Search results for: Research Training

Authors: Niall J. English, Sylvia Leatham, Maria Isabel Meza Silva, Denis P. Dowling

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The training and education of under- and post-graduate students can be promoted by more active learning especially in engineering, overcoming more passive and vicarious experiences and approaches in their documented effectiveness. However, the possibility of outreach to young pupils and school-children in primary and secondary schools is a lesser explored area in terms of Education and Public Engagement (EPE) efforts – as relates to feedback and influence on shaping 3rd-level engineering training and education. Therefore, the outreach and school-visit agenda constitutes an interesting avenue to observe how active learning, careers stimulus and EPE efforts for young children and teenagers can teach the university sector, to improve future engineering-teaching standards and enhance both quality and capabilities of practice. This intervention involved careers-outreach efforts to lead to statistical determinations of motivations towards engineering, manufacturing and training. The aim was to gauge to what extent this intervention would lead to an increased careers awareness in engineering, using the method of the schools-visits programme as the means for so doing. It was found that this led to an increase in engagement by school pupils with engineering as a career option and a greater awareness of the importance of manufacturing. 

Keywords: outreach, education and public engagement, careers, peer interactions

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Authors: F. Rashno Seydari, M. Nikafrooz

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This paper intends to study needs analysis of hearing-impaired students’ teachers in elementary schools all over Iran. The subjects of this study were 275 teachers who were teaching hearing-impaired students in elementary schools. The participants were selected by a quota sampling method. To collect the data, questionnaires of training needs consisting of 41 knowledge items and 31 performance items were used. The collected data were analyzed by using SPSS software in the form of descriptive analyses (frequency and mean) and inferential analyses (one sample t-test, paired t-test, independent t-test, and Pearson correlation coefficient). The findings of the study indicated that teachers generally have considerable needs in knowledge and performance domains. In 32 items out of the total 41 knowledge domain items and in the 27 items out of the total 31 performance domain items, the teachers had considerable needs. From the quantitative point of view, the needs of the performance domain were more than those of the knowledge domain, so they have to be considered as the first priority in training these teachers. There was no difference between the level of the needs of male and female teachers. There was a significant difference between the knowledge and performance domain needs and the teachers’ teaching experience, 0.354 and 0.322 respectively. The teachers who had been trained in working with hearing-impaired students expressed more training needs (both knowledge and performance).

Keywords: Needs analysis, hearing impaired students, hearing impaired students’ teachers, knowledge domain, performance domain.

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Authors: A. Ruimi, S. Goyal, B. M. Nour

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Interactive web-based computer simulations are needed by the medical community to replicate the experience of surgical procedures as closely and realistically as possible without the need to practice on corpses, animals and/or plastic models. In this paper, we offer a review on current state of the research on simulations of surgical threads, identify future needs and present our proposed plans to meet them. Our goal is to create a physics-based simulator, which will predict the behavior of surgical thread when subjected to conditions commonly encountered during surgery. To that end, we will i) develop three dimensional finite element models based on the Cosserat theory of elasticity ii) test and feedback results with the medical community and iii) develop a web-based user interface to run/command our simulator and visualize the results. The impacts of our research are that i) it will contribute to the development of a new generation of training for medical school students and ii) the simulator will be useful to expert surgeons in developing new, better and less risky procedures.

Keywords: Cosserat rod-theory, FEM simulations, Modeling, Surgical thread.

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Authors: Mona Soliman Habib

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This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: Beata Wentura-Dudek

Abstract:

In Sweden the needs of the labor market are regularly monitored. Test results and forecasts translate directly into the education system in this country, which is largely a state system. Sweden is one of the first countries in Europe that has used active labor market policies. It is realized that there is an active unemployment which includes a wide range of activities that can be divided into three groups: Active forms of influencing the creation of new jobs, active forms that affect the labor supply and active forms for people with disabilities. Most of the funding is allocated there for subsidized employment and training. Research conducted in Sweden shows that active forms of counteracting unemployment focused on the long-term unemployed can significantly raise the level of employment in this group.

Keywords: Sweden, research conducted in Sweden, labour market, labour market policies, unemployment, active forms of influencing the creation of new jobs, active forms of counteracting unemployment, employment, subsidized employment education.

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Authors: Chih Chin Yang, Chung Shan Sun

Abstract:

In this paper the relationships between professional competences and school curriculain IC design industry are explored. The semi-structured questionnaire survey and focus group interview is the research method. Study participants are graduates of microelectronics engineering professional departments who are currently employed in the IC industry. The IC industries are defined as the electronic component manufacturing industry and optical-electronic component manufacturing industry in the semiconductor industry and optical-electronic material devices, respectively. Study participants selected from IC design industry include IC engineering and electronic & semiconductor engineering. The human training with IC design professional competence in microelectronics engineering professional departments is explored in this research. IC professional competences of human resources in the IC design industry include general intelligence and professional intelligence.

Keywords: IC design, curricula, competence, task, duty.

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Authors: Z. Zainuddin, W. K. Lye

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In this paper, a clustering algorithm named KHarmonic means (KHM) was employed in the training of Radial Basis Function Networks (RBFNs). KHM organized the data in clusters and determined the centres of the basis function. The popular clustering algorithms, namely K-means (KM) and Fuzzy c-means (FCM), are highly dependent on the initial identification of elements that represent the cluster well. In KHM, the problem can be avoided. This leads to improvement in the classification performance when compared to other clustering algorithms. A comparison of the classification accuracy was performed between KM, FCM and KHM. The classification performance is based on the benchmark data sets: Iris Plant, Diabetes and Breast Cancer. RBFN training with the KHM algorithm shows better accuracy in classification problem.

Keywords: Neural networks, Radial basis functions, Clusteringmethod, K-harmonic means.

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Authors: Kavita Burse, Manish Manoria, Vishnu P. S. Kirar

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The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Keywords: Three term back propagation, multiplicative neuralnetwork, proportional factor, local minima.

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Authors: P. Maheshwari, M. Shapurkar

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The present research aimed at studying the awareness and attitudes of teachers towards inclusive education. The sample consisted of 60 teachers, teaching in the primary section (1st – 4th) of regular schools affiliated to the SSC board in Mumbai. Sample was selected by Multi-stage cluster sampling technique. A semi-structured self-constructed interview schedule and a self-constructed attitude scale was used to study the awareness of teachers about disability and Inclusive education, and their attitudes towards inclusive education respectively. Themes were extracted from the interview data and quantitative data was analyzed using SPSS package. Results revealed that teachers had some amount of awareness but an inadequate amount of information on disabilities and inclusive education. Disability to most (37) teachers meant “an inability to do something”. The difference between disability and handicap was stated by most as former being cognitive while handicap being physical in nature. With regard to Inclusive education, a large number (46) stated that they were unaware of the term and did not know what it meant. Majority (52) of them perceived maximum challenges for themselves in an inclusive set up, and emphasized on the role of teacher training courses in the area of providing knowledge (49) and training in teaching methodology (53). Although, 83.3% of teachers held a moderately positive attitude towards inclusive education, a large percentage (61.6%) of participants felt that being in inclusive set up would be very challenging for both children with special needs and without special needs. Though, most (49) of the teachers stated that children with special needs should be educated in regular classroom but they further clarified that only those should be in a regular classroom who have physical impairments of mild or moderate degree.

Keywords: Attitudes, awareness, inclusive education, teachers.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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Authors: Suzana Basaruddin, Haryani Haron, Siti Arpah Noodin

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Managing knowledge of research is one way to ensure just in time information and knowledge to support research strategist and activities. Unfortunately researcher found the vital research knowledge in IHL (Institutions of Higher Learning) are scattered, unstructured and unorganized. Aiming on lay aside conceptual foundations for understanding and developing OMS (Organizational Memory System) to facilitate research in IHL, this research revealed ten factors contributed to the needs of research in the IHL and seven internal challenges of IHL in promoting research to their academic members. This study then suggested a comprehensive support of managing research knowledge using Organizational Memory System (OMS). Eight OMS characteristics to support research were identified. Finally the initial work in designing OMS was projected using knowledge taxonomy. All analysis is derived from pertinent research paper related to research in IHL and OMS. Further study can be conducted to validate and verify results presented.

Keywords: corporate memory, Institutions of Higher Learning, organizational memory system, research

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Authors: José L. Jiménez

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The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: Digital tools, on-line learning, social networks, technology.

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Authors: Abd Aziz Bin Abd Shukor, Eftah Binti Moh Hj Abdullah

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This case study aims to identify teachers’ perception as regards integrity in School-Ba sed Assessment (PBS) practice. This descriptive study involved 9 teachers from 4 secondary schools in 3 districts in the state of Perak. The respondents had undergone an integrity in PBS Practice interview using a focused group discussion method. The overall findings showed that the teachers believed that integrity in PBS practice could be achieved by adjusting the teaching methods align with learning objectives and the students’ characteristics. Many teachers, parents and student did not understand the best practice of PBS. This would affect the integrity in PBS practice. Teachers did not emphasis the principles and ethics. Their integrity as an innovative public servant may also be affected with the frequently changing assessment system, lack of training and no prior action research. The analysis of findings showed that the teachers viewed that organizational integrity involving the integrity of PBS was difficult to be implemented based on the expectations determined by Malaysia Ministry of Education (KPM). A few elements which assisted in the achievement of PBS integrity were the training, students’ understanding, the parents’ understanding of PBS, environment (involving human resources such as support and appreciation and non-human resources such as technology infrastructure readiness and media). The implications of this study show that teachers, as the PBS implementers, have a strong influence on the integrity of PBS. However, the transformation of behavior involving PBS integrity among teachers requires the stabilisation of support and infrastructure in order to enable the teachers to implement PBS in an ethical manner.

Keywords: Assessment integrity, integrity, perception, school-based assessment.

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Authors: Sotiria Tzivinikou, Dimitra Kagkara

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Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: Inclusive education, pre-service, self-efficacy, training program.

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Authors: S.I Sulaiman, T.K Abdul Rahman, I. Musirin, S. Shaari

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This paper presents performance analysis of the Evolutionary Programming-Artificial Neural Network (EPANN) based technique to optimize the architecture and training parameters of a one-hidden layer feedforward ANN model for the prediction of energy output from a grid connected photovoltaic system. The ANN utilizes solar radiation and ambient temperature as its inputs while the output is the total watt-hour energy produced from the grid-connected PV system. EP is used to optimize the regression performance of the ANN model by determining the optimum values for the number of nodes in the hidden layer as well as the optimal momentum rate and learning rate for the training. The EPANN model is tested using two types of transfer function for the hidden layer, namely the tangent sigmoid and logarithmic sigmoid. The best transfer function, neural topology and learning parameters were selected based on the highest regression performance obtained during the ANN training and testing process. It is observed that the best transfer function configuration for the prediction model is [logarithmic sigmoid, purely linear].

Keywords: Artificial neural network (ANN), Correlation coefficient (R), Evolutionary programming-ANN (EPANN), Photovoltaic (PV), logarithmic sigmoid and tangent sigmoid.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour, A.V. Hoseini

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In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: Back-propagation artificial neural network(BPANN), deep drawing, prediction, limiting drawing ratio (LDR).

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Authors: Shuhe Shao

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This article provides partial evaluation index and its standard of sports aerobics, including the following 12 indexes: health vitality, coordination, flexibility, accuracy, pace, endurance, elasticity, self-confidence, form, control, uniformity and musicality. The three-layer BP artificial neural network model including input layer, hidden layer and output layer is established. The result shows that the model can well reflect the non-linear relationship between the performance of 12 indexes and the overall performance. The predicted value of each sample is very close to the true value, with a relative error fluctuating around of 5%, and the network training is successful. It shows that BP network has high prediction accuracy and good generalization capacity if being applied in sports aerobics performance evaluation after effective training.

Keywords: BP neural network, sports aerobics, performance, evaluation.

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: Audit, machine learning, assessment, metrics.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour, M. Goodarzi

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In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: BPANN, deep drawing, prediction, limiting drawingratio (LDR), Levenberg–Marquardt algorithm

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Authors: Abdullah A. AlShaher

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In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: Shape recognition, Arabic handwritten characters, regression curves, expectation maximization algorithm.

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: Palm oil, fatty acid, NIRS, regression.

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Authors: Guenther Schuh, Sebastian Woelk

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Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. Goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: Interorganizational cooperation, design of network governance, research network.

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Authors: Jiří Barta

Abstract:

The paper deals with results of a project “Interoperability Workplaces to Support Teaching of Security Management in a Computer Network". This project is focused on the perspectives and possibilities of "new approaches" to education, training and crisis communication of rescue teams in the Czech Republic. It means that common technologies considering new perspectives are used to educate selected members of crisis management. The main part concentrates on possibilities of application of new technology and computer-aided tools to education and training of Integrated Rescue System teams.This project uses the COST principle for the creation of specialized centers and for all communication between these workplaces.

Keywords: Communication of Crisis Management, Information System, Interoperability, specializedcenter, Security Oriented Information System.

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Authors: Pedro Llanos, Diego García

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Spaceflight is considered the last frontier in terms of science, technology, and engineering. But it is also the next frontier in terms of human physiology and performance. After more than 200,000 years humans have evolved under earth’s gravity and atmospheric conditions, spaceflight poses environmental stresses for which human physiology is not adapted. Hypoxia, accelerations, and radiation are among such stressors, our research involves suborbital flights aiming to develop effective countermeasures in order to assure sustainable human space presence. The physiologic baseline of spaceflight participants is subject to great variability driven by age, gender, fitness, and metabolic reserve. The objective of the present study is to characterize different physiologic variables in a population of STEM practitioners during an aerobatic flight. Cardiovascular and pulmonary responses were determined in Science Astronaut Candidates (SACs) during unusual attitude aerobatic flight indoctrination. Physiologic data recordings from 20 subjects participating in high-G flight training were analyzed. These recordings were registered by wearable sensor-vest that monitored electrocardiographic tracings (ECGs), signs of dysrhythmias or other electric disturbances during all the flight. The same cardiovascular parameters were also collected approximately 10 min pre-flight, during each high-G/unusual attitude maneuver and 10 min after the flights. The ratio (pre-flight/in-flight/post-flight) of the cardiovascular responses was calculated for comparison of inter-individual differences. The resulting tracings depicting the cardiovascular responses of the subjects were compared against the G-loads (Gs) during the aerobatic flights to analyze cardiovascular variability aspects and fluid/pressure shifts due to the high Gs. In-flight ECG revealed cardiac variability patterns associated with rapid Gs onset in terms of reduced heart rate (HR) and some scattered dysrhythmic patterns (15% premature ventricular contractions-type) that were considered as triggered physiological responses to high-G/unusual attitude training and some were considered as instrument artifact. Variation events were observed in subjects during the +Gz and –Gz maneuvers and these may be due to preload and afterload, sudden shift. Our data reveal that aerobatic flight influenced the breathing rate of the subject, due in part by the various levels of energy expenditure due to the increased use of muscle work during these aerobatic maneuvers. Noteworthy was the high heterogeneity in the different physiological responses among a relatively small group of SACs exposed to similar aerobatic flights with similar Gs exposures. The cardiovascular responses clearly demonstrated that SACs were subjected to significant flight stress. Routine ECG monitoring during high-G/unusual attitude flight training is recommended to capture pathology underlying dangerous dysrhythmias in suborbital flight safety. More research is currently being conducted to further facilitate the development of robust medical screening, medical risk assessment approaches, and suborbital flight training in the context of the evolving commercial human suborbital spaceflight industry. A more mature and integrative medical assessment method is required to understand the physiology state and response variability among highly diverse populations of prospective suborbital flight participants.

Keywords: Aerobatic maneuvers, G force, hypoxia, suborbital flight, commercial astronauts.

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Authors: Triyanto

Abstract:

Government of Indonesia held a certification program to enhance the professionalism of teachers by using portfolio assessment. This research discusses about the effectiveness of certification programs to enhance the professionalism of teacher in Indonesia. Portfolio assessment method has drawbacks. The certified teachers do not show significant performance improvement. Therefore, the government changes the portfolio assessment method to the education and training for teachers.

Keywords: Profesionalism, Teacher, Certification, Indonesia

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Authors: E. Podhovnik

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Cultures play a role in business communication and in research. At the example of language in international business, this paper addresses the issue of how the research cultures of management research and linguistics as well as cultures as such can be linked. After looking at existing research on language in international business, this paper approaches communication in international business from a linguistic angle and attempts to explain communication issues in businesses based on linguistic research. Thus the paper makes a step into cross-disciplinary research combining management research with linguistics.

Keywords: Language in international business, sociolinguistics, ethnopragmatics, cultural scripts.

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Authors: Gabriel Jinga, Madalina Dumitru

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The objective of this paper is to present the process of change in management accounting in Romania, a former communist country from Eastern Europe. In order to explain this process, we used the contingency and institutional theories. We focused on the following directions: the presentation of the scientific context and motivation of this research and the case study. We presented the state of the art in the process of change in the management accounting from the international and national perspective. We also described the evolution of management accounting in Romania in the context of economic and political changes. An important moment was the fall of communism in 1989. This represents a starting point for a new economic environment and for new management accounting. Accordingly, we developed a case study which presented this evolution. The conclusion of our research was that the changes in the management accounting system of the company analysed occurred in the same time with the institutionalisation of some elements (e.g. degree of competition, training and competencies in management accounting). The management accounting system was modelled by the contingencies specific to this company (e.g. environment, industry, strategy).

Keywords: Management accounting, change, Romania, contingency and institutional theory.

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Authors: J. F. Arthur, R. M. Hodge

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The Defence Materials Technology Centre has evolved from the Australian Cooperative Research Centres Program. The Centre receives funding from Government, industry and research sources to fund collaborative research within its participant organisations. The research centre is structured as a company with a small administrative staff and plays the role of the “honest broker” within the collaboration. A corporate culture has been established that is pervasive into the research projects are undertaken. The model is an effective mechanism to deliver outcomes to each of the participant stakeholders.

Keywords: Collaboration, Research Centre.

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Authors: Hei-Chia Wang, Wei-Pin Chiu

Abstract:

As research performance in academia is treated as one of indices for national competency, many countries devote much attention and resources to increasing their research performance. Understand the research trend is the basic step to improve the research performance. The goal of this research is to design an analysis system to evaluate research trends from analyzing data from different countries. In this paper, information system researches in Taiwan and other countries, including Asian countries and prominent countries represented by the Group of Eight (G8) is used as example. Our research found the trends are varied in different countries. Our research suggested that Taiwan-s scholars can pay more attention to interdisciplinary applications and try to increase their collaboration with other countries, in order to increase Taiwan's competency in the area of information science.

Keywords: Bibliometric analysis, research trend, scientometric analysis.

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