• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.416-423
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• 2000

The existing self-organizing feature map of Kohonen has weakpoint that need too much input patterns in order to converse into the learning rate and equilibrium state when it trains. Making up for the current weak point, B.Bavarian suggested the method of that distributed the learning rate such as Gaussian function. However, this method has also a disadvantage which can not achieve the right self-organizing. In this paper, we proposed the method of improving the convergence speed and the convergence rate of self-organizing feature map converting the Gaussian function into dynamic approximate curve used in when trains the self-organizing feature map.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.203-208
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• 2022

The occurrence of Type 2 Diabetes Mellitus (T2DM) is hoarding globally. All kinds of Diabetes Mellitus is controlled to disrupt over 415 million grownups worldwide. It was the seventh prime cause of demise widespread with a measured 1.6 million deaths right prompted by diabetes during 2016. Over 90% of diabetes cases are T2DM, with the utmost persons having at smallest one other chronic condition in UK. In valuation of contemporary applications of Big Data (BD) to Diabetes Medicare by sighted its upcoming abilities, it is compulsory to transmit out a bottomless revision over foremost theoretical literatures. The long-term growth in medicine and, in explicit, in the field of "Diabetology", is powerfully encroached to a sequence of differences and inventions. The medical and healthcare data from varied bases like analysis and treatment tactics which assistances healthcare workers to guess the actual perceptions about the development of Diabetes Medicare measures accessible by them. Apache Spark extracts "Resilient Distributed Dataset (RDD)", a vital data structure distributed finished a cluster on machines. Machine Learning (ML) deals a note-worthy method for building elegant and automatic algorithms. ML library involving of communal ML algorithms like Support Vector Classification and Random Forest are investigated in this projected work by using Jupiter Notebook - Python code, where significant quantity of result (Accuracy) is carried out by the models.

• Asian Journal of Business Environment
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• v.12 no.3
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• pp.1-12
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• 2022

Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.97-104
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• 2023

In this paper, we propose a harmful bird repellent system using directional speakers. Existing sound systems for the extermination of harmful birds have the disadvantage of reducing effectiveness due to the learning effect of birds due to problems caused by noise pollution and monotonous sounds. In this paper, directional speakers are used to minimize surrounding noise. In addition, the up-down and left-right angles of the speaker driving device were freely adjusted to maximize usability. Additionally, the problem of performance degradation due to learning effects was solved by using various scanning patterns. In the future, we plan to develop a platform capable of central control by applying remote control functions and a deep learning model that can recognize bird species.

• The Journal of Korean Physical Therapy
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• v.21 no.1
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• pp.65-71
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• 2009

Purpose: Numerous investigators demonstrated that adaptative changes were induced by motor skill acquisition in the central nervous system. We investigated the changes of neuroelectric potential following motor learning with serial reaction time task in young healthy subjects, using electroencephalography (EEG). Methods: Twelve right-handed normal volunteers were recruited, who have no history of neurological dysfunction and were given to written the informed consent. All subjects were assigned to flex to extend the wrist joint or flex the thumb for pressing the matched button as quickly and accurately as possible, when one of five colored lights was displayed on computer screen (red, yellow, green, blue, white). EEG was measured, whenfive types simulations ware presented randomly with equal probabilities of 20% in total 200 times at the pre and post test. And they were scheduled for 30 minutes practice session during two consecutive days in the laboratory. Results: The results showed that the reaction time at the post test was significantly reduced, compared to one of the pre test in serial reaction time task. In EEG map analysis, the broaden bilateral activation tended to be changed to the focused contralateral activation in the frontoparietal area. Conclusion: These findings showed that acquisition of motor skill led to product more fast motor execution, and that motor learning could change cortical activation pattern, from the broaden bilateral activation to the focused contralateral activation. Thus we concluded that the adaptative change was induced by motor learning in healthy subjects.

• Journal of the Korean Society of Physical Medicine
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• v.5 no.3
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• pp.395-404
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• 2010

Purpose : The object of this study was to examine the effect of motor learning on brain activation depending on the method of motor learning. Methods : The brain activation was measured in 9 men by fMRI. The subjects were divided into the following groups depending on the method of motor learning: actually practice (AP, n=3) group, action observation (AO, n=3) group and motor imagery (MI, n=3) group. In order to examine the effect of motor learning depending on the method of motor learning, the brain activation data were measured during learning. For the investigation of brain activation, fMRI was conducted. Results : The results of brain activation measured before and during learning were as follows; (1) During learning, the AP group showed the activation in the following areas: primary motor area located in precentral gyrus, somatosensory area located in postcentral gyrus, supplemental motor area and prefrontal association area located in precentral gyrus, middle frontal gyrus and superior frontal gyrus, speech area located in superior temporal gyrus and middle temporal gyrus, Broca's area located in inferior parietal lobe and somatosensory association area of precuneus; (2) During learning, the AD groups showed the activation in the following areas: primary motor area located in precentral gyrus, prefrontal association area located in middle frontal gyrus and superior frontal gyrus, speech area and supplemental motor area located in superior temporal gyrus and middle temporal gyrus, Broca's area located in inferior parietal lobe, somatosensory area and primary motor area located in precentral gyrus of right cerebrum and left cerebrum, and somatosensory association area located in precuneus; and (3) During learning, the MI group showed activation in the following areas: speech area located in superior temporal gyrus, supplemental area, and somatosensory association area located in precuneus. Conclusion : Given the results above, in this study, the action observation was suggested as an alternative to motor learning through actual practice in serial reaction time task of motor learning. It showed the similar results to the actual practice in brain activation which were obtained using activation of mirror neuron. This result suggests that the brain activation occurred by the activation of mirror neuron, which was observed during action observation. The mirror neurons are located in primary motor area, somatosensory area, premotor area, supplemental motor area and somatosensory association area. In sum, when we plan a training program through physiotherapy to increase the effect during reeducation of movement, the action observation as well as best resting is necessary in increasing the effect of motor learning with the patients who cannot be engaged in actual practice.

• Journal of Gifted/Talented Education
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• v.21 no.1
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• pp.175-191
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• 2011

This study is to investigate the creative thinking style and it's leaning that normal students and scientifically gifted students use mainly at processing information. Right Brain vs Left Brain Creativity Test(R/LCT) and Brain Preference Indicator(BPI) is taken to investigate the creative thinking style of normal students(N=144) and scientifically gifted students(N=97). In the R/LCT, the normal students responded that they prefer to use right-brain thinking rather than left-brain thinking. But the scientifically gifted students prefer to left-brain thinking. The normal students showed most preference for Holistic Processing of right side brain and they did most avoiding for Verbal Processing of left side brain. The scientifically gifted students showed most preference for Logical Processing of left side brain. And they did most avoiding for Random Processing of right side brain. There was a meaningful difference between left side brain preference group and right side brain preference group on Sequential, Symbolic, Logical, Verbal, Random, Intuitive, Fantasy-oriented Processing of normal Students. But the scientifically gifted students showed a meaningful difference in right side brain processing mainly. In other word, all the scientifically gifted students took an lean processing in Logical, Symbolic, Linear Processing, etc. In sum, the scientifically gifted students are unequal in at processing information against the normal students. So it is required more appropriate teaching-learning method based on the creative thinking style and it's leaning for effective gifted education.

• Journal of Korea Multimedia Society
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• v.23 no.5
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• pp.641-649
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• 2020

As the usage of mobile devices extremely increases, malicious mobile apps(applications) that target mobile users are also increasing. It is challenging to detect these malicious apps using traditional malware detection techniques due to intelligence of today's attack mechanisms. Deep learning (DL) is an alternative technique of traditional signature and rule-based anomaly detection techniques and thus have actively been used in numerous recent studies on malware detection. In order to develop DL-based defense mechanisms against intelligent malicious apps, feeding recent datasets into DL models is important. In this paper, we develop a DL-based model for detecting intelligent malicious apps using KU-CISC 2018-Android, the most up-to-date dataset consisting of benign and malicious Android apps. This dataset has hardly been addressed in other studies so far. We extract OPcode sequences from the Android apps and preprocess the OPcode sequences using an N-gram model. We then feed the preprocessed data into LSTM and apply the concept of Information Gain to improve performance of detecting malicious apps. Furthermore, we evaluate our model with numerous scenarios in order to verify the model's design and performance.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• East Asian mathematical journal
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• v.30 no.2
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• pp.197-222
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• 2014

The purpose of this research is to find out if it is possible to apply the Waldorf School's mathematics education method to Korean alternative schools which are run under the national curriculum. To achieve this, the researcher conducted class on geometry for three weeks with ten 7th graders(four girls and six boys) from Apple Tree Waldorf alternative school in Busan, which has adopted Valdorf education courses. For the first two weeks, the class was about 'fundamental geometrical construction', and then it was evaluated. On the third week, the lesson was on plane figures, followed by a test with 9 plane figure questions that are based on general middle school mathematics curriculum. The result shows that most of the students understood 'fundamental geometrical construction'. When it comes to the test on 'plane figures', seven students got 8 out of 9 right, two students got 6 out of 9 right, and one of them had difficulty solving the questions. According to the results of this research, it is thought that there will be no problem for students to understand mathematical concept even if the Waldorf School's mathematics education method is applied to Korean alternative schools. Also, the Waldorf School's mathematics education method is considered to be a good teaching model for the Korean mathematics curriculum which places emphasis on 'mathematical creativity' in regard to the curriculum and contents.