• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.355-356
• /
• 2009

점자 체계와 CMYK 모델을 이용하여 시각 장애인과 일반인이 읽을 수 있는 책을 만들기 위한 방법론을 제시한다. CMYK의 K를 이용해 8개의 점으로 구성된 셀 문자를 텍스트에 삽입하여, 텍스트 스캔 시 빠르고 정확한 문자 인식이 가능하게 한다.

• The Journal of Korean Academy of Prosthodontics
• /
• v.60 no.2
• /
• pp.202-210
• /
• 2022

Recently with the advance in digital dentistry, the fabrication of dentures using computer-aided design and computer-aided manufacturing (CAD-CAM) is on the rise. The denture designed through a CAD software can be produced in a 3-dimensional manufacturing process. This process includes a subtractive processing method such as milling and an additive processing method such as 3D printing and in which it can be applied efficiently in more complex structures. In this case, complete dentures were fabricated using Stereolithography (SLA)-based 3D printing to shorten the production time and interval of visits in patient with physical disabilities due to cerebral infarction. For definitive impression, the existing interim denture was digitally replicated and used as an individual tray. The definitive impression obtained with polyvinyl siloxane impression material was including information about the inclination and length of the maxillary anterior teeth, vertical dimension, and centric relation. In addition, facial scan data with interim denture was obtained so that it can be used as a reference in determination of the occlusal plane and in arrangement of artificial teeth during laboratory work. Artificial teeth were arranged through a CAD program, and a gingival festooning was performed. The definitive dentures were printed by SLA-based 3D printer using a FDA-approved liquid photocurable resin. The denture showed adequate retention, support, and stability, and results were satisfied functionally and aesthetically.

• Journal of KIBIM
• /
• v.14 no.2
• /
• pp.1-12
• /
• 2024

The paper proposes a methodology that combines the Random Sample Consensus (RANSAC) algorithm and the Point Cloud Encoder-Decoder Network (PCEDNet) algorithm to automatically extract the length of infrastructure elements from point cloud data acquired through 3D LiDAR scans of retaining walls. This methodology is expected to significantly improve time and cost efficiency compared to traditional manual measurement techniques, which are crucial for the data-driven analysis required in the precision-demanding construction sector. Additionally, the extracted positional and dimensional data can contribute to enhanced accuracy and reliability in Scan-to-BIM processes. The results of this study are anticipated to provide important insights that could accelerate the digital transformation of the construction industry. This paper provides empirical data on how the integration of digital technologies can enhance efficiency and accuracy in the construction industry, and offers directions for future research and application.

• The KIPS Transactions:PartD
• /
• v.16D no.3
• /
• pp.423-432
• /
• 2009

Advances in information and communication technologies are changing our society greatly. In knowledge-based society, information can be obtained easily via communication tools such as web and e-mail. However, obtaining right and up-to-date information is difficult in spite of overflowing information. The concept of adaptive web site has been initiated recently. The purpose of the site is to provide information only users want out of tons of data gathered. In this paper, an algorithm is developed for adaptive web site construction. The proposed algorithm is based on association rules that are major principle in adaptive web site construction. The algorithm is constructed by analysing log data in web server and extracting meaning documents through finding behavior patterns of users. The proposed algorithm has the following characteristics. First, it is superior to existing algorithms using association rules in time complexity. Its superiority is proved theoretically. Second, the proposed algorithm is effective in space complexity. This is due to that it does not need any intermediate products except a linked list that is essential for finding frequent item sets.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2009.05a
• /
• pp.239-242
• /
• 2009

최근 3 차원 측정 기술을 활용한 운동 기능성의 향상을 위한 연구가 활발히 진행되고 있다. 그 예로 3 차원 인체 정보를 이용한 의복패턴 제작 시에 필요한 절개선으로 피부상에서 동작 시 늘어나지 않는 선(Lines of Non-Extension, LoNE)을 찾아내어 활용한 연구가 발표된 바 있다. 이러한 LoNE 은 기존 의복구성을 위한 봉제선이나 기능선으로 활용될 때 동작기능성을 저해하지 않는 특징이 있다. 이에 본 연구에서는 스포츠웨어에서 활동성이 큰 상체의 어깨부위에서 Lines of Non-Extension 을 탐색하고자 하였다. 연구 방법으로는 20 대 후반 남성 2 명을 대상으로 체표의 등 부분에서 3cm 간격으로 계측점을 표시한 후 3D 인체 데이터 (Cyberware, WB)를 획득하였다. 측정시의 자세는 팔을 $30^{\circ}$, $90^{\circ}$, $135^{\circ}$, $180^{\circ}$ 외전시켰다. 피부 표면에서의 길이 변화는 구획의 크기를 달리하면서 가로, 세로, 사선방향으로 동작에 따라서 측정하였다. 변화량은 정자세($30^{\circ}$)를 기준으로 A 라 하였을 때, 기준자세와의 차이가 가장 큰 변화량을 보인 자세를 B 라 하고 A 와 B 간의 차이로 계산하였다. 연구결과, NASA 의 Biosuit 에서 소개된 Iberall(1970)의 LoNE 중 진동둘레를 포함한 팔 부위와 등, 어깨 부위에서 유사한 라인을 찾았다. 본 연구에서와 같이 구획별 사선방향 피부 변화량을 측정하는 것은 피부면에 숨겨진 인간공학적 의복 기능선을 탐색하는 데 효과적임을 확인하였다.

• Journal of Broadcast Engineering
• /
• v.28 no.3
• /
• pp.293-301
• /
• 2023

Unstandardized medical data collection and management are still being conducted manually, and studies are being conducted to classify CT data using deep learning to solve this problem. However, most studies are developing models based only on the axial plane, which is a basic CT slice. Because CT images depict only human structures unlike general images, reconstructing CT scans alone can provide richer physical features. This study seeks to find ways to achieve higher performance through various methods of converting CT scan to 2D as well as axial planes. The training used 1042 CT scans from five body parts and collected 179 test sets and 448 with external datasets for model evaluation. To develop a deep learning model, we used InceptionResNetV2 pre-trained with ImageNet as a backbone and re-trained the entire layer of the model. As a result of the experiment, the reconstruction data model achieved 99.33% in body part classification, 1.12% higher than the axial model, and the axial model was higher only in brain and neck in contrast classification. In conclusion, it was possible to achieve more accurate performance when learning with data that shows better anatomical features than when trained with axial slice alone.

• Journal of the Korean Society of Radiology
• /
• v.17 no.1
• /
• pp.1-9
• /
• 2023

For optimal image quality of computer tomography angiography (CTA), different iodine concentrations and scan parameters were applied to quantitatively evaluate the image quality characteristics of filtered back projection (FBP), hybrid-iterative reconstruction (hybrid-IR), and deep learning reconstruction (DLR). A 320-row-detector CT scanner scanned a phantom with various iodine concentrations (1.2, 2.9, 4.9, 6.9, 10.4, 14.3, 18.4, and 25.9 mg/mL) located at the edge of a cylindrical water phantom with a diameter of 19 cm. Data obtained using each reconstruction technique was analyzed through noise, coefficient of variation (COV), and root mean square error (RMSE). As the iodine concentration increased, the CT number value increased, but the noise change did not show any special characteristics. COV decreased with increasing iodine concentration for FBP, adaptive iterative dose reduction (AIDR) 3D, and advanced intelligent clear-IQ engine (AiCE) at various tube voltages and tube currents. In addition, when the iodine concentration was low, there was a slight difference in COV between the reconstitution techniques, but there was little difference as the iodine concentration increased. AiCE showed the characteristic that RMSE decreased as the iodine concentration increased but rather increased after a specific concentration (4.9 mg/mL). Therefore, the user will have to consider the characteristics of scan parameters such as tube current and tube voltage as well as iodine concentration according to the reconstruction technique for optimal CTA image acquisition.

• Journal of Conservation Science
• /
• v.31 no.2
• /
• pp.131-145
• /
• 2015

Cultural assets restoration is being considered highly as a practical way to extend the lifespan of damaged cultural assets and re-highlight their value. However, restoration process has been mostly dependent on the manual work involving the experience and skill of a person performing restoration, thereby requiring much time and effort. In recent, it became possible to apply a method allowing restoration to be performed more accurately and easily according to the material characteristics and shape of cultural assets. Namely, it is to use a method of printing out the 3D shape data computed in computer as real object by using 3D printer for the restoration that has been performed manually. The missing part of a cultural asset is computed into computer data first and is printed out by using 3D printer to undergo a simple shaping process. The result of 3D printer application showed that repetitive output and shape and figure revision of digital data were possible, and it was possible to improve the degree of completedness of restoration through test output using various types of restoration materials using various materials. For the purpose of verifying the possibility of applying 3D printer to restore missing part of earthenware, two pieces of modern reproductions, namely, the Seven Treasure Incense Burner and Earthenware with Wagon Wheel Decoration, were artificially damaged. The restoration result showed that compared to manual work, it showed better effectiveness in curtailing work time and reproducing accurate shape. On the other hand, secondary manual work was slightly needed for detailed binding and to vividly express surface texture.

• The Korean Journal of Nuclear Medicine
• /
• v.38 no.4
• /
• pp.288-293
• /
• 2004

Purpose: increased uptake of wrist and hand joints in three phase bone scintigraphy (TPBS) have been used in the detection of reflex sympathetic dystrophy syndrome (RSDS). TPBS frequently shows increased shoulder uptake in the hemiplegic RSDS patients. We investigated the significance of the shoulder uptake in the detection of these patients. Materials and Methods: Twenty three patients who had hemiplegia due to brain stroke and diagnosed as RSD were enrolled in this study (M:F=16:7, R:L=11:12). The mean age was $63{\pm}10$ yrs. Ter normal volunteer (mean age: $60{\pm}5$, M:F=1:9) data was used as control group. TPBS was performed $59{\pm}32$ days after stoke (acute stage). We obtained the count ratios of bilateral hands by drawing a region of interest (ROI) in three phase images and compared to the count ratios of shoulders in the delayed image. Hand ROI included an ipsilateral wrist. Sensitivity of detecting the affected limb was defined using the right/left count ratio of normal control. Results: Sensitivities using count ratios of hand blood flow, blood pool and delayed image were 45%, 76% and 78%, respectively. Sensitivity of shoulder count ratio was 74%. Log of right/left counts of hand delayed image and that of shoulder delayed image were correlated well with statistical significance (Spearman's R=0.824, p<0.001). Conclusion: Shoulder uptake showed good correlation with hand uptake in the delayed image of TPBS. Shoulder uptake maybe helpful in the diagnosis of reflex sympathetic dystrophy syndrome in patients with hemiplegia.

• Korean Journal of Human Ecology
• /
• v.19 no.3
• /
• pp.555-563
• /
• 2010

With recent advances in 3D scanning technology, three-dimensional (3D) patternmaking is becoming a powerful way to develop garments pattern. This technology is now applicable to the made to measure (MTM) system of both ordinary and tightly fitting garments. Although the pattern of fitted clothing has been developed using 3D human data, it is still interesting to develop cycling pants by considering while-cycling body posture and fabric elasticity. This study adopted the Garland's triangle simplification method in order to simplify data without distorting the original 3D scan. Next, the Runge-Kutta method (2C-AN program) was used to develop a 2D pattern from the triangular pixels in the 3D scanned data. The 3D scanned data of four male, university students aged from 21 to 25, was obtained using Whole body scanner (Model WB4, Cyberware, Inc., USA). Results showed the average error of measurement was $4.58cm^2$ (0.19%) for area and 0~0.61cm for the length between the 3D body scanned data and the 2D developed pattern data. This is an acceptable range of error for garment manufacture. Additionally, the 2D pattern developed, based on the 3D body scanned data, did not need ease for comfort or ease of movement when cycling. This study thus provides insights into how garment patterns may be developed for ergonomic comfort in certain special environments.