• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.123-133
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• 2011

The objective of this study was to find optimal nutrient condition of container seedling production of two tropical species for high seedling quality. This study was conducted to investigate photosynthesis, chlorophyll fluorescence, chlorophyll contents, and growth performances of container seedlings of Eucalyptus pellita and Acacia mangium growing under four different fertilization treatments (Con., $0.5\;g{\cdot}l^{-1}$, $1.0\;g{\cdot}l^{-1}$, and $2.0\;g{\cdot}l^{-1}$ fertilization). E. pellita showed outstanding photosynthetic capacity, photochemical efficiency, and chlorophyll contents at $1.0\;g{\cdot}l^{-1}$ fertilization. Meanwhile, E. pellita showed the highest photosynthetic capacity, photochemical efficiency, and chlorophyll contents at $2.0\;g{\cdot}l^{-1}$ fertilization, as fertilization rate were increased, those of A. mangium increased. Like physiological characteristics, Both E. pellita at $1.0\;g{\cdot}l^{-1}$ fertilization and A. mangium at $2.0\;g{\cdot}l^{-1}$ fertilization were higher root collar diameter, height, biomass, and seedling quality index than other treatments. These results showed that E. pellita at $1\;g{\cdot}l^{-1}$ fertilization and A. mangium at $2.0\;g{\cdot}l^{-1}$ fertilization is optimal nutrient condition, respectively. Moreover, fertilization rate controlling is very important for growth and seedling quality of container seedling.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.53-53
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• 2018

전라북도 동부권 지역은 중산악지형으로 표고 100~500m 산지가 69%, 500~1,000m가 26%로 이루어져 있어, 산채를 재배하기에 유리한 지리적 조건을 갖고 있다. 따라서 소비자의 수요가 높은 산채류의 재배 및 이용에 대한 농업인들의 기술개발이 요구되고 있다. 이에 전라북도 준고랭지역에서 재배하기 적합한 산채작목을 선발하고자 본 시험을 실시하였다. 시험은 표고 500m 전라북도 남원시 운봉읍 허브시험장에서 노지재배, 남원시 주천면 표고 530~540m, 진안군 주천면 표고 340~350m에 위치한 농가포장에서 임간재배를 실시하였다. 대상작물은 개미취(Aster tataricus), 갯기름나물(Peucedanum japonicum), 곤달비(Ligularia stenocephala), 눈개승마(Aruncus dioicus var. kamtschaticus), 단풍취(Ainsliaea acerifolia), 산마늘(Allium microdictyon), 섬쑥부쟁이(Aster glehnii), 어수리(Heracleum moellendorffii), 우산나물(Syneilesis palmata) 등 9종을 2016년 종묘를 정식하였다. 정식 2년차에 해당지역의 5월~9월 평균기온 및 조도 등 생육환경을 조사하고, 시험작물의 출현율, 생육특성, 수량 등을 조사하였다. 조사기간 동안의 평균기온은 노지가 $20.8^{\circ}C$, 남원임간은 $20.3^{\circ}C$, 진안임간은 $20.5^{\circ}C$이었으며, 평균조도는 노지가 37,362Lux, 남원임간은 7,816Lux, 진안임간은 25,316Lux이었다. 노지에서 출현율은 개미취, 갯기름나물, 눈개승마, 산마늘, 섬쑥부쟁이, 우산나물이, 임간에서는 개미취, 곤달미, 눈개승마, 단풍취, 산마늘, 어수리, 우산나물이 높았다. 생육특성은 노지에서 개미취, 갯기름나물, 눈개승마, 섬쑥부쟁이, 임간에서는 단풍취, 산마늘, 우산나물의 생육이 좋았다. 수량은 노지에서 개미취, 갯기름나물, 곤달비, 산마늘, 섬쑥부쟁이, 어수리가 높았으며, 남원임간에서는 곤달비, 단풍취, 우산나물, 어수리가, 진안임간에서는 개미취, 갯기름나물, 산마늘, 우산나물의 수량이 많았다. 이와 더불어 준고랭지에 적합한 산채류률 선발하기 위해서는 차후 재배 지역 및 방법의 차이에 따른 산채작물의 연차별 수량성과 경제성에 관한 연구가 이루어져야 할 것으로 여겨진다.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.658-668
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• 2011

Over the past decade, the improvement of communications technologies and the rapid spread of www (World Wide Web) have brought on the exponential growth of users using Internet and real time multimedia multicast services like video conferencing, tele-immersive virtual reality, and Internet games. The dense-wavelength division multiplexing (DWDM) networks have been widely accepted as a promising approach to meet the ever-increasing bandwidth demands of Internet users, especially in next generation Internet backbone networks for nation-wide or global coverage. A major challenge in the next generation Internet backbone networks based on DWDM technologies is the resolution of the multicasting RWA (Routing and Wavelength Assignment) problem; given a set of wavelengths in the DWDM network, we set up light-paths by routing and assigning a wavelength for each connection so that the multicast connections are set-upped as many as possible. Finding such optimal multicast connections has been proven to be Non-deterministic Polynomial-time-complete. In this paper, we suggest a new heuristic multicast routing and wavelength assignment method for multicast sessions called DVS-PMIPMR (Differentiated Virtual Source-based Priority Minimum Interference Path Multicast Routing algorithm). We measured the performance of the proposed algorithm in terms of number of wavelength and wavelength channel. The simulation results demonstrate that DVS-PMIPMR algorithm is superior to previous multicast routing algorithms.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1323-1337
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• 2020

GEO-KOMPSAT-2A AMI (Advanced Meteorological Imager) radiometric calibration evaluation is an essential element not only for functional and performance verification of the payload but for the quality of the sensor data. AMI instrument consists of six reflective channels and ten thermal infrared ones. One of the key parameters representing radiometric properties of the sensor is a SNR (Signal-to-Noise Ratio) for the reflective channels and a NEdT (Noise Equivalent delta Temperature) for the IR ones respectively. Other important radiometric calibration parameters are a dynamic range and a gain value related with the responsivity of detectors. To verify major radiometric calibration performance of AMI, an offline radiometric evaluation tool was developed separately with a real-time AMI data processing system. Using the evaluation tool, validation activities were carried out during the GEO-KOMPSAT-2A In-Orbit Test period. The results from the evaluation tool were cross checked with those of the HARRIS, which is the AMI payload vendor. AMI radiometric evaluation activities were conducted through three phases for both sides (Side 1 and Side 2) of AMI payload. Results showed that performances of the key radiometric properties were outstanding with respect to the radiometric requirements of the payload. The effectiveness of the evaluation tool was verified as well.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.131-143
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• 2022

The lunar exploration autonomous vehicle operates based on the lunar topography information obtained from real-time image characterization. For highly accurate topography characterization, a large number of training images with various background conditions are required. Since the real lunar topography images are difficult to obtain, it should be helpful to be able to generate mimic lunar image data artificially on the basis of the planetary analogs site images and real lunar images available. In this study, we aim to artificially create lunar topography images by using the location information-based style transfer algorithm known as Wavelet Correct Transform (WCT2). We conducted comparative experiments using lunar analog site images and real lunar topography images taken during China's and America's lunar-exploring projects (i.e., Chang'e and Apollo) to assess the efficacy of our suggested approach. The results show that the proposed techniques can create realistic images, which preserve the topography information of the analog site image while still showing the same condition as an image taken on lunar surface. The proposed algorithm also outperforms a conventional algorithm, Deep Photo Style Transfer (DPST) in terms of temporal and visual aspects. For future work, we intend to use the generated styled image data in combination with real image data for training lunar topography objects to be applied for topographic detection and segmentation. It is expected that this approach can significantly improve the performance of detection and segmentation models on real lunar topography images.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.573-581
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• 2022

This paper deals with the development of CanSat system, which ejects two maple seed-type autorotating science payloads and collects weather information. The CanSat consists of two autorotating science payloads and a container. The container is equipped with devices for launching science payloads and communication with the ground station, and launches science payloads one by one at different designated altitudes. The science payload consists of a space for loading and a large wing, and rotates to generate lift for slowing down the fall speed. Specifically, after being ejected, it descends at a speed of 20 m/s or less, measures the rotation rate, atmospheric pressure, and temperature, and transmits the measured value to the container at a rate of once per second. The communication system is a master-slave structure, and the science payload transmits all data to the master container, which aggregates both the received data and its own data, and transmits it to the ground station. All telemetry can be checked in real time using the ground station software developed in-house. A simulation was performed in the simulation environment, and the performance of the CanSat system that satisfies the mission requirements was confirmed.

• Journal of Korea Port Economic Association
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• v.25 no.4
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• pp.21-44
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• 2009

This study aims to understand the conditions for using logistics outsourcing of Korean enterprises, present existing problems, examine factors affecting utility, and analyze the pattern of logistics outsourcing based on contract term, and to ultimately contribute to enhancing competitiveness of logistics enterprises. Through the literature survey 8 factors were identified as three broad factors of corporate strategy, corporate characteristics, and environment. Factor analysis was conducted on the bases of 155 collected data among 400 distributions for 2 months from April to May in 2008. From the result of analysis, the implication and finding can be summarized into three aspects. Firstly, Korean companies value factors relative to corporate strategies as motivating factors for logistics outsourcing. Secondly, Korean companies consider logistics outsourcing depending on how to handle customers' demands and the severity of competition. Thirdly, it was found that product and organization characteristics are perceived as more important when contract term with logistics business is longer. The implications can be observed into two aspects. Firstly once the logistics outsourcing between manufacturers and logistics companies are determined, it was verified that mutual agreement, particular contracts and periodic communications can increase the outcome. Secondly the logistics outsourcing appeared to be different depending on the level of entering to foreign market and resulted in higher performance as well.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.159-159
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• 2017

스마트 시설환경은 대표적으로 원예, 축산 분야 등 여러 형태의 농업현장에 정보 통신 및 데이터 분석 기술을 도입하고 있는 시설화된 생산 환경이라 할 수 있다. 근래에 하드웨어적으로 급증한 스마트 시설환경에서 생산되는 방대한 생육/환경 데이터를 올바르고 적합하게 사용하기 위해서는 일반 산업 현장과는 차별화 된 분석기법이 요구된다고 할 수 있다. 소프트웨어 공학 분야에서 연구된 빅데이터 처리 기술을 기계적으로 농업 분야의 빅데이터에 적용하기에는 한계가 있을 수 있다. 시설환경 내/외부의 다양한 환경 변수는 시계열 데이터의 난해성, 비가역성, 불특정성, 비정형 패턴 등에 기인하여 예측 모델 연구가 매우 난해한 대상이기 때문이라 할 수 있다. 본 연구에서는 근래에 관심이 급증하고 있는 인공신경망 연구 소프트웨어인 Tensorflow (www.tensorflow.org)와 대표적인 Open source인 OpenNN (www.openn.net)을 스마트 시설환경 환경변수 상호간 상관성 분석에 응용하였다. 해당 소프트웨어 라이브러리의 운영환경을 살펴보면 Tensorflow 는 Linux(Ubuntu 16.04.4), Max OS X(EL capitan 10.11), Windows (x86 compatible)에서 활용가능하고, OpenNN은 별도의 운영환경에 대한 바이너리를 제공하지 않고 소스코드 전체를 제공하므로, 해당 운영환경에서 바이너리 컴파일 후 활용이 가능하다. 소프트웨어 개발 언어의 경우 Tensorflow는 python이 기본 언어이며 python(v2.7 or v3.N) 가상 환경 내에서 개발이 수행이 된다. 주의 깊게 살펴볼 부분은 이러한 개발 환경의 제약으로 인하여 Tensorflow의 주요한 장점 중에 하나인 고속 연산 기능 수행이 일부 운영 환경에 국한이 되어 제공이 된다는 점이다. GPU(Graphics Processing Unit)의 제공하는 하드웨어 가속기능은 Linux 운영체제에서 활용이 가능하다. 가상 개발 환경에 운영되는 한계로 인하여 실시간 정보 처리에는 한계가 따르므로 이에 대한 고려가 필요하다. 한편 근래(2017.03)에 공개된 Tensorflow API r1.0의 경우 python, C++, Java언어와 함께 Go라는 언어를 새로 지원하여 개발자의 활용 범위를 매우 높였다. OpenNN의 경우 C++ 언어를 기본으로 제공하며 C++ 컴파일러를 지원하는 임의의 개발 환경에서 모두 활용이 가능하다. 특징은 클러스터링 플랫폼과 연동을 통해 하드웨어 가속 기능의 부재를 일부 극복했다는 점이다. 상기 두 가지 패키지를 이용하여 2016년 2월부터 5월 까지 충북 음성군 소재 딸기 온실 내부에서 취득한 온도, 습도, 조도, CO2에 대하여 Large-scale linear model을 실험적(시간단위, 일단위, 주단위 분할)으로 적용하고, 인접한 세그먼트의 환경변수 예측 모델링을 수행하였다. 동일한 조건의 학습을 수행함에 있어, Tensorflow가 개발 소요 시간과 학습 실행 속도 측면에서 매우 우세하였다. OpenNN을 이용하여 대등한 성능을 보이기 위해선 병렬 클러스터링 기술을 활용해야 할 것이다. 오프라인 일괄(Offline batch)처리 방식의 한계가 있는 인공신경망 모델링 기법과 현장 보급이 불가능한 고성능 하드웨어 연산 장치에 대한 대안 마련을 위한 연구가 필요하다.