Search results for: student-centered learning technologies
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9968

Search results for: student-centered learning technologies

2528 Moving Oman’s Economy to Knowledge-Based Economy: A Study on the Role of SMEs from the Perspective of Experts

Authors: Hanin Suleiman Alqam

Abstract:

The knowledge-based economy, as its name implies relies on knowledge, information and high levels of skills made available for all economic agents. Delving a bit more deeply, the concept of a knowledge-based economy is showcasing four main pillars, which are: Education and Training, Information and Communication Technology, Economic incentives and Institutional regimes, and Research and Development (R&D) and Innovation system. A good number of researches are showing its positive contribution to economic diversification underpinning sustainable development and growth. The present paper aimed at assessing the role of SMEs in moving Oman’s economy from a traditional economy to a knowledge-based economy. To lay down a groundwork that should lead to future studies, the methodology selected is based on exploratory research. Hence, the interview was conducted as a data collection tool. Based on a purposive sampling technique, seven handpicked experts have partaken in the study as they are working in different key organizations considered to be directly or indirectly the backbone of the Omani national economy. A thematic approach is employed for the purpose of data analysis. Results of the study showed that SMEs are not really contributing in the knowledge-based economy due to a lack of awareness about its importance to the country and to the enterprise within SMEs in Oman. However, it was shown that SMEs owners are interested in innovation and are trying to support innovative individuals by attracting them to their enterprises. On the other hand, the results revealed that SMEs' performance in e-solution is still not up to the level as 32% of SMEs only are using e-solutions in their internal processes and procedures like accounting systems. It is recommended to SMEs owners to use new and modern technologies in marketing and customer relation, encourage creativity, research and development, and allow the youth to have opportunities and facilitate the procedure in terms of innovation so that their role in contributing to the knowledge-based economy could be improved.

Keywords: knowledge-based economy, SMEs, ICT pillars, research and innovation

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2527 Relation between Physical and Mechanical Properties of Concrete Paving Stones Using Neuro-Fuzzy Approach

Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

Abstract:

This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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2526 A Case Study on How Biomedical Engineering (BME) Outreach Programmes Serve as An Alternative Educational Approach to Form and Develop the BME Community in Hong Kong

Authors: Sum Lau, Wing Chung Cleo Lau, Wing Yan Chu, Long Ching Ip, Wan Yin Lo, Jo Long Sam Yau, Ka Ho Hui, Sze Yi Mak

Abstract:

Biomedical engineering (BME) is an interdisciplinary subject where knowledge about biology and medicine is applied to novel applications, solving clinical problems. This subject is crucial for cities such as Hong Kong, where the burden on the medical system is rising due to reasons like the ageing population. Hong Kong, who is actively boosting technological advancements in recent years, sets BME, or biotechnology, as a major category, as reflected in the 2018-19 Budget, where biotechnology was one of the four pillars for development. Over the years, while resources in terms of money and space have been provided, there has been a lack of talents expressed by both the academia and industry. While exogenous factors, such as COVID, may have hindered talents from outside Hong Kong to come, endogenous factors should also be considered. In particular, since there are already a few local universities offering BME programmes, their curriculum or style of education requires to be reviewed to intensify the network of the BME community and support post-academic career development. It was observed that while undergraduate (UG) studies focus on knowledge teaching with some technical training and postgraduate (PG) programmes concentrate on upstream research, the programmes are generally confined to the academic sector and lack connections to the industry. In light of that, a “Biomedical Innovation and Outreach Programme 2022” (“B.I.O.2022”) was held to connect students and professors from academia with clinicians and engineers from the industry, serving as a comparative approach to conventional education methods (UG and PG programmes from tertiary institutions). Over 100 participants, including undergraduates, postgraduates, secondary school students, researchers, engineers, and clinicians, took part in various outreach events such as conference and site visits, all held from June to July 2022. As a case study, this programme aimed to tackle the aforementioned problems with the theme of “4Cs” (connection, communication, collaboration, and commercialisation). The effectiveness of the programme is investigated by its ability to serve as an adult and continuing education and the effectiveness of causing social change to tackle current societal challenges, with the focus on tackling the lack of talents engaging in biomedical engineering. In this study, B.I.O.2022 is found to be able to complement the traditional educational methods, particularly in terms of knowledge exchange between the academia and the industry. With enhanced communications between participants from different career stages, there were students who followed up to visit or even work with the professionals after the programme. Furthermore, connections between the academia and industry could foster the generation of new knowledge, which ultimately pointed to commercialisation, adding value to the BME industry while filling the gap in terms of human resources. With the continuation of events like B.I.O.2022, it provides a promising starting point for the development and relationship strengthening of a BME community in Hong Kong, and shows potential as an alternative way of adult education or learning with societal benefits.

Keywords: biomedical engineering, adult education for social change, comparative methods and principles, lifelong learning, faced problems, promises, challenges and pitfalls

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2525 Refugees’inclusion: The Psychological Screening and the Educational Tools in Portugal

Authors: Sandra Figueiredo

Abstract:

To guarantee the well-being and the academic achievement it is crucial into the global society to develop techniques to assess language competence and control psychological aspects on the second language learning context. The current scenario of the war conflicts that are emerging mostly in Europe and Middle East have been resulting in forced immigration and refugees’ maladjustment. The inclusion is the priority for United Nations concerning the sustainability of societies. For inclusion, psychological screening tests and educational tools are urgent. Method: Approximately 100 refugees from Ukraine were assessed, in Portugal, under the administration of the PCL-5. This 20-item instrument evaluates the Post-Traumatic Disorder. Expected results: The statistical analysis will be performed with the International Database Analyzer and SPSS (v. 28). The results expected are the relationship between traumatic events caused by war and post-traumatic symptomatology (anxiety, hypervigilance, stress). Implications: The data will be discussed concerning the problems of belonging, the psychological constraints and educational attainment (language needs included) experienced by the individuals more recently arrived to the hosting societies. The refugees’ acculturation process and the emotional regulation will be addressed.

Keywords: refugees, immigration, educational needs, trauma, inclusion, second language.

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2524 Investigating the Influence of L2 Motivational Self-System on Willingness to Communicate in English: A Study of Chinese Non-English Major Students in EFL Classrooms

Authors: Wanghongshu Zhou

Abstract:

This study aims to explore the relationship between the L2MSS and WTC among Chinese non-English major students in order to provide pedagogical implications for English as a Foreign Language (EFL) classrooms in Chinese universities. By employing a mixed methods approach, we involved 103 Chinese non-English major students from a typical university in China, conducted questionnaire survey to measure their levels of L2WTC and L2MSS level, and then analyzed the correlation between the two above mentioned variables. Semi-structured interviews were conducted with eight participants to provide a deeper understanding and explanation of the questionnaire data. Findings show that 1) Chinese non-English major students’ ideal L2 self and L2 learning experience could positively predict their L2 WTC in EFL class; 2) Chinese non-English major students’ ought-to L2 self might have no significant impact on their L2 WTC in EFL class; and 3) self-confidence might be another main factor that will influence Chinese non-English major students’ L2 WTC in EFL class. These findings might shed light on the second language acquisition field and provide pedagogical recommendations for pre-service as well as in-service EFL teachers.

Keywords: L2 willingness to communicate, L2 motivation, self-confidence, Chinese non-English major students

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2523 Towards Understanding the Notions of Quality Education among Internationally-Accredited Christian Schools in Southeast Asia

Authors: Selaphares Jatico Tajale

Abstract:

This research aims to understand the notions of quality education by conducting case studies among internationally-accredited Christian schools in Southeast Asia. Five internationally-accredited Christian schools from Cambodia, Indonesia, Malaysia, The Philippines, and Singapore will be chosen as cases for this study. This study will utilize the processes of interviews, filling up of questionnaires, and writing of reflections in order to obtain data and relevant information. These processes will be conducted through multi-sectoral respondents such as administrators, academic heads, and faculty. This study employs five aspects within the realm of education as guides in the formulation of questionnaire and guide questions in the interview, namely: a) school context, b) classroom, c) quality assurance, d) stakeholders, e) faculty and staff. Guide interview questions and questions in the questionnaires are formulated to uncover information on how those five aspects were managed to achieve desired student learning outcomes and uncover other information useful for the study.

Keywords: internationally-accredited, notions of quality education, quality education, quality education in Southeast Asia

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2522 The Impact of Transformational Leadership on Individual Attributes

Authors: Bilal Liaqat, Muhammad Umar, Zara Bashir, Hassan Rafique, Mohsin Abbasi, Zarak Khan

Abstract:

Transformational leadership is one of the most studied topics in the organization sciences. However, the impact of transformational leadership on employee’s individual attributes have not yet been studied. Purpose: This research aims to discover the relationship between transformational leadership and employee motivation, performance and creativity. Moreover, the study will also investigate the influence of transformational leadership on employee performance through employee motivation and employee creativity. Design-Methodology-Approach: The data was collected from employees in different organization. This cross-sectional study collected data from employees and the methodology used includes survey data that were collected from employees in organizations. Structured interviews were also conducted to explain the outcomes from the survey. Findings: The results of this study reveal that transformational leadership has a positive impact on employee’s individual attributes. Research Implications: Although this study expands our knowledge about the role of learning orientation between transformational leadership and employee motivation, performance and creativity, the prospects for further research are still present.

Keywords: employee creativity, employee motivation, employee performance, transformational leadership

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2521 Buddhism and Education for Children: Cultivating Wisdom and Compassion

Authors: Harry Einhorn

Abstract:

This paper aims to explore the integration of Buddhism into educational settings with the goal of fostering the holistic development of children. By incorporating Buddhist principles and practices, educators can create a nurturing environment that cultivates wisdom, compassion, and ethical values in children. The teachings of Buddhism provide valuable insights into mindfulness, compassion, and critical thinking, which can be adapted and applied to educational curricula to enhance children's intellectual, emotional, and moral growth. One of the fundamental aspects of Buddhist philosophy that is particularly relevant to education is the concept of mindfulness. By introducing mindfulness practices, such as meditation and breathing exercises, children can learn to cultivate present-moment awareness, develop emotional resilience, and enhance their ability to concentrate and focus. These skills are essential for effective learning and can contribute to reducing stress and promoting overall well-being in children. Mindfulness practices can also teach children how to manage their emotions and thoughts, promoting self-regulation and creating a positive classroom environment. In addition to mindfulness, Buddhism emphasizes the cultivation of compassion and empathy toward all living beings. Integrating teachings on kindness, empathy, and ethical behavior into the educational framework can help children develop a deep sense of interconnectedness and social responsibility. By engaging children in activities that promote empathy and encourage acts of kindness, such as community service projects and cooperative learning, educators can foster the development of compassionate individuals who are actively engaged in creating a more harmonious and compassionate society. Moreover, Buddhist teachings encourage critical thinking and inquiry, which are crucial skills for intellectual development. By introducing children to fundamental Buddhist concepts such as impermanence, interdependence, and the nature of suffering, educators can engage them in philosophical reflections and broaden their perspectives on life. These teachings promote open-mindedness, curiosity, and a deeper understanding of the interconnectedness of all things. Through the exploration of these concepts, children can develop critical thinking skills and gain insights into the complexities of the world, enabling them to navigate challenges with wisdom and discernment. While integrating Buddhism into education requires sensitivity, cultural awareness, and respect for diverse beliefs and backgrounds, it holds great potential for nurturing the holistic development of children. By incorporating mindfulness practices, fostering compassion and empathy, and promoting critical thinking, Buddhism can contribute to the creation of a more compassionate, inclusive, and harmonious educational environment. This integration can shape well-rounded individuals who are equipped with the necessary skills and qualities to navigate the complexities of the modern world with wisdom, compassion, and resilience. In conclusion, the integration of Buddhism into education offers a valuable framework for cultivating wisdom, compassion, and ethical values in children. By incorporating mindfulness, compassion, and critical thinking into educational practices, educators can create a supportive environment that promotes children's holistic development. By nurturing these qualities, Buddhism can help shape individuals who are not only academically proficient but also morally and ethically responsible, contributing to a more compassionate and harmonious society.

Keywords: Buddhism, education, children, mindfulness

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2520 A Comprehensive Model of Professional Ethics Based on the Teachings of the Holy Quran

Authors: Zahra Mohagheghian, Fatema Agharebparast

Abstract:

Professional ethic is a subject that has been an issue today, so most of the businesses, including the teaching profession, understand the need and importance of it. So they need to develop a code of professional ethics for their own. In this regard, this study seeks to answer the question, with respect to the integrity of the Qur'an (Nahl / 89), is it possible to contemplate the divine teachers conduct to extract the divine pattern for teaching and training? In the code of conduct for divine teachers what are the most important moral obligations and duties of the teaching professionals? The results of this study show that the teaching of Khidr, according to the Quran’s verses, Abundant and subtle hints emphasized that it can be as comprehensive and divine pattern used in teaching and in the drafting of the charter of professional ethics of teachers used it. Also, the results show that in there have been many ethical principles in prophet Khidr’s teaching pattern.The most important ethical principles include: Student assessment, using objective and not subjective examples, assessment during teaching, flexibility, and others. According to each of these principles can help teachers achieve their educational goals and lead human being in their path toward spiritual evaluation.

Keywords: professional ethics, teaching-learning process, teacher, student, Quran

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2519 INCIPIT-CRIS: A Research Information System Combining Linked Data Ontologies and Persistent Identifiers

Authors: David Nogueiras Blanco, Amir Alwash, Arnaud Gaudinat, René Schneider

Abstract:

At a time when the access to and the sharing of information are crucial in the world of research, the use of technologies such as persistent identifiers (PIDs), Current Research Information Systems (CRIS), and ontologies may create platforms for information sharing if they respond to the need of disambiguation of their data by assuring interoperability inside and between other systems. INCIPIT-CRIS is a continuation of the former INCIPIT project, whose goal was to set up an infrastructure for a low-cost attribution of PIDs with high granularity based on Archival Resource Keys (ARKs). INCIPIT-CRIS can be interpreted as a logical consequence and propose a research information management system developed from scratch. The system has been created on and around the Schema.org ontology with a further articulation of the use of ARKs. It is thus built upon the infrastructure previously implemented (i.e., INCIPIT) in order to enhance the persistence of URIs. As a consequence, INCIPIT-CRIS aims to be the hinge between previously separated aspects such as CRIS, ontologies and PIDs in order to produce a powerful system allowing the resolution of disambiguation problems using a combination of an ontology such as Schema.org and unique persistent identifiers such as ARK, allowing the sharing of information through a dedicated platform, but also the interoperability of the system by representing the entirety of the data as RDF triplets. This paper aims to present the implemented solution as well as its simulation in real life. We will describe the underlying ideas and inspirations while going through the logic and the different functionalities implemented and their links with ARKs and Schema.org. Finally, we will discuss the tests performed with our project partner, the Swiss Institute of Bioinformatics (SIB), by the use of large and real-world data sets.

Keywords: current research information systems, linked data, ontologies, persistent identifier, schema.org, semantic web

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2518 Permeable Bio-Reactive Barriers to Tackle Petroleum Hydrocarbon Contamination in the Sub-Antarctic

Authors: Benjamin L. Freidman, Sally L. Gras, Ian Snape, Geoff W. Stevens, Kathryn A. Mumford

Abstract:

Increasing transportation and storage of petroleum hydrocarbons in Antarctic and sub-Antarctic regions have resulted in frequent accidental spills. Migrating petroleum hydrocarbon spills can have a significant impact on terrestrial and marine ecosystems in cold regions, as harsh environmental conditions result in heightened sensitivity to pollution. This migration of contaminants has led to the development of Permeable Reactive Barriers (PRB) for application in cold regions. PRB’s are one of the most practical technologies for on-site or in-situ groundwater remediation in cold regions due to their minimal energy, monitoring and maintenance requirements. The Main Power House site has been used as a fuel storage and power generation area for the Macquarie Island research station since at least 1960. Soil analysis at the site has revealed Total Petroleum Hydrocarbon (TPH) (C9-C28) concentrations as high as 19,000 mg/kg soil. Groundwater TPH concentrations at this site can exceed 350 mg/L TPH. Ongoing migration of petroleum hydrocarbons into the neighbouring marine ecosystem resulted in the installation of a ‘funnel and gate’ PRB in November 2014. The ‘funnel and gate’ design successfully intercepted contaminated groundwater and analysis of TPH retention and biodegradation on PRB media are currently underway. Installation of the PRB facilitates research aimed at better understanding the contribution of particle attached biofilms to the remediation of groundwater systems. Bench-scale PRB system analysis at The University of Melbourne is currently examining the role biofilms play in petroleum hydrocarbon degradation, and how controlled release nutrient media can heighten the metabolic activity of biofilms in cold regions in the presence of low temperatures and low nutrient groundwater.

Keywords: groundwater, petroleum, Macquarie island, funnel and gate

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2517 Review on Future Economic Potential Stems from Global Electronic Waste Generation and Sustainable Recycling Practices.

Authors: Shamim Ahsan

Abstract:

Abstract Global digital advances associated with consumer’s strong inclination for the state of art digital technologies is causing overwhelming social and environmental challenges for global community. During recent years not only economic advances of electronic industries has taken place at steadfast rate, also the generation of e-waste outshined the growth of any other types of wastes. The estimated global e-waste volume is expected to reach 65.4 million tons annually by 2017. Formal recycling practices in developed countries are stemming economic liability, opening paths for illegal trafficking to developing countries. Informal crude management of large volume of e-waste is transforming into an emergent environmental and health challenge in. Contrariwise, in several studies formal and informal recycling of e-waste has also exhibited potentials for economic returns both in developed and developing countries. Some research on China illustrated that from large volume of e-wastes generation there are recycling potential in evolving from ∼16 (10−22) billion US$ in 2010, to an anticipated ∼73.4 (44.5−103.4) billion US$ by 2030. While in another study, researcher found from an economic analysis of 14 common categories of waste electric and electronic equipment (WEEE) the overall worth is calculated as €2.15 billion to European markets, with a potential rise to €3.67 billion as volumes increase. These economic returns and environmental protection approaches are feasible only when sustainable policy options are embraced with stricter regulatory mechanism. This study will critically review current researches to stipulate how global e-waste generation and sustainable e-waste recycling practices demonstrate future economic development potential in terms of both quantity and processing capacity, also triggering complex some environmental challenges.

Keywords: E-Waste, , Generation, , Economic Potential, Recycling

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2516 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

Abstract:

Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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2515 A Real-Time Bayesian Decision-Support System for Predicting Suspect Vehicle’s Intended Target Using a Sparse Camera Network

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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2514 Teacher in Character Strengthening for Early Childhood

Authors: Siti Aisyah

Abstract:

This article discusses character education which is a very basic education for early childhood with the aim of instilling moral values to prevent unacceptable behaviours. Children can absorb good character when they are in a supportive environment, for that schools should understand and implement character education in the learning process. In the school environment, good character education and habituation can be developed. All parties in the school should be involved, especially the teachers. This research discusses how teachers apply characters on the values of responsibility, honesty, discipline, love and compassion, caring, courage, independence, hard work, mutual cooperation, courtesy, justice, self-control and tolerance. The respondents of this study were teachers involving 200 children from all over Indonesia. The methodology used was a survey method with the result that more than 80% of teachers have been able to exhibit the expected behaviours. The survey was conducted based on observations, types of tasks and assessed performance. The character values can be optimally taught in the school environment based on the teacher's ability to implement them. Through the character education in schools, children can also instil a positive outlook on life.

Keywords: teachers, character strengthening, early childhood, behavior

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2513 Success Factors and Challenges of Startup Businesses in a Crisis Context

Authors: Joanna Konstantinou

Abstract:

The study is about the challenges faced by entrepreneurs in a crisis context and in turbulent economies. The scope is to determine which factors, if any, are related to the success of a new business venture, such as innovation, access to funding and capital, enhanced digital skills, employment relations and organizational culture as well as a company’s strategic orientation towards international markets. The crisis context has been recorded to have affected the number of SMEs in the Greek economy, the number of people employed as well as the volume of the output produced. Although not all SMEs have been equally impacted by the crisis, which has been identified to affect certain sectors more than others, and although research is not exhaustive in that end, employment relations and patterns, firm’s age, and innovation practices in relation to employees’ learning curve seem to have a positive correlation with the successful survival and resilience of the firm. The aim is to identify important factors that can contribute positively to the success of a startup business, and that will allow businesses to acquire resilience and survive economic adversities, and it will focus on businesses of the Greek economy, the country with the longer lasting economic crisis and the findings will be lessons to learn for other economies.

Keywords: entrepreneurship, innovation, crisis, challenges

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2512 Design of Self-Balancing Bicycle Using Object State Detection in Co-Ordinate System

Authors: Mamta M. Barapatre, V. N. Sahare

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Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

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2511 A Genetic Algorithm Based Ensemble Method with Pairwise Consensus Score on Malware Cacophonous Labels

Authors: Shih-Yu Wang, Shun-Wen Hsiao

Abstract:

In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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2510 Hyperspectral Imagery for Tree Speciation and Carbon Mass Estimates

Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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2509 The Synchronous Online Environment: Impact on Instructor’s Empathy

Authors: Lystra Huggins

Abstract:

The COVID-19 pandemic affected all facets of life, including pedagogical strategies and perceptual experiences for both instructors and students. While there have also been many challenges and advantages to the online teaching and learning environment, when students’ cameras are on, the daily experiences of students’ lives have been magnified during synchronous online instruction and have served to humanize them in the classroom. This means that students’ everyday experiences, now often on display on ZOOM, allow instructors to see the realities of students. They include children running, spouses walking by parents cooking or sitting on the sofa following the lecture, students at their place of employment or driving from work, or having their classroom engagement interrupted by a delivery. Students’ backgrounds and spaces create unique dynamics during synchronous instruction, which offers a holistic view of them outside academia. This research explores whether witnessing students’ daily experiences leads to empathy from their instructors and whether it results in a greater understanding of students’ challenges and circumstances. Ultimately, it will amplify instructors’ stance on the advantages of students having their cameras on during synchronous online classes to develop a connection with the instructor and a more cohesive classroom environment.

Keywords: instructor’s empathy, synchronous class, asynchronous class, online environment

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2508 System Analysis of Quality Assurance in Online Education

Authors: Keh-Wen Carin Chuang, Kuan-Chou Chen

Abstract:

Our society is in a constant state of change. Technology advancements continue to affect our daily lives. How we work, communicate and entertain ourselves has changed dramatically in the past decades. As our society learns to accept and adapt to the many different technological advances that seem to inundate every part of our lives, the education institutions must migrate from traditional methods of instruction to online education in order to take full advantage of the opportunities provided by these technology advancements. There are many benefits that can be gained for university and society from offering online programs by utilizing advanced technologies. But the programs must not be implemented carelessly. The key to providing a quality online program is the issue of perceived quality, which takes into account the viewpoint of all stakeholders involved. To truly ensure the institutional quality, however, a systemic view of all factors contributing to the quality must be analyzed and linked to one another — allowing education administrators to understand how each factor contributes to the perceived quality of online education. The perceived quality of an online program will be positively reinforced only through an organizational-wide effort that focuses on managed administration, augmenting online program branding, skilled faculty, supportive alumni, student satisfaction, and effective delivery systems — each of which is vital to a quality online program. This study focuses on the concept of quality assurance in the start-up, implementation, and sustainability of online education. A case of online MBA program will be analyzed to explore the quality assurance. The difficulties in promoting online education quality is the fact that universities are complex networks of disciplinary, social, economic, and political fiefdoms, both internal and external factors to the institutions. As such, the system analysis, a systems-thinking approach, on the issue of perceived quality is ideal to investigate the factors and how each factor contributes to the perceived quality in the online education domain.

Keywords: systems thinking, quality assurance, online education, MBA program

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2507 Oxidation and Reduction Kinetics of Ni-Based Oxygen Carrier for Chemical Looping Combustion

Authors: J. H. Park, R. H. Hwang, K. B. Yi

Abstract:

Carbon Capture and Storage (CCS) is one of the important technology to reduce the CO₂ emission from large stationary sources such as a power plant. Among the carbon technologies for power plants, chemical looping combustion (CLC) has attracted much attention due to a higher thermal efficiency and a lower cost of electricity. A CLC process is consists of a fuel reactor and an air reactor which are interconnected fluidized bed reactor. In the fuel reactor, an oxygen carrier (OC) is reduced by fuel gas such as CH₄, H₂, CO. And the OC is send to air reactor and oxidized by air or O₂ gas. The oxidation and reduction reaction of OC occurs between the two reactors repeatedly. In the CLC system, high concentration of CO₂ can be easily obtained by steam condensation only from the fuel reactor. It is very important to understand the oxidation and reduction characteristics of oxygen carrier in the CLC system to determine the solids circulation rate between the air and fuel reactors, and the amount of solid bed materials. In this study, we have conducted the experiment and interpreted oxidation and reduction reaction characteristics via observing weight change of Ni-based oxygen carrier using the TGA with varying as concentration and temperature. Characterizations of the oxygen carrier were carried out with BET, SEM. The reaction rate increased with increasing the temperature and increasing the inlet gas concentration. We also compared experimental results and adapted basic reaction kinetic model (JMA model). JAM model is one of the nucleation and nuclei growth models, and this model can explain the delay time at the early part of reaction. As a result, the model data and experimental data agree over the arranged conversion and time with overall variance (R²) greater than 98%. Also, we calculated activation energy, pre-exponential factor, and reaction order through the Arrhenius plot and compared with previous Ni-based oxygen carriers.

Keywords: chemical looping combustion, kinetic, nickel-based, oxygen carrier, spray drying method

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2506 Future Design and Innovative Economic Models for Futuristic Markets in Developing Countries

Authors: Nessreen Y. Ibrahim

Abstract:

Designing the future according to realistic analytical study for the futuristic market needs can be a milestone strategy to make a huge improvement in developing countries economics. In developing countries, access to high technology and latest science approaches is very limited. The financial problems in low and medium income countries have negative effects on the kind and quality of imported new technologies and application for their markets. Thus, there is a strong need for shifting paradigm thinking in the design process to improve and evolve their development strategy. This paper discusses future possibilities in developing countries, and how they can design their own future according to specific future models FDM (Future Design Models), which established to solve certain economical problems, as well as political and cultural conflicts. FDM is strategic thinking framework provides an improvement in both content and process. The content includes; beliefs, values, mission, purpose, conceptual frameworks, research, and practice, while the process includes; design methodology, design systems, and design managements tools. In this paper the main objective was building an innovative economic model to design a chosen possible futuristic scenario; by understanding the market future needs, analyze real world setting, solve the model questions by future driven design, and finally interpret the results, to discuss to what extent the results can be transferred to the real world. The paper discusses Egypt as a potential case study. Since, Egypt has highly complex economical problems, extra-dynamic political factors, and very rich cultural aspects; we considered Egypt is a very challenging example for applying FDM. The paper results recommended using FDM numerical modeling as a starting point to design the future.

Keywords: developing countries, economic models, future design, possible futures

Procedia PDF Downloads 258
2505 Encounters of English First Additional Language Teachers in Rural Schools

Authors: Rendani Mercy Makhwathana

Abstract:

This paper intends to explore teachers' encounters when teaching English First Additional Language in rural public schools. Teachers are pillars of any education system around the globe. Educational transformations hinge on them as critical role players in the education system. Thus, teachers' encounters are worth consideration, for they impact learners' learning and the well-being of education in general. An exploratory qualitative approach was used in this paper. The population for this paper comprised all Foundation Phase teachers in the district. A purposive sample of 15 Foundation Phase teachers from five rural-based schools was used. Data were collected through classroom observation and individual face-to-face interviews. Data were categorized, analyzed, and interpreted. Amongst the revealed teachers' encounters are learners' inability to read and write and learners' lack of English language background and learners' lack of the vocabulary to express themselves. This paper recommends the provision of relevant resources and support to effectively teach English First Additional Language to enable learners' engagement and effective use of the English language.

Keywords: first additional language, english second language, medium of instruction, teacher professional development

Procedia PDF Downloads 66
2504 A Modular Reactor for Thermochemical Energy Storage Examination of Ettringite-Based Materials

Authors: B. Chen, F. Kuznik, M. Horgnies, K. Johannes, V. Morin, E. Gengembre

Abstract:

More attention on renewable energy has been done after the achievement of Paris Agreement against climate change. Solar-based technology is supposed to be one of the most promising green energy technologies for residential buildings since its widely thermal usage for hot water and heating. However, the seasonal mismatch between its production and consumption makes buildings need an energy storage system to improve the efficiency of renewable energy use. Indeed, there exist already different kinds of energy storage systems using sensible or latent heat. With the consideration of energy dissipation during storage and low energy density for above two methods, thermochemical energy storage is then recommended. Recently, ettringite (3CaO∙Al₂O₃∙3CaSO₄∙32H₂O) based materials have been reported as potential thermochemical storage materials because of high energy density (~500 kWh/m³), low material cost (700 €/m³) and low storage temperature (~60-70°C), compared to reported salt hydrates like SrBr₂·6H₂O (42 k€/m³, ~80°C), LaCl₃·7H₂O (38 k€/m³, ~100°C) and MgSO₄·7H₂O (5 k€/m³, ~150°C). Therefore, they have the possibility to be largely used in building sector with being coupled to normal solar panel systems. On the other side, the lack in terms of extensive examination leads to poor knowledge on their thermal properties and limit maturity of this technology. The aim of this work is to develop a modular reactor adapting to thermal characterizations of ettringite-based material particles of different sizes. The filled materials in the reactor can be self-compacted vertically to ensure hot air or humid air goes through homogenously. Additionally, quick assembly and modification of reactor, like LEGO™ plastic blocks, make it suitable to distinct thermochemical energy storage material samples with different weights (from some grams to several kilograms). In our case, quantity of stored and released energy, best work conditions and even chemical durability of ettringite-based materials have been investigated.

Keywords: dehydration, ettringite, hydration, modular reactor, thermochemical energy storage

Procedia PDF Downloads 122
2503 A Web-Based Self-Learning Grammar for Spoken Language Understanding

Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

Abstract:

One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

Procedia PDF Downloads 331
2502 The Effects of Damping Devices on Displacements, Velocities and Accelerations of Structures

Authors: Radhwane Boudjelthia

Abstract:

The most recent earthquakes occurred in the world have killed thousands of people and severe damage. For all the actors involved in the building process, the earthquake is the litmus test for construction. The goal we set ourselves is to contribute to the implementation of a thoughtful approach to the seismic protection of structures. For many engineers, the most conventional approach to protection works (buildings and bridges) the effects of earthquakes is to increase rigidity. This approach is not always effective, especially when there is a context that favors the phenomenon of resonance and amplification of seismic forces. Therefore, the field of earthquake engineering has made significant inroads, among others catalyzed by the development of computational techniques in computer form and the use of powerful test facilities. This has led to the emergence of several innovative technologies, such as the introduction of special devices insulation between infrastructure and superstructure. This approach, commonly known as "seismic isolation," to absorb the significant efforts without the structure is damaged and thus ensuring the protection of lives and property. In addition, the restraints to the construction by the ground shaking are located mainly at the supports. With these moves, the natural period of construction is increasing, and seismic loads are reduced. Thus, there is an attenuation of the seismic movement. Likewise, the insulation of the base mechanism may be used in combination with earthquake dampers in order to control the deformation of the insulation system and the absolute displacement of the superstructure located above the isolation interface. On the other hand, only can use these earthquake dampers to reduce the oscillation amplitudes and thus reduce seismic loads. The use of damping devices represents an effective solution for the rehabilitation of existing structures. Given all these acceleration reducing means considered passive, much research has been conducted for several years to develop an active control system of the response of buildings to earthquakes.

Keywords: earthquake, building, seismic forces, displacement, resonance, response.

Procedia PDF Downloads 61
2501 The Effects of Green Logistics Management Practices on Sustainability Performance in Nigeria

Authors: Ozoemelam Ikechukwu Lazarus, Nizamuddin B. Zainuddi, Abdul Kafi

Abstract:

Numerous studies have been carried out on Green Logistics Management Practices (GLMPs) across the globe. The study on the practices and performance of green chain practices in Africa in particular has not gained enough scholarly attention. Again, the majority of supply chain sustainability research being conducted focus on environmental sustainability. Logistics has been a major cause of supply chain resource waste and environmental damage. Many sectors of the economy that engage in logistical operations significantly rely on vehicles, which emit pollutants into the environment. Due to urbanization and industrialization, the logistical operations of manufacturing companies represent a serious hazard to the society and human life, making the sector one of the fastest expanding in the world today. Logistics companies are faced with numerous difficulties when attempting to implement logistics practices along their supply chains. In Nigeria, manufacturing companies aspire to implement reverse logistics in response to stakeholders’ requirements to reduce negative environmental consequences. However, implementing this is impeded by a criteria framework, and necessitates the careful analysis of how such criteria interact with each other in the presence of uncertainty. This study integrates most of the green logistics management practices (GLMPs) into the Nigerian firms to improve generalizability, and credibility. It examines the effect of Green Logistics Management Practices on environmental performance, social performance, market performance, and financial performance in the logistics industries. It seeks to identify the critical success factors in order to develop a model that incorporates different factors from the perspectives of the technology, organization, human and environment to inform the adoption and use of technologies for logistics supply chain social sustainability in Nigeria. It uses exploratory research approach to collect and analyse the data.

Keywords: logistics, management, sustainability, environment, operations

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2500 Effectiveness of Climate Smart Agriculture in Managing Field Stresses in Robusta Coffee

Authors: Andrew Kirabira

Abstract:

This study is an investigation into the effectiveness of climate-smart agriculture (CSA) technologies in improving productivity through managing biotic and abiotic stresses in the coffee agroecological zones of Uganda. The motive is to enhance farmer livelihoods. The study was initiated as a result of the decreasing productivity of the crop in Uganda caused by the increasing prevalence of pests, diseases and abiotic stresses. Despite 9 years of farmers’ application of CSA, productivity has stagnated between 700kg -800kg/ha/yr which is only 26% of the 3-5tn/ha/yr that CSA is capable of delivering if properly applied. This has negatively affected the incomes of the 10.6 million people along the crop value chain which has in essence affected the country’s national income. In 2019/20 FY for example, Uganda suffered a deficit of $40m out of singularly the increasing incidence of one pest; BCTB. The amalgamation of such trends cripples the realization of SDG #1 and #13 which are the eradication of poverty and mitigation of climate change, respectively. In probing CSA’s effectiveness in curbing such a trend, this study is guided by the objectives of; determining the existing farmers’ knowledge and perceptions of CSA amongst the coffee farmers in the diverse coffee agro-ecological zones of Uganda; examining the relationship between the use of CSA and prevalence of selected coffee pests, diseases and abiotic stresses; ascertaining the difference in the market organization and pricing between conventionally and CSA produced coffee; and analyzing the prevailing policy environment concerning the use of CSA in coffee production. The data collection research design is descriptive in nature; collecting data from farmers and agricultural extension workers in the districts of Ntungamo, Iganga and Luweero; each of these districts representing a distinct coffee agroecological zone. Policy custodian officers at district, cooperatives and at the crop’s overseeing national authority were also interviewed.

Keywords: climate change, food security, field stresses, Productivity

Procedia PDF Downloads 47
2499 Toward Automatic Chest CT Image Segmentation

Authors: Angely Sim Jia Wun, Sasa Arsovski

Abstract:

Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

Procedia PDF Downloads 83