• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.1
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• pp.55-64
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• 2022

The potassium cream soap with fatty acid called cleaning foam has a crystal gel structure, and unlike an emulsion system, it is weak to shear stress and shows characteristics that are easily separated under high temperature storage conditions. The crystal gel structure of cleansing foams is significantly influenced by the nature and proportion of fatty acids, degree of neutralization, and the nature and proportion of polyols. In order to investigate the effect of these parameters on the crystal gel structure, a ternary system consisting of water/KOH/fatty acid was investigated in this study. The investigation of differential scanning calorimeter (DSC) revealed that the eutectic point was found at the ratio of myristic acid (MA) : stearic acid (SA) = 3 : 1 and ternary systems were the most stable at the eutectic point. However, the increase in fatty acid content had little effect on stability. On the basis of viscosity and polarized optical microscopy (POM) measurements, the optimum degree of neutralization was found to be about 75%. The system was stable when the melting point (T_m) of the ternary system was higher than the storage temperature and the crystal phase was transferred to lamellar gel phase, but the increase in fatty acid content had little effect on stability. The addition of polyols to the ternary system played an important role in changing the T_m and causing phase transition. The structure of the cleansing foams were confirmed through cryogenic scanning electron microscope (Cryo-SEM), small and wide angle X-ray scattering (SAXS and WAXS) analysis. Since butylene glycol (BG), propylene glycol (PG), and dipropylene glycol (DPG) lowered the T_m and hindered the lamellar gel formation, they were unsuitable for the formation of stable cleansing foam. In contrast, glycerin, PEG-400, and sorbitol increased the T_m, and facilitated the formation of lamellar gel phase, which led to a stable ternary system. Glycerin was found to be the most optimal agent to prepare a cleansing foam with enhanced stability.

• The monthly packaging world
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• s.285
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• pp.82-94
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• 2017

2016년 우수디자인(GD)상품선정 시상식이 지난해 12월 14일코리아디자인센터 컨벤션홀에서 열렸다. '우수디자인(GD)상품선정제도'는 1985년부터 산업디자인진흥법 제6조에 의거하여 상품의 경제성, 사용성, 환경친화성, 심미성 등을 종합적으로 심사하여 디자인이 우수한 상품과 서비스에 GD마크를 부여하는 제도로, 산업통상자원부가 주최하고 한국디자인진흥원이 주관하고 있다. GD마크는 우수한 디자인 상품 개발을 장려하여 국가경쟁력을 확보하고 국민 삶의 질을 향상시키는 것을 목표로 선정하고 있다. 또한 창의 디자인강국 구현을 위해 세계적 인증가치를 구축하고, 유니버설디자인, 서비스디자인, 전통시장 산업단지 디자인을 고도화(우수디자인 선정 장려 등)함으로써 사회적 문제해결과 지속가능한 창조경제 실현에 그 의의가 있다. 올해 선정대상품목은 제품, 커뮤니케이션, 포장, 공간환경, 서비스 등의 부문에서 39개 항목으로 출품됐다. 포장 부문은 소비자제품, 식음료, 뷰티/헬스, 의료, 산업/B2B, 기타 포장 등 6개 항목으로 구성됐다. 올해 포장 부문에서는 플러긴스의 STONE JEJU CANDLE이 국무총리상을, 엘지전자(주)의 LG Sound 360 패키지가 산업통상자원부장관상을, 유씨엘(주)의 아꼬제, (주)퍼스트마켓의 코코스타 핸드모이스쳐 팩, (주)웰코스의 후르디아 크림이 조달청장상을, 일동홀딩스(주)의 그녀는 프로다, 삼성전자(주)의 삼성 모바일 액세서리 패키지 시리즈, 피치앤드의 피치앤드는 KIDP원장상을, (주)유니베라의 남양알로에 맥스피는 중소기업청장상 등을 수상했다. 다음에 우수디자인으로 선정된 포장부문 제품들을 살펴보도록 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.205-206
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• 2018

본 논문에서는 IoT 환경의 무선 센서 네트워크 시스템 상의 효율적인 패킷 전달을 위해 큐러닝(Q-learning)에 기반한 다중 대기열 동적 스케쥴링 기법을 제안한다. 이 정책은 다중 대기열(Multiple queue)의 각 큐가 요구하는 딜레이 조건에 맞춰 최대한 패킷 처리를 미룸으로써 효율적으로 CPU자원을 분배한다. 또한 각 노드들의 상태를 큐러닝(Q-learning)을 통해 지속적으로 상태를 파악하여 기아상태(Starvation)를 방지한다. 제안하는 기법은 무선 센서 네트워크 상의 가변적이고 예측 불가능한 환경에 대한 사전지식이 없이도 요구하는 서비스의 질(Quality of service)를 만족할 수 있도록 한다. 본 논문에서는 모의실험을 통해 기존의 학습 기반 패킷 스케쥴링 알고리즘과 비교하여 제안하는 스케쥴링 기법이 복잡한 요구조건에 따라 유연하고 공정한 서비스를 제공함에 있어 우수함을 증명하였다.

• The monthly packaging world
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• s.267
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• pp.80-92
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• 2015

산업통상자원부가 주최하고 한국생산기술연구원이 주관하는 2015년도 "제9회 미래패키징 신기술 정부포상"수상작이 선정됐다. 미래지식산업인 패키징산업 종사자의 긍지와 자부심 함양의 계기를 실천하고, 패키징산업 종사자의 사기진작과 패키징산업 활성화를 도모하기 위해 매년 진행되고 있는 미래패키징신기술 정부포상은 패키징 산업 기술인의 기술개발 의욕을 고취하고 패키징산업 기술성과 및 산업발전 기여도에 대한 정부포상를 실현하며 패키징산업 종사자간 정보교류 극대화 및 공동체 의식 함양으로 일체감을 조성시켜왔다는 평가를 받고 있다. 미래패키징 신기술 정부포상은 기업부문 및 학생부문, 그리고 공로부문으로 나누어 수상자를 선정, 진행되고 있다. 기업부문은 패키징 완제품, 친환경패키징, 패키징관련기계(설비) 및 관련부품, 패키징인쇄(라벨링), 패키징원부자재 생산 및 가공공정, 패키징디자인 등의 분야에서 신기술 개발 또는 개선으로 수출신장, 매출 수익 증대 및 발명특허 획득을 통해 패키징 기술력 발전에 기여한 기업의 패키징제품 또는 패키징디자인을 대상으로 하고 있으며, 학생부문은 패키징 디자인 관련분야 전공자로 패키징과 연관된 컨셉으로 상품성, 창의성, 표현성, 친환경성, 지속가능성 등이 어우러진 독창적인 패키징제품 또는 패키징디자인을 대상으로 진행하고 있다. 또한 공로부문은 패키징 산업 관련 산업계, 학계, 연구계, 유관기관에 종사하는 자로서 패키징 관련 핵심 기술개발, 경영, 마케팅 면에서 패키징 산업 발전에 기여한 공적이 뚜렷한 자, 패키징산업발전 정책연구 및 패키징산업 육성에 기여한 기업 또는 개인을 대상으로 하고 있다. 제9회 미래패키징 신기술 정부포상 심사 결과 삼성전자(주)의 'Curved UHD TV 용(用) Curved 포장 Box'가 국무총리상으로 선정됐으며, (주)대륙제관의 '폭발방지 맥스부탄'을 비롯해 4개사가 산업통상자원부 장관상으로 선정되는 등 총 29개사가 수상 기업으로 선정됐다. 공로부문에서는 (주)남경의 김선창 회장과 (주)화남인더스트리의 석용찬 회장이 산업통상자원부장관 표창자로 선정됐다. 이 외에도 학생부문에 17개 작품이 선정, 수상이 예정되어 있다. 본 고에서는 기업부문 수상작 및 공로부문 수상자들의 활약상을 살펴보도록 한다.

• Resources Recycling
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• v.33 no.1
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• pp.22-30
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• 2024

To synthesize the Ti₃AlC₂ MAX phase, a crucial precursor for generating the two-dimensional material MXene, the use of Ti scrap as an initial material is an economically feasible approach. This study aims to optimize the synthesis conditions for the phase fraction of the Ti₃AlC₂ MAX phase utilizing Ti scrap as the Ti source. The deoxidation of Ti powders, prepared through the hydrogenation-dehydrogenation process from Ti scrap, was effectively accomplished using the deoxidation in solid-state (DOSS) process. The optimal synthesis conditions were established by blending DOSS-Ti, Al, and graphite powders with particle sizes ranging from 25 ~ 32 ㎛ in a molar ratio of 3:1.1:2. The resulting phase fractions were as follows: Ti₃AlC₂ at 97.25 wt.%, TiC at 0.93 wt.%, and Al₃Ti at 1.82 wt.%. Furthermore, the oxygen content of the Ti₃AlC₂ MAX powder, spanning from 25 ~ 45 ㎛, was measured at 4,210 ppm.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1327-1334
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• 2004

The purpose of this paper is to implement Web 3D environment that is not provider - oriented but client-oriented in order to provide dynamic information and to analyze knowledges by executing programs on Web pages. For these, The 3D Viewer program that parses and renders ASE files - the most general 3D Model Data file and exported text file of 3D Max Studio - is made and then converted into ActiveX 3D Viewer Component that can be used on the Web. With the purpose of managing ASE and texture file efficiently and interacting between clients and server, ActiveX Component link ASP and Database with Web Service. The 3D View Web Service can make dynamic information and cooperative works easier in Networked Virtual Reality.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.97-103
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• 2019

Mn+1AXn (MAX) phases are a family of nano-laminated compounds that possess unique combination of typical ceramic properties and typical metallic properties. As a member of MAX-phase, $Ti_2AlN$ bulk materials are attractive for some high temperature applications. In this study, $Ti_2AlN$ bulk with high density were synthesized by spark plasma sintering method. X-ray diffraction, micro-hardness, electrical and thermal conductivity were measured to compare the effect of material properties both $Ti_2AlN$ bulk samples and a conventional Ti-6Al-4V alloy. A femto-second laser conditions were conducted at a repetition rate of 6 kHz and laser intensity of 50 %, 70% and 90 %, respectively, laser confocal microscope were used to evaluate the width and depth of ablation. Consequently, the laser ablation result of the $Ti_2AlN$ sample than that of the Ti-6Al-4V alloys show a considerably good ablation characteristics due to its higher thermal conductivity regardless of to high densification and high hardness.

• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.833-844
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• 2018

Dual energy X-ray absorptiometry is mainly used as an X-ray test method. For equipment manufactured GE and Hologic, cross-calibration analyses (CCA) of machines from the same manufacturer and between units from different manufacturers have been conducted, but the CCA of equipment manufactured in Korea are inadequate. Through CCA, we present a formula of the intersections between the Korean medical equipment company (KEC) with GE and Hologic manufactured DXA, and among the KEC DXA. The CCA was conducted for the European Spine Phantom on DXA from four KEC and three global medical equipment company (GEC) manufacturers. We compared bone mineral density (BMD) values and calculated the CCA equation by linear regression analysis. The standard-deviations (SD) of the BMD values were highest for the Dexxum T for the low, medium, and high spine, which were 0.030, 0.029, and 0.037, respectively. The smallest SD in the low and medium vertebrae were 0.005 and 0.004 for the Horizon Ci, respectively, and 0.005 for the Osteo Pro Max in the high vertebrae. Based on the intersection equations of the KEC DXA established in this study, CCA of various KEC DXA should be established for more accurate follow-up of BMD tests in clinical environments.

• Journal of the Korean Geographical Society
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• v.41 no.2 s.113
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• pp.150-167
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• 2006

This study was conducted to determine the pedogenesis of dense subsurface horizons (denoted either Bx or Bd) observed within closed depressions and in toeslope positions at loess-covered glacial tillplains in southern Wisconsin. Some of these dense subsurface horizons, especially those occurring within depressions, show a close morphological resemblance to fragipans elsewhere, even though the existence of fragipans has not been previously reported in southern Wisconsin. The spatial occurrence of fragipans was first examined over the landscape to characterize general soil-landscape relationships. Detailed physico-chemical and micromorphological analyses were followed to investigate the development of fragipans within a closed depression along a catenary sequence. The formation of fragipans at the study site is a result of sequential processes of physical ripening and accumulation of colloidal materials. A very coarse prismatic structure with a closely packed soil matrix was formed via physical ripening processes of loess deposited in small glacial lakes and floodplains that existed soon after the retreat of the last glacier. The physically formed dense horizons became hardened by the accumulation of colloidal materials, notably amorphous Si. The accumulation intensity of amorphous Si varies with mass balance relationships, which are governed by topography and local drainage conditions. Well-developed Bx horizons evolve at closed depressions where net accumulation of amorphous Si occurs, but the collapsed layers remain as Bd horizons at other locations where soluble Si has continuously been removed downslope or downvalley. Hydromorphic processes caused by the presence of fragipans are degrading upper parts of the prisms, resulting in the formation of an eluvial fragic horizon (Ex).

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.