• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.94-100
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• 2010

Purpose: We can evaluate function of kidney by Glomerular Filtration Rate (GFR) test using $^{99m}Tc$-DTPA which is simple. This test is influenced by several parameter such as net syringe count, kidney depth, corrected kidney count, acquisition time and characters of gamma camera. In this study, we evaluated predose count according to matrix size in the GFR test using $^{99m}Tc$-DTPA. Materials and Methods: Gamma camera of Infinia in GE was used, and LEGP collimator, three types of matrix size ($64{\times}64$, $128{\times}128$, $256{\times}256$) and 1.0 of zoom factor were applied. We increased radioactivity concentration from 222 (6), 296 (8), 370 (10), 444 (12) up to 518 MBq (14 mCi) respectively and acquired images according to matrix size at 30 cm distance from detector. Lastly, we evaluated these values and then substituted them for GFR formula. Results: In $64{\times}64$, $128{\times}128$ and $256{\times}256$ of matrix size, counts per second was 26.8, 34.5, 41.5, 49.1 and 55.3 kcps, 25.3, 33.4, 41.0, 48.4 and 54.3 kcps and 25.5, 33.7, 40.8, 48.1 and 54.7 kcps respectively. Total counts for 5 second were 134, 172, 208, 245 and 276 kcounts from $64{\times}64$, 127, 172, 205, 242, 271 kcounts from $128{\times}128$, and 137, 168, 204, 240 and 273 kcounts from $256{\times}256$, and total counts for 60 seconds were 1,503, 1,866, 2,093, 2,280, 2,321 kcounts, 1,511, 1,994, 2,453, 2,890 and 3,244 kcounts, and 1,524, 2,011, 2,439, 2,869 and 3,268 kcounts respectively. It is different from 0 to 30.02 % of percentage difference in $64{\times}64$ of matrix size. But in $128{\times}128$ and $256{\times}256$, it is showed 0.60 and 0.69 % of maximum value each. GFR of percentage difference in $64{\times}64$ represented 6.77% of 222 MBq (6 mCi), 42.89 % of 518 MBq (14 mCi) at 60 seconds respectively. However it is represented 0.60 and 0.63 % each in $128{\times}128$ and $256{\times}256$. Conclusion: There was no big difference in total counts of percentage difference and GFR values acquiring from $128{\times}128$ and $256{\times}256$ of matrix size. But in $64{\times}64$ of matrix size when the total count exceeded 1,500 kcounts, the overflow phenomenon was appeared differently according to predose radioactivity of concentration and acquisition time. Therefore, we must optimize matrix size and net syringe count considering the total count of predose to get accurate GFR results.

• International Journal of Industrial Entomology and Biomaterials
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• v.30 no.1
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• pp.6-16
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• 2015

This study established the genetic characterisation of 10 microsporidian isolates infecting non-mulberry silkworms (Antheraea assamensis and Samia cynthia ricini) collected from biogeographical forest locations in the State of Assam, India, using PCR-based markers assays: inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD). A Nosema type species (NIK-1s_mys) was used as control for comparison. The shape of mature microsporidian spores were observed oval to elongated, measuring 3.80 to $4.90{\mu}m$ in length and 2.60 to $3.05{\mu}m$ in width. Fourteen ISSR primers generated reproducible profiles and yielded 178 fragments, of which 175 were polymorphic (98%), while 16 RAPD primers generated reproducible profiles with 198 amplified fragments displaying 95% of polymorphism. Estimation of genetic distance coefficients based on dice coefficients method and clustering with un-weighted pair group method using arithmetic average (UPGMA) analysis was done to unravel the genetic diversity of microsporidians infecting Indian muga and eri silkworm. The similarity coefficients varied from 0.385 to 0.941 in ISSR and 0.083 to 0.938 in RAPD data. UPGMA analysis generated dendrograms with two microsporidian groups, which appear to be different from each other. Based on Euclidean distance matrix method, 2-dimensional distribution also revealed considerable variability among different identified microsporidians. Clustering of these microsporidian isolates was in accordance with their host and biogeographic origin. Both techniques represent a useful and efficient tool for taxonomical grouping as well as for phylogenetic classification of different microsporidians in general and genotyping of these pathogens in particular.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.642-648
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• 2009

In this paper, we use SA (Seysen's Algorithm) instead of LLL (Lenstra-Lenstra-Lovasz) to perform LRA (Lattice Reduction-Aided) detection. By using SA, the complexity of lattice reduction is reduced and the detection performance is improved Although the performance is improved using SA, there still exists a gap in the performance between SA-LRA and ML detection. To reduce the performance difference, we apply list of candidates scheme to SA-LRA. The list of candidates scheme finds a list of candidates. Then, the candidate with the smallest squared Euclidean distance is considered as the estimate of the transmitted signal. Simulation results show that the SA-LRA detection learn to quasi-ML performance. Moreover, the efficiency of the SA is shown to highly improve the channel matrix conditionality.

• Development and Reproduction
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• v.17 no.3
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• pp.199-205
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• 2013

Genomic DNAs were extracted from the turtle leg (Pollicipes mitella, 1798) population of Tongyeong, Yeosu and Manjaedo located in the southern sea of Korea. The turtle leg population from Tongyeong (0.929) exhibited higher bandsharing values than did turtle leg from Manjaedo (0.852). The higher fragment sizes (>1,200 bp) are much more observed in the Yeosu population. The number of unique loci to each population and number of shared loci by the three populations, generated by PCR using 7 primers in the turtle leg (P. mitella) population of Tongyeong, Yeosu and Manjaedo. Genetic distances among different individuals of the Tongyeong population of the turtle leg (lane 1-07), Yeosu population of the turtle leg (lane 08-14) and Manjaedo population of the turtle leg (lane 15-21), respectively, were generated using the CLASSIFICATION option in Systat version 10 according to the bandsharing values and similarity matrix. The dendrogram, obtained by the seven decamer primers, indicated three genetic clusters: cluster 1 (TONGYEONG 01 TONGYEONG 07), cluster 2 (YEOSU 08 YEOSU 14), and cluster 3 (MANJEDO 15 MANJEDO 21). Tongyeong population could be evidently discriminated with the other two Yeosu and Manjaedo populations among three populations. The longest genetic distance (0.305) was found to exist between individuals' no. 02 of the Tongyeong population and no. 13 of the Yeosu population. It seems to the authors that this is a result of a high degree of inbreeding in narrow region for a long while.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2599-2613
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• 2015

Multi-index hashing (MIH) is the state-of-the-art method for indexing binary codes, as it di-vides long codes into substrings and builds multiple hash tables. However, MIH is based on the dataset codes uniform distribution assumption, and will lose efficiency in dealing with non-uniformly distributed codes. Besides, there are lots of results sharing the same Hamming distance to a query, which makes the distance measure ambiguous. In this paper, we propose a data-oriented multi-index hashing method (DOMIH). We first compute the covariance ma-trix of bits and learn adaptive projection vector for each binary substring. Instead of using substrings as direct indices into hash tables, we project them with corresponding projection vectors to generate new indices. With adaptive projection, the indices in each hash table are near uniformly distributed. Then with covariance matrix, we propose a ranking method for the binary codes. By assigning different bit-level weights to different bits, the returned bina-ry codes are ranked at a finer-grained binary code level. Experiments conducted on reference large scale datasets show that compared to MIH the time performance of DOMIH can be improved by 36.9%-87.4%, and the search accuracy can be improved by 22.2%. To pinpoint the potential of DOMIH, we further use near-duplicate image retrieval as examples to show the applications and the good performance of our method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.427-431
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• 2010

Multidimensional scaling (MDS) is a widely used method for dimensionality reduction, of which purpose is to represent high-dimensional data in a low-dimensional space while preserving distances among objects as much as possible. MDS has mainly been applied to data visualization and feature selection. Among various MDS methods, the classical MDS is not readily applicable to data which has large numbers of objects, on normal desktop computers due to its computational complexity. More precisely, it needs to solve eigenpair problems on dissimilarity matrices based on Euclidean distance. Thus, running time and required memory of the classical MDS highly increase as n (the number of objects) grows up, restricting its use in large-scale domains. In this paper, we propose an efficient approximation algorithm for the classical MDS based on divide-and-conquer and CUDA. Through a set of experiments, we show that our approach is highly efficient and effective for analysis and visualization of data consisting of several thousands of objects.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

• Journal of IKEEE
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• v.11 no.4
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• pp.187-192
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• 2007

Since wireless sensor networks (WSN) have relatively narrow bandwidth and have limited memory space. Mosaic by inlaying images transmitted by adjacent sensors can provide wider field of view and smaller storage memory. Most WSN are used for surveillance purpose, image acquisition period should be sufficiently short, so that mosaic algorithm has to be run in real time. Proposed algorithm is derived by using the fact that position of sensor nodes are fixed and known. Transformation matrix can be calculated by using distance between sensor nodes and distance between sensor nodes and predefined object. Simulation result shows that proposed algorithm provides very short processing time whereas it preserves image quality.

• Journal of Korean Society of Forest Science
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• v.95 no.4
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• pp.381-387
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• 2006

This study tried to develop a model which can predict a long-term of forest recreation quantity corresponded with econometrics. Simultaneously this study was conducted with the aim of development of practical matrix which is able to apply forest recreation management with policy-control variables about forest supplement with some problem of former study using only a cross-section analysis. As the results of analyses, forest recreation quantity is affected (-) relation by distance, (+) relation by population of the origin area, the size of forest, and a destination's annual social expenditure. In addition, the distance variable is elastic, however, the other variables are inelastic. This results might correspond to a general gravity model theory about forest recreation quantity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.227-232
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• 2016

3D body scan data are used widely in various fields to make products and living spaces for superior human body fitness. Based on the 3D measurements of human bodies for teens in Size Korea 2013, this research provides a way of finding the representative body sizes and 3D body scan data. First, a multi-dimensional vector space consisting of many measurement items was projected onto a 2D vector space with circumference and length components via factor analysis. The representative body sizes and 3D scan data close to these values were obtained via the Mahalanobis distance in 2D space. Considering the adolescent growth pattern shown on this 2D space, males were divided into 4 age groups and females were divided into 3 age groups. Using the eigenbodies corresponding to the column vectors of the component score coefficient matrix, the representative body sizes of 13 measurement items (male) and 14 measurement items (female) for each age group were calculated. The representative body sizes and 3D scan data are very useful for modeling representative 3D human figures.