In this paper, we propose a binarization algorithm using LVQ-Merge clustering method for fast and accurate extraction of cells from cell images. The proposed method clusters pixel data of a given image by using LVQ to remove noise and divides the result into two clusters by applying a hierarchical clustering algorithm to improve the accuracy of binarization. As a result, the execution speed is somewhat slower than that of the conventional LVQ or Otsu algorithm. However, the results of the binarization have very good quality and are almost identical to those judged by the human eye. Especially, the bigger and the more complex the image, the better the binarization quality. This suggests that the proposed method is a useful method for medical image processing field where high-resolution and huge medical images must be processed in real time. In addition, this method is possible to have many clusters instead of two cluster, so it can be used as a method to complement a hierarchical clustering algorithm.

HD padding area is essential redundancy in HD broadcasting. It is possible to use this padding area for the purpose of improving DTV broadcasting services. For utilization of this area, The bit of a service data was converted to black and white $8{\times}8$ block image. Converted block images are compressed with active video and are delivered to a receiver as only DC coefficients in a video stream. video quality is not effected by the proposed method, and service data was perfectly recovered in receiver without errors by using block average and threshold. The proposed utilization of HD essential padding area can possibly overcome the limited transmission stream rate with the bandwidth of HD broadcasting. If service data in transport or video stram were transferred using this padding area, it is possible to improve video quality with expanded video stream rate. Additionally, because the proposed methods are based on well-established standards, it is also useful for world-wide HD broadcasting systems such as ATSC, DVB, and IPTV.

Recent advance in electronics and scintillators makes it possible to utilize the time-of-flight (TOF) information in improving image reconstruction of positron emission tomography(PET). In this paper, we propose a TOF-based fast image reconstruction method for PET. The proposed method uses the deconvolution of TOF data for each angle view and the rotational averaging of deconvolved images. Simulation results show an improved performance of the proposed method, as compared with filtered backprojection (FBP) method, TOF-FBP, and TOF version of expectation-maximization(EM) methods. Simulation results also show a great potentiality of the proposed method in limited angle tomography applications.

Prevention of drowsy driving is one of the important issues for safe driving. In this study, the algorithm for detection of drowsy driving has been developed. The algorithm was implemented by applying template matching and line profile, which detects eye blink. The accuracy of eye detection and blink detection was $97.45{\pm}3.67%$ and $98.50{\pm}0.92%$, which was resulted from the verification experiment that 21 subjects participated. Consequently, the algorithm is expected to be used to prevent sleep-deprived driving.

Locally Likely Arrangement Hashing (LLAH) is a method that describes image features based on the geometry between their neighbors. Thus, it has been preferred to implement augmented reality on poorly-textured objects such as text documents. However, LLAH strongly requires that image features be detected with high repeatability and located at a distance from one another. To fulfill the requirement for text document, this paper proposes a method that facilitates the word detection in infrared (IR) range by adjusting the IR-reflectance of words. Specifically, the words are printed out with two different black inks: one is using the K(carbon black) ink only, the other is mixing the C(cyan), M(magenta), Y(yellow) inks. Since only the words printed out with the K ink is visible in IR range, a part of words are selected in advance to be used as features and printed out the K ink. The selected words can be robustly detected with high repeatability in IR range and this enables to implement augmented reality on text documents with high fidelity. The validity of the proposed method was verified through experiments.

In this paper, we propose a simple online multiple object (human) tracking method, LKDeep (Lucas-Kanade feature and Detection based Simple Online Multiple Object Tracker), which can run in fast online enough on CPU core only with acceptable tracking performance for embedded surveillance purpose. The proposed LKDeep is a pragmatic hybrid approach which tracks multiple objects (humans) mainly based on LK features but is compensated by detection on periodic times or on necessity times. Compared to other state-of-the-art multiple object tracking methods based on 'Tracking-By-Detection (TBD)' approach, the proposed LKDeep is faster since it does not have to detect object on every frame and it utilizes simple association rule, but it shows a good object tracking performance. Through experiments in comparison with other multiple object tracking (MOT) methods using the public DPM detector among online state-of-the-art MOT methods reported in MOT challenge [1], it is shown that the proposed simple online MOT method, LKDeep runs faster but with good tracking performance for surveillance purpose. It is further observed through single object tracking (SOT) visual tracker benchmark experiment [2] that LKDeep with an optimized deep learning detector can run in online fast with comparable tracking performance to other state-of-the-art SOT methods.

Tor proxy tool is studied which is most frequently used for ransomeware to penetrate into sensitive information. It will be researched for the malicious methods to spread virus by using Tor and considered a countermeasure to prevent them. We present exit relay methodology for Tor security policy, simulate it, and get a probability to detect the ransomeware. And we compare it with TSS technology which is able to protect the attack via virtual server on exit relay.

Various types of media services are emerging due to the development of Internet and digital media production and distribution technologies. Various DRM technologies are being developed to prevent illegal copying of media contents and to protect the rights of content creators. There is a problem that the DRM provider and the content service provider must provide services in a mutually dependent manner through individual contracts. In this paper, we propose a cloud-based DRM market system which can be used only by content service providers when necessary for various DRM. The DRM market system is expected to show the effect of service activation for related small and medium sized companies by providing an interface that satisfies the requirements of DRM providers and contents service providers by using multi DRM technology.

As the technology of drone develops, the use of drone is increasing, In addition, the types of sensors that are inside of smart phones are becoming various and the accuracy is enhancing day by day. Various of researches are being progressed. Therefore, we need to control drone by using smart phone's sensors. In this paper, we propose the most suitable machine learning model that matches the gyro sensor data with drone's moving. First, we classified drone by it's moving of the gyro sensor value of 4 and 8 degree of freedom. After that, we made it to study machine learning. For the method of machine learning, we applied the One-Rule, Neural Network, Decision Tree, and Navie Bayesian. According to the result of experiment that we designated the value from gyro sensor as the attribute, we had the 97.3 percent of highest accuracy that came out from Naive Bayesian method using 2 attributes in 4 degree of freedom. On and the same, in 8 degree of freedom, Naive Bayesian method using 2 attributes showed the highest accuracy of 93.1 percent.

The purpose of this study was to analyze the characteristics of virtual manipulatives apps that can be used to teach students struggling to learn mathematics. To achieve this goal, ten general characteristics of 23 virtual manipulatives apps were evaluated. The instructional, interface, and interactive design features of apps were also evaluated on five-point scale ratings of 18 items. In addition, SPSS frequency analysis and the correlation between each feature was analyzed. Frequently presented instructional contents among 23 virtual manipulatives apps were geometry, arithmetic operation, number concept and measurement. The frequently presented level of instructional contents was lower grade elementary school and kindergarten age. The frequently presented instructional type was the simulation. Regarding the design features, instructional design was rated as the highest (mean = 3.7); interactive design (mean = 3.6) and interface design (mean = 3.3) were also rated higher than neural. In addition, as the learning strategy was appropriately presented, it was evaluated that there was less screen linkage and content error.

Even though there are many studies on emotion recognition using EEG, there is a few research on specific emotion recognition in detail. In this paper, we construct test videos and conduct congruent-incongruent test for analysis on fear of crime. We compared the differences of event-related potential of subjects before and after watching the video using the congruent-incongruent test and analyzed the fear that subject perceived. Our results demonstrate that subjects showed lower amplitudes for unexpected stimuli in the PZ, POZ, and OZ electrodes of the occipital lobe, which process visual stimuli. These results indicate that the perception of subject is slower for unexpected objects.

Machinima is a new medium of artistic expression that allows creators to produce faster and cheaper 3D animated works than ever before. However, the software owner controls all rights in the game. The principle of fair use allows for limited use of works without permission of the copyright owner for certain purposes. The application of the principle of fair use to any particular machinima will depend on the specific circumstances. In conclusion, in order to maintain the balance between the copyright owner and the user, the reasonable role of the court in Korea seems to be more important in interpreting the fair use clause.

Through Rene Girard's theory of triangle of the desire, this research investigates the mimetic nature of desire as shown in the main character of the movie The Servant. This paper analyzes the structural transformation of desire in the character, which is revealed by the process of reinterpretation via the medium change and convergence from Chunhyangjeon, a classic oral novel in Korea, to The Servant, a movie created by director Dae-woo Kim in 2010. The Servant is a meaningful research subject as the transformation of the inner desire of the character is accomplished by boldly designating Bangja, who is supposed to be a minor character, as the protagonist. In particular, Rene Girard's argument on the indirectness of desire in the theory of triangle of the desire helps understand the point where the character' inner desire, which naturally occurred in the existing narrative, transforms into the mimetic desire by an intermediary. This indirectness of the mimetic desire of the main character suggests a similarity with modern men's vanity which is offered by the capitalist era. Through this, the modern meaning of the mimetic aspect of desire as revealed by the transformation from the movie The Servant to Chunhyangjeon can be understood.