• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.267-272
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• 2010

For the last decade, recurrent neural networks (RNNs) have been commonly applied to communications channel equalization. The major problems of gradient-based learning techniques, employed to train recurrent neural networks are slow convergence rates and long training sequences. In high-speed communications system, short training symbols and fast convergence speed are essentially required. In this paper, the derivative-free Kalman filter, so called the unscented Kalman filter (UKF), for training a fully connected RNN is presented in a state-space formulation of the system. The main features of the proposed recurrent neural equalizer are fast convergence speed and good performance using relatively short training symbols without the derivative computation. Through experiments of nonlinear channel equalization, the performance of the RNN with a derivative-free Kalman filter is evaluated.

• Journal of National Security and Military Science
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• s.7
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• pp.233-270
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• 2009

Serious game played with a computer in accordance with specific rules, that uses entertainment to further government or corporate training, education, health, public policy, and strategic communication objectives. The main goal of a serious game is usually to train or educate users while giving them an enjoyable experience. Serous games are video games with serious purposes such as teaching or training and whose principal aim is education. The major characteristics of serious games involve pedagogy which are all of the activities that educate, train, or instruct the player. Other characteristics of serious games are that they use entertainment principles, creativity and technology to build games that carry out serious purposes. This study is to introduce a serious game for the military training and to describe the elements of game design for developing it.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.1
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• pp.5-22
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• 2017

This study discusses the library professionals' perception of the ICT Applications in engineering college libraries in Tamil Nadu. The relevant data was collected from the library professionals in the self financing engineering colleges situated in Kanchipuram and Thiruvallur district of Tamil Nadu. 625 questionnaires were distributed, 504 replied with a response rate of 80.64%. It was found that the respondents with experience 'Below 5 years'gave 'Lack of infrastructure' as the first priority. 'Lack of interest on the part of users' and 'No support from administration in training library professionals' were the second and third preferences indicated by the respondents. The least preferences were given for 'Fear of ICT application'. Similarly, respondents with experience '6-10 years' indicated 'No support from administration in training library professionals' as the first priority. The least preference was given for 'Inadequate training in ICT applications' by the above respondents. It can be inferred that the professionals accepted and need the training in ICT applications.

• English Language & Literature Teaching
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• v.13 no.2
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• pp.129-153
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• 2007

When English language teachers are deciding on their priorities for teaching pronunciation, it is imperative to know what kind of differences and errors are most likely to interfere with communication, and what special problems particular first-language speakers will have with English pronunciation. In other words, phoneme discrimination skill is an integral part of speech processing for the EFL learners' learning to converse in English. Training using sound visualization technique can be effective in improving second language learners' perceptions and productions of segmental and suprasegmental speech contrasts. This study assessed the efficacy of a pronunciation training that provided visual feedback for EFL learners acquiring pitch and durational contrasts to produce and perceive English phonemic distinctions. The subjects' ability to produce and to perceive novel English words was tested in two contexts before and after training; words in isolation and words in sentences. In comparison with an untrained control group, trainees showed improved perceptual and productive performance, transferred their knowledge to new contexts, and maintained their improvement three months after training. These findings support the feasibility of learner-centered programs using sound visualization technique for English language pronunciation instruction.

• ETRI Journal
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• v.38 no.1
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• pp.81-89
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• 2016

In this paper, a beam ID preamble (BIDP) technique, where a beam ID is transmitted in the physical layer, is proposed for efficient beam training in millimeter-wave cellular communication systems. To facilitate beam ID detection in a multicell environment with multiple beams, a BIDP is designed such that a beam ID is mapped onto a Zadoff-Chu sequence in association with its cell ID. By analyzing the correlation property of the BIDP, it is shown that multiple beams can be transmitted simultaneously with the proposed technique with minimal interbeam interference in a multicell environment, where beams have different time delays due to propagation delay or multipath channel delay. Through simulation with a spatial channel model, it is shown that the best beam pairs can be found with a significantly reduced processing time of beam training in the proposed technique.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.159-166
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• 2023

The COI gene is a sequence of approximately 650 bp at the 5' terminal of the mitochondrial Cytochrome c Oxidase subunit I (COI) gene. As an effective DeoxyriboNucleic Acid (DNA) barcode, it is widely used for the taxonomic identification and evolutionary analysis of species. We created a CNN-LSTM hybrid model by combining the gene features partially extracted by the Long Short-Term Memory ( LSTM ) network with the feature maps obtained by the CNN. Compared to K-Means Clustering, Support Vector Machines (SVM), and a single CNN classification model, after training 278 samples in a training set that included 15 genera from two orders, the CNN-LSTM hybrid model achieved 94% accuracy in the test set, which contained 118 samples. We augmented the training set samples and four genera into four orders, and the classification accuracy of the test set reached 100%. This study also proposes calculating the cosine similarity between the training and test sets to initially assess the reliability of the predicted results and discover new species.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.487-495
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• 2018

The goal of this study is to examine the effectiveness of assertiveness training program for nurses' fear of negative evaluation, assertiveness behavior, and communication competency. The study is quasi-experimental study by nonequivalence control group design. The subjects of this study consisted of 32 graduate students in nursing department located in G city; 14 in experimental group and 18 in control group. The data is collected from March 13th, 2018 to May 8th, 2018. The experimental group participated in assertiveness training program composed of six times session for 180 minutes once a week and were asked to fill out the structured questionnaire. Collected data is analyzed by Fisher's exact test, $x^2-test$ and t-test. The result reveals the significant difference in assertiveness behavior and communication competency of nurses. This study contribute to improve the effectiveness of convergence-based assertiveness training program for nurses' assertiveness competency, communication competency.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.5
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• pp.277-294
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• 2020

This study analyzed the effect of internal marketing factors of agricultural enterprises on corporate performance by using SNS as a moderating variable for agricultural enterprises workers. Internal marketing factors were divided into education and training, communication and compensation system, and corporate performance was set as a sub-variable of financial performance and non-financial performance. 349 questionnaires collected from agricultural enterprises workers were used for empirical analysis. The results of the analysis using SPSS v22.0 and Process macro v3.4 showed that first, communication and compensation systems had a significant effect on financial performance and education and training did not have a significant effect on financial performance. Second, communication has a significant effect on non-financial performance, and education and training has a negative effect on non-financial performance., and compensation system had no significant effect on non-financial performance. Third, SNS utilization significantly moderated the relationship between internal marketing factors and financial performance. Fourth, SNS utilization significantly moderated the relationship between internal marketing factors and non-financial aptitude. This study has significance that internal marketing factors that affect general companies are different due to the characteristics of agricultural management organizations, and that internal marketing factors that affect the performance of agricultural management organizations have been discovered. In particular, it was found that communication must be dealt with importantly to expand the performance of agricultural management. As a follow-up study, it is necessary to study the mediating model formed by the discovery of mediators and to study the moderated mediating analysis through the conditional process model in which the mediators are introduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.569-577
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• 2014

As of December 2013, 63 distance education training centers has been operating in the form of private, university affiliated and national/public centers. LMS is related to distance training quality as the system because distance education training centers are managing training by using LMS. In this paper, LMS functions of distance education training centers were analyzed to enhance the quality of distance training. In results of the analysis, it is showed 70.07%, 72.09% and 70.41% that implementation ratio of necessary LMS functions for trainee, manager and tutor. Functions of the lowest implementation ratio were "training support" of trainee mode, "statistics management" of manager mode and "communication" of tutor mode. The results of this paper will be helped to improve LMS for effective distance training of distance education training centers.