• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3434-3439
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• 2015

As a criterion of information theoretic learning, the Euclidean distance (ED) of two error probability distribution functions (minimum ED of error, MEDE) has been adopted in nonlinear (decision feedback, DF) supervised equalizer algorithms and has shown significantly improved performance in severe channel distortion and impulsive noise environments. However, the MEDE-DF algorithm has the problem of heavy computational complexity. In this paper, the recursive ED for MEDE-DF algorithm is derived first, and then the feed-forward and feedback section gradients for weight update are estimated recursively. To prove the effectiveness of the recursive gradient estimation for the MEDE-DF algorithm, the number of multiplications are compared and MSE performance in impulsive noise and underwater communication environments is compared through computer simulation. The ratio of the number of multiplications between the proposed DF and the conventional MEDE-DF algorithm is revealed to be $2(9N+4):2(3N^2+3N)$ for the sample size N with the same MSE learning performance in the impulsive noise and underwater channel environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.561-566
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• 2021

The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.

• Safety and Health at Work
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• v.3 no.3
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• pp.199-208
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• 2012

Objectives: Although evidence-based medicine (EBM) is a useful method for integrating evidence into the decision-making process of occupational physicians, occupational physicians lack EBM knowledge and skills, and do not have the time to learn the EBM method. In order to enable them to educate themselves at the time and place they prefer, we designed an electronic EBM course. We studied the feasibility and utility of the course as well as its effectiveness in increasing EBM knowledge, skills, and behaviour. Methods: Occupational physicians from various countries were included in a within-subjects study. Measurements were conducted on participants' EBM knowledge, skills, behaviour, and determinants of behaviour at baseline, directly after finishing the course and 2 months later (n = 36). The feasibility and utility of the course were evaluated directly after the course (n = 42). Results: The course is applicable as an introductory course on EBM for occupational physicians in various countries. The course is effective in enhancing EBM knowledge and self-efficacy in practising EBM. No significant effect was found on EBM skills, behaviour, and determinants of behaviour. After the course, more occupational physicians use the international journals to solve a case. Conclusion: An electronic introductory EBM course is suitable for occupational physicians. Although it is an effective method for increasing EBM knowledge, it does not seem effective in improving skills and behaviour. We recommend integrating e-learning courses with blended learning, where it can be used side by side with other educational methods that are effective in changing behaviour.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.105-112
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• 2022

Innovation is considered as an implemented innovation in education - in the content, methods, techniques and forms of educational activity and personality education (methods, technologies), in the content and forms of organizing the management of the educational system, as well as in the organizational structure of educational institutions, in the means of training and education and in approaches to social services in education, distance and multimedia learning, which significantly increases the quality, efficiency and effectiveness of the educational process. The classification of currently known pedagogical technologies that are most often used in practice is shown. The basis of the innovative activity of a modern teacher is the formation of an innovative program-methodical complex in the discipline. Along with programmatic and content provision of disciplines, the use of informational tools and their didactic properties comes first. It combines technical capabilities - computer and video technology with live communication between the lecturer and the audience. In pedagogical innovation, the principles reflecting specific laws and regularities of the implementation of innovative processes are singled out. All principles are elements of a complex system of organization and management of innovative activities in the field of education and training. They closely interact with each other, which enhances the effect of each of them due to the synergistic effect. To improve innovative activities in the training of students, today computer technologies are widely used in pedagogy as a science, as well as directly in the practice of the pedagogical process. They have gained the most popularity in such activities as distance learning, online learning, assistance in the education management system, development of programs and virtual textbooks in various subjects, searching for information on the network for the educational process, computer testing of students' knowledge, creation of electronic libraries, formation of a unified scientific electronic environment, publication of virtual magazines and newspapers on pedagogical topics, teleconferences, expansion of international cooperation in the field of Internet education. The article considers computer technologies as the main building material for the entire society. In the modern world, there is a need to prepare a person for life in a multimedia environment. This process should be started as early as possible, because the child's contact with the media is present almost from the moment of his birth.

• Journal of Korean Biological Nursing Science
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• v.3 no.2
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• pp.63-68
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• 2001

Increasing interest in computer-mediated learning technologies has prompted educators to incorporate them into many learning environments ; however, there is still little evaluative evidence to support their effectiveness. This report describes the development and evaluation of a web-based instructional program on basic nursing science for nursing students. Researcher-designed questionnaires were used to assess the characteristics of our students, and to solicit their ratings of the instructional program on ease of use, accuracy of content, clarity of content, interest, and convenience of the program, using 5-point Likert scales. The respondents indicated that the package was easy and convenient to use, with high technical quality, and of a level challenging to some but not all of the students. On-line quizzes were most highly rated. Also it was confirmed that frequent users of electronic bulletin board showed much higher achievement score than that of nonfrequent users. It was also found that the effect of cyber education was dependent on the active participation of the students. These data suggest that the use of web-based instructional program as a distance education strategy can be an effective method for nursing students and nurses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1774-1794
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• 2024

In the field of environmental sensing, it is necessary to develop radio planning techniques for the next generation Internet of Things (IoT) networks over mixed terrains. Such techniques are needed for smart remote monitoring of utility supplies, with links situated close to but out of range of cellular networks. In this paper, a three-dimension (3-D) geometric optimization algorithm is proposed, considering the positions of edge IoT devices and antenna coupling factors. Firstly, a multi-level single linkage (MLSL) iteration method, based on geometric objectives, is derived to evaluate the data rates over ISM 915 MHz channels, utilizing optimized power-distance profiles of continuous waves. Subsequently, a federated learning (FL) data selection algorithm is designed based on the 3-D geometric positions. Finally, a measurement example is taken in a meadow biome of the Mexican Colima district, which is prone to fluvial floods. The empirical path loss model has been enhanced, demonstrating the accuracy of the proposed optimization algorithm as well as the possibility of further prediction work.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.39-46
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• 2016

While the difficulty of the music can be classified by a variety of standard, conventional methods are classified by the subjective judgment based on the experience of many musicians or conductors. Music score is difficult to evaluate as there is no quantitative criterion to determine the degree of difficulty. In this paper, we propose a new classification method for determining the degree of difficulty of the music. In order to determine the degree of difficulty, we convert the score, which is expressed as a traditional music score, into electronic music sheet. Moreover, we calculate information about the elements needed to play sheet music by distance of notes, tempo, and quantifying the ease of interpretation. Calculating a degree of difficulty of the entire music via the numerical data, we suggest the difficulty evaluation of the score, and show the difficulty of music through experiments.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.366-370
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• 2022

The article deals with the theoretical and methodological foundations of innovative approaches in the modern education system. The issues of introducing computerized and telecommunication technologies are characterized, which allow switching to distance learning (DL), which is a promising form of the system of open education support in the modern educational process. Special attention is paid to the study of practical technologies of vocational training and the activities of a teacher and innovative areas of vocational training of students.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.21-28
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• 2015

Feature normalization as a pre-processing step has been widely used to reduce the effect of different scale in each feature dimension and error rate in classification. Most of the existing normalization methods, however, do not use the class labels of data points and, as a result, do not guarantee the optimality of normalization in classification aspect. A supervised rank normalization method, combination of rank normalization and supervised learning technique, was proposed and demonstrated better result than others. In this paper, another technique, training sample selection, is introduced in supervised feature normalization to reduce classification error more. Training sample selection is a common technique for increasing classification accuracy by removing noisy samples and can be applied in supervised normalization method. Two sample selection measures based on the classes of neighboring samples and the distance to neighboring samples were proposed and both of them showed better results than previous supervised rank normalization method.

• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.