Search results for: project based learning

Authors: Kien Tsong Chau, Zarina Samsudin, Wan Ahmad Jaafar Wan Yahaya

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The paper examined the capability of a prototype of a tangible multimedia system that was augmented with tangible objects in motivating young preschoolers in learning. Preschoolers’ learning behaviour is highly captivated and motivated by external physical stimuli. Hence, conventional multimedia which solely dependent on digital visual and auditory formats for knowledge delivery could potentially place them in inappropriate state of circumstances that are frustrating, boring, or worse, impede overall learning motivations. This paper begins by discussion with the objectives of the research, followed by research questions, hypotheses, ARCS model of motivation adopted in the process of macro-design, and the research instrumentation, Persuasive Multimedia Motivational Scale was deployed for measuring the level of motivation of subjects towards the experimental tangible multimedia. At the close, a succinct description of the findings of a relevant research is provided. In the research, a total of 248 preschoolers recruited from seven Malaysian kindergartens were examined. Analyses revealed that the tangible multimedia system improved preschoolers’ learning motivation significantly more than conventional multimedia. Overall, the findings led to the conclusion that the tangible multimedia system is a motivation conducive multimedia for preschoolers.

Keywords: Tangible multimedia, preschooler, motivation, multimedia.

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Authors: P. Bogas

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As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences resulted from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the students' response can be described as: students who reinforce the initial deep approach, students who maintain the initial deep approach level and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to a possible adoption of deep approaches to learning, since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding to the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: Experiential learning, higher education, marketing, mixed methods, reflective thinking.

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Authors: D. Hişam, S. İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three ML models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest (RF) Classifier was the most accurate model.

Keywords: Vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting.

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Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua

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The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.

Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.

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Authors: Wafa Labib

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Teaching methods include lectures, workshops and tutorials for the presentation and discussion of ideas have become out of date; were developed outside the discipline of architecture from the college of engineering and do not satisfy the architectural students’ needs and causes them many difficulties in integrating structure into their design. In an attempt to improve structure teaching methods, this paper focused upon proposing a supportive teaching/learning tool using multi-media applications which seeks to better meet the architecture student’s needs and capabilities and improve the understanding and application of basic and intermediate structural engineering and technology principles. Before introducing the use of multi-media as a supportive teaching tool, a questionnaire was distributed to third year students of a structural design course who were selected as a sample to be surveyed forming a sample of 90 cases. The primary aim of the questionnaire was to identify the students’ learning style and to investigate whether the selected method of teaching could make the teaching and learning process more efficient. Students’ reaction on the use of this method was measured using three key elements indicating that this method is an appropriate teaching method for the nature of the students and the course as well.

Keywords: Teaching Method, Architecture, Learning style, Multi-Media.

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Authors: K´evin Fernagut, Olivier Flauzac, Erick M. Gallegos R, Florent Nolot

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The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-based Virtual Machine (KVM), LinuX Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: Containerization, containers, cyber-security, cyber-attacks, isolation, performance, security, virtualization, virtual machines.

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Authors: Young-Seok Choi

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Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a “backdoor” to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.

Keywords: Cerebellar ataxia, Electroencephalogram, brain-computer interface, motor imagery.

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Authors: Ju-Young Kim, Tae-Heon Moon, Jung-Hun Cho

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Urban regeneration projects have been actively promoted in Korea. In particular, Jeonju Hanok Village is evaluated as one of representative cases in terms of utilizing local cultural heritage sits in the urban regeneration project. However, recently, there has been a growing concern in this area, due to the ‘gentrification’, caused by the excessive commercialization and surging tourists. This trend was changing land and building use and resulted in the loss of identity of the region. In this regard, this study analyzed the land use transformation between 2010 and 2016 to identify the commercialization trend in Jeonju Hanok Village. In addition, it conducted SNS big data analysis on Jeonju Hanok Village from February 14th, 2016 to March 31st, 2016 to identify visitors’ awareness of the village. The study results demonstrate that rapid commercialization was underway, unlikely the initial intention, so that planners and officials in city government should reconsider the project direction and rebuild deliberate management strategies. This study is meaningful in that it analyzed the land use transformation and SNS big data to identify the current situation in urban regeneration area. Furthermore, it is expected that the study results will contribute to the vitalization of regeneration area.

Keywords: Land use, SNS, text mining, urban regeneration.

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Authors: Simran Ballani

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The purpose of this paper is to call education professionals to implement etiquette and public speaking skills for preschoolers, primary, middle and higher school students. In this paper the author aims to present importance of etiquette learning and public speaking curriculum for preschoolers, reflect on experiences from implementation of the curriculum and discuss the effect of the said implementation on higher education/global job market. Author’s aim to introduce this curriculum was to provide children with innovative learning and all around development. This training of soft skills at kindergarten level can have a long term effect on their social behaviors which in turn can contribute to professional success once they are ready for campus recruitment/global job markets. Additionally, if preschoolers learn polite, appropriate behavior at early age, it will enable them to become more socially attentive and display good manners as an adult. It is easier to nurture these skills in a child rather than changing bad manners at adulthood. Preschool/Kindergarten education can provide the platform for children to learn these crucial soft skills irrespective of the ethnicity, economic or social background they come from. These skills developed at such early years can go a long way to shape them into better and confident individuals. Unfortunately, accessibility of the etiquette learning and public speaking skill education is not standardized in pre-primary or primary level and most of the time embedding into the kindergarten curriculum is next to nil. All young children should be provided with equal opportunity to learn these soft skills which are essential for finding their place in job market.

Keywords: Etiquette learning, public speaking, preschoolers, overall child development, early childhood interventions, soft skills.

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Authors: Sou Watanabe, Hiromichi Ogi, Atsuhiro Shibata, Kazunori Nomura

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As a part of STRAD project conducted by JAEA, condensation of radioactive liquid waste containing various chemical compounds using reverse osmosis (RO) membrane filter was examined for efficient and safety treatment of the liquid wastes accumulated inside hot laboratories. NH₄⁺ ion in the feed solution was successfully concentrated, and NH₄⁺ ion involved in the effluents became lower than target value; 100 ppm. Solidification of simulated aqueous and organic liquid wastes was also tested. Those liquids were successfully solidified by adding cement or coagulants. Nevertheless, optimization in materials for confinement of chemicals is required for long time storage of the final solidified wastes.

Keywords: Radioactive liquid waste, condensation, solidification, STRAD project.

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Authors: Rekha Kandwal, Kamal K.Bharadwaj

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Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.

Keywords: Censored production rules, cumulative learning, data mining, machine learning.

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Authors: C. Malça, N. Alves, A. Mateus

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This work was one of the tasks of the Manufacturing2Client project, whose objective was to develop a frontal deflector to be commercialized in the automotive industry, using new project and manufacturing methods. In this task, in particular, it was proposed to develop the ability to predict computationally the aerodynamic influence of flow in vehicles, in an effort to reduce fuel consumption in vehicles from class 3 to 8. With this aim, two deflector models were developed and their aerodynamic performance analyzed. The aerodynamic study was done using the Computational Fluid Dynamics (CFD) software Ansys CFX and allowed the calculation of the drag coefficient caused by the vehicle motion for the different configurations considered. Moreover, the reduction of diesel consumption and carbon dioxide (CO2) emissions associated with the optimized deflector geometry could be assessed.

Keywords: Aerodynamic analysis, CFD, CO2 emissions, Drag coefficient, Frontal deflector, Fuel consumption.

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Authors: K. Dimitropoulos, N. Grammalidis, I. Gragopoulos, H. Gao, Th. Heuer, M. Weinmann, S. Voit, C. Stockhammer, U. Hartmann, N. Pavlidou

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Existing ground movement surveillance technologies at airports are subjected to limitations due to shadowing effects or multiple reflections. Therefore, there is a strong demand for a new sensing technology, which will be cost effective and will provide detection of non-cooperative targets under any weather conditions. This paper aims to present a new intelligent system, developed within the framework of the EC-funded ISMAEL project, which is based on a new magnetic sensing technology and provides detection, tracking and automatic classification of targets moving on the airport surface. The system is currently being installed at two European airports. Initial experimental results under real airport traffic demonstrate the great potential of the proposed system.

Keywords: Air traffic management, magnetic sensors, multitracking, A-SMGCS.

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Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

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The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system thus the proposed solution has been verified. The paper documents how is possible to apply the new discovery knowledge to use in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: Hierarchical process control, knowledge discovery from databases, neural network.

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Authors: Y. A. Adla, R. Soubra, M. Kasab, M. O. Diab, A. Chkeir

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Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals out of which 11 were chosen based on their Intraclass Correlation Coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, five features were introduced to the Linear Discriminant Analysis classifier and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90% respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

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Authors: S. Homrossukon, A. Anurathapunt

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This is an application research presenting the improvement of production quality using the six sigma solutions and the analyses of benefit-cost ratio. The case of interest is the production of tile-concrete. Such production has faced with the problem of high nonconforming products from an inappropriate surface coating and had low process capability based on the strength property of tile. Surface coating and tile strength are the most critical to quality of this product. The improvements followed five stages of six sigma solutions. After the improvement, the production yield was improved to 80% as target required and the defective products from coating process was remarkably reduced from 29.40% to 4.09%. The process capability based on the strength quality was increased from 0.87 to 1.08 as customer oriented. The improvement was able to save the materials loss for 3.24 millions baht or 0.11 million dollars. The benefits from the improvement were analyzed from (1) the reduction of the numbers of non conforming tile using its factory price for surface coating improvement and (2) the materials saved from the increment of process capability. The benefit-cost ratio of overall improvement was high as 7.03. It was non valuable investment in define, measure, analyses and the initial of improve stages after that it kept increasing. This was due to there were no benefits in define, measure, and analyze stages of six sigma since these three stages mainly determine the cause of problem and its effects rather than improve the process. The benefit-cost ratio starts existing in the improve stage and go on. Within each stage, the individual benefitcost ratio was much higher than the accumulative one as there was an accumulation of cost since the first stage of six sigma. The consideration of the benefit-cost ratio during the improvement project helps make decisions for cost saving of similar activities during the improvement and for new project. In conclusion, the determination of benefit-cost ratio behavior through out six sigma implementation period provides the useful data for managing quality improvement for the optimal effectiveness. This is the additional outcome from the regular proceeding of six sigma.

Keywords: Six Sigma Solutions, Process Improvement, QualityManagement, Benefit Cost Ratio

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Authors: Sandoval Villa Héctor, Estrada Velazco Evaristo, Chavarría Alamilla Luis

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Pleurotus ostreatus is a common edible mushroom with a number of properties that can help to solve the nutritional and economical problems of people in Chiapas, Mexico. The objective of this project was to produce the mushroom under a sustainable management in which only regional products were allowed as a way to promote the cultivation and consumption of Pleurotus ostreatus; 5 different substrates were tested as well as 2 sanitation methods. The obtained results showed that the highest yields were obtained using corn husk and a thermal sanitation method. Pests and diseases were not a problem during the project but they appeared more in the substrates sanitized with calcium hydroxide.

Keywords: Pleurotus ostreatus, substrates, sanitation.

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Authors: Ronbanchob Apiratikul

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This research studied recycled waste by the Recyclable Material Bank Project of 4 universities in the central region of Thailand for the evaluation of reducing greenhouse gas emissions compared with landfilling activity during July 2012 to June 2013. The results showed that the projects collected total amount of recyclable wastes of about 911,984.80 kilograms. Office paper had the largest amount among these recycled wastes (50.68% of total recycled waste). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables, and metal, respectively. The project reduced greenhouse gas emissions equivalent to about 2814.969 metric tons of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gas emissions is office paper which is 70.16% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metals, mixed recyclables, and glass, respectively.

Keywords: Recycling, garbage bank, waste management, recyclable wastes, greenhouse gasses.

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: Actionable pattern discovery, education, emotion, data mining.

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Authors: Julinda Keçi

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In many countries, governments have been promoting the involvement of private sector entities to enter into long-term agreements for the development and delivery of large infrastructure projects, with a focus on overcoming the limitations upon public fund of the traditional approach. The involvement of private sector through public private partnerships (PPP) brings in new capital investments, value for money and additional risks to handle. Worldwide research studies have shown that an objective, systematic, reliable and useroriented risk assessment process and an optimal allocation mechanism among different stakeholders is crucial to the successful completion. In this framework, this paper, which is the first stage of a research study, aims to identify the main risks for the delivery of PPP projects. A review of cross-countries research projects and case studies was performed to map the key risks affecting PPP infrastructure delivery. The matrix of mapping offers a summary of the frequency of factors, clustered in eleven categories: construction, design, economic, legal, market, natural, operation, political, project finance, project selection and relationship. Results will highlight the most critical risk factors, and will hopefully assist the project managers in directing the managerial attention in the further stages of risk allocation.

Keywords: Construction, infrastructure, public private partnerships, risks.

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Authors: Nasrin Farajiparvar

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In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.

Keywords: Condition-based maintenance, Economic savings, Iran industries, Machine life prediction software.

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Authors: Saidu Ibrahim, Winston M. W. Shakantu

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The problem of construction material waste remains unresolved, as a significant percentage of the materials delivered to some project sites end up as waste which might result in additional project cost. Cost overrun is a problem which affects 90% of the completed projects in the world. The argument on how to eliminate it has been on-going for the past 70 years, but there is neither substantial improvement nor significant solution for mitigating its detrimental effects. Research evidence has proposed various construction cost overruns and material-waste management approaches; nonetheless, these studies failed to give a clear indication on the framework and the equation for managing construction material waste and cost overruns. Hence, this research aims to develop a conceptual framework and a mathematical equation for managing material waste and cost overrun in the construction industry. The paper adopts the desktop methodological approach. This involves comparing the causes of material waste and those of cost overruns from the literature to determine the possible relationship. The review revealed a relationship between material waste and cost overrun that; increase in material waste would result to a corresponding increase in the amount of cost overrun at both the pre-contract and the post contract stages of a project. It was found from the equation that achieving an effective construction material waste management must ensure a “Good Quality-of-Planning, Estimating, and Design Management” and a “Good Quality- of-Construction, Procurement and Site Management”; a decrease in “Design Complexity” which would reduce “Material Waste” and subsequently reduce the amount of cost overrun by 86.74%. The conceptual framework and the mathematical equation developed in this study are recommended to the professionals of the construction industry.

Keywords: Conceptual framework, cost overrun, material waste, project stags.

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Authors: Md. Athar Imtiaz, Abduljalil S. Al-Mudhary, Md. Taha Mirhashemi, Roslina Ibrahim

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Information Technology (IT) is being used by almost all organizations throughout the world. However its success at supporting and improving business is debatable. There is always the risk of IT project failure and studies have proven that a large number of IT projects indeed do fail. There are many components that further the success of IT projects; these have been studied in previous studies. Studies have found the most necessary components for success in software development projects, executive information systems etc. In this study previous literatures that have looked into these success promoting factors have been critically reviewed and analyzed. 15 Critical Success Factors (CSF) of IT projects were enlisted and examined. These factors can be applied to all IT projects and is not specific to a particular type of IT/IS project. A hypothesis was also generated after the evaluation of the factors.

Keywords: Critical Success Factors, CSF, IT Projects, IS Projects, Software Development Projects.

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Authors: Mustafa Engin Başoğlu, Bekir Çakir

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Since large part of electricity is generated by using fossil based resources, energy is an important agenda for countries. In this context, renewable energy sources are alternative to conventional sources due to the depletion of fossil resources, increasing awareness of climate change and global warming concerns. Solar, wind and hydropower energy are the main renewable energy sources. Among of them, since installed capacity of wind power has increased approximately eight times between 2008 - November of 2014, wind energy is a promising source for Turkey. Furthermore, signing of Kyoto Protocol can be accepted as a milestone for Turkey's energy policy. Turkish Government has announced Vision 2023 (energy targets by 2023) in 2010-2014 Strategic Plan prepared by Ministry of Energy and Natural Resources (MENR). Energy targets in this plan can be summarized as follows: Share of renewable energy sources in electricity generation is 30% of total electricity generation by 2023. Installed capacity of wind energy will be 20 GW by 2023. Other renewable energy sources such as solar, hydropower and geothermal are encouraged with new incentive mechanisms. Dependence on foreign energy is reduced for sustainability and energy security. On the other hand, since Turkey is surrounded by three coastal areas, wind energy potential is convenient for wind power application. As of November of 2014, total installed capacity of wind power plants is 3.51 GW and a lot of wind power plants are under construction with capacity 1.16 GW. Turkish government also encourages the locally manufactured equipments. In this context, one of the projects funded by private sector, universities and TUBİTAK names as MILRES is an important project aimed to promote the use wind energy in electricity generation. Within this project, wind turbine with 500 kW power has been produced and will be installed at the beginning of the 2015. After that, by using the experience obtained from the first phase of the project, a wind turbine with 2.5 MW power will be manufactured in an industrial scale.

Keywords: Wind energy, wind speed, Vision 2023, MILRES (national wind energy system), wind energy potential, Turkey.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Keywords: Censored Production Rule, Data Mining, GeneticAlgorithm, Learning Classifier System, Machine Learning, PittsburgApproach, , Reinforcement learning.

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Authors: Galeano R. Katherine, Rincon L. David, Luengas C. Lely

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This paper describes the development of an electronic instrument that looks like a flute, which is able to sense the basic musical notes being executed by a specific user. The principal function of the instrument is to teach how to play a flute. This device will generate a significant academic impact, in a field of virtual reality interactive that combine art and technology. With this example is expected to contribute in research and implementation of teaching devices around the world.

Keywords: Flute, Hardware, Learning, Virtual Reality.

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Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin

Abstract:

MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.

Keywords: Computer Vision, MediaPipe, Adaptive Boosting, Fast Dynamic Time Warping.

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Authors: Revanth Sai Kosaraju, Michael Ramscar, Melody Dye

Abstract:

Accounts of language acquisition differ significantly in their treatment of the role of prediction in language learning. In particular, nativist accounts posit that probabilistic learning about words and word sequences has little to do with how children come to use language. The accuracy of this claim was examined by testing whether distributional probabilities and frequency contributed to how well 3-4 year olds repeat simple word chunks. Corresponding chunks were the same length, expressed similar content, and were all grammatically acceptable, yet the results of the study showed marked differences in performance when overall distributional frequency varied. It was found that a distributional model of language predicted the empirical findings better than a number of other models, replicating earlier findings and showing that children attend to distributional probabilities in an adult corpus. This suggested that language is more prediction-and-error based, rather than on abstract rules which nativist camps suggest.

Keywords: Abstractness, child psychology, language acquisition, prediction and error.

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Authors: Barry Ardley, Abi Hunt, Nick Taylor

Abstract:

As a theoretical and practical framework this study uses the student as producer approach to learning in higher education, as adopted by the Lincoln International Business School, University of Lincoln, UK. Student as producer positions learners as skilled and capable agents, able to participate as partners with tutors in live research projects. To illuminate the nature of this approach to learning and to highlight its critical issues, the authors report on two guided student consultancy projects. These were set up with the assistance of two local organisations in the city of Lincoln UK. Using the student as producer model to deliver the projects enabled learners to acquire and develop a range of key skills and knowledge, not easily accessible in more traditional educational settings. This paper presents a systematic case study analysis of the eight organising principles of the student as producer model, as adopted by university tutors. The experience of tutors implementing student as producer suggests that the model can be widely applied to benefit not only the learning and teaching experiences of higher education students, and staff, but additionally, a university’s research programme and its community partners.

Keywords: Experiential learning, consultancy clients, student as producer.

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Authors: Anwar Sadat

Abstract:

Today, the Internet based communication has widen the opportunity of event monitoring system in the medical field. There is always a need of analyzing and designing secure and reliable mobile communication between the hospital and biomedical engineers mobile units. This study has been carried out to find possible solution using SIP-based event notification for alerting the technical staff about the Biomedical Device (BMD) status and Patients treatment session. The Session Initiation Protocol (SIP) can be used to create a medical event notification system. SIP can work on a variety of devices. Its adoption as the protocol of choice for third generation wireless networks allows for a robust and scalable environment. One of the advantages of SIP is that it supports personal mobility through the separation of user addressing and device addressing. The solution for Telemed alert notification system is based on SIP - Specific Event Notification. The aim of this project is to extend mobility service to the hospital technicians who are using Telemedicine system.

Keywords: Biomedical, Mobility Service, Notify, Proxy Server, SIP, Subscribe, Telemedicine.

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