In recent years, there has been developed systems such as a surveillance system and access control using a face recognition function instead of a password or an RFID chip, thereby reducing the risk of falsification. Moreover, deep learning technology has been applied to real-time face recognition technology in video, so it makes possible the development of access control system that improves the accuracy of recognition and efficiency of management. In this paper, we propose a real-time access management system based on face recognition using ResNet. The system is based on web server, which make it possible to manage the access by recognizing the person of the image through the camera and access information stored in the database. It can be accessed by a user application to receive various information. The implemented system identifies a person in real time and allows access control by accurately distinguishing whether they are members or not, and the test results can recognize in 0.2 seconds. The accuracy of recognition rate is up to about 97% depending on the experiment environment. With this system, access can be managed quickly and effectively, even many people rush to it.

Prostate cancer is a high-risk with a high incidence and is a disease that occurs only in men. Accurate diagnosis of cancer is necessary as the incidence of cancer patients is increasing. Prostate cancer is also a disease that is difficult to predict progress, so it is necessary to predict in advance through prognosis. Therefore, in this paper, grade classification is attempted based on texture feature extraction. There are two main methods of classification: Uses One-way Analysis of Variance (ANOVA) to determine whether texture features are significant values, compares them with all texture features and then uses only one classification i.e. Benign versus. The second method consisted of more detailed classifications without using ANOVA for better analysis between different grades. Results of both these methods are compared and analyzed through the machine learning models such as Support Vector Machine and K-Nearest Neighbor. The accuracy of Benign versus Grade 4&5 using the second method with the best results was 90.0 percentage.

In this paper, we propose a loss function in CNN that introduces inter-class amplitudes to increase inter-class loss and reduce intra-class loss to increase of face recognition performance. This loss function increases the distance between the classes and decreases the distance in the class, thereby improving the performance of the face recognition finally. It is confirmed that the accuracy of face recognition for visible light image of proposed loss function is 99.62%, which is better than other loss functions. We also applied it to face recognition of visible and near-infrared complex images to obtain satisfactory results of 99.76%.

With the development of IT technology and smart devices, various applications utilizing image information are being developed. In order to provide an intuitive interface for pronunciation recognition, there is a growing need for research on pronunciation recognition using mouth feature values. In this paper, we propose a system to distinguish Korean vowel pronunciations by detecting feature points of lips region in images and applying Bayesian based learning model. The proposed system implements the recognition system based on Bayes' theorem, so that it is possible to improve the accuracy of speech recognition by accumulating input data regardless of whether it is speaker independent or dependent on small amount of learning data. Experimental results show that it is possible to effectively distinguish Korean vowels as a result of applying probability based Bayesian classification using only visual information such as mouth shape features.

LCD backlight boosting and the integration of boosting and dimming are proposed based on image analysis to maximize perceptual image qualities and to reduce display system power. Based on the histogram of the image data, methods for selecting an image suitable for boosting and for adjusting the optimum backlight brightness are proposed. A comprehensive combined optimization method of LCD backlight boosting, dimming and bypass based on image characteristics is also described. Perceptual image quality enhancement and power consumption are evaluated based on well known image databases. Average subjective image quality is improved by 24.8%, RMS contrast is improved more than 20%, and average power consumption is reduced by 15.94% compared to conventional uniform boosting.

To delve into the semantic gap problem of the automatic video summarization, we focused on an endogenous ERP responses at around 400ms and 600ms after the on-set of audio-visual stimulus. Our experiment included two factors: the topic exploration of experimental conditions (Topic Given vs. Topic Exploring) as a between-subject factor and the topic relevance of the shots (Topic-Relevant vs. Topic-Irrelevant) as a within-subject factor. For the Topic Given condition of 22 subjects, 6 short historical documentaries were shown with their video titles and written summaries, while in the Topic Exploring condition of 25 subjects, they were asked instead to explore topics of the same videos with no given information. EEG data were gathered while they were watching videos in real time. It was hypothesized that the cognitive activities to explore topics of videos while watching individual shots increase the amplitude of endogenous ERP at around 600 ms after the onset of topic relevant shots. The amplitude of endogenous ERP at around 400ms after the onset of topic-irrelevant shots was hypothesized to be lower in the Topic Given condition than that in the Topic Exploring condition. The repeated measure MANOVA test revealed that two hypotheses were acceptable.

In this paper, we discuss an optimization approach for time-synchronizations in networked simulators. This method is a sub-technology that is required to combine heterogeneous simulators into a single simulation. In previous time-synchronization studies, they had built a network system among networked simulators. The network system collects network packets and adds time-stamps to the networked packets based on the time that occurs in events of simulation objects in the individual simulators. Then, it sorts them in chronological order. Finally, the network system applies time-synchronization to each simulator participating in interworking sequentially. However, the previous approaches have a limitation in that other participating simulators should wait for while processing an event in a simulator in a time stamp order. In this paper, we attempt to solve the problem by optimizing time-synchronizations in networked simulation environments. In order to prove the practicality of our approach, we have conducted an experiment. Finally, we discuss the contributions of this paper.

The growth of domestic fashion industry market went sluggish affected by long-term slow growth and shrinking consumer sentiment since 2012, and the entire market has shown a slight growth since 2017. Yet only some conglomerates or global businesses experience this growth. Small and medium-sized fashion companies or rising fashion designers in South Korea, face real limitations and problems poor capital, lack of professional workforce, experience, information and educational opportunity as well as difficulty of acquiring distribution network, which lead to further polarization between conglomerates and small businesses. Thus, this study proposed mobile virtual viewer system-based collaborative application prototype capable of overcoming limitations and problems drawn by analyzing business environment of domestic brands launched by rising fashion designers. Especially, through applied template-based 3D virtual fashion design technology and performing the entire process in the virtual reality beyond spatial and temporal restraints, it is assumed that more effective and efficient outcomes can be obtained compared to the previous method.

The Internet of Things (IoT) envisions smart objects collecting and sharing data at a massive scale via the Internet. One challenging issue is how to disseminate data to relevant data consuming objects efficiently. In such a massive IoT network, Mission critical data dissemination imposes constraints on the message transfer delay between objects. Due to the low power and communication range of IoT objects, data is relayed over multi-hops before arriving at the destination. In this paper, we propose a quorum-based adaptive dissemination algorithm (QADA) for the critical data in the monitoring-based applications of massive IoTs. To design QADA, we first design a new stepped-triangular grid structures (sT-grid) that support data dissemination, then construct a triangular grid overlay in the fog layer on the lower IoT layer and propose the data dissemination algorithm of the publish/subscribe model that adaptively uses triangle grid (T-grid) and sT-grid quorums depending on the mission critical in the overlay constructed to disseminate the critical data, and evaluate its performance as an analytical model.

In this paper, biomimetic based physical ear model proposed for measuring the characteristics of a hybrid-acoustic sensor for fully implantable middle-ear hearing aid. The proposed physical ear model consists of the external ear, middle-ear, and cochlea. The physical ear model was implemented based on the anatomical structure and CT images of the human ear. To confirm the characteristics of the ear model, the vibrational characteristics of the stapes was measured after applying sound pressure to the tympanic membrane. The measured results were compared with the vibrational characteristics of the human temporal bone specified by ASTM F2504-05. Through the comparison results, the feasibility of the proposed ear model was confirmed. Then, after attaching the hybrid-acoustic sensor to the ear model, the output characteristics of the ECM and acceleration sensor were measured according to the sound pressure. The measured results were compared with previous studies using human temporal bone, and the usefulness of the proposed physical ear model was verified through the analysis results.

High-Level Architecture(HLA)/Run-Time Infrastructure(RTI) are standards for distributed simulation systems and offer a technology to interconnect them and form one single simulation system. In defense domain, M&S is the only way to prove effectiveness of weapon systems except for Live Fire Testing (LFT). This paper focuses on guided missile simulations in weapon systems for engagement analyses and proposes the integrated flying vehicle model that is based on HLA/RTI. There are a lot of missiles in real world; therefore, we should develop each missile models in M&S in order to apply battlefield scenarios. To deal with the difficulties, in this paper, firstly, I classify these missiles into three models: ballastic, cruise, and surface-to-air missile models, and then I design each missile model and integrates them into a single model. This paper also offers a case study with my integrated flying vehicle model. At the conclusion, this paper presents contributions of this paper.

Classroom response systems (CRS) have been proven to have positive educational effects on student engagement and participation by allowing immediate feedback to both students and instructors. We explore the use of a chatbot and slide widget-based CRS to overcome some of the challenges of existing mobile-based CRSs while retaining their advantages. Our system uses widely available instant messaging services and operates web-based slide widgets that can be seamlessly integrated into instructors' slides to visualize student feedback in various formats. The student survey results indicate that our system is as effective as conventional CRSs in promoting student engagement and participation.

The purpose of this study was to investigate the effect of integrated teaching and learning method using augmented reality for effective promotion of child - friendly attitude and environmental preservation attitude and explored its applicability. For this purpose, based on the augmented reality fairy tale, we designed an experience - oriented integrated teaching and learning method such as reading book, story - telling, drawing, environmental conservation practice activity. The experimental group was divided into two groups: augmented reality reading fairy tales (A) and children's book reading fairy tales (B). First, interest, immersion, and empathy were higher in the application environment of integrated learning teaching method based on Augmented Reality. Second, there was no difference between the two groups in content understanding. Third, in terms of expressiveness, it was verified that various expressions were expressed in the applying environment of the integrated teaching - learning method based on augmented reality through drawing activities. Fourth, in practice activities, more students were practicing in the augmented reality - based integrated teaching - learning method applied environment, and the number of practice activities of individual students was also confirmed. This study suggests that the application of the integrated teaching and learning method can enhance the effect of education when using the smart teaching media using the augmented reality in early childhood education.

The increased use of smartphones has made it easier to plan travel. Especially for people travelling in Europe, it is common to move between cities by train, and reserving passes with a mobile app offers many advantages. The Czech Republic, which is a familiar destination for Koreans, is called the "heart of Europe" and it is in central Europe, so it is inevitable to use the railway when travelling. This study has been compared with the structural characteristics of the railway reservation service operated by the Czech and Korean railways. In general, when evaluating the usability of an app, we often use a method that allows a group of users or experts to spot problems. However, this study suggests an analytical method to obtain more reliable and objective results. Also, the analysis of the structural characteristics has an advantage that the problem can be predicted at the prototype stage. This, of course, comes with time and financial benefits. The purpose of this research is to contribute to the development of applications that are more convenient to use and efficiency of development.

Contemporary narrative and documentary share across boundaries between the 'actuality' and the 'creative treatment.' The documentary has blended modes of representation from various genre to reflect the world changing. The narrative movies also has applied the historicality of 'evidence' and 'documents' from documentary to obtain the new form of realism. Boyhood shows a differentiated realism to retain both the narrative structure and the documentary temporality, containing 12 years of timeline with the limited artificial space time. Boyhood also takes the analogical concept of 'the dramatization of the actual materials' from the early documentary films.