• Spatial Information Research
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• v.22 no.5
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• pp.43-52
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• 2014

Recently, Big Data is a buzzword in the creative economy generation. The organizations related to spatial information society focus on building the spatial big data systems. As spatial big data is a combination of spatial information and big data, the data visualization is essential in order to utilize them efficiently. One of the great methodologies for data visualization is infographics. Nationally, Chousn.com initiated the infographics news in 2010. Korean Administration Branches also recognized the importance of infographic and they adopted infographics for their briefings from 2013. Internationally, Visual.ly is leading company in the infographics market and they produced noticeable interactive infographics for Egypt Parliamentary Elections results. In the defense part, Guardian's datajournalism of Afghanistan war log was a good example of utilizing infographics. Throughout the research, five requirements are extracted. First source data should have precision and accuracy in terms of time and space manner. Second, infographics images have a compressibility. Third, the infographics is properly processed for military commanders. Fourth, sharing, openness and communication are essential for high quality infographic. Lastly, infographics should be an analytic tool for predicting future event based on the past data. Infographics is not a direct representation of data but an analytic tool for helping user's choice and decision in critical moments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.15-23
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• 2017

The person Re-identification is the most challenging part of computer vision due to the significant changes in human pose and background clutter with occlusions. The picture from non-overlapping cameras enhance the difficulty to distinguish some person from the other. To reach a better performance match, most methods use feature selection and distance metrics separately to get discriminative representations and proper distance to describe the similarity between person and kind of ignoring some significant features. This situation has encouraged us to consider a novel method to deal with this problem. In this paper, we proposed an enhanced recurrent neural network with three-tier hierarchical network for person re-identification. Specifically, the proposed recurrent neural network (RNN) model contain an iterative expectation maximum (EM) algorithm and three-tier Hierarchical network to jointly learn both the discriminative features and metrics distance. The iterative EM algorithm can fully use of the feature extraction ability of convolutional neural network (CNN) which is in series before the RNN. By unsupervised learning, the EM framework can change the labels of the patches and train larger datasets. Through the three-tier hierarchical network, the convolutional neural network, recurrent network and pooling layer can jointly be a feature extractor to better train the network. The experimental result shows that comparing with other researchers' approaches in this field, this method also can get a competitive accuracy. The influence of different component of this method will be analyzed and evaluated in the future research.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.100-110
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• 2007

When compressed video data is transmitted over error-prone network such as wireless channel, data is likely to be lost, so the quality of reconstructed picture is severely decreased. It is specially so in case that important information such as motion vector or macroblock mode is lost. H.264/AVC standard includes DP as error resilient technique for protecting important information from error in which data is labeled according to its relative importance. But DP technique requires a network that supports different reliabilities of transmitted data. In general, the benefits of UEP is sought by sending multiple times of same packets corresponding to important information. In this paper, we propose MDC technique based on data partitioning technique. The proposed method encodes motion vector of H.264/AVC standard into multiple parts using MDC and transmits each part as independent packet. Even if partial packet is lost, the proposed scheme can decode the compressed bitstream by using estimated motion vector with partial packets correctly transmitted, so that achieving improved performance of error concealment with minimal effect of channel error. Also in decoding process, the proposed multiple description matching increases the accuracy of estimated lost motion vector and quality of reconstructed video.

• Publications of The Korean Astronomical Society
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• v.32 no.2
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• pp.367-380
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• 2017

The life and astronomical activity of Lee Deok-Seong (李德星, 1720-1794) was studied using various historical sources, including the astronomical almanac, Seungjeongwon-Ilgi (Daily records of Royal Secretariat of Joseon dynasty), and the Gwansang-Gam's logbooks during Joseon dynasty (A.D. 1392-1910). We present the results of the study including the following main findings. First, from the investigation of Lee's family tree, we find that a number of his relatives were also astronomers, notably Samryeok-Gwan (三曆官, the post of calendrical calculation). Second, we find that he took part in the compilation of an annual astronomical almanac over a period of at least 16 years. His major achievements in the astronomy of the Joseon dynasty were to establish a new method of calendar-making calculation and to bring astronomical materials to the Joseon court through a visit to China. The Joseon dynasty enforced the Shixianli (時憲曆, a Chinese calendar made by Adam Shall) in 1654 without fully understanding the calendar. So an astronomer and an envoy were dispatched to China in order to master the intricacies of the calendar and to learn as much of Western science as was available in that time and place. Lee Deok-Seong worked at the Gwansang-Gam (觀象監, Royal Astronomical Bureau) during the reigns of King Yeongjo (英祖) and Jeongjo (正祖). As best as we can ascertain in relation with the calculations in the Shixian calendar, Lee visited China four times. During his trips and interactions, he learned a new method for calendar-making calculations, and introduced many Western-Chinese astronomical books to Joseon academia. Lee greatly improved the accuracy of calendrical calculations, even while simplifying the calculation process. With these achievements, he finally was promoted to the title of Sungrok-Daebu (崇祿大夫), the third highest grade of royal official. In conclusion, history demonstrates that Lee Deok-Seong was one of the most outstanding astronomers in the late-Joseon dynasty.

• Journal of Korean Medicine Rehabilitation
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• v.18 no.3
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• pp.147-156
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• 2008

Objectives : Oriental Medicine Music Therapy is a new way of treating and preventing various diseases and promoting health by means of music specially picked and designed to produce Qi(氣) fitting to an individual person in the areas of the structure of human body, physiological function, pathological change, diagnosis and treatment. Therefore, it can facilitate the efficiency of the treatment much better and faster than only with herb or acupuncture. Equilibrium between body and mind is its originality. Methods : A 38-year old man came to hospital suffering from left side weakness, dysarthria because of cerebral infarction. After one week's medication in the part of neurology, he was sent to the oriental medicine music therapy center, and he took ten times' medical treatments once a day. Before and after the treatments, implementing 'Ink foot print analysis', as for the movement capacity and walking of left side weakness, these results are acquired. Results and Conclusions : 1. Before the oriental medicine music therapy, except the acceleration and deceleration section, within three meters, a right foot's step was measured 30.55 cm and a left foot was measured 15.2 cm, and the step distance was 15.2 cm. After the 10 times treatments, the right foot's step was 112.6 cm, the left foot's step was 113 cm, and the step distance improved to 51.8 cm. 2. The normal person's average step is about 38 cm, and it could be decreased owing to a decreptitude, pain, fatigue, and the weakness of the legs. In spite of all, from the increased 50 cm step measurement with the patient's body condition, it means that his movement capacity is recovered. 3. In the measurement of walking time, before 10 times treatments, it took 46.35 seconds within 6M, but after the treatments, it increased to 7.47 seconds as same as a normal person's walking speed. 4. In insomnia, and the abnormality of a facial muscle, it shows lots of improvement, and even the accuracy of a pronunciation, but despite of the 10 times treatments, the 'ㄹ(r)' sound placed under a vowel is unclear. 5. Before the 10 times' treatments, he can move the left side shoulder with pain and cannot move below the left elbow. After the treatments, the pain was disappeared, and he was able to move over 60 cm without pain. And improving of the movement of fingers, he can beat over 8 times with a drumstick.

• Journal of Radiation Protection and Research
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• v.40 no.1
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• pp.55-64
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• 2015

Dose calculations which are a crucial requirement for radiotherapy treatment planning systems require accuracy and rapid calculations. The conventional radiotherapy treatment planning dose algorithms are rapid but lack precision. Monte Carlo methods are time consuming but the most accurate. The new combined system that Monte Carlo methods calculate part of interesting domain and the rest is calculated by neural can calculate the dose distribution rapidly and accurately. The preliminary study showed that neural networks can map functions which contain discontinuous points and inflection points which the dose distributions in inhomogeneous media also have. Performance results between scaled conjugated gradient algorithm and Levenberg-Marquardt algorithm which are used for training the neural network with a different number of neurons were compared. Finally, the dose distributions of homogeneous phantom calculated by a commercialized treatment planning system were used as training data of the neural network. In the case of homogeneous phantom;the mean squared error of percent depth dose was 0.00214. Further works are programmed to develop the neural network model for 3-dimensinal dose calculations in homogeneous phantoms and inhomogeneous phantoms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.279-282
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• 2017

Kinect depth sensor, a depth camera developed by Microsoft as a natural user interface for game appeared as a very useful tool in computer vision field. In this paper, due to kinect's depth sensor and its high frame rate, we developed a distance measurement system using Kinect camera to test it for unmanned vehicles which need vision systems to perceive the surrounding environment like human do in order to detect objects in their path. Therefore, kinect depth sensor is used to detect objects in its field of view and enhance the distance measurement system from objects to the vision sensor. Detected object is identified in accuracy way to determine if it is a real object or a pixel nose to reduce the processing time by ignoring pixels which are not a part of a real object. Using depth segmentation techniques along with Open CV library for image processing, we can identify present objects within Kinect camera's field of view and measure the distance from them to the sensor. Tests show promising results that this system can be used as well for autonomous vehicles equipped with low-cost range sensor, Kinect camera, for further processing depending on the application type when they reach a certain distance far from detected objects.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.643-652
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• 2006

Decision trees are mainly used for the classification and prediction in data mining. The distribution of spatial data and relationships with their neighborhoods are very important when conducting classification for spatial data mining in the real world. Spatial decision trees in previous works have been designed for reflecting spatial data characteristic by rating Euclidean distance. But it only explains the distance of objects in spatial dimension so that it is hard to represent the distribution of spatial data and their relationships. This paper proposes a decision tree based on spatial entropy that represents the distribution of spatial data with the dispersion and dissimilarity. The dispersion presents the distribution of spatial objects within the belonged class. And dissimilarity indicates the distribution and its relationship with other classes. The rate of dispersion by dissimilarity presents that how related spatial distribution and classified data with non-spatial attributes we. Our experiment evaluates accuracy and building time of a decision tree as compared to previous methods. We achieve an improvement in performance by about 18%, 11%, respectively.

• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.51-56
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• 2009

Time synchronization algorithm in wireless sensor networks is essential to various applications such as object tracking, data encryption, duplicate detection, and precise TDMA scheduling. This paper describes CDRS that is a time synchronization algorithm using the Clock Drift rate and Reference Signals between two sensor nodes. CDRS is composed of two steps. At first step, the time correction is calculated using offset and the clock drift rate between the two nodes based on the LTS method. Two nodes become a synchronized state and the time variance can be compensated by the clock drift rate. At second step, the synchronization node transmits reference signals periodically. This reference signals are used to calculate the time difference between nodes. When this value exceeds the maximum error tolerance, the first step is performed again for resynchronization. The simulation results on the performance analysis show that the time accuracy of the proposed algorithm is improved, and the energy consumption is reduced 2.5 times compared to the time synchronization algorithm with only LTS, because CDRS reduces the number of message about 50% compared to LTS and reference signals do not use the data space for timestamp.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.55-63
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• 2008

Ridge orientations of fingerprint image are crucial informations in many parts of fingerprint recognition such as enhancement, matching and classification. Therefore it is essential to extract the ridge orientations of image accurately because it directly affects the performance of the system. The two main properties of ridge orientation are 1) global characteristic(gradual change in whole part of fingerprint) and 2) local characteristic(abrupt change around core and delta points). When we only consider the local characteristic, estimated ridge orientations are well around singular points but not robust to noise. When the global characteristic is only considered, to estimate ridge orientation is robust to noise but cannot represent the orientation around singular points. In this paper, we propose a novel method for estimating ridge orientation which represents local characteristic specifically as well as be robust to noise. We reduce the noise caused by scar using iterative outlier rejection. We apply adaptive measurement resolution in each fingerprint area to estimate the ridge orientation around singular points accurately. We evaluate the performance of proposed method using synthetic fingerprint and FVC 2002 DB. We compare the accuracy of ridge orientation. The performance of fingerprint authentication system is evaluated using FVC 2002 DB.