• Journal of IKEEE
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• v.26 no.2
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• pp.240-248
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• 2022

Floating-point images that express pixel information as real numbers are used in HDR images. There have been various researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth images and there are only a few number of algorithms applicable to floating-point images, including Gil and Werman's algorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images by improving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that the execution time is improved by about 10% compared to the Kim's algorithm by reducing the redundant work for the repetitively used binary search tree and applying the inverted index.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.83-97
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• 2021

Wireless sensors that make up the Wireless Sensor Network generally have extremely limited power and resources. The wireless sensor enters the sleep state at a certain interval to conserve power. The Sleep deflation attack is a deadly attack that consumes power by preventing wireless sensors from entering the sleep state, but there is no clear countermeasure. Thus, in this paper, using clustering-based binary search tree structure, the Sleep deprivation attack detection model is proposed. The model proposed in this paper utilizes one of the characteristics of both attack sensor nodes and normal sensor nodes which were classified using machine learning. The characteristics used for detection were determined using Long Short-Term Memory, Decision Tree, Support Vector Machine, and K-Nearest Neighbor. Thresholds for judging attack sensor nodes were then learned by applying the SVM. The determined features were used in the proposed algorithm to calculate the values for attack detection, and the threshold for determining the calculated values was derived by applying SVM.Through experiments, the detection model proposed showed a detection rate of 94% when 35% of the total sensor nodes were attack sensor nodes and improvement of up to 26% in power retention.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.466-478
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• 2022

Objective: ¹⁸F-fluorodeoxyglucose (FDG) PET/CT is often used for detecting malignancy in patients with newly diagnosed hemophagocytic lymphohistiocytosis (HLH), with acceptable sensitivity but relatively low specificity. The aim of this study was to improve the diagnostic ability of ¹⁸F-FDG PET/CT in identifying malignancy in patients with HLH by combining ¹⁸F-FDG PET/CT and clinical parameters. Materials and Methods: Ninety-seven patients (age ≥ 14 years) with secondary HLH were retrospectively reviewed and divided into the derivation (n = 71) and validation (n = 26) cohorts according to admission time. In the derivation cohort, 22 patients had malignancy-associated HLH (M-HLH) and 49 patients had non-malignancy-associated HLH (NM-HLH). Data on pretreatment ¹⁸F-FDG PET/CT and laboratory results were collected. The variables were analyzed using the Mann-Whitney U test or Pearson's chi-square test, and a nomogram for predicting M-HLH was constructed using multivariable binary logistic regression. The predictors were also ranked using decision-tree analysis. The nomogram and decision tree were validated in the validation cohort (10 patients with M-HLH and 16 patients with NM-HLH). Results: The ratio of the maximal standardized uptake value (SUVmax) of the lymph nodes to that of the mediastinum, the ratio of the SUVmax of bone lesions or bone marrow to that of the mediastinum, and age were selected for constructing the model. The nomogram showed good performance in predicting M-HLH in the validation cohort, with an area under the receiver operating characteristic curve of 0.875 (95% confidence interval, 0.686-0.971). At an appropriate cutoff value, the sensitivity and specificity for identifying M-HLH were 90% (9/10) and 68.8% (11/16), respectively. The decision tree integrating the same variables showed 70% (7/10) sensitivity and 93.8% (15/16) specificity for identifying M-HLH. In comparison, visual analysis of ¹⁸F-FDG PET/CT images demonstrated 100% (10/10) sensitivity and 12.5% (2/16) specificity. Conclusion: ¹⁸F-FDG PET/CT may be a practical technique for identifying M-HLH. The model constructed using ¹⁸F-FDG PET/CT features and age was able to detect malignancy with better accuracy than visual analysis of ¹⁸F-FDG PET/CT images.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.101-113
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• 2007

The period of military personnel service will be phased down by 2014 according to 'The law of National Defense Reformation' issued by the Ministry of National Defense. For this reason, the ROK army provides discrimination education to 'newly recruited privates' for more effective individual performance in the on-the-job training. For the training to be more effective, it would be essential to predict the degree of achievements by new privates in the training. Thus, we used data mining techniques to develop a classification model which classifies the new privates into one of two achievements groups, so that different skills of education are applied to each group. The target variable for this model is a binary variable, whose value can be either 'a group of general control' or 'a group of special control'. We developed four pure classification models using Neural Network, Decision Tree, Support Vector Machine and Naive Bayesian. We also built four hybrid models, each of which combines k-means clustering algorithm with one of these four mining technique. Experimental results demonstrated that the highest performance model was the hybrid model of k-means and Neural Network. We expect that various military education programs could be supported by these classification models for better educational performance.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.6
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• pp.337-343
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• 2006

The Stack Resource Policy (SRP) is a real-time synchronization protocol with some distinct properties. One of such properties is early blocking; the execution of a job is delayed instead of being blocked when requesting shared resources. If SRP is used with dynamic priority scheduling such as Earliest Deadline First (EDF), the early blocking requires that a scheduler should select the highest-priority job among the jobs that will not be blocked, incurring runtime overhead. In this paper, we analyze the runtime overhead of EDF scheduling when SRP is used. We find out that the overhead of job search using the conventional implementations of ready queue and job search algorithms becomes serious as the number of jobs increases. To solve this problem, we propose an alternative data structure for the ready queue and an efficient job-search algorithm with O([log$_2n$]) time complexity.

• The Plant Pathology Journal
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• v.30 no.4
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• pp.384-396
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• 2014

Vegetative compatibility groups (VCGs) are determined for many fungi to test for the ability of fungal isolates to undergo heterokaryon formation. In several fungal plant pathogens, isolates belonging to a VCG have been shown to share significantly higher genetic similarity than those of different VCGs. In this study we sought to examine the relationship between VCG and genetic similarity of an important cool season turfgrass pathogen, Sclerotinia homoeocarpa. Twenty-two S. homoeocarpa isolates from the Midwest and Eastern US, which were previously characterized in several studies, were all evaluated for VCG using an improved nit mutant assay. These isolates were also genotyped using 19 microsatellites developed from partial genome sequence of S. homoeocarpa. Additionally, partial sequences of mitochondrial genes cytochrome oxidase II and mitochondrial small subunit (mtSSU) rRNA, and the atp6-rns intergenic spacer, were generated for isolates from each nit mutant VCG to determine if mitochondrial haplotypes differed among VCGs. Of the 22 isolates screened, 15 were amenable to the nit mutant VCG assay and were grouped into six VCGs. The 19 microsatellites gave 57 alleles for this set. Unweighted pair group methods with arithmetic mean (UPGMA) tree of binary microsatellite data were used to produce a dendrogram of the isolate genotypes based on microsatellite alleles, which showed high genetic similarity of nit mutant VCGs. Analysis of molecular variance of microsatellite data demonstrates that the current nit mutant VCGs explain the microsatellite genotypic variation among isolates better than the previous nit mutant VCGs or the conventionally determined VCGs. Mitochondrial sequences were identical among all isolates, suggesting that this marker type may not be informative for US populations of S. homoeocarpa.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1180-1192
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• 1996

On demand of many users, basic networks of a parallel computer system are required to have a property that can embed various topologies. Bisectional interconnection network is known to satisfy this property, and it can embed various topologies optimally. Nowadays one is very interested in the hypercube as a message pssing multicomputer system, so it is very important to implement a hypercube in bisectional network. In this paper, a hypercube is implemented in a versatile bisecional netork, and its routing and broadcasting algorithm are proposed. Conventional bisectional network can accomodata linear array, complete binary tree and mesh structure as its topology. Now hypercube is implemented to be utilized as a general purpose supercomputercommunication architecture. The proposed routing and broadcasting algorithm embedded in bisectional network are general purpose algorithms which satisfy property of conventional hypercube.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.48-55
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• 2009

In this paper, We propose Adaptive Group Separation algorithm for efficient RFID system AGS algorithm determines the optimized initial prefix size j, and divides the group of. A reader requests the group and searches the tag ID. If a tag collision occurred, reader adds a one bit, '0' or '1' at first bit of collision point, As a result we observe that transmitted data bits and the recognition time are decreased. The proposed algorithms have been verified by computer simulation. The performance of the proposed anti-collision algorithm is evaluated in terms of the number of repetitions and the amount of transmission bits according to the in crease of the number of tags is 256. The AGS algorithm improve the number of repetitions by about 32.3% and reduce tile amount of the transmission bits by about 1/40 than slotted binary tree algorithm.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.16-24
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• 2009

In this paper, we propose a new noise cancellation system for the NDIR based optical analyzer, that can measure various environmental air-pollution materials (CO, $SO_2$, NOx, etc.) in real-time. The sensed signals are contaminated by the different noise sources that measurement noise with high frequencies and the drift noise with the low frequencies. They can be eliminated by a pre-processing that considering their time-domian properties and by a post-processing that using sub-power ratios in subband structure. In the proposed method, the ore and pose-processing for noise cancelling are useful for hardware implementation of the NDIR based optical analyzer with a precision measuring.