• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• Korean Journal of Plant Tissue Culture
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• v.21 no.5
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• pp.309-314
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• 1994

To develop simple and efficient transformation methods of monocotyledonous plane, electroporation-mediated delivery of DNA into intact embryogenic cell clumps was investigated in zoysiagrass and rice. Calli of zoysiagrass, induced from 3-week-old immature embryos, were suspension-cultured in MS basic medium supplemented with 1.0 mg/t 2.4-D and used for elechuporation. Calli, derived from immature inflorescences of 20 mm lenth of rice, were also suspension-cultured on N6 basic medium supplemented with 1.0 mg/L 2.4-D. Suspension-cultured embryogenic cell clumps were electroporated in liqid MS medium added with a Plasmid DNA (30 $\mu\textrm{m}$/ml), pGA1074, encoding ${\beta}$-glucuronidiase (GUS). DNA delivery into the cells through cell walls and cell membrane was confirmed by the transient expression of the GUS gene. Cell clumps of zoysiagrass and rice, electroporated with 400 volt at 800 pF capacitance, expressed GUS gene activity at a mean frequency of 25 units (one unit = one clony of blue cells) per 200 ${\mu}\ell$ of packed cell volume. Untreated cells and healed non-embryogenic cells did not exhibit GUS activity These results indicate that electroporation-mediated transformation can use intact embryogenic cells (thus avoiding the use protoplasts) in zoysiagrass and rice.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.434-445
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• 2009

Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.

• Journal of Korean Neurosurgical Society
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• v.30 no.7
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• pp.831-841
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• 2001

Objective : Somatosensory evoked potentials(SSEPs) have been used widely both experimentally and clinically to monitor the function of central nervous system and peripheral nervous system. Studies of SSEPs have reported the various recording techniques and patterns of SSEP. The previous SSEP studies used scalp recording electrodes, showed mean vector potentials which included relatively constant brainstem potentials(far-field potentials) and unstable thalamocortical pathway potentials(near-field potentials). Even in invasive SSEP recording methods, thalamocortical potentials were variable according to the kinds, depths, and distance of two electrodes. So they were regarded improper method for monitoring of upper level of brainstem. The present study was conducted to investigate the characteristics of somatosensory evoked field potentials(SSEFPs) of the cerebral cortex that evoked by hindlimb stimulation using ball electrode and the pathways of SSEFP by recording the potentials simultaneously in the cortex, VPL nucleus of thalamus, and nucleus gracilis. Methods : In the first experiment, a specially designed recording electrode was inserted into the cerebral cortex perpendicular to the cortical surface in order to recording the constant cortical field potentials and SSEFPs mapped from different areas of somatosensory cortex were analyzed. In the second experiment, SSEPs were recorded in the ipsilateral nucleus gracilis, the contralateral ventroposterolateral thalamic nucleus(VPL), and the cerebral cortex along the conduction pathway of somatosensory information. Results : In the first experiment, we could constantly obtain the SSEFPs in cerebral cortex following the transcutaneous electrical stimulation of the hind limb, and it revealed that the first large positive and following negative waves were largest at the 2mm posterior and 2mm lateral to the bregma in the contralateral somatosensory cortex. The second experiment showed that the SSEPs were conducted by way of posterior column somatosensory pathway and thalamocortical pathway and that specific patterns of the SSEPs were recorded from the nucleus gracilis, VPL, and cerebral cortex. Conclusion : The specially designed recording electrode was found to be very useful in recording the localized SSEFPs and the transcutaneous electrical stimulation using ball electrode was effective in evoking SSEPs. The characteristic shapes, latencies, and conduction velocities of each potentials are expected to be used the fundamental data for the future study of brain functions, including the hydrocephalus model, middle cerebral artery ischemia model, and so forth.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.99-108
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• 2021

There are unrestricted conditions on the driver's face inside the vehicle, such as changes in lighting, partial occlusion and various changes in the driver's condition. In this paper, we propose a face identification system in an unrestricted vehicle environment. The proposed method uses a near-infrared (NIR) camera to minimize the changes in facial images that occur according to the illumination changes inside and outside the vehicle. In order to process a face exposed to extreme light, the normal face image is changed to a simulated overexposed image using mean and variance for training. Thus, facial classifiers are simultaneously generated under both normal and extreme illumination conditions. Our method identifies a face by detecting facial landmarks and aggregating the confidence score of each landmark for the final decision. In particular, the performance improvement is the highest in the class where the driver wears glasses or sunglasses, owing to the robustness to partial occlusions by recognizing each landmark. We can recognize the driver by using the scores of remaining visible landmarks. We also propose a novel robust rejection and a new evaluation method, which considers the relations between registered and unregistered drivers. The experimental results on our dataset, PolyU and ORL datasets demonstrate the effectiveness of the proposed method.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.56-68
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• 2022

In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.

• Clinical and Experimental Vaccine Research
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• v.12 no.1
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• pp.25-31
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• 2023

Purpose: Since late 2019, the novel coronavirus disease has been a global concern, and alongside preventive strategies, including social distancing and personal hygiene, vaccination is now the primary hope for controlling the pandemic. Sputnik V is an adenovirus vector vaccine used against coronavirus disease 2019 (COVID-19) among Iranian health care providers, and there is a lack of information regarding the Adverse Events Following Immunisation (AEFI) by Sputnik V among the Iranian population. The present study aimed to evaluate AEFI by Sputnik V vaccine among Iranian population. Materials and Methods: Every member of the Islamic Republic of Iran Medical Council received their first dose of the Sputnik V vaccine in Mashhad (Iran) and was referred to receive their second dose enrolled in the present study and asked to fill an English language checklist asking about development of any AEFI following immunization with the first dose of Sputnik V vaccine. Results: A total number of 1,347 with a mean±standard deviation age of 56.2±9.6 years filled the checklist. Most of the participants were male (838 [62.2%]). The present study demonstrated that immunization with the first dose of Sputnik V results in at least one AEFI in 32.8% of the Iranian medical council members. Most of the AEFI was related to musculoskeletal symptoms, including myalgia. By considering the age of 55 years as a cut-off point, individuals younger than 55 had a higher rate of AEFI (41.3% vs. 22.5%, p=0.0001). Male gender, use of analgesics, beta-blockers, and previous COVID-19 infection have a lower chance of developing AEFI (p<0.05). Conclusion: The present study demonstrated that most of the AEFI was related to musculoskeletal symptoms, including myalgia, and older individuals, male gender and those receiving analgesics and beta-blockers were less likely to develop AEFI following immunization with the first dose of Sputnik V.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.19-32
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• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.3-14
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• 2006

Music summarization means a technique which automatically generates the most importantand representative a part or parts ill music content. The techniques of music summarization have been studied with two categories according to summary characteristics. The first one is that the repeated part is provided as music summary and the second provides the combined segments which consist of segments with different characteristics as music summary in music content In this paper, we propose and evaluate two kinds of music summarization techniques. The algorithm using multi-level vector quantization which provides a repeated part as music summary gives fixed-length music summary is evaluated by overlapping ration between hand-made repeated parts and automatically generated summary. As results, the overlapping ratios of conventional methods are 42.2% and 47.4%, but that of proposed method with fixed-length summary is 67.1%. Optimal length music summary is evaluated by the portion of overlapping between summary and repeated part which is different length according to music content and the result shows that automatically-generated summary expresses more effective part than fixed-length summary with optimal length. The cluster-based algorithm using 2-D similarity matrix and k-means algorithm provides the combined segments as music summary. In order to evaluate this algorithm, we use MOS test consisting of two questions(How many similar segments are in summarized music? How many segments are included in same structure?) and the results show good performance.