Search results for: Computer based training

Authors: Lin, Huifen, Fang, Yueh-chiu

Abstract:

This study explores perceptions of English as a Foreign Language (EFL) learners on using computer mediated communication technology in their learner of English. The data consists of observations of both synchronous and asynchronous communication participants engaged in for over a period of 4 months, which included online, and offline communication protocols, open-ended interviews and reflection papers composed by participants. Content analysis of interview data and the written documents listed above, as well as, member check and triangulation techniques are the major data analysis strategies. The findings suggest that participants generally do not benefit from computer-mediated communication in terms of its effect in learning a foreign language. Participants regarded the nature of CMC as artificial, or pseudo communication that did not aid their authentic communicational skills in English. The results of this study sheds lights on insufficient and inconclusive findings, which most quantitative CMC studies previously generated.

Keywords: computer-mediated communication, EFL, writing

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2549

Authors: C. Kwan, X. Li, D. Lao, Y. Deng, Z. Ren, B. Raj, R. Singh, R. Stern

Abstract:

Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.

Keywords: Non-stationary, speech recognition, voice commands.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1512

Authors: TamásMatuszka, Attila Kiss

Abstract:

Due the proliferation of smartphones in everyday use, several different outdoor navigation systems have become available. Since these smartphones are able to connect to the Internet, the users can obtain location-based information during the navigation as well. The users could interactively get to know the specifics of a particular area (for instance, ancient cultural area, Statue Park, cemetery) with the help of thus obtained information. In this paper, we present an Augmented Reality system which uses Semantic Web technologies and is based on the interaction between the user and the smartphone. The system allows navigating through a specific area and provides information and details about the sight an interactive manner.

Keywords: Augmented Reality, Semantic Web, Human Computer Interaction, Mobile Application.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2688

Authors: Isao Taguchi, Yasuo Sugai

Abstract:

This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.

Keywords: data selection, function approximation problem, multistage leaning, neural network, voluntary oscillation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1412

Authors: In Hoi Lee, Seong Baeg Kim, Je Eung Jeon, Gwang Yong Choi, Joo Sub Lee, Ik Sang Kim

Abstract:

Recently, the interest of globalization in the field of  teacher education has increased. In the U.S., the government is trying  to enhance the quality of education through a global approach in  education. To do so, the schools in the U.S. are recruiting teachers with  global capability from countries like Korea where competent teachers  are being trained. Meanwhile, in the case of Korea, although excellent  teachers have been cultivated every year, due to a low birth rate it is  not easy to become a domestic teacher. To solve the trouble that the  two countries are facing, the study first examines the demand and  necessity of globalization in the field of teacher education between  Korea and the U.S. Second, we propose a new project, called the  ‘Global Teachers University (GTU)’ program to satisfy the demands  of both countries. Finally, we provide its implications to build the  future educational cooperation for teacher training in a global context.

Keywords: Educational cooperation, globalization, teachers education program, teacher training institutions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2513

Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

Abstract:

The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: Input-Output Analysis, Monetary Input-Output Model, Manufacturing Process, Laptop Computer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4604

Authors: Sangsuree Vasupongayya

Abstract:

Fair share is one of the scheduling objectives supported on many production systems. However, fair share has been shown to cause performance problems for some users, especially the users with difficult jobs. This work is focusing on extending goaloriented parallel computer job scheduling policies to cover the fair share objective. Goal-oriented parallel computer job scheduling policies have been shown to achieve good scheduling performances when conflicting objectives are required. Goal-oriented policies achieve such good performance by using anytime combinatorial search techniques to find a good compromised schedule within a time limit. The experimental results show that the proposed goal-oriented parallel computer job scheduling policy (namely Tradeofffs( Tw:avgX)) achieves good scheduling performances and also provides good fair share performance.

Keywords: goal-oriented parallel job scheduling policies, fairshare.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1168

Authors: Nikolina Ribarić

Abstract:

E-learning is most commonly defined as a set of applications and processes, such as Web-based learning, computer-based learning, virtual classrooms and digital collaboration, that enable access to instructional content through a variety of electronic media. The main goal of an e-learning system is learning, and the way to evaluate the impact of an e-learning system is by examining whether students learn effectively with the help of that system. Testmoz is a program for online preparation of knowledge evaluation assignments. The program provides teachers with computer support during the design of assignments and evaluating them. Students can review and solve assignments and also check the correctness of their solutions. Research into the increase of motivation by the practice of providing teaching content by applying online tests prepared in the Testmoz program, was carried out with students of the 8th grade of Ljubo Babić Primary School in Jastrebarsko. The students took the tests in their free time, from home, for an unlimited number of times. SPSS was used to process the data obtained by the research instruments. The results of the research showed that students preferred to practice teaching content, and achieved better educational results in chemistry, when they had access to online tests for repetition and practicing in relation to subject content which was checked after repetition and practicing in "the classical way" – i.e., solving assignments in a workbook or writing assignments in worksheets.

Keywords: Chemistry class, e-learning, online test, Testmoz.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 499

Authors: Patricia M. Boechler, Heather M. Gautreau

Abstract:

In this research study, postsecondary students completed an information learning task in an avatar-based 3D virtual learning environment. Three factors were of interest in relation to learning; 1) the influence of collaborative vs. independent conditions, 2) the influence of the spatial arrangement of the virtual environment (linear, random and clustered), and 3) the relationship of individual differences such as spatial skill, general computer experience and video game experience to learning. Students completed pretest measures of prior computer experience and prior spatial skill. Following the premeasure administration, students were given instruction to move through the virtual environment and study all the material within 10 information stations. In the collaborative condition, students proceeded in randomly assigned pairs, while in the independent condition they proceeded alone. After this learning phase, all students individually completed a multiple choice test to determine information retention. The overall results indicated that students in pairs did not perform any better or worse than independent students. As far as individual differences, only spatial ability predicted the performance of students. General computer experience and video game experience did not. Taking a closer look at the pairs and spatial ability, comparisons were made on pairs high/matched spatial ability, pairs low/matched spatial ability and pairs that were mismatched on spatial ability. The results showed that both high/matched pairs and mismatched pairs outperformed low/matched pairs. That is, if a pair had even one individual with strong spatial ability they would perform better than pairs with only low spatial ability individuals. This suggests that, in virtual environments, the specific individuals that are paired together are important for performance outcomes. The paper also includes a discussion of trends within the data that have implications for virtual environment education.

Keywords: Avatar-based, virtual environment, paired learning, individual differences.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 754

Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

Abstract:

Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram (PCG) signals can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded PCG signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded Electrocardiograms (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show on average a segmentation testing performance average of 76% sensitivity and 94% specificity.

Keywords: Heart sounds, PCG segmentation, event detection, Recurrent Neural Networks, PCG curve length.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 272

Authors: H. M. Haytham, E. A. Azza, E.S. Mohamed, E. G. Nesreen

Abstract:

Thoracotomy is a great surgery that has serious pulmonary complications, so purpose of this study was to determine the response of diaphragmatic excursion to inspiratory muscle trainer post thoracotomy. Thirty patients of both sexes (16 men and 14 women) with age ranged from 20 to 40 years old had done thoracotomy participated in this study. The practical work was done in cardiothoracic department, Kasr-El-Aini hospital at faculty of medicine for individuals 3 days Post operatively. Patients were assigned into two groups: group A (study group) included 15 patients (8 men and 7 women) who received inspiratory muscle training by using inspiratory muscle trainer for 20 minutes and routine chest physiotherapy (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Group B (control group) included 15 patients (8 men and 7 women) who received the routine chest physiotherapy only (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Ultrasonography was used to evaluate the changes in diaphragmatic excursion before and after training program. Statistical analysis revealed a significant increase in diaphragmatic excursion in the study group (59.52%) more than control group (18.66%) after using inspiratory muscle trainer post operatively in patients post thoracotomy. It was concluded that the inspiratory muscle training device increases diaphragmatic excursion in patients post thoracotomy through improving inspiratory muscle strength and improving mechanics of breathing and using of inspiratory muscle trainer as a method of physical therapy rehabilitation to reduce post-operative pulmonary complications post thoracotomy.

Keywords: Diaphragmatic excursion, inspiratory muscle trainer, ultrasonography, thoracotomy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1536

Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

Abstract:

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3160

Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

Abstract:

The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1628

Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed. The scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: Computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 538

Authors: M. Movahedi Rad

Abstract:

In this study, a general approach to the reliability based limit analysis of laterally loaded piles is presented. In engineering practice the uncertainties play a very important role. The aim of this study is to evaluate the lateral load capacity of free-head and fixed-head long pile when plastic limit analysis is considered. In addition to the plastic limit analysis to control the plastic behaviour of the structure, uncertain bound on the complementary strain energy of the residual forces is also applied. This bound has significant effect for the load parameter. The solution to reliability-based problems is obtained by a computer program which is governed by the reliability index calculation.

Keywords: Reliability, laterally loaded pile, residual strain energy, probability, limit analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1884

Authors: A. Alrasheed, I. Connerton

Abstract:

Daily provision of high quality food and hygiene to patients is a challenging goal of the healthcare. In Saudi Arabia, matters related to food safety and hygiene are regulated by the Ministry of Health (MOH) and the Saudi Food and Drugs Authority (SFDA). The purpose of this research is to discuss the food safety management inconsistencies and flaws, in particular the ones related to Hazard Analysis and Critical Control Points (HACCP) in Riyadh’s MOH hospitals. As required by law, written HACCP regulations must be implemented, and food handlers need to receive the training accordingly. However, in Saudi hospitals, this is not a requirement, and the food handlers do not need to hold training certificates in food safety or HACCP. Nowadays, the matter of food safety and hygiene have become increasingly important since the decision makers want to align these regulations with the majority of the world and to implement HACCP fully and for this purpose, the SFDA was established. 

Keywords: Food safety, patients, hospitals, HACCP, Saudi Arabia.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1295

Authors: Young-Seok Choi

Abstract:

We present a subband adaptive infinite-impulse response (IIR) filtering method, which is based on a polyphase decomposition of IIR filter. Motivated by the fact that the polyphase structure has benefits in terms of convergence rate and stability, we introduce the polyphase decomposition to subband IIR filtering, i.e., in each subband high order IIR filter is decomposed into polyphase IIR filters with lower order. Computer simulations demonstrate that the proposed method has improved convergence rate over conventional IIR filters.

Keywords: Subband adaptive filter, IIR filtering. Polyphase decomposition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2467

Authors: Quoc-Nam Tran

Abstract:

The theory of Groebner Bases, which has recently been honored with the ACM Paris Kanellakis Theory and Practice Award, has become a crucial building block to computer algebra, and is widely used in science, engineering, and computer science. It is wellknown that Groebner bases computation is EXP-SPACE in a general polynomial ring setting. However, for many important applications in computer science such as satisfiability and automated verification of hardware and software, computations are performed in a Boolean ring. In this paper, we give an algorithm to show that Groebner bases computation is PSPACE in Boolean rings. We also show that with this discovery, the Groebner bases method can theoretically be as efficient as other methods for automated verification of hardware and software. Additionally, many useful and interesting properties of Groebner bases including the ability to efficiently convert the bases for different orders of variables making Groebner bases a promising method in automated verification.

Keywords: Algorithm, Complexity, Groebner basis, Applications of Computer Science.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1942

Authors: Kazunari Meguro, Daisuke Yamamoto, Shinichi Motomura, Toshihiko Sasama, Takao Kawamura, Kazunori Sugahara

Abstract:

We have developed a distributed asynchronous Web based training system. In order to improve the scalability and robustness of this system, all contents and functions are realized on mobile agents. These agents are distributed to computers, and they can use a Peer to Peer network that modified Content-Addressable Network. In the proposed system, only text data can be included in a exercise. To make our proposed system more useful, the mechanism that it not only adapts to multimedia data but also it doesn-t influence the user-s learning even if the size of exercise becomes large is necessary.

Keywords: e-Learning, multimedia, Mobile Agent.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1469

Authors: Sean Paulsen, Michael Casey

Abstract:

In this work, we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: Transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 97

Authors: Dewan Md. Farid, Nouria Harbi, Emna Bahri, Mohammad Zahidur Rahman, Chowdhury Mofizur Rahman

Abstract:

Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today's commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98% detection rate (DR) in comparison with other existing methods.

Keywords: Detection rate, decision tree, intrusion detectionsystem, network security.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3589

Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint

Abstract:

Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.

Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1898

Authors: Roselyn A. Maaño

Abstract:

Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may results from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: Algorithms, Blind, Computer Vision, Embedded Systems, Image Analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3569

Authors: Hui-jun Ren, Da-kun ZHang

Abstract:

VRML( The virtual reality modeling language) is a standard language used to build up 3D virtualized models. The quick development of internet technology and computer manipulation has promoted the commercialization of reality virtualization. VRML, thereof, is expected to be the most effective framework of building up virtual reality. This article has studied plans to build virtualized scenes based on the technology of virtual reality and Java programe, and introduced how to execute real-time data transactions of VRML file and Java programe by applying Script Node, in doing so we have the VRML interactivity being strengthened.

Keywords: VRML, Java, Virtual scene, Script.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1480

Authors: Shin-Jer Yang, Kai-Tai Yang

Abstract:

In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: Cloud service, multi-tenancy, NFC, IAM, mobile device.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1100

Authors: Thitaporn Thoopputra, Tipaporn Pongmesa, Shuchuen Li

Abstract:

Aims: To evaluate the application of non-invasive diabetes risk assessment tool in community pharmacy setting. Methods: Thai diabetes risk score was applied to assess individuals at risk of developing type 2 diabetes. Interactive computer-based risk screening (IT) and paper-based risk screening (PT) tools were applied. Participants aged over 25 years with no known diabetes were recruited in six participating pharmacies. Results: A total of 187 clients, mean aged (+SD) was 48.6 (+10.9) years. 35% were at high risk. The mean value of willingness-to-pay for the service fee in IT group was significantly higher than PT group (p=0.013). No significant difference observed for the satisfaction between groups. Conclusions: Non-invasive risk assessment tool, whether paper-based or computerized-based can be applied in community pharmacy to support the enhancing role of pharmacists in chronic disease management. Long term follow up is needed to determine the impact of its application in clinical, humanistic and economic outcomes.

Keywords: Community pharmacy, intervention, prevention, risk assessment, type 2 diabetes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2170

Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

Abstract:

The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: Surface flattening, Strain energy, Minimum energy, approximate implicit method, Fashion design.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2568

Authors: Somayeh Negahdari, Mohsen Ghanbarzadeh, Masoud Nikbakht, Heshmatolah Tavakol

Abstract:

Asthma, obesity and overweight are the main factors causing change within the heart and respiratory airways. Asthma symptoms are normally observed during exercising. Epidemiological studies have indicated asthma symptoms occurring due to certain lifestyle habits; for example, a sedentary lifestyle. In this study, eight weeks of aerobic exercises resulted in a positive effect overall in overweight women experiencing mild chronic asthma. The quasi-experimental applied research has been done based on experimental and control groups. The experimental group (seven patients) and control group (n = 7) were graded before and after the test. According to the Borg dyspnea and fatigue Perception Index, the training intensity has determined. Participants in the study performed a sub-maximal aerobic activity schedule (45% to 80% of maximum heart rate) for two months, while the control group (n = 7) stayed away from aerobic exercise. Data evaluation and analysis of covariance compared both the pre-test and post-test with paired t-test at significance level of P≤ 0.05. After eight weeks of exercise, the results of the experimental group show a significant decrease in resting heart rate, systolic blood pressure, minute ventilation, while a significant increase in maximal oxygen uptake and tolerance activity (P ≤ 0.05). In the control group, there was no significant difference in these parameters ((P ≤ 0.05). The results indicate the aerobic activity can strengthen the respiratory muscles, while other physiological factors could result in breathing and heart recovery. Aerobic activity also resulted in favorable changes in cardiovascular parameters, and exercise tolerance of overweight women with chronic asthma.

Keywords: Asthma, respiratory cardiac index, exercise tolerance, aerobic, overweight.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 736

Authors: Andreas Ahrens, Jelena Zascerinska

Abstract:

Emotions are crucial in online classes in adult education. Despite that, a little attention was devoted to the emotional experience of being an online teacher in the field of andragogy, and the online teacher’s emotional perspectives in ever changing environments have to be analysed. The paper aims at the analysis of teachers’ emotional experience in online classes in adult education in selected European countries. The research tends to propose implications for training of teachers who work in online classes in adult education. The survey was conducted in April 2022. In the selected European countries 78 respondents took part in the study. Among them, 30 respondents represented Germany, 28 respondents Greece, and 20 respondents were from Italy. The theoretical findings allow defining teacher emotional experience. The analysis of the elements of the respondents’ emotional experience allows concluding that teachers’ attitude to online classes has to be developed. The key content for teacher training is presented. Directions of further work are proposed.

Keywords: Adult education, online classes, teacher emotional experience, European countries.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 398

Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

Abstract:

Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4788