• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.667-685
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• 2022

This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.80-87
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• 2006

Recently, the distribution and using of the digital multimedia contents are easy by developing the internet application program and related technology. However, the digital signal is easily duplicated and the duplicates have the same quality compare with original digital signal. To solve this problem, there is the multimedia fingerprint which is studied for the protection of copyright. Fingerprinting scheme is a techniques which supports copyright protection to track redistributors of electronic inform on using cryptographic techniques. Only regular user can know the inserted fingerprint data in fingerprinting schemes differ from a symmetric/asymmetric scheme and the scheme guarantee an anonymous before recontributed data. In this paper, we present a new scheme which is the detection of colluded multimedia fingerprint by neural network. This proposed scheme is consists of the anti-collusion code generation and the neural network for the error correction. Anti-collusion code based on BIBD(Balanced Incomplete Block Design) was made 100% collusion code detection rate about the average linear collusion attack, and the hopfield neural network using (n,k)code designing for the error bits correction confirmed that can correct error within 2bits.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.12
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• pp.1101-1106
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• 2014

Hybrid manufacturing technology has been advanced to overcome limitations due to traditional fabrication methods. To fabricate a micro/nano-scale structure, various manufacturing technologies such as lithography and etching were attempted. Since these manufacturing processes are limited by their materials, temperature and features, it is necessary to develop a new three-dimensional (3D) printing method. A novel nano-scale 3D printing system was developed consisting of the Nano-Particle Deposition System (NPDS) and the Focused Ion Beam (FIB) to overcome these limitations. By repeating deposition and machining processes, it was possible to fabricate micro/nano-scale 3D structures with various metals and ceramics. Since each process works in different chambers, a transfer process is required. In this research, nanoscale 3D printing system was briefly explained and an alignment algorithm for nano-scale 3D printing system was developed. Implementing the algorithm leads to an accepted error margin of 0.5% by compensating error in rotational, horizontal, and vertical axes.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.1-8
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• 2017

Tool path generation is a part of process planning in 3D printing. This is done before actual printing by a computer rather than an AM machine. The mesh geometry of the 3D model is sliced layer-by-layer along the Z-axis and tool paths are generated from the sliced layers. Each 2-dimensional layer can have two types of printing paths: (i) shell and (ii) infill. Shell paths are made of offset loops. During shell generation, twists can be produced in offset loops which will cause twisted tool paths. As a twisted tool path cannot be printed, it is necessary to remove these twists during process planning. In this research, An algorithm is presented to remove twists from the offset loops. To do so the path segments are traversed to identify twisted points. Outer offset loops are represented in the counter-clockwise segment order and clockwise rotation for the inner offset loop to decide which twisted loop should be removed. After testing practical 3D models, the proposed algorithm is verified to use in tool path generation for 3D printing.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.763-773
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• 2012

본 논문에서는 Wi-Fi를 이용한 RSSI (Received Signal Strength Indication)기반의 측위 시스템에서 전파환경변화에 민감한 시스템의 문제를 보완하기 위하여 랜드마크 발신기 기반의 측위 시스템을 제안한다. 이를 위하여 핑거프린팅 알고리즘 및 랜드마크 발신기를 구현 하였으며 간단한 측위 정확도 예측모델을 만들어 수신된 전파세기를 기반으로 측위 정확도를 예측하였다. 이를 바탕으로 실내 TEST BED를 구축하였고 주요 지점에 랜드마크 발신기를 부착하여 시스템의 효용성을 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.963-965
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• 2017

최근 3D 프린터에 대한 관심이 커지고 있다. 3D 프린팅을 위해서 전용 소프트웨어를 이용하여 설계 파일을 생성하고 출력하지만, 각 3D 프린트마다 지원하는 파일 형식이 다르고, 특정 데이터 파일 형식을 변환할 때에는 별도의 프로그램이 필요하기 때문에 많은 시간과 노력이 필요하다. 본 논문에서는 이러한 일련의 복잡한 과정을 개선하기 위해 입력 파일을 각 3D 프린터가 지원하는 파일 형태로 손쉽게 변환하여 출력할 수 있는 모델링 기법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.68-70
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• 2016

3D 프린터는 연속적인 계층에 특수한 재료를 출력시켜 3차원 물체를 만들어 내는 장치이다. 3D 프린팅을 위해서는 3D 모델을 생성한 후, 이를 3D 프린터에 출력할 수 있도록 G-code로 변환해야 한다. 본 논문에서는 이 변환 작업을 완전 분산 방식으로 처리할 수 있는 알고리즘을 제안한다. 이를 위해 하나의 메인 노드와 N개의 작업 노드로 구성한 시스템에서 2단계에 걸쳐 분할 정복(divide-and-conquer) 방식으로 변환하도록 하였다. 실제 구현한 시스템을 이용하여, 성능에 미치는 요소(모델의 크기 및 정밀도)에 따른 변환 시간의 단축 효과를 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1448-1450
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• 2015

본 논문은 3D 스캐너 및 센서 등으로 캡처되어 3D로 복원된 얼굴 객체의 부위별 의미 있는 영역에 대한 분할을 자동으로 수행하는 기술을 제안한다. 3D 스캔된 얼굴 모델을 모델링, 애니메이션, 3D 프린팅 등의 다양한 응용분야에 활용하기 위해서는 스캔된 영역의 의미 있는 부위별 인식이 필수적이다. 본 논문에서는 부위별 의미 있는 영역 레이블링이 된 템플릿 모델을 입력된 3D 복원 모델로 전이하여 복원된 3D 모델의 부위별 의미 있는 영역을 자동으로 분할하고 분할된 영역의 일관성을 유지하는 알고리즘을 제안한다.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.92-97
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• 2019

In this paper, we investigated the problems and solutions in the production of scaffolds using commercially available FDM 3D printers. We used ADRIGE TRIZ algorithm to systematically analyze the problems and suggest solutions. We printed scaffolds using suggested solutions. We measured the pore size and printing time of the scaffolds. We have confirmed that the printing precision is greater than 99% and the printing time is decreased by half. The suggested solutions proved its validity through experiments and showed satisfactory results.