Search results for: online learning activities

Authors: N. J. M. Yusof, T. Sabir, J. McLoughlin

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Garment manufacturing industry involves sequential processes that are subjected to uncontrollable variations. The industry depends on the skill of labour in handling the varieties of fabrics and accessories, machines, and also a complicated sewing operation. Due to these reasons, garment manufacturers created systems to monitor and control the product’s quality regularly by conducting quality approaches to minimize variation. The aims of this research were to ascertain the quality approaches deployed by Malaysian garment manufacturers in three key areas-quality systems and tools; quality control and types of inspection; sampling procedures chosen for garment inspection. The focus of this research also aimed to distinguish quality approaches used by companies that supplied the finished garments to both domestic and international markets. The feedback from each of company’s representatives was obtained using the online survey, which comprised of five sections and 44 questions on the organizational profile and quality approaches used in the garment industry. The results revealed that almost all companies had established their own mechanism of process control by conducting a series of quality inspection for daily production either it was formally been set up or vice versa. Quality inspection was the predominant quality control activity in the garment manufacturing and the level of complexity of these activities was substantially dictated by the customers. AQL-based sampling was utilized by companies dealing with the export market, whilst almost all the companies that only concentrated on the domestic market were comfortable using their own sampling procedures for garment inspection. This research provides an insight into the implementation of quality approaches that were perceived as important and useful in the garment manufacturing sector, which is truly labour-intensive.

Keywords: garment manufacturing, quality approaches, quality control, inspection, Acceptance Quality Limit (AQL), sampling

Procedia PDF Downloads 447

Authors: Motahareh Fadaei

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: clustering, energy consumption‎, learning automata, underwater sensor networks

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Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

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This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

Procedia PDF Downloads 327

Authors: Nisrine Chlif, Mohammed Diouri, Amar Bentayeb

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Background: The Leaves of Brocchia cinerea (Vis.) (Asteraceae) is used traditionally and ethnomedicinally to alleviate pain, fever, and inflammation conditions. Objective: The current study investigates the anti-inflammatory, analgesic, and antipyretic activities of aqueous extract of the leaves of Brocchia cinerea (LBC). Material and methods: The extract was screened for anti-inflammatory (carrageenan-induced paw edema) and analgesic (acetic acid-induced writhing) activities in Wistar rats. Before acetic acid or carrageenan injection, rats were orally fed LBC (200 and 400 mg/ kg), Indomethacin (10 mg/kg), or Aspirin (100 mg/kg). The antipyretic effect was studied in brewer’s yeast-induced pyrexia model in rats using Paracetamol (100 mg/kg) as a standard drug. Results: The crude extract tested significantly prevented the increase in paw volume as compared to the control at 200 mg/kg and 400 mg/kg. The LBC treatment significantly inhibited pain at 400 mg/kg with a percent inhibition of 55.82%, as well as showing a significant reduction in hyperpyrexia in rats at 400 mg/kg. LBC extract produced a comparable activity to paracetamol at 100 mg/kg (p <0.01). Conclusion: The results of the present study that the leaves of B. cinerea extract exhibited strongly anti-inflammatory, analgesic, and antipyretic properties and justify the traditional use of this plant in inflammation, pain, and fever.

Keywords: analgesic, anti-inflammation, antipyretic, brocchia cinerea

Procedia PDF Downloads 161

Authors: Azyz Sharafy

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3D Text Toys is an innovative and creative approach that utilizes 3D text objects to enhance creativity, literacy, and basic learning in an enjoyable and gamified manner. By using 3D Text Toys, children can develop their creativity, visually learn words and texts, and apply their artistic talents within their creative abilities. This process incorporates haptic engagement with 2D and 3D texts, word building, and mechanical construction of everyday objects, thereby facilitating better word and text retention. The concept involves constructing visual objects made entirely out of 3D text/words, where each component of the object represents a word or text element. For instance, a bird can be recreated using words or text shaped like its wings, beak, legs, head, and body, resulting in a 3D representation of the bird purely composed of text. This can serve as an art piece or a learning tool in the form of a 3D text toy. These 3D text objects or toys can be crafted using natural materials such as leaves, twigs, strings, or ropes, or they can be made from various physical materials using traditional crafting tools. Digital versions of these objects can be created using 2D or 3D software on devices like phones, laptops, iPads, or computers. To transform digital designs into physical objects, computerized machines such as CNC routers, laser cutters, and 3D printers can be utilized. Once the parts are printed or cut out, students can assemble the 3D texts by gluing them together, resulting in natural or everyday 3D text objects. These objects can be painted to create artistic pieces or text toys, and the addition of wheels can transform them into moving toys. One of the significant advantages of this visual and creative object-based learning process is that students not only learn words but also derive enjoyment from the process of creating, painting, and playing with these objects. The ownership and creation process further enhances comprehension and word retention. Moreover, for individuals with learning disabilities such as dyslexia, ADD (Attention Deficit Disorder), or other learning difficulties, the visual and haptic approach of 3D Text Toys can serve as an additional creative and personalized learning aid. The application of 3D Text Toys extends to both the English language and any other global written language. The adaptation and creative application may vary depending on the country, space, and native written language. Furthermore, the implementation of this visual and haptic learning tool can be tailored to teach foreign languages based on age level and comprehension requirements. In summary, this creative, haptic, and visual approach has the potential to serve as a global literacy tool.

Keywords: 3D text toys, creative, artistic, visual learning for world literacy

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Authors: Aregamalage Sujeewa Vijayanthi Polgampala, Fang Huang

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This study explores the genesis and development of concept mapping as a useful tool for science education and its effectiveness as technique for teaching and learning and evaluation for secondary science in schools and the role played by National College of Education science teachers. Concept maps, when carefully employed and executed serves as an integral part of teaching method and measure of effectiveness of teaching and tool for evaluation. Research has shown that science concept maps can have positive influence on student learning and motivation. The success of concept maps played in an instruction class depends on the type of theme selected, the development of learning outcomes, and the flexibility of instruction in providing library unit that is equipped with multimedia equipment where learners can interact. The study was restricted to 6 male and 9 female respondents' teachers in third-year internship pre service science teachers in Gampaha district Sri Lanka. Data were collected through 15 item questionnaire provided to learners and in depth interviews and class observations of 18 science classes. The two generated hypotheses for the study were rejected, while the results revealed that significant difference exists between factors influencing teachers' choice of concept maps, its usefulness and problems hindering the effectiveness of concept maps for teaching and learning process of secondary science in schools. It was examined that concept maps can be used as an effective measure to evaluate students understanding of concepts and misconceptions. Even the teacher trainees could not identify, key concept is on top, and subordinate concepts fall below. It is recommended that pre service science teacher trainees should be provided a thorough training using it as an evaluation instrument.

Keywords: concept maps, evaluation, learning science, misconceptions

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

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We propose the use of reinforcement learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making makes it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and statistical analysis of the results. We study the generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: inventory management, reinforcement learning, supply chain optimization, uncertainty

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Authors: Ci Lin, Tet Yeap, Iluju Kiringa

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This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Nadja Ylvestedt

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Uppsala University Library is a geographically dispersed research library consisting of nine subject libraries located in different campus areas throughout the city of Uppsala. Despite the geographical dispersion, it is the library's ambition to be perceived as a cohesive library with consistently high service and quality. A key factor to being one cohesive library is the library's online services, especially the virtual reference service. E-mail, chat and phone are answered by a team of specially trained staff under the supervision of a team leader. When covid-19 hit, well-established routines and processes to provide an infrastructure for students and researchers at the university changed radically. The strong connection between services provided at the library locations as well as at the VRS has been one of the key components of the library’s success in providing patrons with the help they need. With radically minimized availability at the physical locations, the infrastructure was at risk of collapsing. Objectives:- The objective of this project has been to evaluate the consequences of the sudden change in the organization of the library. The focus of this evaluation is the library’s VRS as an important space for learning, interaction and communication between the library and the community when other traditional spaces were not available. The goal of this evaluation is to capture the lessons learned from providing infrastructure for learning and research in times of crisis both on a practical, user-centered level but also to stress the importance of leadership in ever-changing environments that supports and creates agile, flexible services and teams instead of rigid processes adhering to obsolete goals. Results:- Reduced availability at the physical library locations was one of the strategies to prevent the spread of the covid-19 virus. The library staff was encouraged to work from home, so student workers staffed the library’s physical locations during that time, leaving the VRS to be the only place where patrons could get expert help. The VRS had an increase of 65% of questions asked between spring term 2019 and spring term 2020. The VRS team had to navigate often complicated and fast-changing new routines depending on national guidelines. The VRS team has a strong emphasis on agility in their approach to the challenges and opportunities, with methods to evaluate decisions regularly with user experience in mind. Fast decision-making, collecting feedback, an open-minded approach to reviewing rules and processes with both a short-term and a long-term focus and providing a healthy work environment have been key factors in managing this crisis and learn from it. This was resting on a strong sense of ownership regarding the VRS, well-working communication tools and agile and active communication between team members, as well as between the team and the rest of the organization who served as a second-line support system to aid the VRS team. Moving forward, the VRS has become an important space for communication, interaction and provider of infrastructure, implementing new routines and more extensive availability due to the lessons learned during crisis. The evaluation shows that the virtual environment has become an important addition to the physical spaces, existing in its own right but always in connection with and in relationship with the library structure as a whole. Thereby showing that the basis of human interaction stays the same while its form morphs and adapts to changes, thus leaving the virtual environment as a space of communication and infrastructure with unique opportunities for outreach and the potential to become a staple in patron’s education and learning.

Keywords: virtual reference service, leadership, digital infrastructure, research library

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Authors: Samatha Ss Sutton, Kaouther Kooli

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In recent years social media influences (SMI) have become integrated into many companies marketing strategies to create buzz, target new and younger markets and further expand social media coverage in business (Lim et al 2017). SMI’s can be defined as online personalities with a substantial number of followers, across one or more social media platforms, with influence on their followers (Lou and Yuan 2018). Recently expenditure on influencer marketing has increased exponentially becoming an important area for marketing opportunities and strategies in the future (Lou and Yuan 2018). In order to market products and brands effectively through SMI’s it is important for business to understand the attributes of SMI that effect purchase intention (Lim et al 2017) of their followers and whether or not these attributes vary across generations so to market effectively to their specific segment or target market. The present study involves quantitative research to understand the attributes by which influence differs across generations namely Generation X and Millennials and its effects on purchase intentions of these generational groups. A survey will be conducted using an online questionnaire. Structural Equation Modelling and Multi group analysis will be applied. The study provides insight to marketers/decision makers on how to use influencers accordingly with their target consumer.

Keywords: social media marketing, social media influencers, attitude towards social media influencers, intention to purchase

Procedia PDF Downloads 138

Authors: AnjalI A. Prasad

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Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms.

Keywords: BERT, CNN, LSTM, RNN

Procedia PDF Downloads 209

Authors: Khedidja Benaicha Mati

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The present research tries to highlight a very crucial issue which exists at the level of the faculty of Economics and Management at Chlef university. This issue is represented by the challenges and difficulties which face the teaching / learning process in the faculty on the part of the language teachers, the learners, and the administration staff, including mainly the absence of an agreed syllabus, lack of teaching materials, teachers’ qualifications and training, timing, coefficient, and lack of motivation and interest amongst students. All these negative factors make teaching and learning EFL rather ambiguous, ineffective and unsatisfactory. The students at the faculty of Economics and Management are looking for acquiring not only GE but also technical English to respond efficiently to the ongoing changes at the various levels most notably economy, business, technology, and sciences. Therefore, there is a need of ESP programmes which would focus on developing the communicative competence of the learners in their specific field of study or work. The aim of the present research is to explore the ways of improving the actual situation of teaching English in the faculty of Economics and to make the English courses more purposive, fulfilling and satisfactory. The sample population focused on second and third-year students of Economics from different specialties mainly commercial sciences, insurance and banking, accountancy, and management. This is done through a questionnaire which inquires students about their learning weaknesses, difficulties and challenges they encounter, and their expectations of the subject matter.

Keywords: faculty of economics and management, challenges, teaching/ learning process, EFL, GE, ESP, English courses, communicative competence

Procedia PDF Downloads 507

Authors: Gloria Ogungbade, Ogaba Oche, Moses Duruji, Chris Ehiobuche, Lady Ajayi

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Human’s continued sustenance on earth and the quality of living are heavily dependent on the environment. The major components of the environment being air, water and land are the supporting pillars of the human existence, which they depend on directly or indirectly for survival and well-being. Unfortunately, due to some of the human activities on the environment, there seems to be a war between humans and the environment, which is evident in his over-exploitation and inadequate management of the basic components of the environment. Since the discovery of crude oil in the Niger Delta, the region has experienced various forms of degradation caused by pollution from oil spillage, gas flaring and other forms of environmental pollution, as a result of reckless way and manner with which oil is being exploited by the International Oil Corporations (IOCs) operating within the region. The Nigerian government on the other, not having strong regulations guiding the activities of the operations of these IOCs, has done almost nothing to curtail the activities of these IOCs because of the revenue generated the IOCs, as such the region is deprived of the basic social amenities and infrastructures. The degree of environmental pollution suffered within the region affects their major sources of livelihood – being fishing and farming, and has also left the region in poverty, which has led to a large number of people migrating to the urban areas to escape poverty. This paper investigates how environment degradation impact urbanization and security in the region.

Keywords: environmental degradation, environmental pollution, gas flaring, oil spillage, urbanization

Procedia PDF Downloads 292

Authors: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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Authors: Karen Jacob

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Over the last decades, there has been a rise in the use of CLIL (content and language integrated learning) methodology as a way of reinforcing FL (foreign language) acquisition. CLIL techniques have also been transferred to the formal instruction-based FL classroom where through content-based lessons and project work it can very often say that teachers are ‘clilling’ in the FL classroom. When it comes to motivating students to acquire an FL, we have to take into account that English is not your run-of-the-mill FL: English is an international language (EIL). Consequently, this means that EFL students should be able to use English as an international medium of communication. This leads to the assumption that along with FL competence, speakers of EIL will need to become competent international citizens with knowledge of other societies, both contextually and geographically, and be flexible, open-minded, respectful and sensitive towards other world groups. Rather than ‘intercultural’ competence we should be referring to ‘transcultural’ competence. This paper reports the implementation of a content- and task-based approach to EFL teaching which was applied to two groups of 15 year-olds from two schools on the Spanish island of Mallorca during the school year 2015-2016. Students worked on three units of work that aimed at ‘internationalising’ the classroom by introducing topics that would encourage them to become transculturally aware of the world in which they live. In this paper we discuss the feedback given by the teachers and students on various aspects of the approach in order to answer the following research questions: 1) To what extent were the students motivated by the content and activities of the classes?; 2) Did this motivation have a positive effect on the students’ overall results for the subject; 3) Did the participants show any signs of becoming transculturally aware. Preliminary results from qualitative data show that the students enjoyed the move away from the more traditional EFL content and, as a result, they became more competent in speaking and writing. Students also appeared to become more knowledgeable and respectful towards the ‘other’. The EFL approach described in this paper takes a more qualitative approach to research by describing what is really going on in the EFL classroom and makes a conscious effort to provide real examples of not only the acquisition of linguistic competence but also the acquisition of other important communication skills that are of utmost importance in today's international arena.

Keywords: CLIL, content- and task-based learning, internationalisation, transcultural competence

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Authors: Yuanyuan Liu, Yuanqing Wang, Di Li

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Carbon dioxide (CO2) emissions mitigation from road construction activities is one of the potential pathways to deal with climate change due to its higher use of materials, machinery energy consumption, and high quantity of vehicle and equipment fuels for transportation and on-site construction activities. Aiming to assess the environmental impact of the road infrastructure construction activities and to identify hotspots of emissions sources, this study developed a life-cycle CO2 emissions assessment framework covering three stages of material production, to-site and on-site transportation under the guidance of the principle of LCA ISO14040. Then streamlined inventory analysis on sub-processes of each stage was conducted based on the budget files from cases of highway projects in China. The calculation results were normalized into functional unit represented as ton per km per lane. Then a comparison between the amount of emissions from each stage, and sub-process was made to identify the major contributor in the whole highway lifecycle. In addition, the calculating results were used to be compared with results in other countries for understanding the level of CO2 emissions associated with Chinese road infrastructure in the world. The results showed that materials production stage produces the most of the CO2 emissions (for more than 80%), and the production of cement and steel accounts for large quantities of carbon emissions. Life cycle CO2 emissions of fuel and electric energy associated with to-site and on-site transportation vehicle and equipment are a minor component of total life cycle CO2 emissions from highway project construction activities. Bridges and tunnels are dominant large carbon contributor compared to the road segments. The life cycle CO2 emissions of road segment in highway project in China are slightly higher than the estimation results of highways in European countries and USA, about 1500 ton per km per lane. In particularly, the life cycle CO2 emissions of road pavement in majority cities all over the world are about 500 ton per km per lane. However, there is obvious difference between the cities when the estimation on life cycle CO2 emissions of highway projects included bridge and tunnel. The findings of the study could offer decision makers a more comprehensive reference to understand the contribution of road infrastructure to climate change, especially understand the contribution from road infrastructure construction activities in China. In addition, the identified hotspots of emissions sources provide the insights of how to reduce road carbon emissions for development of sustainable transportation.

Keywords: carbon dioxide emissions, construction activities, highway, life cycle assessment

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Authors: André M. Senna, Mary L. G. S. Senna, Rosa M. Machado-de-Sena

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One of the great challenges presented in educational practice is how to ensure the students not only acquire knowledge of training courses throughout their academic life, but also how to apply it in their current professional activities. Consequently, aiming to incite changes in the education system of healthcare professionals noticed the inadequacy of the training providers to solve the social problems related to health, the education related to these procedures should initiate in the earliest years of process. Following that idea, there is another question that needs an answer: If the change in the education should start sooner, in the period of basic training of healthcare professionals, what guidelines should a permanent education program incorporate to promote changes in an already established system? For this reason, the objective of this paper is to present different views of the teaching-learning process, with the purpose of better understanding the behavior adopted by healthcare professionals, through bibliographic study. The conclusion was that more than imparting knowledge to the individual, a larger approach is necessary on permanent education programs concerning the performance of professional health services in order to foment significant changes in education.

Keywords: Health Education, continuing education, training, behavior

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Authors: Malik Ghulam Behlol, Alison Fox, Faiza Masood, Sabiha Arshad

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This paper explores the barriers to the application of learning-supportive assessment at teaching practicum while investigating the role of university teachers (UT), cooperative teachers (CT), prospective teachers ( PT) and heads of the practicum schools (HPS) in the selected universities of Pakistan and the UK. It is a qualitative case study and data were collected through the lesson observation of UT in the pre-service teacher education setting and PT in practicum schools. Interviews with UT, HPS, and Focus Group Discussions with PT were conducted too. The study has concluded that as compared to the UK counterpart, PT in Pakistan faces significant barriers in applying learning-supportive assessment in the school practicum settings because of large class sizes, lack of institutionalised collaboration between universities and schools, poor modelling of the lesson, ineffective feedback practices, lower order thinking assignments, and limited opportunities to use technology in school settings.

Keywords: assessment, pre-service teacher education, theory-practice gap, teacher education

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Authors: Kathaleeya Chanda

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The schools under the Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn in Nakhonnayok Educational Service Area Office are the small schools, situated in a remote and undeveloped area.Thus, the school-age youth didn’t have or have fewer opportunities to study at the higher education level which can lead to many social and economic problems. This study aims to solve these educational issues of the schools, under The Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn, Nakhonnayok Educational Service Area Office, by the development of teachers, so that teachers could develop teaching and learning system with the ultimate goal to increase students’ academic achievement, increase the educational opportunities for the youth in the area, and help them learn happily. 154 in-service teachers from 22 schools and 4 different districts in Nakhonnayok participated in this teacher training. Most teachers were satisfied with the training content and the trainer. Thereafter, the teachers were given the test to assess the skills and knowledge after training. Most of the teachers earned a score higher than 75%. Accordingly, it can be concluded that after attending the training, teachers have a clear understanding of the contents. After the training session, the teachers have to write a lesson plan that is integrated or adapted to the Sufficiency Economy Philosophy. The teachers can either adopt intradisciplinary or interdisciplinary integration according to their actual teaching conditions in the school. Two weeks after training session, the researchers went to the schools to discuss with the teachers and follow up the assigned integrated lesson plan. It was revealed that the progress of integrated lesson plan could be divided into 3 groups: 1) the teachers who have completed the integrated lesson plan, but are concerned about the accuracy and consistency, 2) teachers who almost complete the lesson plan or made a great progress but are still concerned, confused in some aspects and not fill in the details of the plan, and 3), the teachers who made few progress, are uncertain and confused in many aspects, and may had overloaded tasks from their school. However, a follow-up procedure led to the commitment of teachers to complete the lesson plan. Regarding student learning assessment, from an experiment teaching, most of the students earned a score higher than 50 %. The rate is higher than the one from actual teaching. In addition, the teacher have assessed that the student is happy, enjoys learning, and providing a good cooperates in teaching activities. The students’ interview about the new lesson plan shows that they are happy with it, willing to learn, and able to apply such knowledge in daily life. Integrated lesson plan can increases the educational opportunities for youth in the area.

Keywords: sufficiency, economy, philosophy, integrated education syllabus

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Authors: Leigh Ann Wilson, Melanie Borrego

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The purpose of institutional learning outcomes (ILOs) is to assess what students across the university know and what they do not. The issue is gathering this information in a systematic and usable way. This presentation will explain how one institution has engineered this process for both student success and maximum faculty curriculum and course design input. At Brandman University, there are three levels of learning outcomes: course, program, and institutional. Institutional Learning Outcomes (ILOs) are mapped to specific courses. Faculty course developers write the signature assignments (SAs) in alignment with the Institutional Learning Outcomes for each course. These SAs use a specific rubric that is applied consistently by every section and every instructor. Each year, the 12-member General Education Team (GET), as a part of their work, conducts the calibration and assessment of the university-wide SAs and the related rubrics for one or two of the five ILOs. GET members, who are senior faculty and administrators who represent each of the university's schools, lead the calibration meetings. Specifically, calibration is a process designed to ensure the accuracy and reliability of evaluating signature assignments by working with peer faculty to interpret rubrics and compare scoring. These calibration meetings include the full time and adjunct faculty members who teach the course to ensure consensus on the application of the rubric. Each calibration session is chaired by a GET representative as well as the course custodian/contact where the ILO signature assignment resides. The overall calibration process GET follows includes multiple steps, such as: contacting and inviting relevant faculty members to participate; organizing and hosting calibration sessions; and reviewing and discussing at least 10 samples of student work from class sections during the previous academic year, for each applicable signature assignment. Conversely, the commitment for calibration teams consist of attending two virtual meetings lasting up to three hours in duration. The first meeting focuses on interpreting the rubric, and the second meeting involves comparing scores for sample work and sharing feedback about the rubric and assignment. Next, participants are expected to follow all directions provided and participate actively, and respond to scheduling requests and other emails within 72 hours. The virtual meetings are recorded for future institutional use. Adjunct faculty are paid a small stipend after participating in both calibration meetings. Full time faculty can use this work on their annual faculty report for "internal service" credit.

Keywords: assessment, assurance of learning, course design, institutional learning outcomes, rubrics, signature assignments

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Pirada Techaratpong

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This qualitative research has 2 objectives: to study marketing management of the cultural learning center in Suansunandha Rajabhat University and to suggest guidelines to improve its marketing management. This research is based on a case study of the Arts and Culture Office in Suansunandha Rajabhat University, Bangkok. This research found the Art and Culture Office has no formal marketing management. However, the marketing management is partly covered in the overall business plan, strategic plan, and action plan. The process can be divided into 5 stages. The marketing concept has long been introduced to its policy but not apparently put into action due to inflexible system. Some gaps are found in the process. The research suggests the Art and Culture Office implement the concept of marketing orientation, meeting the needs and wants of its target customers and adapt to the changing situation. Minor guidelines for improvement are provided.

Keywords: cultural learning center, marketing, management, museum

Procedia PDF Downloads 387

Authors: Temesgen Yadeta, Abbi Lemma, Maina Faith, Adula Bekele Hunde

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Effective teaching plays a central role in students’ success in school. The main purpose of the study was to understand how engaging in a lesson study could help to develop secondary school mathematics teachers’ effective teaching practices to support students’ learning better. The research was conducted in Jimma City and employed design-based research with qualitative and quantitative data collected from two secondary schools and 12 mathematics teachers. A purposive sampling technique was used to select participants. Interviews, observations, document analysis, and questionnaires were the main sources of data. Qualitative data were analyzed through coding, categorizing, and thematizing supported by Atlas-ti qualitative data analysis software. Quantitative data were analyzed using mean, standard deviations, medians, and a Wilcoxon-ranked signed test supported by statistical packages for social sciences software. The findings of the study revealed that engaging in lesson study built mathematics teachers’ effective teaching practices. School leaders’ positive attitudes and initiative towards the lesson study were found to be supportive. Teachers’ collaboration, commitment with determination, and active participation during the study periods were also found to be supportive. Shortage of time and teachers’ high teaching load had constrained teachers’ active engagement in lesson study during study periods. In conclusion, the lesson study provided a more practical link between teachers’ professional learning activities and actual classroom practices. Therefore, it would be crucial to integrate lesson study into the present school-based teachers’ pedagogical capacity-building program in the country. It would also be beneficial to extend the merits of lesson study to other school subjects and more schools in the country based on their specific school contexts to build teachers’ effective teaching practices.

Keywords: effective teaching practices, lesson study, mathematics teachers, professional development, secondary school

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Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle

Abstract:

The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.

Keywords: complex-valued signal processing, synthetic aperture radar, 2-D radar imaging, compressive sensing, sparse Bayesian learning

Procedia PDF Downloads 135

Authors: M. Roberts Masillamani

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There is a phenomenal difference, as regard to the teaching methodology adopted at the urban and the rural area colleges. However, bright and talented student may be from rural back ground even. But there is huge dearth of the digitization in the rural areas and lesser developed countries. Today’s students need new skills to compete and successful in the future. Education should be combination of practical, intellectual, and social skills. What does this mean for rural classrooms and how can it be achieved. Rural colleges are not able to hire the best resources, since the best teacher’s aim is to move towards the city. If city is provided everywhere, then there will be no rural area. This is possible by forming university clusters (UC). The University cluster is a group of renowned and accredited universities coming together to bridge this dearth. The UC will deliver the live lectures and allow the students’ from remote areas to actively participate in the classroom. This paper tries to present a plan of action of providing a better live classroom teaching and learning system from the city to the rural and the lesser developed countries. This paper titled “University Clusters using ICT for teaching and learning” provides a true concept of opening live digital classroom windows for rural colleges, where resources are not available, thus reducing the digital divide. This is different from pod casting a lecture or distance learning and eLearning. The live lecture can be streamed through digital equipment to another classroom. The rural students can collaborate with their peers and critiques, be assessed, collect information, acquire different techniques in assessment and learning process. This system will benefit rural students and teachers and develop socio economic status. This will also will increase the degree of confidence of the Rural students and teachers. Thus bringing about the concept of ‘Train the Trainee’ in reality. An educational university cloud for each cluster will be built remote infrastructure facilities (RIF) for the above program. The users may be informed, about the available lecture schedules, through the RIF service. RIF with an educational cloud can be set by the universities under one cluster. This paper talks a little more about University clusters and the methodology to be adopted as well as some extended features like, tutorial classes, library grids, remote laboratory login, research and development.

Keywords: lesser developed countries, digital divide, digital learning, education, e-learning, ICT, library grids, live classroom windows, RIF, rural, university clusters and urban

Procedia PDF Downloads 476

Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Iyad Alazzam, Kenneth Magel, Izzat Alsmadi

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The different activities and approaches in software testing try to find the most possible number of errors or failures with the least amount of possible effort. Mutation is a testing approach that is used to discover possible errors in tested applications. This is accomplished through changing one aspect of the software from its original and writes test cases to detect such change or mutation. In this paper, we present a mutation approach for testing software components integration aspects. Several mutation operations related to components integration are described and evaluated. A test case study of several open source code projects is collected. Proposed mutation operators are applied and evaluated. Results showed some insights and information that can help testing activities in detecting errors and improving coverage.

Keywords: software testing, integration testing, mutation, coverage, software design

Procedia PDF Downloads 434

Authors: Silka Abyadati, Dadi Rusdiana, Enjang Akhmad Juanda

Abstract:

This study aims to investigate the students’ mastery concepts enhancement between students who are studying by using Integrated Real-Life Video and Animation (IRVA) and students who are studying without using IRVA. The development of IRVA is conducted by five stages: Analyze, Design, Development, Implementation and Evaluation (ADDIE) based on constructivist for Rotational Dynamics material in Physics learning. A constructivist model-based learning used is Interpretation Construction (ICON), which has the following phases: 1) Observation, 2) Construction interpretation, 3) Contextualization prior knowledge, 4) Conflict cognitive, 5) Learning cognitive, 6) Collaboration, 7) Multiple interpretation, 8) Multiple manifestation. The IRVA is developed for the stages of observation, cognitive conflict and cognitive learning. The sample of this study consisted of 32 students experimental group and a control group of 32 students in class XI of the school year 2015/2016 in one of Senior High Schools Bandung. The study was conducted by giving the pretest and posttest in the form of 20 items of multiple choice questions to determine the enhancement of mastery concept of Rotational Dynamics. Hypothesis testing is done by using T-test on the value of N-gain average of mastery concepts. The results showed that there is a significant difference in an enhancement of students’ mastery concepts between students who are studying by using IRVA and students who are studying without IRVA. Students in the experimental group increased by 0.468 while students in the control group increased by 0.207.

Keywords: ADDIE, constructivist learning, Integrated Real-Life Video and Animation, mastery concepts, rotational dynamics

Procedia PDF Downloads 234