• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.249-252
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• 2019

본 논문은 파충류 시장의 활성화와 파충류 사육 부담감을 해소하고자 사육자들에게 편리하고 접근성이 높은 서비스를 제공하는 파충류 사육을 위한 스마트 환경제어시스템을 제공한다. 본 논문이 제시하는 주요한 기능은 다음과 같다. 첫째, 사육장 내 습도를 미스팅 시스템과 팬을 통해 제어를 한다. 둘째, 사육장 내 온도를 조광기를 활용한 스팟 램프의 밝기 조절을 통해 제어한다. 셋째, 파충류 먹이 공급 및 물 공급을 자동화하여 체계적인 식단을 관리한다. 넷째, 적외선 감지 센서를 통한 데이터를 활용해 파충류의 활동량과 탈피 및 질병의 가능성을 예상한다. 제안된 시스템은 IoT 기술을 접목함으로써 현대 사회에서 추구하는 편리함과 기존 파충류 사육의 번거로움을 해소하는 것을 목표로 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.939-941
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• 2019

단조는 강괴를 고온으로 가열하고 원하는 형상으로 만드는 공정이다. 가열로에 강괴를 장입하여 가열하고, 고온의 강괴에 프레스, 절단 공정을 적절히 반복하여 원하는 형상으로 만든다. 형상이 완성된 강괴의 경도 및 강도를 조절하기 위해 열처리 공정을 진행한다. 열처리로에 여러 개의 강괴를 장입하여 가열하기 때문에 에너지 비용이 많이 소모된다. 열처리 공정 비용은 열처리 공정의 종류와 장입되는 강괴들의 특성 및 수량 등에 따라서 결정된다. 열처리로에 장입할 강괴 조합을 최적화함으로써 비용을 최소화시킬 수 있다. 따라서 본 논문에서는 비용 예측 모형을 이용하여 열처리로 작업 계획을 최적화하는 방안을 제안한다. 비용 예측 모형은 IoT 인프라를 기반으로 수집한 공정 데이터를 이용하여 학습한다. 다양한 열처리로 작업 계획은 학습한 모형 기반의 시뮬레이션을 통해 평가하여 유전 알고리즘을 기반으로 최적화한다. 최적의 열처리로 작업 계획을 수립함으로써 공정 비용을 최소화하고 에너지 효율을 극대화할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1020-1023
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• 2021

본 논문에서는 기존의 책상에서 발생하는 문제점을 개선하고 효율적인 공부를 할 수 있도록 도와주는 "학습 능률을 높이는 스마트 책상" 시스템을 제안한다. 제안하는 시스템의 주요 기능은 다음과 같다. 첫째, 아두이노와 Linear actuator를 사용하여 책상의 높낮이와 책받침의 각도를 조절한다. 둘째, 심박 센서를 통해 사용자의 집중도를 확인하고 이와 연동된 어플리케이션으로 각종 센서와 모듈을 제어하여 최적의 공부환경을 조성한다. 셋째, 책상 위 모든 동작이 어플리케이션을 통해 자동으로 수행되어 Human task를 감소시킨다. IoT 기술과 집중력 관리 알고리즘을 활용한 제안 시스템을 통해 학습자의 책상 앞 올바른 자세 교정과 학습 시 높은 집중력을 유지시키는데 도움을 줄 수 있을 것으로 기대된다.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.267-273
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• 2015

Recently, a wide range of products incorporating cutting-edge technology are being introduced in various sectors of design. Belkin's WeMo or Phillips' Hue are representative examples. In this context, the color-responsive lighting bookcase is a design product that would satisfy the needs of contemporary consumers who seek entertainment in their purchases. By installing lightings that change color according to the user's behavior, this design reconceptualizes the bookcase as a source of entertainment rather than a mundane object of household furnishing. The lighting apparatus can be detached and reattached, serving as stand-alone equipment. The lighting bookcase is modularized, comprising extensions equipped with MCU (Micro Controller Unit), RGB LED and color sensors. The bookcase as a whole is extendable towards four directions up to nine units with the lighting bookcase at the center. The extended, multiple lighting bookcases are wired to receive power from the main bookcase, and are equipped with RGB LEDs but not with MCUs or color sensors. Receiving power and color signals from the main lighting bookcase, the sub-bookcases feature changing shades of color. Also, it includes IoT(internet of Things). This study is a proposal of a design product, modularized to control the shades of the bookcase lighting using these sensors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.145-152
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• 2020

In this paper, we propose the Crop Classification Management System (CCMS) that detects changes in growth environment to improve crop production rate. The CCMS consists of two modules. First, the Crop Classification Module (CCM) classifies crops through CNN. Second, the Farm Anomaly Detection Module (FADM) detects abnormal crops by comparing accumulated data of farms. The CCM recognizes crops currently grown on farms and sends them to the FADM, and the FADM picks up the weather data from the past to the present day of the farm growing the crops and applies them to the Nelson rules. The FADM uses the Nelson rules to find out weather data that has occurred and adjust farm conditions through IoT devices. The performance analysis of CCMS showed that the CCM had a crop classification accuracy of about 90%, and the FADM improved the estimated yield by up to about 30%. In other words, managing farms through the CCMS can help increase the yield of smart farms.

• Physical Therapy Korea
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• v.25 no.1
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• pp.1-11
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• 2018

Background: The continuous co-contraction of the trunk muscles through trunk stabilization exercises is important to patients with lumbar spinal stenosis (LSS). However, intentional abdominal muscle contraction (IAMC) for trunk stabilization has been used only for specific training in the treatment room. Objects: The purpose of this study was to provide feedback to adults with LSS to enable IAMC during activities of daily living (ADLs). Methods: The participants with spinal stenosis were divided into an experimental group of 15 adults and a control group of 16 adults. Electromyographic signals were measured while the subjects kept their both hands held up at $90^{\circ}$. The measured muscles were the rectus abdominis (RA), external oblique (EO), internal oblique (IO), and erector spinae (ES). Pelvic tilt was measured using a digital pelvic inclinometer. The degree of pain was measured using the visual analogue scale (VAS) and functional capacity was measured using the Korean version of the Oswestry disability index (KODI). Results: While the experimental group showed statistically significantly higher activities in the RA, EO, and IO after the intervention compared with the control group. Pelvic tilt was significantly decreased only in the experimental group. Both the experimental and control groups exhibited statistically significant declines in the VAS and KODI (p<.01). In terms of the levels of changes, the experimental group exhibited a statistically significant larger decline only in the VAS and the pelvic tilt when compared with the control group (p<.05). Conclusions: The subjects could stabilize their trunks, and relieve their pain and dysfunctions and reduce pelvic tilt by learning abdominal muscle contraction during ADLs. The combination of therapeutic exercises and IAMC may have greater effects on patients with LSS.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.100-105
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• 2017

This work presents an ECG biometric recognition system for the purpose of biometric authentication. ECG biometric approaches are divided into two major categories, fiducial-based and non-fiducial-based methods. This paper proposes a new non-fiducial framework using discrete cosine transform and a Random Forest classifier. When using DCT, most of the signal information tends to be concentrated in a few low-frequency components. In order to apply feature vector of Random Forest, DCT feature vectors of ECG heartbeats are constructed by using the first 40 DCT coefficients. RF is based on the computation of a large number of decision trees. It is relatively fast, robust and inherently suitable for multi-class problems. Furthermore, it trade-off threshold between admission and rejection of ID inside RF classifier. As a result, proposed method offers 99.9% recognition rates when tested on MIT-BIH NSRDB.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.4
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• pp.341-362
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• 2017

This study is to analyze the applicability of new technologies to be applied to the foreseeable future's library. For this purpose, we measured the users' intention to accept the service by using the NFC based self-check out service as a new technology applicable to the library. Based on the Unified Theory of Acceptance Use of Technology (UTAUT), research models were derived, and the structural relationships between performance expectations, effort expectations, facilitation conditions, and perceived risks were analyzed. As a result of the analysis, perceived threats in the library did not affect the intention to use, and the performance expectation, effort expectation, and facilitation condition partially affected the intention to use. The gender of the moderator variable, there were some significant difference in promoting conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1679-1686
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• 2019

The main purpose of this research is to propose an approach for solving the packet loss problem by quickly adapting to topology change when nodes move in RPL-based IoT environment. In order to enhance mobility, every node is aware of the mobility of its neighbor nodes and quantifies the mobility level based on the number of control messages and all received packets. According to the mobility level, the DIO timer is changed. The proposed approach allows nodes to change their DIO timers according to their mobility levels to adapt topology changes and update paths to the sink. The performance of the proposed approach is evaluated using a Contiki-based Cooja simulator in various moving speeds. The simulation results show that the proposed approach copes with mobility scenarios better than the standard RPL by ascertaining that the packet delivery ratio is improved by 31.03%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.74-87
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• 2020

Overloaded trucks are the main source that threatens road safety and directly affects the reduction of pavement life. The On-board truck scale is the only equipment that could prevent overloading by measuring and adjusting the loading weight before driving. Legislation is needed to encourage its installation so that the driver can prevent overloading. In this study, an on-board truck scale system was installed on 30 dump trucks for transporting construction waste, such as soil and aggregates, which are major loads of 36.55% for overloading, and the trucks were monitored remotely. The overload prevention effect was analyzed by comparing driving data for 1 month before distribution of the weight display app that can recognize the weight to the driver and 1 month after distribution. After installation, overloading could be 6.1% reduced, and the transportation efficiency could be increased by checking the weight provided from the On-board truck scale system.