate the policy on the student’s access and activities on facebook.

Keywords: facebook, religiosity, academic performance, effect of student activities

Procedia PDF Downloads 305

Authors: Amy M. Kwon

Abstract:

Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

Procedia PDF Downloads 36

Authors: Huynh Tan Hoi

Abstract:

Considered as one of the hardest languages in the world, Japanese is still the language that many young people choose to learn. Today, with the development of technology, learning foreign languages in general and Japanese language, in particular, is not an impossible barrier. Learning materials are not only from paper books, songs but also through software programs of smartphones or computers. Especially, students who begin to explore effective skills to study this language need to access modern technologies to improve their learning much better. When using the software, some students may feel embarrassed and challenged, but everything would go smoothly after a few days. After completing the course, students will get more knowledge, achieve a higher knowledge such as N2 or N1 Japanese Language Proficiency Test Certificate. In this research paper, 35 students who are studying at Ho Chi Minh City FPT University were asked to complete the questionnaire at the beginning of July up to August of 2018. Through this research, we realize that with the guidance of lecturers, the necessity of using modern software and some effective methods are indispensable in term of improving quality of teaching and learning process.

Keywords: higher knowledge, Japanese, methods, software, students

Procedia PDF Downloads 228

Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

Abstract:

This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

Procedia PDF Downloads 79

Authors: Sabli, Eddy Rismunandar, Akhirudin, Nana Halim, Zulfikar, Nining Dwirosanti, Wila Ningsih, Pipih Siti Sofiah, Danik Dania Asadayanti, Dewi Eka Arini Algozi, Gita Mahardika Pamuji, Ajun, Mangasa Aritonang, Nanang Rukmana, Arief Rachman Wonodhipo, Victor Imanuel Nahumury, Lili Husada, Wawan Saepul Irwan, Al Mukhlas Fikri

Abstract:

Covid-19 pandemic has widely impacted the lives. An adaptive strategy must be quickly formulated to maintain the quality of education, especially by vocational school which technical skill competencies are highly needed. This study aimed to evaluate the effectiveness of e-training on the attitude and skill competencies of vocational high school teachers in Indonesia. A total of 720 Indonesian vocational high school teachers with various programs, including hospitality, administration, online business and marketing, culinary arts, fashion, cashier, tourism, haircut, and accounting participated e-training for a month. The training used electronic learning management system to provide materials (modules, presentation slides, and tutorial videos), tasks, and evaluations. Tutorial class was carried out by video conference meeting. Attitude and skill competencies were evaluated before and after the training. Meanwhile, the teachers also gave satisfactory feedback on the quality of the organizer and tutors. Data analysis used paired sample t-test and Anova with Tukey’s post hoc test. The results showed that e-training significantly increased the score of attitude and skill competencies of the teachers (p <0,05). Moreover, the remarkable increase was found among hospitality (57,5%), cashier (50,1%), and online business and marketing (48,7%) teachers. However, the effect among fashion, tourism and haircut teachers was less obvious. In addition, the satisfactory score on the quality of the organizer and tutors were 88,9 (very good), and 93,5 (excellence), respectively. The study concludes that a well-organized e-training could increase the attitude and skill competencies of Indonesian vocational high school teachers during Covid-19 pandemic.

Keywords: E-training, skill, teacher, vocational high school

Procedia PDF Downloads 152

Authors: Yi-De Liu

Abstract:

The aim of this paper is to discuss how the construct of networking and social capital can be used to understand the effect events can have on the cultural sector. Based on case study, this research sought the views of those working in the cultural sector on Liverpool’s year as the European Capital of Culture (ECOC). Methodologically, this study involves literature review to prompt theoretical sensitivity, the collection of primary data via online survey (n= 42) and follow-up telephone interviews (n= 8) to explore the emerging findings in more detail. The findings point to a number of ways in which the ECOC constitutes a boost for networking and its effects on city’s cultural sector, including organisational learning, aspiration and leadership. The contributions of this study are two-fold: (1) Evaluating the long-term effects on network formation in the cultural sector following major event; (2) conceptualising the impact assessment of organisational social capital for future ECOC or similar events.

Keywords: network, social capital, cultural impact, european capital of culture

Procedia PDF Downloads 205

Authors: Jung-En Kuan, Whei-Fen Wu

Abstract:

In this study, a symbiotic bacteria from yellow mealworm's (Tenebrio molitor) mid-gut was isolated with characteristics of growth on minimal-tributyrin medium. After a PCR-amplification of its 16s rDNA, the resultant nucleotide sequences were then analyzed by schemes of the phylogeny trees. Accordingly, it was designated as Pseudomonas nitroreducens D-01. Next, by searching the lipolytic enzymes in its protein data bank, one of those potential lipolytic α/β hydrolases was identified, again using PCR-amplification and nucleotide-sequencing methods. To construct an expression of this lipolytic gene in plasmids, the target-gene primers were then designed, carrying the C-terminal his-tag sequences. Using the vector pET21a, a recombinant lipolytic hydrolase D gene with his-tag nucleotides was successfully cloned into it, of which the lipolytic D gene is under a control of the T7 promoter. After transformation of the resultant plasmids into Eescherichia coli BL21 (DE3), an IPTG inducer was used for the induction of the recombinant proteins. The protein products were then purified by metal-ion affinity column, and the purified proteins were found capable of forming a clear zone on tributyrin agar plate. Shortly, its enzyme activities were determined by degradation of p-nitrophenyl ester(s), and the substantial yellow end-product, p-nitrophenol, was measured at O.D.405 nm. Specifically, this lipolytic enzyme efficiently targets p-nitrophenyl butyrate. As well, it shows the most reactive activities at 40°C, pH 8 in potassium phosphate buffer. In thermal stability assays, the activities of this enzyme dramatically drop when the temperature is above 50°C. In metal ion assays, MgCl₂ and NH₄Cl induce the enzyme activities while MnSO₄, NiSO₄, CaCl₂, ZnSO₄, CoCl₂, CuSO₄, FeSO₄, and FeCl₃ reduce its activities. Besides, NaCl has no effects on its enzyme activities. Most organic solvents decrease the activities of this enzyme, such as hexane, methanol, ethanol, acetone, isopropanol, chloroform, and ethyl acetate. However, its enzyme activities increase when DMSO exists. All the surfactants like Triton X-100, Tween 80, Tween 20, and Brij35 decrease its lipolytic activities. Using Lineweaver-Burk double reciprocal methods, the function of the enzyme kinetics were determined such as Km = 0.488 (mM), Vmax = 0.0644 (mM/min), and kcat = 3.01x10³ (s⁻¹), as well the total efficiency of kcat/Km is 6.17 x10³ (mM⁻¹/s⁻¹). Afterwards, based on the phylogenetic analyses, this lipolytic protein is classified to type IV lipase by its homologous conserved region in this lipase family.

Keywords: enzyme, esterase, lipotic hydrolase, type IV

Procedia PDF Downloads 134

Authors: Abdelghani Boudiaf

Abstract:

The profusion of studies relating to the concept of organizational learning shows the importance that has been given to this concept in the management sciences. A few years ago, companies leaned towards ISO 9001 certification; this requires the implementation of the quality management system (QMS). In order for this objective to be achieved, companies must have a set of skills, which pushes them to develop learning through continuous training. The results of empirical research have shown that implementation of the QMS in the company promotes the development of learning. It should also be noted that several types of learning are developed in this sense. Given the nature of skills development is normative in the context of the quality demarche, companies are obliged to qualify and improve the skills of their human resources. Continuous training is the keystone to develop the necessary learning. To carry out continuous training, companies need to be able to identify their real needs by developing training plans based on well-defined engineering. The training process goes obviously through several stages. Initially, training has a general aspect, that is to say, it focuses on topics and actions of a general nature. Subsequently, this is done in a more targeted and more precise way to accompany the evolution of the QMS and also to make the changes decided each time (change of working method, change of practices, change of objectives, change of mentality, etc.). To answer our problematic we opted for the method of qualitative research. It should be noted that the case study method crosses several data collection techniques to explain and understand a phenomenon. Three cases of companies were studied as part of this research work using different data collection techniques related to this method.

Keywords: changing mentalities, continuing training, organizational learning, quality management system, skills development

Procedia PDF Downloads 111

Authors: Y. L. Chang, Y. H. Huang

Abstract:

This study designed a mobile guide system that integrates the design principles of guidance and interpretation with augmented reality (AR) as an auxiliary tool for National Taiwan Science Education Center guidance and explored the learning performance of participants who were divided into two visiting groups: AR-guided mode and non-guided mode (without carrying any auxiliary devices). The study included 96 college students as participants and employed a quasi-experimental research design. This study evaluated the learning performance of education center students aided with different guided modes, including their flow experience, activity involvement, learning effects, as well as their attitude and acceptance of using the guide systems. The results showed that (a) the AR guide promoted visitors’ flow experience; (b) the AR-guidance activity involvement and flow experience having a significant positive effect; (c) most of the visitors of mobile guide system with AR elicited a positive response and acceptance attitude. These results confirm the necessity of human–computer–context interaction. Future research can continue exploring the advantages of enhanced learning effectiveness, activity involvement, and flow experience through application of the results of this study.

Keywords: augmented reality, mobile guide system, informal learning, flow experience, activity involvement

Procedia PDF Downloads 232

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

Abstract:

Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

Procedia PDF Downloads 39

Authors: Julius Onyancha, Valentina Plekhanova

Abstract:

One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

Procedia PDF Downloads 265

Authors: Juan Du

Abstract:

Climate change is one of the most crucial issues of this era, with contentious debates on it among scholars. But there are sparse studies on climate change discourse in China. Including China in the study of climate change is essential for a sociological understanding of climate change. China -- as a developing country and an essential player in tackling climate change -- offers an ideal case for studying climate change for scholars moving beyond developed countries and enriching their understandings of climate change by including diverse social settings. This project contrasts the macro- and micro-level understandings of climate change in China, which helps scholars move beyond a focus on climate skepticism and denialism and enriches sociology of climate change knowledge. The macro-level understanding of climate change is obtained by analyzing over 4,000 newspaper articles from various official outlets in China. State-controlled newspapers play an essential role in transmitting essential and high-quality information and promoting broader public understanding of climate change and its anthropogenic nature. Thus, newspaper articles can be seen as tools employed by governments to mobilize the public in terms of supporting the development of a strategy shift from economy-growth to an ecological civilization. However, media is just one of the significant factors influencing an individual’s climate change concern. Extreme weather events, access to accurate scientific information, elite cues, and movement/countermovement advocacy influence an individual’s perceptions of climate change. Hence, there are differences in the ways that both newspaper articles and the public frame the issues. The online forum is an informative channel for scholars to understand the public’s opinion. The micro-level data comes from Zhihu, which is China’s equivalence of Quora. Users can propose, answer, and comment on questions. This project analyzes the questions related to climate change which have over 20 answers. By open-coding both the macro- and micro-level data, this project will depict the differences between ideology as presented in government-controlled newspapers and how people talk and act with respect to climate change in cyberspace, which may provide an idea about any existing disconnect in public behavior and their willingness to change daily activities to facilitate a greener society. The contemporary Yellow Vest protests in France illustrate that the large gap between governmental policies of climate change mitigation and the public’s understanding may lead to social movement activity and social instability. Effective environmental policy is impossible without the public’s support. Finding existing gaps in understanding may help policy-makers develop effective ways of framing climate change and obtain more supporters of climate change related policies. Overall, this qualitative project provides answers to the following research questions: 1) How do different state-controlled newspapers transmit their ideology on climate change to the public and in what ways? 2) How do individuals frame climate change online? 3) What are the differences between newspapers’ framing and individual’s framing?

Keywords: climate change, China, framing theory, media, public’s climate change concern

Procedia PDF Downloads 133

Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

Abstract:

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

Procedia PDF Downloads 154

Authors: Degale Desta, Cheng Jian

Abstract:

The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

Procedia PDF Downloads 140

Authors: Azaze-Azizi Abdul Adis, Hyung Jun Kim, Mohamad Rizwan Abdul Majid, Zaiton Osman, Izyanti Awang Razli

Abstract:

The increase of online advertising, specifically advergame has become a popular method of strengthening consumer brand recognition by inserting attractive characters and enhancing entertainment value. There have been several remarkable studies on spokes-characters in advertising effectiveness. However, few studies have examined the link between character presence and consumers' brand recall and attitude in advergame. Moreover, how the entertainment value of an advergame influences brand recall and brand attitude and the mediating role of brand recall in influencing character presence and entertainment on brand attitude are still lacking in the advergaming literature. An online survey was conducted with 366 Malaysian gamers. Using structural equation modeling, the results showed that character presence had no influence but entertainment value had a positive influence on brand recall and brand attitude. This study confirmed the role of brand recall as a mediator of the effect of between entertainment and brand attitude in advergame.

Keywords: character presence, entertainment, brand recall, brand attitude, advergame

Procedia PDF Downloads 538

Authors: Diriba Gemechu, Lamessa Abebe

Abstract:

The aim of this study was to examine the effect of cooperative learning method on student’s academic achievement and on the achievement level over a usual method in teaching different topics of mathematics. The study also examines the perceptions of students towards cooperative learning. Cooperative learning is the instructional strategy in which pairs or small groups of students with different levels of ability work together to accomplish a shared goal. The aim of this cooperation is for students to maximize their own and each other learning, with members striving for joint benefit. The teacher’s role changes from wise on the wise to guide on the side. Cooperative learning due to its influential aspects is the most prevalent teaching-learning technique in the modern world. Therefore the study was conducted in order to examine the effect of cooperative learning on the academic achievement of grade 9 students in Mathematics in case of Mettu secondary school. Two sample sections are randomly selected by which one section served randomly as an experimental and the other as a comparison group. Data gathering instruments are achievement tests and questionnaires. A treatment of STAD method of cooperative learning was provided to the experimental group while the usual method is used in the comparison group. The experiment lasted for one semester. To determine the effect of cooperative learning on the student’s academic achievement, the significance of difference between the scores of groups at 0.05 levels was tested by applying t test. The effect size was calculated to see the strength of the treatment. The student’s perceptions about the method were tested by percentiles of the questionnaires. During data analysis, each group was divided into high and low achievers on basis of their previous Mathematics result. Data analysis revealed that both the experimental and comparison groups were almost equal in Mathematics at the beginning of the experiment. The experimental group out scored significantly than comparison group on posttest. Additionally, the comparison of mean posttest scores of high achievers indicates significant difference between the two groups. The same is true for low achiever students of both groups on posttest. Hence, the result of the study indicates the effectiveness of the method for Mathematics topics as compared to usual method of teaching.

Keywords: academic achievement, comparison group, cooperative learning, experimental group

Procedia PDF Downloads 249

Authors: Kazumoto Tanaka

Abstract:

It is well known that sport skill learning is facilitated by video observation of players’ actions in sports. The optimal viewpoint for the observation of actions depends on sport scenes. On the other hand, it is impossible to change viewpoint for the observation in general, because most videos are filmed from fixed points. The study has tackled the problem and focused on karate match as a first step. The study developed a method for observing karate player’s actions from any point of view by using 3D-CG model (i.e. virtual player) obtained from video images, and verified the effectiveness of the method on karate match.

Keywords: computer graphics, karate training, learning by observation, motion capture, virtual player

Procedia PDF Downloads 276

Authors: Abdulrahman M. Alhowikan, Nadra E. Elamin, Sarah S. Aldayel, Sara A. AlSiddiqi, Fai S. Alrowais, Laila Y. Al-Ayadhi

Abstract:

Background: A growing body of research has suggested that physical activities (PA) have important implications for improving the performance of ASD children. They revealed that the physiological, cognitive, psychological, and behavioral functioning had improved after performing some physical activities. Methods: We compared the sedentary behavior and physical activities between children with autism spectrum disorder (n=21) and age-matched control group (n=30), using the ActiGraph GT3X+ for the assessments. Results: Our results revealed that the total time spent in sedentary activity and the total sedentary activity counts were highly significant in the control group compared to the ASD group (p < 0.001, p=0.001, respectively). ASD spent a significantly longer time than the controls engaging on vigorous physical activity (VPA) (p=0.017). The results also indicated that there were no significant differences between both groups for the total counts and time spent in light physical activity (LPA) and moderate physical activity (MPA). Conclusion: The finding highlights the importance of physical activity intervention for ASD children, using accurate and precise measurement tools to record all activities.

Keywords: Autism spectrum disorders, motor skills, physical activity, ActiGraph GT3X+, moderate-to vigorous-intensity physical activity

Procedia PDF Downloads 140

Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

Abstract:

In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

Procedia PDF Downloads 83

Authors: Amaal Ali Al-Gamde

Abstract:

The Syrian revolution is a major issue in the Middle East, which draws in world powers and receives a great focus in international mass media since 2011. The heavy global reliance on cyber news and digital sources plays a key role in conveying a sense of bias to a wide range of online readers. Thus, based on the assumption that media discourse possesses ideological implications, this study investigates the representation of Syrian revolution in online media. The paper explores the discursive constructions of anti and pro-government powers in Syrian revolution in 1000,000-word corpus of Fars online reports (an Iranian news agency), issued between 2013 and 2015. Taking a corpus assisted discourse analysis approach, the analysis investigates three types of lexicosemantic relations, the semantic macrostructures within which the two social actors are framed, the lexical collocations characterizing the news discourse and the discourse prosodies they tell about the two sides of the conflict. The study utilizes computer-based approaches, sketch engine and AntConc software to minimize the bias of the subjective analysis. The analysis moves from the insights of lexical frequencies and keyness scores to examine themes and the collocational patterns. The findings reveal the Fars agency’s ideological mode of representations in reporting events of Syrian revolution in two ways. The first is by stereotyping the opposition groups under the umbrella of terrorism, using words such as (law breakers, foreign-backed groups, militant groups, terrorists) to legitimize the atrocities of security forces against protesters and enhance horror among civilians. The second is through emphasizing the power of the government and depicting it as the defender of the Arab land by foregrounding the discourse of international conspiracy against Syria. The paper concludes discussing the potential importance of triangulating corpus linguistic tools with critical discourse analysis to elucidate more about discourses and reality.

Keywords: discourse prosody, ideology, keyness, semantic macrostructure

Procedia PDF Downloads 136