• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.11-18
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• 2016

Since GNSS signals get blocked by buildings in urban canyons or narrow alleys, it is very difficult to secure a enough number of visible satellites for satellite navigation in those poor signal-reception environments. In those situations, one cannot get their coordinates or obtain accurate positions. In this study, a couple of strategies for improving positioning accuracy in urban canyons were developed and their performance was verified. First of all, we combined GPS and GLONASS measurements together and devised algorithms to quality-control observed signals and eliminate outliers. Also, a new multipath reduction scheme was applied to minimize its effect by utilizing SNR values of the observed signals. For performance verification of the developed technique, a narrow alley of 10m width located near the back gate of the Inha University was selected as the test-bed, and then we conducted static and kinematic positioning at four pre-surveyed points. We found that our new algorithms produced an 45% improvement in an open-sky environment compared with the positioning result of a low-cost u-blox receiver. In the alleys, 3-D accuracy improved by an average of 37%. In the case of kinematic positioning, especially, biases showing up in regular receivers got eliminated significantly through our new filtering algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.141-147
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• 2012

The purpose of the study is the acquisitions of knowledge related in job searching from local companies and job seekers using data mining techniques. At the first step, for the study, we had selected the local companies their headquarters are located in Jeonbuk province. Then we had picked the graduating students out from the high schools, colleges, and universities in the same area as the job seekers. After the targeting of the sample, we had surveyed 560 local companies and 14 schools for the collecting of the preliminary data. As the result of the survey, we could collect 173 responses from the companies and 551 responses from the job seekers. At the second step using data mining, we had adapted the C5.0 algorithm to extract the inference rules. Then we had used the Visual Basic (VB) programming language to visualize the rules at the third step. At the fourth step, we transformed the inference rules into DB tables. At the final step, we had executed the rule inferences to support the development of the long-term human resources development (HRD) strategies. As the result of the study, we could suggest the helpful information to the HRD directors and job seekers in designing their strategies in managing their jobs and career development.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.105-115
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• 2011

In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.105-111
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• 2017

With the emergence of the fourth industrial revolution, more and more attempts have been made to apply IoT technology to the manufacturing process and launch the product. In this paper, we propose IoT authentication scheme based on hash chain which can easily apply IoT device to small and medium enterprises in Korea. In the proposed method, the companies that installed IoT devices suitable for the manufacturing environment are selected to maintain the linkage between IoT devices so that product information and release information can be efficiently collected and managed during the entire manufacturing process. In addition, the proposed scheme is characterized in that it does not require an additional encryption / decryption algorithm because the authentication information of the IoT device is constructed based on a hash chain. As a result of the performance evaluation, the efficiency of the manufacturing process was improved by 18.5% and the processing of the manufacturing process with the IoT device was shortened by 20.1% on the average according to the application of the IoT device. In addition, the labor cost reduction costs in the manufacturing process decreased by an average of 30.7%.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2002.02a
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• pp.592-599
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• 2002

본 연구에서는 수삼의 가공전 선별을 위해 현장에서 편리하게 사용할 수 있는 초음파 전달 속도 계측 자동화 시스템을 개발하여 그 성능을 평가하고자 하였으며 결과를 요약하면 다음과 같다. 1. 개발된 시스템은 제어용 컴퓨터, 시스템 구동 및 탐촉자 이동 장치, 하중 변환장치, 초음파 발생 및 송수신 장치 등으로 구성되었다. 2. 제어 및 계측용 프로그램은 압축력, 측정 대상물의 크기, 초음파 전달 시간을 순차적으로 계측하여 초음파 전달 속도를 계산하는 알고리즘을 개발하였으며, Visual Basic 6.0으로 작성되었다. 모터의 작동, A/D 변환, RS232C 통신 등과 관련된 부분은 각각의 모듈화된 함수로서 구동하고자 하였다. 3. 개발된 시스템의 속도와 거리별 이동 거리별 오차를 측정한 결과 0∼0.04mm 범위를 나타내었다. 이 값은 시스템의 허용오차인 0.17mm 오차보다는 현저히 작은 값이었고 15mm/s와 30mm/s의 이동 속도에서 모두 비슷한 크기의 오차값을 나타내었다. 4. 개발된 시스템의 속도별 반복정밀도 실험 결과 측정위치에서의 반복에 의한 정지 위치 오차는 전 구간에서 0.02mm 이내로 나타났고, 이동 평판의 이동속도가 15mm/s였을 경우에는 이동 회수 30회, 이동 거리 60mm일 때 최대 편차 0.019mm를 나타냈으며 이동속도가 30mm/s일 경우에는 이동 회수 40회, 이동거리 20mm에서 0.02mm의 최대 편차를 나타내었다. 5. 5개의 알루미늄 조각의 크기를 시스템으로 측정한 결과 측정값의 최대 편차는 0.08mm였다. 이 값은 시스템의 허용오차인 0.17mm의 50% 수준으로 시스템은 대상물의 크기 측정에 적당하다고 사료되었다. 6. 절단된 수삼의 초음파 전달속도는 평균 396.4m/s였다.를 축열재로 사용할 경우 재생기를 반으로 나누어서 가열부 쪽에 철선을, 냉각부 쪽에 철망을 삽입한 것이 반대로 삽입한 것보다 재생기 양단의 온도차는 높게 나타났고, 재생기 양단의 압력 차는 낮게 나타났다. 재생기 축열재로서 철망-철선을 사용할 경우 철선-철망 ø1.2-150이 전열 표면적은 작으나 재생기 양단의 온도차가 가장 큰 것으로 나타났으며 재생기 양단의 압력 차는 가장 낮게 나타나 공시 철망- 철선 혼합 축열재중 가장 우수함을 알 수 있다. 4. 철망사이에 철선을 삽입한 축열재의 경우, 철망사이에 삽입한 철선의 직경이 큰 것이 철선의 직경이 작은 것보다 재생기의 양단의 온도차가 높게 나타났고 재생기 양단의 압력차는 작게 나타났다. 그러므로 철망사이에 철선을 삽입한 것 중 성능이 우수한 것은 150-ø2. 0-150으로 나타났다. 5. 실험한 재생기 축열재들 중에서 성능이 우수한 것들을 비교한 결과, 복합 철선 ø1.2-1 50이 가장 성능이 좋은 것으로 나타났다.적외선.열풍 복합건조방법이 높게 나타나 이것은 곡물 표면에 원적외선 방사에의한 복사열이 전달되어 열장해를 받았기 때문으로 판단되며, 금후 더 연구하여 적정 열풍온도 및 방사체 크기를 구명해야 할 것이다.으로 보여진다 따라서 옻나무 유래 F는 포유동물의 생식기능에 중요하게 작용하는 것으로 사료된다.된다.정량 분석한 결과이다. 시편의 조성은 33.6 at% U, 66.4 at% O의 결과를 얻었다. 산화물 핵연료의 표면 관찰 및 정량 분석 시험시 시편 표면을 전도성 물질로 증착시키지 않고, Silver Paint 에 시편을 접착하는 방법으로도 만족한 시험 결과를 얻을 수 있었다.째, 회복기 중에 일어나는 입자들의 유입은 자기폭풍의 지속시간을 연장시키는 경향을 보이며 큰 자기폭풍일수

• Horticultural Science & Technology
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• v.31 no.5
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• pp.598-606
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• 2013

Anther is the major organ of flower in responsible to reproduction and outward appearance. From anther-specific cDNA library of Lilium Oriental Hybrid 'Acapulco', 2000 expressed sequence tags were selected randomly. Differential slot blot analysis with cDNA probes from the anther and leaf was used to get anther-expressed clone and 570 non-redundant ESTs were obtained and sequenced. Compared to the GenBank database using BLASTX algorithm, 191 clones showed significant similarity but others (66.5%) did not measured to known sequence. Functional categories according to gene ontology (GO) annotation included sequence representing a significant portion of protein in cell and cell part respectively. A transcriptional analysis at 7 different organs and developmental stage was performed using northern blot with thirty ESTs as putative anther specific gene. This report suggest that selection of anther expressed clone using differential slot blot was considered as very effective tool and our current study can provide fundamental information on the lily anther including pollen furthermore.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.477-484
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• 2016

Small industrial appliances such as fan, audio, electric rice cooker mostly consist of ABS, PP, PS materials. In colored plastics, it is possible to classify by near infrared(NIR) spectroscopy, while in black plastics, it is very difficult to classify black plastic because of the characteristic of black material that absorbs the light. So the RBFNNs pattern classifier is introduced for sorting electrical and electronic waste plastics through LIBS(Laser Induced Breakdown Spectroscopy) spectrometer. At the preprocessing part, PCA(Principle Component Analysis), as a kind of dimension reduction algorithms, is used to improve processing speed as well as to extract the effective data characteristics. In the condition part, FCM(Fuzzy C-Means) clustering is exploited. In the conclusion part, the coefficients of linear function of being polynomial type are used as connection weights. PSO and 5-fold cross validation are used to improve the reliability of performance as well as to enhance classification rate. The performance of the proposed classifier is described based on both optimization and no optimization.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.43-51
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• 2009

In 1998, Kocher et al. introduced Differential Power Attack on block ciphers. This attack allows to extract secret key used in cryptographic primitives even if these are executed inside tamper-resistant devices such as smart card. At FSE 2003 and 2004, Akkar and Goubin presented several masking methods, randomizing the first few and last few($3{\sim}4$) rounds of the cipher with independent random masks at each round and thereby disabling power attacks on subsequent inner rounds, to protect iterated block ciphers such as DES against Differential Power Attack. Since then, Handschuh and Preneel have shown how to attack Akkar's masking method using Differential Cryptanalysis. This paper presents how to combine Truncated Differential Cryptanalysis and Power Attack to extract the secret key from intermediate unmasked values and shows how much more efficient our attacks are implemented than the Handschuh-Preneel method in term of reducing the number of required plaintexts, even if some errors of Hamming weights occur when they are measured.

• The Journal of Bigdata
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• v.5 no.2
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• pp.53-67
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• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.