Search results for: online algorithm

Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: social platforms, buyer behavior, consumer behavior, digital era

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Irni Rahmayani Johan, Ira Kamelia

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One of the impacts of the rapid advancement of technology is the rise of digital finance, including peer-to-peer lending (P2P). P2P lending has been widely marketed, including an online student loan that used the P2P platform. This study aims to analyze the effect of financial literacy, perception of debt, and perception of risk toward student willingness to use the online student loan (P2P lending). Using a cross-sectional study design, in collecting the data this study employed an online survey method, with a total sample of 280 undergraduate students of IPB university, Indonesia. This study found that financial literacy, perception of debt, perception of risk, and interest in using online student loans are categorized as low level. While the level of knowledge is found to be the lowest, the first-year students showed a higher level in terms of willingness to use the online student loan. In addition, the second year students recorded a positive perception toward debt. This study showed that level of study, attendance in personal finance course, and student’ GPA is positively related to financial knowledge. While debt perception is negatively related to financial attitudes. Similarly, the negative relationship is found between risk perception and the willingness to use the online student loan. The determinant factor of the willingness to use online student loans is the level of study, debt perception, financial risk perception, and time risk perception. Students with a higher level of study are more likely to have a lower interest in using online student loans. Moreover, students who perceived debt as a financial stimulator, as well as those with higher level of financial risk perceptions and time risk perceptions, tend to show more interest to use the loan.

Keywords: financial literacy, willingness to use, online student loan, perception of risk, perception of debt

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Authors: Samar Alharbi, Yota Dimitriadi

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The literature on educational technology in Saudi Arabia reveals female learners’ unwillingness to study fully online courses in higher education despite the fact that Saudi universities have offered a variety of online degree programmes to undergraduate students in many regions of the country. The root causes keeping female students from successfully learning in online environments are limited social interaction, lack of motivation and difficulty with the use of e-learning platforms. E-immediacy remains an important method of online teaching to enhance students’ interaction and support their online learning. This study explored Saudi female students’ perceptions, as well as the experiences of lecturers’ immediacy behaviours in online environments, who participate in fully online courses using Blackboard at a Saudi university. Data were collected through interviews with focus groups. The three focus groups included five to seven students each. The female participants were asked about lecturers’ e-immediacy behaviours and which e-immediacy behaviours were important for an effective learning environment. A thematic analysis of the data revealed three main themes: the encouragement of student interaction, the incorporation of social media and addressing the needs of students. These findings provide lecturers with insights into instructional designs and strategies that can be adopted in using e-immediacy in effective ways, thus improving female learners’ interactions as well as their online learning experiences.

Keywords: e-learning, female students, higher education, immediacy

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Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.

Keywords: association rules, FP-growth, multiple minimum supports, Weka tool

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Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

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Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.

Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator

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Authors: Amin Sedighfar, M. R. Moniri

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Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery

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Authors: Ehi E. Aimiuwu

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As of 2017, many researchers in educational journals are still wondering if students are effectively and efficiently engaged in active learning in the online learning environment. The goal of this qualitative single case study and narrative research is to explore if students are actively engaged in their online learning. Seven online students in the United States from LinkedIn and residencies were interviewed for this study. Eleven online learning techniques from research were used as a framework.  Data collection tools were used for the study that included a digital audiotape, observation sheet, interview protocol, transcription, and NVivo 12 Plus qualitative software.  Data analysis process, member checking, and key themes were used to reach saturation. About 85.7% of students preferred individual grading. About 71.4% of students valued professor’s interacting 2-3 times weekly, participating through posts and responses, having good internet access, and using email.  Also, about 57.1% said students log in 2-3 times weekly to daily, professor’s social presence helps, regular punctuality in work submission, and prefer assessments style of research, essay, and case study.  About 42.9% appreciated syllabus usefulness and professor’s expertise.

Keywords: class facilitation, course management, online teaching, online education, student engagement

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Authors: Ling-Lang Huang, Yih-Jer Wu

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Empathy is crucial for a patient-physician relationship and medical professionalism. Internet activity, gaming, or even addiction, have been more and more common among medical students. However, there’s been no report showing whether internet behavior has a substantial impact on empathy in medical students to our best knowledge. All year-2 medical students taking the optional course 'Narrative, Comprehension, and Communication' were enrolled. Internet behaviors are divided into two groups, 'internet users without online gaming (IU)' and 'internet users with online gaming (IG)', each group was further divided into 3 groups according to their average online retention time each day (< 2, 2 - 6, > 6 hours). Empathy was evaluated by the scores of the reports and humanities reflection after watching indicated movies, and by self-measured empathy questionnaire. All students taking the year-2 optional course 'Narrative, Comprehension, and Communication' were enrolled. As compared with students in the IU group, those in the IG group had significantly lower scores for the reports (81.3 ± 3.7 vs. 86.4 ± 5.1, P = 0.014). If further dividing the students into 5 groups (IU < 2, IU 2-6, IG < 2, IG 2 - 6, and IG > 6 hours), the scores were significantly and negatively correlated to online gaming with longer hours (r = -0.556, P = 0.006). However, there was no significant difference between IU and IG groups (33.0 ± 5.4 vs. 34.8 ± 3.2, P = n.s.), in terms of scores in the self-measured empathy questionnaire, neither was there any significant trend of scores along with longer online hours across the 5 groups (r = -0.164, P = n.s.). To date, there has been no evidence showing whether different internet behaviors (with or without online gaming) have distinct impacts on empathy. Although all of the medical students had a similarly good self-perception for empathy, our data suggested that online gaming did have a negative impact on their actual expression of empathy. Our observation has brought up an important issue for pondering: May IT- or gaming-assisted medical learning actually harm students’ empathy? In conclusion, this data suggests that long hours of online gaming harms expression of empathy, though all medics think themselves a person of high empathy.

Keywords: empathy. Internet, medical students, online gaming

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Authors: Nhat-To Huynh, Chen-Fu Chien

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Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.

Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing

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Authors: Raja Arslan Ahmad Khan

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Audience feedback and data play an increasingly crucial role, particularly in the digital age. The advent of digital media and the digitalization of news have given rise to novel forms of audience feedback, markedly different from traditional channels. The engagement of online audiences challenges the conventional role of journalists, introducing a dynamic where audiences can wield both direct and indirect influence. This struggle between the audience and journalists is evident in their contributions and interactions. Media professionals are grappling with challenges such as derogatory remarks, hate speech, online harassment, audience hostility, and attacks from online audiences. The influence of online audiences extends to shaping journalists' daily routines and work practices. Consequently, this study seeks to analyze the impact of online audience feedback on journalists at a routine level within the Malaysian context. Employing a Hierarchy of Influence model as a theoretical framework, the study will utilize a quantitative approach with a snowball survey method. The study's findings aim to enhance our understanding of how online audiences influence journalists and their work practices, encompassing aspects like journalists' autonomy and integrity, editorial decision-making, performance and accountability, daily routines, work practices, as well as the psychological and emotional costs they bear. It's important to note that the study has limitations due to the use of the snowball survey method and its focus within the specific context of Malaysia, making it relatively small in scale.

Keywords: online audiences, feedback, influence, journalists, Malaysia

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Authors: Balwinder Singh, Veerpaul Kaur Mann

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The COVID-19 had a dramatic impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole marketing processes because of the relevant issues emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital technologies that may ensure connections and, thus, help business activities to run smoothly. This could be true, especially with the emergence of strong limitations on physical interactions during the COVID-19 pandemic. In such a scenario, the online channel becomes the most important conducive for online customers to get in contact with the firm and carry out online purchasing activities.

Keywords: COVID-19, business, digital marketing, online customers

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Authors: Choonoh Lee, Seyeon Park, Dongyun Kang, Jaehyeong Choi, Soojee Kim, Younggeun Kim

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Market Kurly is the first South Korean online grocery retailer that guarantees same-day, overnight shipping. More than 1.6 million customers place an average of 4.7 million orders and add 3 to 14 products into a cart per month. The company has sold almost 30,000 kinds of various products in the past 6 months, including food items, cosmetics, kitchenware, toys for kids/pets, and even flowers. The company is operating and expanding multiple dry, cold, and frozen fulfillment centers in order to store and ship these products. Due to the scale and complexity of the fulfillment, pick-pack-ship processes are planned and operated in batches, and thus, the planning that decides the batch of the customers’ orders is a critical factor in overall productivity. This paper introduces a metaheuristic optimization method that reduces the complexity of batch processing in a fulfillment center. The method is an iterative genetic algorithm with heuristic creation and evolution strategies; it aims to group similar orders into pick-pack-ship batches to minimize the total number of distinct products. With a well-designed approach to create initial genes, the method produces streamlined plans, up to 13.5% less complex than the actual plans carried out in the company’s fulfillment centers in the previous months. Furthermore, our digital-twin simulations show that the optimized plans can reduce 3% of operation time for packing, which is the most complex and time-consuming task in the process. The optimization method implements a multithreading design on the Spring framework to support the company’s warehouse management systems in near real-time, finding a solution for 4,000 orders within 5 to 7 seconds on an AWS c5.2xlarge instance.

Keywords: fulfillment planning, genetic algorithm, online grocery retail, optimization

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Authors: Keunhong Chae, Seokho Yoon

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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.

Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm

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Authors: Carrie Prendergast, Lisa Bortman

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The focus of this presentation will be on non-traditional (adult) students as they seek their Bachelors’ degrees online. This presentation will specifically examine nontraditional online student perceptions of Tinto’s success conditions: expectations, support, assessment, and engagement. Expectations include those of the student, the faculty and the institution. Support includes academic, social, and financial support. Feedback and assessment encompasses feedback in the classroom, upon entry, and on an institutional level. The fourth success condition is involvement or engagement of students with their peers and faculty in both academic and social contexts. This program will review and discuss a rich, detailed description of the lived experience of the nontraditional online student to add to the paucity of research on this understudied population and guide higher education professionals in supporting this growing population of students.

Keywords: adult students, online education, student success, vincent tinto

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran

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GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.

Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm

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Authors: Celeste Labuschagne, Sam Ramaila, Thasmai Dhurumraj

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Although formative assessment is acknowledged as crucial for teachers to gauge students’ understanding of subject content, applying formative assessment in an online context is more challenging than in a traditional Physical Sciences classroom. This study examines challenges experienced by Grade 10 Physical Sciences teachers when enacting online formative assessment. The empirical investigation adopted a generic qualitative design and involved three purposively selected Grade 10 Physical Sciences teachers from three different schools and quintiles within the Tshwane North District in South Africa. Data were collected through individual and focus group interviews. Technological, pedagogical, and content knowledge (TPACK) was utilised as a theoretical framework underpinning the study. The study identified a myriad of challenges experienced by Grade 10 Physical Sciences teachers when enacting online formative assessment. These challenges include the utilisation of Annual Teaching Plans, lack of technological knowledge, and internet connectivity. The Department of Basic Education faces the key imperative to provide continuous teacher professional development and concomitant online learning materials that can facilitate meaningful enactment of online formative assessment in various educational settings.

Keywords: COVID-19, challenges, online formative assessment, physical sciences, TPACK

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Authors: Bahar Urhan Torun, Havva Nur Tarakcı

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At the present time, online marketing has become the common target of small and full-scale organizations. Today’s humanbeing who has to spend most of their time in front of the computer because of his job, prefers to socialize by internet due to the easy access to technology. So online marketing area expands day by day. All business organizations from the smallest to the biggest are in a race in order to get a cut from the virtual market share in an extreme competitive environment. However these organizations which use the internet to reach more consumers cannot determine their target group accurately, so this is the biggest handicap of online marketing sales nowadays. The aim of this study is to determine some significant elements about need for communicating efficiently with the consumer on the internet on online marketing. The strategies that can be used in order to increase sales and the limitations of virtual environment where cannot be communicated with the consumer face to face are argued in this study’s scope. As a consequence it is thought that to study on this subject because of lacking and also being limited efficiency of researches and outputs. Within this scope suggesting some proposals about how to communicate efficiently with the consumer and also offering the consumers’ demands efficiently is the essential objective of this study.

Keywords: online marketing, competition, consumer, communication

Procedia PDF Downloads 240

Authors: Chalermpol Tapsai

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The objectives of this research were to develop and find the efficiency of integrated online lessons by investigating the usage of online lessons, the relationship between learners’ background knowledge, and the achievement after learning with online lessons. The sample group in this study consisted of 97 students randomly selected from 121 students registering in 1/2012 at Trimitwittayaram Learning Center. The sample technique employed stratified sample technique of 4 groups according to their proficiency, i.e. high, moderate, low, and non-knowledge. The research instrument included online lessons in integration model on the topic of Java Programming, test after each lesson, the achievement test at the end of the course, and the questionnaires to find learners’ satisfaction. The results showed that the efficiency of online lessons was 90.20/89.18 with the achievement of after learning with the lessons higher than that before the lessons at the statistically significant level of 0.05. Moreover, the background knowledge of the learners on the programming showed the positive relationship with the achievement learning at the statistically significant level at 0.05. Learners with high background knowledge employed less exercises and samples than those with lower background knowledge. While learners with different background in the group of moderate and low did not show the significant difference in employing samples and exercises.

Keywords: integration model, online lessons, learners’ background knowledge, efficiency

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Authors: M. Fernanda Salgado, Alfonso Tierra, Wilbert Aguilar

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The present project consists in applying the informed search algorithm A star (A*) to solve traveler problems, applying it by urban public transportation routes. The digitization of the information allowed to identify 26% of the total of routes that are registered within the Metropolitan District of Quito. For the validation of this information, data were taken in field on the travel times and the difference with respect to the times estimated by the program, resulting in that the difference between them was not greater than 2:20 minutes. We validate A* algorithm with the Dijkstra algorithm, comparing nodes vectors based on the public transport stops, the validation was established through the student t-test hypothesis. Then we verified that the times estimated by the program using the A* algorithm are similar to those registered on field. Furthermore, we review the performance of the algorithm generating iterations in both algorithms. Finally, with these iterations, a hypothesis test was carried out again with student t-test where it was concluded that the iterations of the base algorithm Dijsktra are greater than those generated by the algorithm A*.

Keywords: algorithm A*, graph, mobility, public transport, travel planning, routes

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Authors: Sixing Chen, Shuai Yang

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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

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Authors: Gatut Priyowidodo, I. I. Indrayani

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The relations between Indonesia and Malaysia are always full of colors. Indonesia is always known as old brother of Malaysia since it has similar history, religion also socio culturally. Some decades show that the declination of relationship the both countries. Another time, as ASEAN members the two countries devotes their nationalities to purify their collective identities as Eastern. The objective of the research is to extricate the construction of Kompas online and Utusan online toward news coverage of the borders dispute between Indonesia-Malaysia in 2010. This research is proposed to examine central issues which reported by Kompas online and Utusan online consistently. As a media industry, Kompas coverage dominates circulation nationally. Kompas.com was the pioneer of online news in Indonesia and born in reformation era. Utusan is prominent media industry in Malaysia that conducted by UMNO as the ruling party in Malaysia for some periods. The method used in this research is framing method by Robert N. Entman’s which consists of four steps identification: defining problem, diagnosing causes, moral judgment and a treatment recommendation. This research found that Kompas news covered the border dispute must be negotiated as recognition of Indonesia dignity. In contrary, Utusan’s spectacle focused on the Indonesia demonstrans anarchism during the dispute.

Keywords: online media, media construction, the border dispute, Indonesia-Malaysia’s bilateral relations

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Authors: Chih-Ping Chen

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In recent years, some scholars established the reflection of cultural values in advertisements. However, despite the Internet’s rapid development, few studies have focused on observing cross-cultural differences of values reflected in online advertisements. As mirrors of culture, advertisements are believed to reflect values relevant to consumers. Therefore, this research aims to examine the cultural values reflected on online skincare advertisements between countries with different cultural influences. We argue that culture affects the values presented in the slogans, endorsers, brand prominence, and product prominence of online advertisements; a concept that challenges the standardized manner of communication utilized by most multinational brands. Results highlight that the Philippines and Taiwan are neither located on extreme low-context nor extreme high-context cultures. Moreover, although advertisements reflect culture, it may be affected by potential value shifting caused by globalization, standardized communication, and the advertisers’ marketing priorities.

Keywords: cross-culture, cultural values, online advertising, prominence, beauty

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Authors: Deependra Prasad Sarraf, Gajendra Prasad Rauniar, Robin Maskey, Rajiv Maharjan, Ashish Shrestha, Ramayan Prasad Kushwaha

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Objectives: To assess the perception of faculties towards online teaching-learning activities conducted during the COVID-19 pandemic and to identify barriers and facilitators to conducting online teaching-learning activities in our context. Methods: A cross-sectional study was conducted among faculties at B. P. Koirala Institute of Health Sciences using a 26-item semi-structured questionnaire. A Google Form was prepared, and its link was sent to the faculties via email. Descriptive statistics were calculated, and findings were presented as tables and graphs. Results: Out of 158 faculties, the majority were male (66.46%), medical faculties (85.44%), and assistant professors (46.84%). Only 16 (10.13%) faculties had received formal training regarding preparing and/or delivering online teaching learning activities. Out of 158, 133 (84.18%) faculties faced technical and internet issues. The most common advantage and disadvantage of online teaching learning activities perceived by the faculties were ‘not limited to time or place’ (94.30%) and ‘lack of interaction with the students’ (82.28%), respectively. Majority (94.3%) of them had a positive perception towards online teaching-learning activities conducted during COVID-19 pandemic. Slow internet connection (91.77%) and frequent electricity interruption (82.91%) were the most common perceived barriers to online teaching-learning. Conclusions: Most of the faculties had a positive perception towards online teaching-learning activities. Academic leaders and stakeholders should provide uninterrupted internet and electricity connectivity, training on online teaching-learning platform, and timely technical support.

Keywords: COVID-19 pandemic, faculties, medical education, perception

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Authors: Xinyu Wang

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Given the rapid development of Internet technology and the mainstream trend of online social media, people are spending increasingly more time online. This digital communication method has altered human social behavior. Concurrently, social learning phenomena occurring frequently on various online platforms have attracted significant attention. Past research has categorized social learning into affective, social learning and cognitive, social learning based on the content of learning. Recent studies have observed both types of social learning occurring in online contexts. However, few studies have simultaneously addressed both types of social learning or explored their underlying mechanisms and differences. This study aims to investigate through three behavioral experiments. Experiment 1 manipulates the content of experimental materials and two forms of feedback, emotional valence, sociability, and repetition, to verify whether individuals can achieve online emotional social learning through reinforcement using two social learning strategies. Results reveal that both social learning strategies can assist individuals in affective and social learning through reinforcement, with feedback-based learning strategies outperforming frequency-dependent strategies. Experiment 2 similarly manipulates the content of experimental materials and two forms of feedback to verify whether individuals can achieve online knowledge and social learning through reinforcement using two social learning strategies. Results show that similar to online affective and social learning, individuals adopt both social learning strategies to achieve cognitive and social learning through reinforcement, with feedback-based learning strategies outperforming frequency-dependent strategies. Experiment 3 simultaneously observes online affective and cognitive social learning by manipulating the content of experimental materials and feedback at different levels of social pressure. Results indicate that online affective and social learning exhibits different learning effects under different levels of social pressure, whereas online cognitive social learning remains unaffected by social pressure, demonstrating more stable learning effects. Additionally, to explore the sustained effects of online social learning and differences in duration among different types of online social learning, all three experiments incorporate two test time points. Results reveal significant differences in pre-post-test scores for online social learning in Experiments 2 and 3, whereas differences are less apparent in Experiment 1. To accurately measure the sustained effects of online social learning, the researchers conducted a mini-meta-analysis of all effect sizes of online social learning duration. Results indicate that although the overall effect size is small, the effect of online social learning weakens over time.

Keywords: online social learning, affective social learning, cognitive social learning, social learning strategies, social reinforcement, social pressure, duration

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Authors: E. Behmanesh, J. Pannek

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The distribution-allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution-allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near-optimal solutions particularly for large scales test problems. This paper, presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a novelty in population presentation. To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as a comparison basis for small size problems. In large size cases that we are dealing with in the real world, the Genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.

Keywords: integrated logistics network, flexible path, memetic algorithm, genetic algorithm

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Authors: Stepan Kuchar, Martin Golasowski, Radim Vavrik, Michal Podhoranyi, Boris Sir, Jan Martinovic

Abstract:

The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of high-performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice river catchment is presented that shows actual durations and their gain from the parallel implementation.

Keywords: flood prediction process, high performance computing, online flood prediction system, parallelization

Procedia PDF Downloads 469

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

Abstract:

All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

Procedia PDF Downloads 215

Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

Abstract:

Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

Procedia PDF Downloads 515