• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.355-360
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• 2017

Recently, with the development of autonomous vehicle technology, the importance of precise road maps is increasing. A precise road map is a digital map with lane information, regulations, safety information, and various road facilities. Conventional precise road maps have been tested and developed based on the mobile mapping system (MMS). But they have not been activated due to high introduction costs. However, in the case of unmanned aerial vehicles (UAVs), the application field is continuously increasing. This study tries to extract information through classification of high-resolution UAV images for autonomous driving. Autonomous vehicle test roads were selected as study sites, and high-resolution orthoimages were produced using UAVs. In addition, the utilization of high-resolution orthoimages has been proposed by effectively extracting data for precise road map construction, such as road lines, guards, and machines through image classification. If additional experimentation and verification are performed, the field of UAV image use will be expanded, providing the data to automobile manufacturers and related public and private organizations, and venture companies will contribute to the development of domestic autonomous vehicle technology.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2400-2410
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• 2000

Many researches on recognition of Korean characters have been undertaken. But while the majority are done on Korean character recognition, tasks for developing document recognition system have seldom been challenged. In this paper, I designed a recognizer of Korean courtesy amounts to improve error correction in recognized character string. From the very first step of Korean character recognition, we face the enormous scale of data. We have 2350 characters in Korean. Almost the previous researches tried to recognize about 1000 frequently-used characters, but the recognition rates show under 80%. Therefore using these kinds of recognizers is not efficient, so we designed a statistical multiple recognizer which recognize 16 Korean characters used in courtesy amounts. By using multiple recognizer, we can prevent an increase of errors. For the Postprocessor of Korean courtesy amounts, we use the properties of Korean character strings. There are syntactic rules in character strings of Korean courtesy amounts. By using this property, we can correct errors in Korean courtesy amounts. This kind of error correction is restricted only to the Korean characters representing the unit of the amounts. The first candidate of Korean character recognizer show !!i.49% of recognition rate and up to the fourth candidate show 99.72%. For Korean character string which is postprocessed, recognizer of Korean courtesy amounts show 96.42% of reliability. In this paper, we suggest a method to improve the reliability of Korean courtesy amounts recognition by using the Korean character recognizer which recognize limited numbers of characters and the postprocessor which correct the errors in Korean character strings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5B
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• pp.456-477
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• 2006

Due to advances in wireless communication technology and increasing demand for various types of wireless access, cellular, WLAN, and portable internet(such as WiBro and IEEE 802.16) systems are likely to be integrated into a unified wireless access system. This expectation premises the availability of multi-mode handsets and cooperative interworking of heterogenous wireless access networks allied by roaming contracts. Under such environments, a user may lie in the situation where more than one wireless accesses are available at his/her location, and he/she will want to choose the 'best' access among them. In this paper, we define the 'best' access(es) as the access(es) that charges minimum cost while fulfilling the required QoS of wireless access, and address the problem of choosing the optimal set of accesses theoretically by introducing a graph representation of service environment. Two optimal selection algorithms are proposed, which individually consider cases where single or multiple wireless access can be supported by multi-mode handsets.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.54-67
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• 2010

Applying the conventional machine-learning method which has been frequently used in health-care area has several fundamental problems for modern U-health service analysis. First of all, we are still lack of application examples of the traditional method for our modern U-health environment because of its short term history of U-health study. Second, it is difficult to apply the machine-learning method to our U-health service environment which requires real-time management of disease because the method spends a lot of time in the process of learning. Third, we cannot implement a personalized U-health diagnosis system using the conventional method because there is no way to assign weights on the disease-related variables although various kinds of machine-learning schemes have been proposed. In this paper, a novel diagnosis scheme PCADP is proposed to overcome the problems mentioned above. PCADP scheme is a personalized diagnosis method and it makes the bio-data analysis just a 'process' in the U-health service system. In addition, we offer a semantics modeling of the U-health ontology framework in order to describe U-health data and service specifications as meaningful representations based on this PCADP. The PCADP scheme is a kind of statistical diagnosis method which has characteristics of flexible structure, real-time processing, continuous improvement, and easy monitoring of decision process. Upto the best of authors' knowledge, the PCADP scheme and ontology framework proposed in this paper reveals one of the best characteristics of flexible structure, real-time processing, continuous improvement, and easy monitoring among recently developed U-health schemes.

• Spatial Information Research
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• v.19 no.6
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• pp.101-109
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• 2011

Climate change affects all components of the global environment system and, in turn, all components mutually interact and affect climate change through non-linear feedback processes. It is thus necessary to study the interaction between the climate and the environment, in order to comprehensively understand and predict climate and environment change. However, current relevant systems are limited to particular areas and do not sufficiently support the mutual linking of research studies. Therefore, this study develops prototype a GIS based integrated DB management system for supporting the climate and environment data storage, management and distribution. The integrated DB management system was developed using VB.NET languages and ArcObjects component. First, considering the demands of climate environment experts, the study areas are selected and the methods of data management and utilization were defined. In addition, a location-based GIS DB was created in order to aid in understanding climate change through visual representation. Finally, the integrated DB management system provides an efficient data management and distribution data and it creates synergistic effect on climate and environment study. It also contributes significantly to the comprehensive diagnosis and prediction of climate change and environment systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.609-616
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• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.849-858
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• 2019

Recent developments in computer graphics technology and image processing technology have increased interest in point cloud technology for inputting real space and object information as three-dimensional data. In particular, point cloud technology can accurately provide spatial information, and has attracted a great deal of interest in the field of autonomous vehicles and AR (Augmented Reality)/VR (Virtual Reality). However, in order to provide users with 3D point cloud contents that require more data than conventional 2D images, various technology developments are required. In order to solve these problems, an international standardization organization, MPEG(Moving Picture Experts Group), is in the process of discussing efficient compression and transmission schemes. In this paper, we provide a region division transfer method of 3D point cloud content through extension of existing MPEG-DASH (Dynamic Adaptive Streaming over HTTP)-SRD (Spatial Relationship Description) technology, quality parameters are further defined in the signaling message so that the quality parameters can be selectively determined according to the user's request. We also design a verification platform for ROUTE (Real Time Object Delivery Over Unidirectional Transport)/DASH based heterogeneous network environment and use the results to validate the proposed technology.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.35-42
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• 2022

Visible light communication (VLC) is a method of transmitting data through LED blinking and is vulnerable to eavesdropping because the illumination affects the wide range of area. IEEE standard 802.15.7 defines On-Off Keying (OOK), Variable Pulse Position Modulation (VPPM), and Color Shift Keying (CSK) as modulation. In this paper, we propose an encryption method in VPPM for secure communication. The VPPM uses an encoding method called 4B6B where 16 different outputs are represented with 6-bit. This paper extends the number of outputs to 20, to add complexity while not violating the 4B6B generation conditions. Then each entry in the extended 4B6B table is scrambled using vigenère cipher. The probability of decrypting each 6-bit data is $\frac{1}{20}$. Eavesdropper should perform $\sum\limits_{k=1}^{n}20^k$ number of different trials to decrypt the message if the number of keys is n. The proposed method can be applied to OOK of PHY II and CSK of PHY III. We further discuss the secure encoding that can be used in OOK and CSK without performance degradation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.