• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.3
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• pp.218-229
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• 2003

A new biotelemetry method that the installation and the treatment of equipment is convenient and the instantaneously detailed location of the fish attached the pinger is able to track comparatively easily was developed. The receiving system in this biotelemetry method was advanced for track the detailed behavior of the fish by the miniature tracking pinger, because it was a burden to fish to add the pinger with the water temperature and the pressure sensor. By combining of the super short base line (SSBL) method to detect the direction of pinger and the pinger synchronizing method to measure the range from receiving transducer to pinger, the three dimensional locations of fish to the receiving transducer is gotten instantaneously. The receiving system is devised to realize the high precision or wide detection range by application of the basic design method for receiving system of biotelemetry developed by the present authors and the hydrophone array configuration. The measurement distance error in the pinger synchronizing method is minimized through the correction of which the deviation of transmission pluse period of pinger is caused by changing water temperature. A prototype system which is able to track the instantaneously detailed location of the fish by the SSBL and pinger synchronizing biotelemetry (SPB) method was produced.

• Korean Journal of Optics and Photonics
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• v.31 no.2
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• pp.59-70
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• 2020

We discuss a modified numerical model based on the Monte Carlo radiative transfer (MCRT) method, i.e., the MCRT matrix method, for the analysis of atmospheric scattering effects in three-dimensional flash LIDAR systems. Based on the MCRT method, the radiative transfer function for a LIDAR signal is constructed in a form of a matrix, which corresponds to the characteristic response. Exploiting the superposition and convolution of the characteristic response matrices under the paraxial approximation, an extended computer simulation model of an overall flash LIDAR system is developed. The MCRT matrix method substantially reduces the number of tracking signals, which may grow excessively in the case of conventional Monte Carlo methods. Consequently, it can readily yield fast acquisition of the signal response under various scattering conditions and LIDAR-system configurations. Using the computational model based on the MCRT matrix method, we carry out numerical simulations of a three-dimensional flash LIDAR system operating under different atmospheric conditions, varying the scattering coefficient in terms of visible distance. We numerically analyze various phenomena caused by scattering effects in this system, such as degradation of the signal-to-noise ratio, glitches, and spatiotemporal spread and time delay of the LIDAR signals. The MCRT matrix method is expected to be very effective in analyzing a variety of LIDAR systems, including flash LIDAR systems for autonomous driving.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.40-46
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• 2009

Purpose : The purpose of this study was to investigate the quantitative evaluation of the corticospinal tract (CST) at the multiple levels by using functional MRI (fMRI) co-registered to diffusion tensor tractography (DTT). Materials and Methods : Ten normal subjects without any history of neurological disorder participated in this study. fMRI was performed at 1.5 T MR scanner using hand grasp-release movement paradigm. DTT was performed by using DtiStudio on the basis of fiber assignment continuous tracking algorithm (FACT). The seed region of interest (ROI) was drawn in the area of maximum fMRI activation during the motor task of hand grasp-release movement on a 2-D fractional anisotropy (FA) color map, and the target ROI was drawn in the cortiocospinal portion of anterior lower pons. We have drawn five ROIs for the measurement of FA and apparent diffusion coefficient (ADC) along the corona radiata (CR) down to the medulla. Results : The contralateral primary sensorimotor cortex (SM1) was mainly found to be activated in all subjects. DTT showed that tracts originated from SM1 and ran to the medulla along the known pathway of the CST. In all subjects, FA values of the CST were higher at the level of the midbrain and posterior limb of internal capsule (PLIC) than the level of others. Conclusion : Our study showed that co-registered fMRI and DTT has elucidated the state of CST on 3-D and analyzed the quantitative values of FA and ADC at the multiple levels. We conclude that co-registered fMRI and DTT may be applied as a useful tool for clarifying and investigating the state of CST in the patients with brain injury.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.1-14
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• 2000

The rosette-scan seeker, mounted on the infrared guided missile, is a device that tracks the target It can acquire the 2D image of the target by scanning a space about target in rosette pattern with a single detector Since the detected image is changed according to the position of the object in the field of view and the number of the object is not fixed, the unsupervised methods are employed in clustering it The conventional ISODATA method clusters the objects by using the distance between the seed points and pixels So, the clustering result varies in accordance with the shape of the object or the values of the merging and splitting parameters In this paper, we propose an Array Linkage Clustering Algorithm (ALCA) as a new clustering algorithm improving the conventional method The ALCA has no need for the initial seed points and the merging and splitting parameters since it clusters the object using the connectivity of the array number of the memory stored the pixel Therefore, the ALCA can cluster the object regardless of its shape With the clustering results using the conventional method and the proposed one, we confirm that our method is better than the conventional one in terms of the clustering performance We simulate the rosette scanning infrared seeker (RSIS) using the proposed ALCA as an infrared counter countermeasure The simulation results show that the RSIS using our method is better than the conventional one in terms of the tracking performance.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.43-52
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• 2024

Purpose: Cancer is the leading cause of death in Koreans, with breast cancer being the most common among women. Breast cancer readily metastasizes, and the existing treatment processes impose a significant burden on patients. This study examined whether pomegranate-derived exosome-like nanovesicles (PNVs) have anti-cancer effects by inhibiting cell infiltration and metastasis while increasing apoptosis on breast cancer MDA-MB-231 cells. Methods: Initially, exosome-like nanovesicles were isolated from pomegranate using ultracentrifugation. Subsequently, the size range of these nanovesicles was confirmed using nanoparticle tracking analysis. The ability of breast cancer MDA-MB-231 cells to internalize these natural nanovesicles was assessed with flourescence microscope. The anti-cancer effects of the PNVs were confirmed by applying various concentrations of PNVs (10, 50, 100 ㎍/mL) to MDA-MB-231 cells and systematically assessing their impact on cell viability and migration. Results: The round shape of the lipid bilayer in the PNVs was confirmed, providing crucial insights into their structural properties. We demonstrate that PNVs-associated DiD dye can be efficiently internalized by the MDA-MB-231 cells. The data showed that the PNVs inhibited cell viability, invasion rates, and migration in MDA-MB-231 cells. In addition, PNVs were absorbed into the MDA-MB-231 cells, leading to an increased expression of apoptosis proteins, such as cleaved caspase-3 and phosphorus-JNK, in a concentration-dependent manner. Furthermore, a reduction in cell infiltration and decreased expression of the transition markers MMP-2 and MMP-9 proteins were observed. Conclusion: For the first time, this study suggests that PNVs may be useful in the prevention or treatment of breast cancer by inhibiting the infiltration and metastasis of MDA-MB-231 cells and inducing apoptosis.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.2
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• pp.161-169
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• 1999

This paper describes the swimming and escaping behavior of amber fish, Seriola aureovittata released in the first bag net of the setnet and observed with telemetry techniques. The setnet used in experiment is composed of a leader, a fish court with a flying net and two bag nets having ramp net. The behavior of the fish attached an ultrasonic depth pinger of 50 KHz is observed using a prototype LBL fish tracking system. The 3-D underwater position ofthe fish is calculated by hyperbolic method with three channels of receiver and the depth of pinger. The results obtained are as follows: 1. The fish released on the sea surface was escaped down to 15 m depth and rised up to near the sea surface during 5 minutes after release. The average swimming speed of the fish during this time was 0.87 m/sec. 2. The swimming speed of the fish is decreased slowly in relation to the time elapsed and the fish showed some escaping behavior forward to the fish court staying 1 to 7 m depth layer near the ramp net. The average speed of the fish during this time was 0.52 m/sec. 3. During 25 minutes after beginning of hauling net, the fish showed a faster swimming speed than before hauling and an escaping behavior repeatedly from the first ramp net to the second one in horizontal. In vertical, the fish moved up and down between the sea surface and 20 m depth. After this time, the fish showed the escaping behavior forward to fish court after come back to the first ramp net in spite of the hauling was continued. It is found that the fish was escaped from the first ramp net to the fish court while the hauling was carried out. The average speed of the fish after beginning of hauling was 0.72 m/sec which increased 38.5 ％ than right before the hauling and showed 0.44 to 0.82 m/see of speed till escaping the first bag net. The average swimming speed during observation was 0.67 m/sec (2.2 times of body length).

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.17-26
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• 2012

Purpose: This study mainly focuses on the patients treated with chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO (d,l-hexamethylpropylene amine oxime) which yielded reduced image quality due to a decreased brain extraction rate. $^{99m}Tc$-HMPAO will be examined further to determine whether this product may be accounted as a factor for this cause. Material and Methods: From January 2010 until December 2010, out of 272 patients who were all subjected to $^{99m}Tc$-HMPAO brain blood flow SPECT scans resulting from Cerebral Infarction; 23 patients(ages $55.3{\pm}9$, 21 males, 3 females) with decreased tissue extraction rate were examined in detail. The radiopharmaceutical product $^{99m}Tc$-HMPAO was used on patients with normal brain tissue exchange rate as well as those with reduced rate in order to prove its' chemical stability. The patients' age, sex, blood pressure, existence of diabetes, drug use, current health status, known side effects from CT/MRI, examination of the patients' past SPECT before/after images were accounted to determine the factors and correlations affecting the rate of blood tissue extractions. Result: After multiple linear regression analysis, there were no unusual correlations between the 6 factors excluding sex, and before/after examination images. Male subjects showed reduced brain tissue extraction rate than the females ($p$ > 0.05) 91.3% male, 8.7% female. Wilcoxon Matched-Pairs Signed-Ranks Test was used on the before/after images which yielded a value of 0.06, which did not indicate a significant amount of difference on the 2 tests ($p$ > 0.05). As a result, the before/after images indicated similar brain tissue extraction rates, and there were variations depending on the individual patient. Conclusion: The effects of the chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO depended on the patient's personal characteristics and status, therefore was considered to be a factor in reducing brain tissue extraction rate. The related articles of $^{99m}Tc$-HMPAO cerebral blood flow SPECT speculates a cerebrovascular disease and factors resulting from portal veins, and it was not possible to pin point the exact cause of decreasing brain tissue extraction rate. However, the $^{99m}Tc$-HMPAO cerebral blood flow SPECT scan proved to be extremely useful in tracking and inspecting brain diseases, as well as offering accurate results from patients suffering from reduced brain tissue extraction rates.