• The KIPS Transactions:PartA
• /
• v.16A no.3
• /
• pp.209-216
• /
• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.6 no.1
• /
• pp.59-77
• /
• 2003

This study is to validate the use of macro language for the land suitability analysis aiming to help to resolve land use conflicts. The silver-town suitability analysis is conducted on the Geejang Gun, Busan Metropolitan city. Such digital maps as terrain, road, facility, and water body were created for various cartographic models. A cartographic model identified the best suitable areas for silver-town development based on the such site selection variables as a distance to facility and road, slope and aspect of terrain, land use etc. Then, the other cartographic model identified the most favorable site among the candidate sites based on the comparison of the aspect of proximity, usage and environmental quality. Macro language was used for these modeling process and was used for the manipulation of all these spatial variables used in the models to resolve land use conflicts relating to the decision making process of the final site selection. This study will improve the effectiveness and rationality of the traditional site suitability analysis.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.7
• /
• pp.91-98
• /
• 2008

In digital broadcasting, it is possible to multiplex maximum one hundred audio or music programs into MPEG-2 transport stream, which is suitable for transmitting through one channel. In order to check if multiplex music programs are transmitted well, we need a multiplex audio monitoring system that monitors the programs in real-time. In analog broadcasting, we have used hardware-based audio monitoring system for a small number music programs. However, the effectiveness of hardware-based audio monitoring system from the cost and function viewpoint is so low that a new system is needed for digital broadcasting. In this paper, we have designed and implemented a software-based audio monitoring system to satisfy these requirements. In this implementation, only one PC is used without other hardware facilities, and the system monitors digital broadcasting music programs effectively. Transmitted digital broadcasting streams are demultiplexed into many music programs and the realtime value of audio level and packet error information for these programs are displayed in the screen. Thus, the system detects and shows the abnormal transmitting programs automatically. Simulation results show that effective realtime multiplex audio monitoring is possible for digital broadcasting music programs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.2
• /
• pp.203-211
• /
• 2009

With supply of the domestic digital camera, the relative importance of the digital camera is coming to be high gradually on aerial photogrammetry, the image of digital camera is more applied in image map or digital topographic map production. But, there are cases that do not have position information or attitude information of each photograph in digital camera results. Therefore, we wish to present additional method to get more accurate photograph control point result. In this study, One is called A method, which is the case of entering positioning information of principal point from topographic map as default values that are need to extract tie point automatically using by 56 pieces of photography that are photographed by DMC to the extent to 5 courses and 35 GCP points. The other is called B-method, which is the case of entering exterior orientation parameters that are processed by block adjustment for A-method using by 4 control points in method-1 as default values. We have analyzed about results per control points arrangement for two cases using MATCH-AT that is photograph control point measurement S/W of Germany INPHO company. As a result of analysis, accuracy of B-method was better than that of A-method, and we could get more accurate results if block adjustments are executed including self calibration. Also, it is more effective in expense side that using self calibration for photograph survey in B-method because can reduce GCP numbers.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.11
• /
• pp.39-49
• /
• 2013

In this paper, security mechanism of internal network(CAN) of vehicle is a very incomplete state and the possibility of external threats as a way to build a test environment that you can easily buy from the market by the vehicle's ECU(Electric Control Unit) to verify and obtain a CAN message. Then, by applying it to ECU of the real car to try to attack is proposed. A recent study, Anyone can see plain-text status of the CAN message in the vehicle. so that in order to verify the information is vulnerable to attack from outside, analyze the data in a vehicle has had a successful attack, but attack to reverse engineering in the stationary state and buying a car should attempt has disadvantages that spatial, financial, and time costs occurs. Found through the car's ECU CAN message is applied to a real car for Potential threats outside of the car to perform an experiment to verify and equipped with a wireless network environment, the experimental results, proposed method through in the car to make sure the attack is possible. As a result, reduce the costs incurred in previous studies and in the information absence state of the car, potential of vehicle's ECU attack looks.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.4
• /
• pp.179-188
• /
• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.4
• /
• pp.63-75
• /
• 2016

Aquaculture has historically delivered marine products because the country is surrounded by ocean on three sides. Surveys on production have been conducted recently to systematically manage aquaculture facilities. Based on survey results, pricing controls on marine products has been implemented to stabilize local fishery resources and to ensure minimum income for fishermen. Such surveys on aquaculture facilities depend on manual digitization of aerial photographs each year. These surveys that incorporate manual digitization using high-resolution aerial photographs can accurately evaluate aquaculture with the knowledge of experts, who are aware of each aquaculture facility's characteristics and deployment of those facilities. However, using aerial photographs has monetary and time limitations for monitoring aquaculture resources with different life cycles, and also requires a number of experts. Therefore, in this study, we investigated an automatic prototype system for detecting boundary information and monitoring aquaculture facilities based on satellite images. KOMPSAT-3 (13 Scene), a local high-resolution satellite provided the satellite imagery collected between October and April, a time period in which many aquaculture facilities were operating. The ANN classification method was used for automatic detecting such as cage, longline and buoy type. Furthermore, shape files were generated using a digitizing image processing method that incorporates polygon generation techniques. In this study, our newly developed prototype method detected aquaculture facilities at a rate of 93%. The suggested method overcomes the limits of existing monitoring method using aerial photographs, but also assists experts in detecting aquaculture facilities. Aquaculture facility detection systems must be developed in the future through application of image processing techniques and classification of aquaculture facilities. Such systems will assist in related decision-making through aquaculture facility monitoring.

• The Korean Journal of Nuclear Medicine
• /
• v.38 no.3
• /
• pp.233-240
• /
• 2004

Purpose: We developed a computer-aided classifier using artificial neural network (ANN) to discriminate the cerebral metabolic pattern of medial and lateral temporal lobe epilepsy (TLE). Materials and Methods: We studied brain F-18-FDG PET images of 113 epilepsy patients sugically and pathologically proven as medial TLE (left 41, right 42) or lateral TLE (left 14, right 16). PET images were spatially transformed onto a standard template and normalized to the mean counts of cortical regions. Asymmetry indices for predefined 17 mirrored regions to hemispheric midline and those for medial and lateral temporal lobes were used as input features for ANN. ANN classifier was composed of 3 independent multi-layered perceptrons (1 for left/right lateralization and 2 for medial/lateral discrimination) and trained to interpret metabolic patterns and produce one of 4 diagnoses (L/R medial TLE or L/R lateral TLE). Randomly selected 8 images from each group were used to train the ANN classifier and remaining 51 images were used as test sets. The accuracy of the diagnosis with ANN was estimated by averaging the agreement rates of independent 50 trials and compared to that of nuclear medicine experts. Results: The accuracy in lateralization was 89% by the human experts and 90% by the ANN classifier Overall accuracy in localization of epileptogenic zones by the ANN classifier was 69%, which was comparable to that by the human experts (72%). Conclusion: We conclude that ANN classifier performed as well as human experts and could be potentially useful supporting tool for the differential diagnosis of TLE.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.4
• /
• pp.208-220
• /
• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Radiation Oncology Journal
• /
• v.25 no.1
• /
• pp.54-61
• /
• 2007

[ $\underline{Purpose}$ ]: The purpose of this study is to develop a practical method for determining accurate marker positions for prostate cancer radiotherapy using CT images and kV x-ray images obtained from the use of the on- board imager (OBI). $\underline{Materials\;and\;Methods}$: Three gold seed markers were implanted into the reference position inside a prostate gland by a urologist. Multiple digital image processing techniques were used to determine seed marker position and the center-of-mass (COM) technique was employed to determine a representative reference seed marker position. A setup discrepancy can be estimated by comparing a computed $COM_{OBI}$ with the reference $COM_{CT}$. A proposed algorithm was applied to a seed phantom and to four prostate cancer patients with seed implants treated in our clinic. $\underline{Results}$: In the phantom study, the calculated $COM_{CT}$ and $COM_{OBI}$ agreed with $COM_{actual}$ within a millimeter. The algorithm also could localize each seed marker correctly and calculated $COM_{CT}$ and $COM_{OBI}$ for all CT and kV x-ray image sets, respectively. Discrepancies of setup errors between 2D-2D matching results using the OBI application and results using the proposed algorithm were less than one millimeter for each axis. The setup error of each patient was in the range of $0.1{\pm}2.7{\sim}1.8{\pm}6.6\;mm$ in the AP direction, $0.8{\pm}1.6{\sim}2.0{\pm}2.7\;mm$ in the SI direction and $-0.9{\pm}1.5{\sim}2.8{\pm}3.0\;mm$ in the lateral direction, even though the setup error was quite patient dependent. $\underline{Conclusion}$: As it took less than 10 seconds to evaluate a setup discrepancy, it can be helpful to reduce the setup correction time while minimizing subjective factors that may be user dependent. However, the on-line correction process should be integrated into the treatment machine control system for a more reliable procedure.