• Phonetics and Speech Sciences
• /
• v.12 no.1
• /
• pp.75-83
• /
• 2020

The purpose of this study was to examine how a singing program using self-voice monitoring for children with cochlear implants (CI) influences on the intonation and the accuracy of pitch production. To verify and estimate the effectiveness, a program was conducted with participants of 7 prelingual CI users, whose aged between 4 years and 7 years. The program adopted three stages from the self-voice monitoring: Listen, Explore, and Reproduce (LER stage). All participants received 8 singing sessions over 8 weeks, including pre-test, intervention, and post-test. For the pre and post-test, participants' singing of an excerpt of a song "happy birthday" and speaking three assertive sentences and three interrogative sentences were recorded and analyzed in terms of the intonation slopes at the end of the sentences and the melodic contour. From the sentence speeches, we found that the intonation slopes of the interrogative sentences significantly improved as they showed similar patterns with that of the average normal hearing group. Also, in regard to singing, we observed that the melody contour had progressed, as well as the range of pitch production had extended. The positive result from the intervention indicates that the singing program was effective for children with CI to develop the intonation skill and accuracy of pitch production.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.149-159
• /
• 2008

We present new methods which transfer the color style of a source image into an arbitrary given reference image. Misidentification problem of color cause wrong indexing in low saturation. Therefore, the proposed method do indexing after Image separating chromatic and achromatic color from saturation. The proposed method is composed of the following four steps : In the first step, Image separate chromatic and achromatic color from saturation using threshold. In the second step, image of separation do indexing using cylindrical metric. In the third step, the number and positional dispersion of pixel decide the order of priority for each index color. And average and standard deviation of each index color be calculated. In the final step, color be transferred in Lab color space, and post processing to removal noise and pseudo-contour. Experimental results show that the proposed method is effective on indexing and color transfer.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.6
• /
• pp.1469-1475
• /
• 2010

This paper presents a problem of existing encryption methods using pseudo-random numbers based on MLCA or complemented MLCA and proposes a method to resolve this problem. The existing encryption methods have a problem which the edge of original image appear on encrypted image because the image have color similarity of adjacent pixels. In this proposed method, we transform the value and spatial coordinates of all pixels by using pseudo-random numbers based on MLCA. This method can resolve the problem of existing methods and improve the level of encryption by encrypting pixel coordinates and pixel values of original image. The effectiveness of the proposed method is proved by conducting histogram and key space analysis.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.46 no.12
• /
• pp.102-107
• /
• 2009

As technology gets developed, medical equipments are also modernized and leading-edge systems, such as PACS become popular. Many scientists noticed importance of medical image processing technology. Technique of region segmentation is the first step of digital medical image processing. Segmentation technique helps doctors to find out abnormal symptoms early, such as tumors, edema, and necrotic tissue, and helps to diagnoses correctly. Segmentation of white matter, gray matter and CSF of a brain image is very crucial part. However, the segmentation is not easy due to ambiguous boundaries and inhomogeneous physical characteristics. The rate of incorrect segmentation is high because of these difficulties. Fuzzy-based segmentation algorithms are robust to even ambiguous boundaries. In this paper a modified Fuzzy-based segmentation algorithm is proposed to handle the noise of MR scanners. A proposed algorithm requires minimal computations of mean and variance of neighbor pixels to adjust a new neighbor list. With the addition of minimal compuation, the modified FCM(mFCM) lowers the rate of incorrect clustering below 30% approximately compared the traditional FCM.

• The KIPS Transactions:PartB
• /
• v.11B no.2
• /
• pp.133-140
• /
• 2004

Recently, the dental information systems were rapidly developed in order to store and process the data of patients. But, these systems should serve a doctor a good quality information against disease for diagnostic and surgery purpose so as to success in this field. This function of the system it important to persuade patients to undergo proper surgical operation they needed. Hence, 3D teeth model capable of simulating the dental surgery and treatment is necessary Teeth manipulation of dentistry is performed on individual tooth in dental clinic. io, 3D teeth reconstruction system should have the techniques of segmentation and 3D reconstruction adequate for individual tooth. In this paper, we propose the techniques of adaptive optimal segmentation to segment the individual area of tooth, and reconstruction method of tooth based on contour-based method. Each tooth can be segmented from neighboring teeth and alveolar bone in CT images using adaptive optimal threshold computed differently on tooth. Reconstruction of individual tooth using results of segmentation can be manipulated according to user's input and make the simulation of dental surgery and treatment possible.

• Radiation Oncology Journal
• /
• v.4 no.2
• /
• pp.179-181
• /
• 1986

Computed tomography (CT) adds a new dimension in the study of body contour, organs, and tissues as well as various pathologic conditions. This modality provides a great degree of accuracy in radiation therapy Planning (RTP). However, CT images are usually taken on a small reduced format so that possible errors can be made during inputting the CT data into an automatic planner. Authors have designed a simple inexpensive magnifying device of CT images to obviate errors created by reduced image.

• Proceedings of the Korea Water Resources Association Conference
• /
• 1980.08a
• /
• pp.44-46
• /
• 1980

파의 에너지 감쇠기구의 관점에서 볼 때 분류손실방식인 유공벽식 방파제 중에서 원형공이 벽 전체에 균일하게 분포되어 있고 구멍 직경에 비해 벽 두께가 얇은 삼중 유공벽형 Caisson의 각 벽에 작용하는 파력에 고나해 이론적 접근과 실험을 통한 실증을 시도해 보았다. 이론적인 방법으로는 토굴구효남의 이론을 응용하였으며 주어진 파랑조건에 대해 각 유공벽 전 후면에 연속방정식과 Bernoulli 방정식을 이용하여, 각 영역별 연속 Potential의 진폭과 위상각에 대한 비선형 12원 연립방정식을 만들었고 Computer를 이용하여 반복법으로 각 속도 Potential을 확정하였다. 이렇게 구한 속도 Potential을 압력방정식에 대입하여 각 벽별 파력을 계산하였으며 동일한 파랑조건하의 실험에서 각 벽별 파력을 측정하여 양자를 서로 비교검토하였다. Bernoulli의 방정식중 에너지 손실항은 의사비선형으로 처리하였다. 유공율조합 0.25-0.3-0.2이고, 판두께가 1cm인 모형의 실험결과, 각 벽별 최대파력치의 특성으로서는 첫때, S-2, S-3등 간벽에 작용하는 파력이 전벽 및 후벽에 비해 두드러지게 작다는 사실과, 둘째 작용파력의 크기 순이 파형경사가 작을 때는 대략 S-4, S-1, S-2, S-3순이고 파형경사가 클 때에는 대략 S-1, S-4, S-2, S-3순이라는 점 등을 들 수 있겠다. 굴구효남이 가정한 f의 치 1.5를 사용하여 계산한 각 벽별 최대파력을 실험치와 비교해 본 결과, 파가 각 유공벽을 통과할 때의 손실수두를 실험에서의 양만큼 fr=1.5를 가정한 수학적 model이 설명해 주지 못한다고 볼 수 있으므로 두가지 방법에 의하여 본 실험에서 사용한 유공판의 손실계수를 근사적으로 추정하여 보았다. 추정한 f를 사용하여 다시금 각 벽별 최대파력을 계산하고 실험치와 비교해 보면 훨씬 서로 근접함을 알 수 있었다. 결국 본 논문의 이론을 사용하면 유공Caisson문제의 전체적인 윤곽 및 각 변수들의 파력에 대한 영향을 파악할 수 있겠다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.1
• /
• pp.191-197
• /
• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Progress in Medical Physics
• /
• v.26 no.1
• /
• pp.52-58
• /
• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of forensic and investigative science
• /
• v.1 no.2
• /
• pp.5-19
• /
• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.