• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.8-12
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• 2007

In this paper, we proposed an frequency offset estimation scheme which can be used for packet based OFDM communication systems such as IEEE802.11a and IEEE802.11p physical layer. Proposed estimation scheme can adjust the gain allocation ratio between long training symbol and short training symbol while maintaining average power of overall training sequence so that we can obtain the reference parameters for MSE performance improvement. The preamble structure considered in this paper is based on the preamble specified in IEEE802.11a and IEEE802.11p standardization group. From the simulation results, it is shown that power ratio between long training symbol and short training symbol must vanes for achieving lower frequency offset estimation error as channel SNR condition is changed. Also it is known oat proposed scheme can achieve better performance than conventional one.

• Journal of Practical Engineering Education
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• v.9 no.1
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• pp.49-56
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• 2017

Recently, due to Industry 4.0, there is a great interest in smart factory for productivity improvement and customer satisfaction in manufacturing industry, and construction is also actively pursued by government support. In particular, data integration and fieldbus communication technology to build an efficient production system are essential. Fieldbus is an open control system that is not tied to a specific vendor system and has various advantages such as compatibility with other products, accuracy of data transmission, and remote diagnosis. However, there are no educational equipment for training field buses, training courses and examples for practical training, and there are many limitations in improving the practical skills needed for building smart factories in the industrial field. Therefore, this study develops PLC based fieldbus education equipment and training course based on previous research results that selected PLC and communication technology suitable for domestic industry field for practical fieldbus training and develops the training program of Ethernet IP, Profibus DP, Modbus, CC-Link, and DeviceNet. In addition, it is confirmed that the control and remote diagnosis of distributed field devices are possible by data collection and monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1749-1755
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• 2021

Virtual reality is actively applied in the fields of games, entertainment, communication, sports, and architecture. In particular, many virtual reality-based education systems are being developed in the field of education, creating efficient learning effects. In addition, virtual reality-based education is used in areas such as maintenance, fighter control, medical care, and firefighting as it can maximize the educational effect through the mastery process of the function itself through the curriculum as well as indirect experiences of dangerous situations that are difficult to experience. However, due to technical limitations, lack of contents, and lack of theoretical research, the level of application of military education and training is still insufficient. This paper aim to contribute to the development of a virtual reality-based education system as a military training system by developing a high-quality drop training system applicable to military group descent training, studying key technologies and implementation methods necessary for development.

• Journal of Distribution Science
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• v.20 no.3
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• pp.45-52
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• 2022

Purpose: This study investigated the impact of staff verbal and non-verbal communication on consumer satisfaction and revisit intention. The study sought to identify differences in demographic and eating out characteristics on perceived verbal and non-verbal communication. Research design and methodology: This study used a survey method to collect data. The questionnaire asked about previous experience with verbal and non-verbal communication with staff at a counter service restaurant. The study measured degrees of perceived verbal and non-verbal communication. In addition, the effect of verbal and non-verbal communication on satisfaction and revisit intention was measured. The principal results: Results of ANOVA showed significant differences in monthly income on verbal communication and monthly income and budget for dining out on verbal and non-verbal communication. Both verbal and non-verbal communication affected satisfaction and revisit intention significantly with slightly more power of verbal communication than non-verbal communication. Major conclusions: Results of this study suggest that consumers are affected by both verbal and non-verbal communication. Staff communication is critical to increasing consumer satisfaction and revisit intention; hence, training staff in effective communication is necessary.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.249-256
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• 2016

The International Association of Marine Aids to Navigation and Lighthouse Authorities(IALA) model course recommends specific aspects of basic curriculums for Vessel Traffic Services(VTS) operator education such as modules, course hours, contents, etc. Most domestic training programs for newly appointed VTS operators comply with such recommendations. The objective of this study is to determine whether such modules for VTS operator training recommended by the current IALA model course correspond to the actual opinions of VTS operators who are currently working in the field. To this end, the relative importance of basic modules for vessel traffic services operator training was analyzed using the Analytic Hierarchy Process(AHP) method. A questionnaire was designed to include 8 modules recommended by the IALA model course, and the survey results of 52 individuals working at 5 VTS centers were analyzed. The result showed that, unlike the assumption by the IALA, domestic VTS operators viewed Nautical Knowledge as the most important modules, followed by Emergency Situations, Traffic Management, Language, Equipment, VHF Radio, Communication Co-ordination, and Personal Attributes, in that order.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.151-162
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• 2010

A severe accident training simulator that can simulate important severe accident phenomena and nuclear plant behaviors is developed. The simulator also provides several interactive control devices, which are helpful to assess results of a particular accident management behavior. A simple and direct dynamic linked library (DLL) data communication method is used for the development of the simulator. Using the DLL method, various control devices were implemented to provide an interactive control function during simulation. Finally, a training model is suggested for accident mitigation training and its performance is verified through application runs.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1075-1086
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• 2018

In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.1-5
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• 2000

With the advent of the internet era, web-based virtual training system is gaining its importance in recent years. Because of the fact that the training can take place in any place and at any time, the virtual system is now replacing many of the conventional off-line classes. Hardware environments such as communication bandwidth and computer performance gets fast enough to accommodate the virtual education. Based on the observations on current virtual training system, this paper proposes three critical design rules required when developing a new virtual training system: i) With conceptual mapping, the menu hierarchy can be organized in a clear-cut manner, ii) Extensive use of multimedia tools can help students keep their attention to the lecture materials, and iii) Provision of interaction mechanisms helps students to gain their identity and motivation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.224-226
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• 2015

Outwardly, the people in the shipping industry are aware that multicultural working environments and conditions could have a strong influence on the operation of ships. With a lack of cultural awareness and foreign language skill of crew members on ships, there are lots of misunderstandings and miscommunications among (cross-cultural) crews. More and more maritime accidents are caused by human error in the world's oceans. Nevertheless the research on cultural diversity and human interaction on ships is still in its infancy. Due to the rapid change of the demographic make-up of crews, not only teaching and training technical skills for the crews, but also education in nontechnical skills such as cultural awareness, cultural sensitivity, intercultural competence is urgently needed. This study will deal with intercultural issues on ships. It aims to emphasize the necessity of intercultural training in MET.

• International Journal of Contents
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• v.14 no.4
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• pp.24-29
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• 2018

EEG-based brain-computer interfaces has focused on explicitly expressed intentions to assist physically impaired patients. For EEG-based-computer interfaces to function effectively, it should be able to understand users' implicit information. Since it is hard to gather EEG signals of human brains, we do not have enough training data which are essential for proper classification performance of implicit intention. In this paper, we improve the subject independent classification of implicit intention through the generation of additional training data. In the first stage, we perform the PCA (principal component analysis) of training data in a bid to remove redundant components in the components within the input data. After the dimension reduction by PCA, we train ICA (independent component analysis) network whose outputs are statistically independent. We can get additional training data by adding Gaussian noises to ICA outputs and projecting them to input data domain. Through simulations with EEG data provided by CNSL, KAIST, we improve the classification performance from 65.05% to 66.69% with Gamma components. The proposed sample generation method can be applied to any machine learning problem with fewer samples.