• Journal of information and communication convergence engineering
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• 제18권4호
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• pp.222-229
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• 2020

Recent multi-core processors for smart devices use per-core dynamic voltage and frequency scaling (DVFS) that enables independent voltage and frequency control of cores. However, because the conventional task scheduler was originally designed for per-core DVFS disabled processors, it cannot effectively utilize the per-core DVFS and simply allocates tasks evenly across all cores to core utilization with the same CPU frequency. Hence, we propose a novel task scheduler to effectively utilize percore DVFS, which enables each core to have the appropriate frequency, thereby improving performance and decreasing energy consumption. The proposed scheduler classifies applications into two types, based on performance-sensitivity and allows a performance-sensitive application to have a dedicated core, which maximizes core utilization. The experimental evaluations with a real off-the-shelf smart device showed that the proposed task scheduler reduced 13.6% of CPU energy (up to 28.3%) and 3.4% of execution time (up to 24.5%) on average, as compared to the conventional task scheduler.

• 한국수산과학회지
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• 제56권4호
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• pp.512-519
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• 2023

Pacific oysters Crassostrea gigas are a popular shellfish in the Republic of Korea. However, due to their abundant moisture and nutrient content, oysters are susceptible to microbiological growth and biochemical changes, which lead to quality degradation. Therefore, the present study aimed to investigate the effectiveness of modified atmosphere packaging (MAP) in maintaining the quality of raw oysters during storage. Microbiological and physicochemical parameters such as pH, glycogen content, soluble protein, turbidity, and volatile basic nitrogen (VBN) were analyzed for oysters stored under various gas compositions and storage periods. The results showed that there was no significant increase in viable cell count in MAP oysters after six days in MAP oysters. Moreover, the physicochemical quality of non-MAP oysters deteriorated rapidly, whereas the quality of MAP oysters were maintained during storage. This study suggests that MAP can be an effective technique for maintaining the freshness of raw oysters during distribution and storage, and may also be useful for extending the shelf-life and maintaining the quality of other seafood products.

• 한국컴퓨터정보학회논문지
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• 제22권9호
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• pp.107-113
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• 2017

In this paper, we propose a medication reminder system using IoT platforms and products to help old adults keep track of their medication schedule, one of 10 Korean instrumental activities in daily living (K-IADL). An interworking architecture based on the oneM2M standard platform is designed to allow various IoT products to be connected each other through interworking proxy entities. A prototype system for the medication reminder service is developed, which consists of a pair of off-the-shelf pill bottle and container box embedded with an NFC tag and reader respectively, three types of actuators including a LIFX LED lightbulb, Musaic speaker, Microsoft Band 2, and smartphone applications. The experiment shows that our medication reminder system can make alarms for old adults to take their pills appropriately considering where they are and when they have food inferred from data collected from sensors including ultrasonic sensor and rice cooker, fostering them to keep their medication routine.

• 한국포장학회지
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• 제27권3호
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• pp.187-192
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• 2021

본 연구는 로메인 상추를 대상으로 몇 가지 온도 조건에서 재배된 어린잎의 품질과 MA 저장 시 저장성을 비교하고자 수행하였다. 21℃, 28℃, 그리고 35℃ 챔버 내에서 인공광원(200 µmol·m^-2·s^-1) 하에 5주간 재배되었다. 재배 종료일에 생육 및 품질조사를 진행하였고, 20,000cc OTR 필름과 유공필름으로 각각 36일, 12일간 저장하며 필름 내 산소, 이산화탄소, 그리고 에틸렌 농도를 측정하였다. 그리고 저장 종료일에 엽색, 엽록소, 외관상 품질을 조사하였다. 재배 종료일의 엽장은 28℃ 재배구가 가장 길었고, 엽폭은 21℃와 28℃ 재배구가 넓었다. 엽수는 모든 재배온도에서 5~6장으로 유사하였고, 최대 양자수율은 21℃와 28℃ 재배구가 높았다. 엽중, 근중, 건물중은 21℃가 높았고, 재배온도가 올라갈수록 감소하는 경향을 보였다. 호흡률과 에틸렌 발생률은 35℃가 높았고, 재배온도가 낮아질수록 감소하였다. 저장 중 생체중 감소율은 모든 MA 저장 처리구는 저장 종료일인 36일까지 1% 미만이었고, 모든 유공필름 처리구는 저장 후 급격히 증가하여 저장 종료일인 12일째에 12~15%의 높은 감소율을 보였다. MA 저장 처리구의 필름 내 에틸렌 농도는 재배온도와 관계없이 모든 처리구가 저장 종료일까지 1~2 µL·L^-1의 농도를 유지하였다. 필름 내 산소 농도는 19.5% 내외, 이산화탄소는 1% 내외의 농도를 유지하며 모든 MA 저장 처리구가 CA 조건에 부합하였다. 저장 종료일의 엽색은 Hunter a^*, b^* 값 모두 대체로 MA 저장 처리구에서 높았다. 엽록소 함량은 재배온도가 올라갈수록 낮아지고, 유공필름 처리구와 비교해 MA 저장 처리구에서 낮았다. 패널테스트를 통한 외관상 품질은 21℃ MA 저장 처리구에서만 상품성 한계점인 3점 이상이었다. 이상의 결과를 종합해보면, 로메인 상추 어린잎은 21℃에 재배할 때 최대 양자수율이 높아 생체중 등의 생육이 좋았으며, 재배 중 온도환경이 낮을수록 저장수명이 연장되었다. 또한 저장 방법으로는 CA 조건의 이산화탄소 농도를 충족시킨 MA 저장처리에서 저장 종료일까지 우수한 외관상 품질을 보여 저장수명을 3배까지 연장할 수 있었다.

• 한국산업정보학회논문지
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• 제27권6호
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• pp.69-75
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• 2022

본 논문에서 비대칭 멀티 코어 구조의 스마트 모바일 단말에서 실시간성 보장과 에너지 소비량 절감을 고려한 작업 스케쥴링 기법을 제안한다. 최근 VR, AR, 3D 등 고성능 응용프로그램은 실시간과 고수준 작업이 요구된다. 스마트 단말은 배터리에 의존적이므로 높은 에너지 효율을 위해서 big.LITTLE 구조가 적용되었지만, 이를 제대로 활용하지 못함으로써 에너지 절감효과가 반감되는 문제점이 있었다. 본 논문에서는 big.LITTLE 구조의 단말에서 실시간성과 높은 에너지 효율을 높일 수 있는 비대칭 멀티코어 할당 기법을 제안한다. 이 기법은 SVM 모델을 활용해서 실제 작업의 실행시간을 예측하고 이를 통해서 에너지 소모와 실행시간을 최적화한 알고리즘을 제안한다. 상용 스마트폰에서의 비교실험을 통하여 제안기법이 기존 기법과 유사한 실행시간을 보장하면서 에너지 소비량의 절감을 보였다.

• 한국건설관리학회논문집
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• 제23권1호
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• pp.98-105
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• 2022

밀폐된 공간에서 인공적인 방법으로 작물을 재배하는 수직형 스마트 팜은 공기 환경 설비를 적절히 활용하여 적정한 생육환경을 조성하는 것이 중요하다. 하지만 국내 수직형 스마트 팜 기업들은 체계적인 방법이 아닌 경험적 데이터에 의존하여 생육환경을 조성하고 있다. IoT를 활용하여 체계적이고 정밀한 모니터링을 토대로 생육환경을 조성한다면 작물의 생산 수율을 높이고 수익성을 극대화할 수 있다. 본 연구의 목적은 IoT를 활용하여 모니터링 시스템을 구성하고, 작물 재배에 주요한 요인인 온도 환경의 불균형을 실증하여 그 원인을 분석하는 데 있다. LED와 냉방기의 가동 방식을 달리하며 1) 다층 선반의 수평 온도 분포를 측정한 결과 센서 간에 "최대 1.7℃"의 온도 격차를 보였다. 2) 수직 온도 분포를 측정한 결과 "최대 6.3℃"의 온도 차이를 보였다. 이러한 온도 격차를 줄이기 위해서는 공조설비의 적절한 배치와 운영 방식에 대한 전략이 필요하다.

• IEIE Transactions on Smart Processing and Computing
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• 제1권2호
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• pp.106-116
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• 2012

The huge success of location-aware applications has called for the rapid development of an alternative positioning system to the global positioning system (GPS) for indoor localization based on existing technologies, such as 802.11 wireless networks. This paper proposes the Wireless MAC Processor Positioning System (WMPS), which is a localization system running on off-the-shelf 802.11 Access Points and based on the time-of-flight ranging of users' standard terminals. This paper proves through extensive experiments that the propagation delays can be measured with the accuracy required by indoor applications despite the different noise components that can affect the result: latencies of the hardware transreceivers, multipath, ACK jitters and timer quantization. Key to this solution is the choice of the Wireless MAC Processor architecture, which enables a straightforward implementation of the ranging subsystem directly inside the commercial cards without affecting the basic DCF channel access algorithm. In addition to the proposed measurement framework, this study developed a simple and effective localization algorithm that can work without requiring any preliminary calibration or device characterization. Finally, the architecture allows the measurement methodology to be adjusted as a function of the network load or propagation environments at the run time, without requiring any firmware update.

• Smart Structures and Systems
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• 제18권6호
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• pp.1217-1231
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• 2016

In this research, a slotted patch antenna sensor is designed for wireless strain and crack sensing. An off-the-shelf RFID (radiofrequency identification) chip is adopted in the antenna sensor design for signal modulation. The operation power of the RFID chip is captured from wireless reader interrogation signal, so the sensor operation is completely battery-free (passive) and wireless. For strain and crack sensing of a structure, the antenna sensor is bonded on the structure surface like a regular strain gage. Since the antenna resonance frequency is directly related with antenna dimension, which deforms when strain occurs on the structural surface, the deformation/strain can be correlated with antenna resonance frequency shift measured by an RFID reader. The slotted patch antenna sensor performance is first evaluated through mechanics-electromagnetics coupled simulation. Extensive experiments are then conducted to validate the antenna sensor performance, including tensile and compressive strain sensing, wireless interrogation range, and fatigue crack sensing.

• 한국정밀공학회지
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• 제32권3호
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• pp.285-292
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• 2015

This paper presents a wireless ground reaction force (GRF) sensing system for ambulatory GRF recording. The system is largely divided into three parts: force sensing modules based on optical sensor, outsole type frame, and embedded system for wireless communication. The force sensing module has advantages of the low height, robustness to the moment interference, and stable response in long term use. In simulation study, the strain and stress properties were examined to satisfy the requirements of the GRF sensing system. Four sensing modules were mounted on the toe, ball, and heel of foot shaped frame, respectively. The GRF signals were extracted using Micrpcontroller unit and transferred to the smart phone via Bluetooth communication. We measured the GRF during the normal walking for the validation of the continuous recording capability. The recorded GRF was comparable to the off the shelf stationary force plate.

• Smart Structures and Systems
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• 제22권2호
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• pp.175-183
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• 2018

Time-series data often contain one of the most valuable pieces of information in many fields including manufacturing. Because time-series data are relatively cheap to acquire, they (e.g., vibration signals) have become a crucial part of big data even in manufacturing shop floors. Recently, deep-learning models have shown state-of-art performance for analyzing big data because of their sophisticated structures and considerable computational power. Traditional models for a machinery-monitoring system have highly relied on features selected by human experts. In addition, the representational power of such models fails as the data distribution becomes complicated. On the other hand, deep-learning models automatically select highly abstracted features during the optimization process, and their representational power is better than that of traditional neural network models. However, the applicability of deep-learning models to the field of prognostics and health management (PHM) has not been well investigated yet. This study integrates the "residual fitting" mechanism inherently embedded in the wavelet transform into the convolutional neural network deep-learning structure. As a result, the architecture combines a signal smoother and classification procedures into a single model. Validation results from rotor vibration data demonstrate that our model outperforms all other off-the-shelf feature-based models.