• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.652-655
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• 1997

An exploration for an intelligence paradigm has been delineated. Artificial intelligence and artificial life paradigms seem to fail to show the whole picture of human intelligence. We may understand the human intelligence better by adding the emotional part of human intelligence to the intellectual part of human intelligence. Emotional intelligence is investigated in terms of composing machine as a modern abstract art. Various algorithmic composition and performance concepts are currently being investigated and implemented. Intelligent mapping algorithms restructure the traditional predetermined composition algorithms. Music based on fractals and neural networks is being composed. Also, emotional intelligence and aesthetic aspects of Korean traditional music are investigated in terms of fractal relationship. As a result, this exploration will greatly broaden the potentials of the intelligence research. The exploration of art in the view of intelligence, information and structure will restore the balanced sense, of art and science which seeks happiness in life. The investigations of emotional intelligence will establish the foundations of intelligence, information and control technologies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3355-3372
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• 2022

Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.11-19
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• 2020

Software education is provided for 6th grade students. This study explored the algorithmic composition patterns of elementary school students. After investigating the algorithm for the 6th grade students, the algorithmic pattern of the learner was explored by calculating the cyclomatic complexity of MacCabe based on the structural programming technique. Students often use one or two choice structures to solve problems, which tend to be biased towards the starting and ending points of the problem. It is also passive in the use of selection structures. Algorithm composition depends on visible objects and one's own background. Therefore, in elementary school software education, it is necessary to present the task of thinking about the algorithm structure in the context of the algorithm and the students' experiences in accordance with the algorithm composition pattern.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.618-622
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• 2008

In this paper, we suggest new music composition algorithm based on fractal theory. User can define and control fractal shape by setting an initial state and production rules in L-System. We generate an asymmetric fractal tree based on L-System and probability. Then a music is generated by the fractal tree image using sonification techniques. We introduce two composition algorithm using the fractal tree. First, monophonic music can be generated by mapping x and y axis to velocity and pitch, respectively Second, harmonic music also can be generated by mapping x and y axis to time and pitch, respectively Using our composition algorithm, user can easily generate a music which has repeated pattern created by recursive feature of fractal, and a music which has structure similar to fractal tree image.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.744-748
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• 2008

In this paper, we propose a novel technique that generate a new song with given example songs. Our system use k-th order Markov chain of which each state represents notes in a measure. Because we have to consider very high-dimensional space if we use notes in a measure as a state of Markov chain directly, we exploit a hierarchical clustering technique for given example songs to use each cluster as a state. Each given examples can be represented as sequences of cluster ID, and we use them for training data of the Markov chain. The resulting Markov chain effectively gives new song similar to given examples.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.124-134
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• 1996

Korean has a large set of characters, and has a two-dimensional formation: each character is composed of graphemes in two dimensions. Whereas connections between characters are rare, connections inside a grapheme and between graphemes happen frequently and these connections generate many cursive strokes. To deal with the large character set and the cursive strokes, using the graphemes as a recognition unit is an efffective approach, because it naturally accommodates the structural characteristics of the characters. In this paper, we propose a grapheme-based on-line recognition method for cursive korean characters. Our method uses a TDNN recognition engine to segment cursive strokes into graphemes and a graph-algorithmic postprocessor based on korean grapheme composition rule and viterbi search algorithm to find the best recognition score path. We experimented the method on freely hand-written charactes and obtained a recognition rate of 94.5%.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.733-738
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• 2008

Serial Music, introduced by A. Sch nberg, is a one of the important composition techniques. This music style has features of pantonality and atonality, so it generates unique atmosphere of modern music. In this paper, we introduce an method of generating serial music using mathematical algorithm. This method generates music that satisfy the requirement that the number of pitches belonged to each pitch class are exactly same, though the requirement is less strict than Sch nberg's definition. To do this, our method uses space-filling curves traversing the twelve tone matrix, which is constructed by the serial series, its inversion and its transpose. Using these curves, we can generate a music that has all notes in the matrix exactly once and adequate repeatness because of the curve's locality. Result music, therefore, can be more suitable for people that are not familiar with modern music, while maintaining the features of pantonality and atonality. This paper also introduces a method of generating extended serial music that uses serialism of duration and dynamic of notes, using multi-dimensional space-filling curves.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.479-485
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• 2010

Objectives: The Korean Genome and Epidemiology Study (KoGES), a multicenter-based multi-cohort study, has collected information on body composition using two different bioelectrical impedence analysis (BIA) machines. The aim of the study was to evaluate the possibility of whether the test values measured from different BIA machines can be integrated through statistical adjustment algorithm under excellent inter-rater reliability. Methods: We selected two centers to measure inter-rater reliability of the two BIA machines. We set up the two machines side by side and measured subjects' body compositions between October and December 2007. Duplicated test values of 848 subjects were collected. Pearson and intra-class correlation coefficients for inter-rater reliability were estimated using results from the two machines. To detect the feasibility for data integration, we constructed statistical compensation models using linear regression models with residual analysis and R-square values. Results: All correlation coefficients indicated excellent reliability except mineral mass. However, models using only duplicated body composition values for data integration were not feasible due to relatively low $R^2$ values of 0.8 for mineral mass and target weight. To integrate body composition data, models adjusted for four empirical variables that were age, sex, weight and height were most ideal (all $R^2$ > 0.9). Conclusions: The test values measured with the two BIA machines in the KoGES have excellent reliability for the nine body composition values. Based on reliability, values can be integrated through algorithmic statistical adjustment using regression equations that includes age, sex, weight, and height.