In the HDTV video codec, conventional the padding method of DEPA(DTV essential padding area) region is aimed at minimizing the redundant information to be transmitted. This article propose a method to transmit additional data by using DEPA region. The proposed method is effective for the channel and storage because it can reduce the amount of bits while preventing deterioration of image quality by inserting binary gray image blocks into the DEPA region. Additionally this algorithm can be used in various fields because it conforms to the standards of MPEG-2, ATSC, and DVB encoders.

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

Many parallel lines may be shown in our real life and they are useful for analyzing structure of objects or buildings. In this paper, a vision based technique for estimating three-dimensional direction of parallel lines is suggested, which uses a calibrated camera and is applicable to an image being captured from the camera. Correctness of the technique is theoretically described and discussed in this paper. The technique is well applicable to measurement of orientation of a pallet in a warehouse, because a pair of parallel lines is well detected in the front plane of the pallet. Thereby the technique enables a forklift with a well-calibrated camera to engage the pallet automatically. Such a forklift in a warehouse can engage a pallet on a storing rack as well as one on the ground. Usefulness of the suggested technique for other applications is also discussed. We conducted an experiment of measuring a real commercial pallet with various orientation and distance and found for the technique to work correctly and accurately.

Dynamic adaptation method is an effective technique to enhance the usability by personalizing the soft keyboard layout using the user's key input information. In this paper, we propose a dynamic adaptation method of a keyboard by automatically extracting typos from key input information and using adjacent-typo information classified through the relationship between typos. This technique does not limit a range of adaptation to the inside of the key but extends the range to the neighbor key so that the adaptation effect can be achieved in a wide range at a high speed, thereby the proposed method improves the usability of the keyboard with a small number of inputs. The proposed method showed 25% increase in usability compared to the existing method through experiment and it was confirmed that usability improves up to 33% when used with the existing method.

The NDT using ultrasonic is largely divided into A-Scan and C-Scan methods. Since A-Scan method is subject to subjective judgement by trained personnel, C-Scan method has been introduced, which presents the weld area in two dimensions by placing the transducers two dimensionally used in the A-Scan method. Therefore, it is necessary to develop equipment that can provide weld quality without the help of a welding expert and the presentation of effective C-Scan images. Thus, in this paper, the algorithms that express a low resolution 2-dimensional gray image formed by C-Scan method as a high-resolution color C-Scan image and automatically determine the weld quality from the generated C-Scan color image. The high resolution color C-Scan images proposed in this paper allow the exact shape of the weld point to be expressed, and an objective algorithm to use this image to automatically determine weld quality.

In this paper, a new type of color coordinate conversion is proposed as modified CIEXYZ from RGB to compress the color gamut. The proposed segmentation includes principal component analysis for the optimal projection of a feature vector into a one-dimensional feature. The final step adopted for lip segmentation is Otsu's threshold for a two-class problem. The performance of the proposed method was better than that of conventional methods, especially for the chromatic feature.

PBS(Pairwise Broadcast Synchronization) is a well-known synchronization scheme for WSN(Wireless Sensor Networks). As PBS needs the set of node-pairs for network-wide synchronization by over-hearing, GPA(Group-Wise Pair Selection Algorithm) was also proposed after PBS. However, GPA is complex and requires too many message transmissions, leading to much power consumption. Besides, GPA is not appropriate to topology change or mobile wireless sensor networks. So, we propose a new and energy-efficient pair-node selection algorithm for PBS. The proposed scheme's performance has been evaluated and compared with GPA by simulation. The results are shown to be better than GPA.

Online education, commonly referred to as distance education, has developed rapidly. However, it is questionable whether such distance education has been applied to various educational fields and has achieved satisfactory results in terms of learning effect. One of the reasons for not maximizing the benefits of distance education is non-dynamicity in the production and application of educational content. Educational contents production is made up of collaborative work between the instructor who is the contents expert and the developer who is the production expert. For this reason, existing researches have also concentrated on the improvement of each educational effect. In this paper, we propose to replace a production expert from a developer to an instructor. At this time, the important point is that the educational contents produced by the instructor, who is a development non-expert, should still be able to be maintained with high-quality contents utilizing the characteristics of the web. For this purpose, the production system was developed based on open source to maintain the quality similar to the educational contents developed by the production expert. This will increase the effectiveness of education by applying the developed Smart-Blended Learning System to various educational sites.

Graphical user interface(GUI) has a very important role to interact with software users. However, designing and coding of GUI are tedious and pain taking processes. In many studies, the researchers are trying to convert GUI elements or widgets to code or describe formally their structures by help of domain knowledge of stochastic methods. In this paper, we propose the GUI elements detection approach based on object detection strategy using deep neural networks(DNN). Object detection with DNN is the approach that integrates localization and classification techniques. From the experimental result, if we selected the appropriate object detection model, the results can be used for automatic code generation from the sketch or capture images. The successful GUI elements detection can describe the objects as hierarchical structures of elements and transform their information to appropriate code by object description translator that will be studied at future.

A common treatment for tinnitus rehabilitation is to use a device called a sound generator to continuously supplying the sound stimuli. The devices usually provides a sound called white noise, or pink noise, which are common in nature. In this paper, we developed a mobile system for tinnitus diagnostics and therapy using Android mobile applications. The first step for tinnitus diagnostics is detecting an exact tinnitus frequency of the patients, therefore we provide a bark scale tinnitus detection algorithm for fast and accurate diagnostics. Also, the system can provide various stimuli sounds including white noise, pink noise, brown noise, nature sounds, and binaural beats. Also we provides the therapeutic functions through questionnaires to solve existing problems of the patients.

An AGV(Automated Guided Vehicle) where is running on production automated system is related efficiency of production system similarly. On previous study proposed a path collision avoidance algorithms using shortest path of AGV. Running time about loading and unloading with shortest path of AGV is important factor to decide the production system efficiency. In this paper, we propose a method of shortest path and shortest time. Also propose the decision making method of collision avoidance position for setup a shortest runway for next command. To do verify the proposed method consist a simulation for AGV. Finally, we compare and analyse the proposed system between the existing system and show that our system can effectively the performance.

Recently, alleys, villages and traditional market spaces have been recreated as complex cultural spaces due to urban renewal or village community policies. However, previous studies only refer to buildings such as museums and libraries in dealing with complex cultural spaces. The purpose of this study is to suggest the recreated complex cultural space as a natural convergence type and analyze its characteristics. Therefore, this study aims to reestablish the concept and type of the newly created complex cultural space. For this study, Busan Bosu-dong Bookstores Alley, Daegu Kim Gwangseok-street, Andong Traditional Market and Andong Shin-sedong Mural Village were selected as research examples. As a result of the study, the natural convergence space reflects the locality of the contents constituting the space, and the various values are convergenced. And this type of space is being reborn as an advanced case of urban regeneration and serves as a representative tourist destination in the region. As a next study of this study, we proposed social studies such as quantitative research and qualitative research.

Voice Command systems are important means of ensuring accessibility to digital devices for use in situations where both hands are not free or for people with disabilities. Interests in services using speech recognition technology have been increasing. In this study, we developed a mobile writing application using voice recognition and voice command technology which helps people create and edit documents easily. This application is characterized by the minimization of the touch on the screen and the writing of memo by voice. We have systematically designed a mode to distinguish voice writing and voice command so that the writing and execution system can be used simultaneously in one voice interface. It provides a shortcut function that can control the cursor by voice, which makes document editing as convenient as possible. This allows people to conveniently access writing applications by voice under both physical and environmental constraints.

With the availability of real-time educational data collection and analysis techniques, the education paradigm is shifting from educator-centric to data-driven lectures. However, most offline and online education frameworks collect students' feedback from question-answering data that can summarize their understanding but requires instructor's attention when students need additional help during lectures. This paper proposes a content restructure recommendation framework based on collected student feedback. We list the types of student feedback and implement a web-based framework that collects both implicit and explicit feedback for content restructuring. With a case study of four-week lectures with 50 students, we analyze the pattern of student feedback and quantitatively validate the effect of the proposed content restructuring measured by the level of student engagement.