This paper presents three potential risks in an environment that simultaneously performs the garbage collection and wear leveling in NAND flash memory. These risks may not only disturb the lifespan improvement of NAND flash memory, but also impose an additional overhead of page migrations. In this paper, we analyze the interference of garbage collection and wear leveling and we also provide two theoretical considerations for lifespan prolongation of NAND flash memory. To prove two solutions of three risks, we construct a simulation, based on DiskSim 4.0 and confirm realistic impacts of three risks in NAND flash memory. In experimental results, we found negative impacts of three risks and confirmed the necessity for a coordinator module between garbage collection and wear leveling for reducing the overhead and prolonging the lifespan of NAND flash memory.

In this paper, we propose a method to recognize the moving direction in the indoor environment by using the sensing system equipped with passive infrared (PIR) sensors and a deep learning algorithm. A PIR sensor generates a signal that can be distinguished according to the direction of movement of the user. A sensing system with four PIR sensors deployed by $45^{\circ}$ increments is developed and installed in the ceiling of the room. The PIR sensor signals from 6 users with 10-time experiments for 8 directions were collected. We extracted the raw data sets and performed experiments varying the number of sensors fed into the deep learning algorithm. The proposed sensing system using deep learning algorithm can recognize the users' moving direction by 99.2 %. In addition, with only one PIR senor, the recognition accuracy reaches 98.4%.

This paper proposes a new method using multi-layer overlapped windows to improve the performance of YOLO network which is vulnerable to detect small dense objects. In particular, the proposed method uses the YOLO Network based on the multi-layer overlapped windows to track small dense vehicles that approach from long distances. The method improves the detection performance for location and size of small vehicles. It allows crossing area of two multi-layer overlapped windows to track moving vehicles from a long distance to a short distance. And the YOLO network is optimized so that GPU computation time due to multi-layer overlapped windows should be reduced. The superiority of the proposed algorithm has been proved through various experiments using captured images from road surveillance cameras.

In this study, we introduce a model that satisfies energy efficiency and economical efficiency by introducing and demonstrating cogeneration generators in industrial complexes using various actual data collected at the site. The proposed model is composed of three scenarios, ie, full - time operation, scenario operated according to demand, and a fusion type. In this study, the power generation profit and surplus thermal energy are measured according to the operation of the generator, and the thermal energy is traded according to the demand of the customer to calculate the profit and loss including the heat and evaluate the economic efficiency. As a result of the study, it is relatively profitable to reduce the generation of the generator under the condition that the electricity rate is low and the gas rate is high, while the basic charge is not increased. On the contrary, if the electricity rate is high and the gas rate is low, The more you start up, the more profit you can see. These results show that even a cogeneration power plant with a low economic efficiency due to a low "spark spread" has sufficient economic value if it can sell more than a certain amount of heat energy from a nearby customer and adjust the applied power through peak management.

In this paper, we propose a application of conditional generative adversarial network (cGAN) for generation of contrast enhanced computed tomography (CT) image. Two types of CT data which were the enhanced and non-enhanced were used and applied by the histogram equalization for adjusting image intensities. In order to validate the generation of contrast enhanced CT data, the structural similarity index measurement (SSIM) was performed. Prepared generated contrast CT data were analyzed the statistical analysis using paired sample t-test. In order to apply the optimized algorithm for the lymph node cancer, they were calculated by short to long axis ratio (S/L) method. In the case of the model trained with CT data and their histogram equalized SSIM were $0.905{\pm}0.048$ and $0.908{\pm}0.047$. The tumor S/L of generated contrast enhanced CT data were validated similar to the ground truth when they were compared to scanned contrast enhanced CT data. It is expected that advantages of Generated contrast enhanced CT data based on deep learning are a cost-effective and less radiation exposure as well as further anatomical information with non-enhanced CT data.

The purpose of this study is to analyze the characteristics and meanings of Instagram hashtags related to the exhibitions as a online communication platform of museums. At the same time, it focuses on efficiency of hashtags as a reference framework of inferring viewing experiences. We collect and visualize Instagram hashtags of exhibitions held in Korea for the past two years including 'Paper Present (2017)', 'YOUTH (2017)', 'Monet, Draw Light Exhibition (2018)', 'Van Gogh Inside (2016)', 'Drawn by the Wind: Shin yun-bok & Jeong Seon'. To sum up, significant data related to viewing experiences are not derived, and hashtags as a reference framework of inferring viewing experiences are turned out to be inefficient. Meanwhile, we conclude that potential for distributing information about the exhibitions is inherent in hashtags. In terms of informational characteristics, we notice that the influence of hashtags related to regional information is presented more than the response toward the viewing experiences. This result shows that Instagram users in the exhibitions are worthy of place making rather than viewing experiences.

We consider the D2D sum utility maximization in the cellular system. D2D links reuse the uplink resource of cellular system. This reuse may cause severe interference to cellular users. To protect the cellular users, interference limit from the D2D links is required. In this setting, D2D sum utility maximization problem is investigated. Each D2D link has limited transmit power budget. Because optimum solution may require global information between links and computational complexity, we propose the distributed algorithm which only require the local information from each D2D link and simple broadcasting. Simulation results are provided to verify the performance of the proposed algorithm.

Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.

The advent of Internet of Things (IoT) makes common nowadays computing environments involving programming not a single computer but several heterogeneous distributed computers together. Developing programs separately, one for each computer, increases programmer burden and testing all the programs become more complex. To address the challenge, this paper proposes an RPC-based unified programming language, UniPy, for development of MGC (eMbedded, Gateway, and Cloud) applications in IoT systems configured with popular computers such as Arduino, Raspberry Pi, and Web-based DB server. UniPy offers programmers a view of classes as locations and a very simple form of remote procedure call mechanism. Our UniPy compiler automatically splits a UniPy program into small pieces of the program at different locations supporting the necessary RPC mechanism. An advantage of UniPy programs is to permit programmers to write local codes the same as for a single computer requiring no extra knowledge due to having unified programming models, which is very different from the existing research works such as Fabryq and Ravel. Also, the structure of UniPy programs allows programmers to test them by directly executing them before splitting, which is a feature that has never been emphasized yet.

In this paper, we propose a real-time drone-based violent protest detection system. Our proposed system uses drones to detect scenes of violent protest in real-time. The important problem is that the victims and violent actions have to be manually searched in videos when the evidence has been collected. Firstly, we focused to solve the limitations of existing collecting evidence devices by using drone to collect evidence live and upload in AWS(Amazon Web Service)[1]. Secondly, we built a Deep Learning based violence detection model from the videos using Yolov3 Feature Pyramid Network for human activity recognition, in order to detect three types of violent action. The built model classifies people with possession of gun, swinging pipe, and violent activity with the accuracy of 92, 91 and 80.5% respectively. This system is expected to significantly save time and human resource of the existing collecting evidence.

Crowdsourcing is growing its interests in designing where various designers work independently to a given design task. Recent researchers discovered that collaboration by sharing designs among designers helps to produce high-quality designs. However, design task may still be hard even with that collaboration in case the requirements are not well-defined. Most customers sometimes do not know what they really want and do not know how to clearly define the requirements. Consequently, the lack of requirements creates issues on designers, such as spending much time and effort on collecting requirements alone or from the customers. The designers even end up missing important necessities to complete their tasks. To address this issue, we proposed a collaborative requirements elicitation method that supports designers who are working on the same task. We developed CREFD (Collaborative Requirements Elicitation For Designers and Developers) tool to enable designers collaboratively provide requirements, identify dependencies, add annotations and votes to the provided requirements. We performed the hypothetical and empirical evaluations to test and compare the proposed method with one of the existing elicitation methods, the results show that the proposed method helps in collecting accepted and well-organized requirements better than individual requirements elicitation.

In this paper, we propose a technique to analyze similarity between SQL queries and to assist integrating similar tables. First, the table information was extracted from the SQL queries through the query structure analyzer, and the similarity between the tables was measured using the Jacquard index technique. Then, similar table clusters are generated through hierarchical cluster analysis method and the co-occurence probability of the table used in the query is calculated. The possibility of integrating similar tables is classified by using the possibility of co-occurence of similarity table and table, and classifying them into an integrable cluster, a cluster requiring expert review, and a cluster with low integration possibility. This technique analyzes the SQL query in practice and analyse the possibility of table integration independent of the existing business, so that the existing schema can be effectively reconstructed without interruption of work or additional cost.

In this study, I analyzed the measurement data of the early 20s male who are emphasizing the importance of good clothes in the fashion of body-contact clothes. Through this, I tried to provide basic data necessary for making clothing for early 20s male. Using data from Size Korea's 7th Human Body Survey, 588 people aged 20-25 years were analyzed and classified into four types. Type 1 have a thick and short body, narrow ankle and calf, thin legs. And the hip is not sagged, and height is a little short. So I named it 'short & thick body with bird legs'. Type 2 have a broad shoulder, slim and long body, and no sagging shoulders. So I named it 'slim inverted triangular figure'. Type 3 have a small height, thin and short body, and a thick ankle and calf. So I named it 'short & thin body with thick legs'. Type 4 have a tall height, narrow shoulder, and sagging hip and shoulders. So I named it 'Long triangle'. In order to improve fit of body-contact clothes reflecting the trend of men's wear in recent years, it is necessary to develop clothing prototypes by body type. 20s have the most ideal body shape after completion of growth, but differences in the length, thickness, and thickness of the trunk. This is reflected in the apparel pattern system, and it can be expected to increase consumers' satisfaction if they are used to make excellent ready-to-wear patterns.

Bicycle fitting used to depend on empirical adherence of bicycle Peter and intuitive judgment by hand, but recent developments in industry and the Fourth Industrial Revolution have continuously developed other related tools that can be applied to bicycle fitting. Depending on these circumstances, bicycle fitting technology is also developing, and due to the difficulty of the technicians, there is a limit to popularizing. The Bicycle Integrated Fitting System has the need for this study to make these problems easy for anyone to operate by the system of manual. The purpose of this study is to examine the methods of physical sizing among the various stages of developing these systems. Accurate physical measurements can improve the efficiency of bicycle riding and minimize the injury of bicycle risers issued by incorrect fittings. Thus, in this study, physical measurement methods for bicycle fitting were derived by body region and applied to the post-measurement fitting as well as the location and method of measurement. It has prepared a basis for establishing a core database for physical measurement of development of integrated bicycle fitting system. Research was conducted to enhance understanding and utilization of users after system development and results were derived for the purpose of the study. Research was conducted to establish a database for the development of a bicycle integrated fitting system, and future research on bicycle fitting methods, application of the system, and hardware development should be carried out.

The purpose of this study was to analyze the direct measurement data of 20-25 years male university students of 7th Size Korea data and to characterize and to type the body shape of lower body. It was to provide basic data for male university students' pants pattern production. The lower body part consisted of the 'horizontal factor' of the lower body composed of circumference, thickness, width, and 'vertical factor' of the lower body composed of the length and height. This was consistent with the analysis of the body shape factor of the lower half of male adolescents. The lower body shape was classified into four types. Type 1 was thick and relatively long in the lower body and was named 'thick long leg'. Type 2 was named 'short bird legs' because the lower body was thin and relatively short. Type 3 was relatively thin and long, so the lower body was named 'long crane leg'. In Type 4, the lower body was relatively thick and short, which means 'short pillar leg'. In the case of 20-25 year-old male university students, they have different body shapes depending on the girth and length of the lower half of their body as they have reached adulthood. Therefore, it would be necessary to provide a sales system that allows the repair of the length of the pants to be facilitated, and the length of the pants to be repaired when the pants are selected according to the circumference. Future studies will need to classify the body shape according to angle and flatness.

This study aimed to analyze the keyword related to Health Disparity in Korea through the method of keyword network analysis and to establish a basic database for suggesting ideas for prospective studies in physical education. To achieve the goal, this study crawled co-occured keyword with 'health' and 'disparity' from news casted in 20 different channels. The duration of the news was 3 months, from September 11th, 2018 to December 11th. The results are as follows. First, among the news during recent 3 months, there were 1,383 keyword related to health disparity and this study selected 173 keyword which had co-occured over 3 times. Second, the inclusiveness of the network was 97.674% and the density was .038. Third, analyzing news related to health disparity, 'mortality' was the most co-occured keyword and 'disparity', 'reinforcement', 'the most', 'health', '6 times', 'Seoul', 'half', 'medicine', and 'local' were shown similarly. And common keyword in 4 centrality were 13 keyword. Lastly, by analyzing eigenvector centrality, significantly different result has shown. 'Disparity' was the most co-occured keyword. Based on this result, this study showed the necessity for reinforcing the public physical education in public education system in Korea. In order to achieve it, the field of physical education must look beyond present elite-focused physical education to public physical activity.

In this paper, we present a prototype system for controlling IoT home appliances via voice-based commands. A voice command has been widely deployed as one of unobtrusive user interfaces for applications in a variety of IoT domains. However, interoperability between diverse IoT systems is limited by several dominant companies providing voice assistants like Amazon Alexa or Google Now due to their proprietary systems. A global IoT standard, oneM2M has been proposed to mitigate the lack of interoperability between IoT systems. In this paper, we deployed oneM2M-based platforms for a voice record device like a wrist band and LED control device like a home appliance. We developed all the components for recording voices and controlling IoT devices, and demonstrate the feasibility of our proposed method based on oneM2M platforms and Google STT (Speech-to-Text) API for controlling home appliances by showing a user scenario for turning the LED device on and off via voice commands.

The collection and manipulation of Internet of Things (IoT) data is increasing at a fast pace and its importance is recognized in every sector of our society. For efficient utilization of IoT data, the vast and varied IoT data needs to be reliable and meaningful. In this paper, we propose an IoT framework to realize this need. The IoT framework is based on a four layer IoT architecture onto which context aware computing technology is applied. If the collected IoT data is unreliable it cannot be used for its intended purpose and the whole service using the data must be abandoned. In this paper, we include techniques to remove uncertainty in the early stage of IoT data capture and collection resulting in reliable data. Since the data coming out of the various IoT devices have different formats, it is important to convert them into a standard format before further processing, We propose the RDF format to be the standard format for all IoT data. In addition, it is not feasible to process all captured Iot data from the sensor devices. In order to decide which data to process and understand, we propose to use contexts and reasoning based on these contexts. For reasoning, we propose to use standard AI and statistical techniques. We also propose an experiment environment that can be used to develop an IoT application to realize the IoT framework.

It is a descriptive study for the relationship between appearance management behaviors and mental health of some female college students. We analyzes 433 self-administered questionnaires from March to June 2017 for female students who enrolled in three-year colleges in Seoul and Gyeonggi province, South Korea. The conclusion is as follows. We used IBM SPSS Statistics 22.0(SPSS Inc., Chicago, IL, USA) for the analysis by person's characteristics, t-test and one way ANOVA, multiple regression analyses. The second-year grade shows higher points than the first-year grade in appearance management behaviors and mental health level(p<0.001, p<0.05). In addition, when students has the higher level of the household as the humanities students, they have higher level of mental health level(p<0.001). The most influential factors affecting the mental health level of female college students are domestic economic level and cosmetic management behavioral factors. The level of mental health was higher in the middle and upper group of the domestic economic level. When they do more cosmetic management behavior, they have lower the mental health level. In conclusion, it is deemed necessary for students to attend intensive and sufficient counseling with an academic advisor. The continuous attention through school counseling management services depending on grade, domestic economy level, and cosmetic management behavior is necessary in order to enhance the level of mental health for female students. In addition to that, the college needs to develop individual customized psychology counseling and educational programs through U-mental healthcare service in order to lessen the great pressure of sensitive information and provide mental consultation. The college needs to consider students' characteristics and needs from the results of this study. It is considered that a smart mental healthcare program will be needed to identify mental health of the individual through the systematic approach.

This study is a descriptive research of paramedic students who could be exposed to blood and body fluids during the clinical practicum to analyze the risk factors. From June 1 to June 30, 2018, 172 paramedic students who attended the University in Jeolla-do region were analyzed. The collected data were analyzed by using the SPSS WIN 21.0 program. The general characteristics of subjects, the exposure level of blood and body fluids, and etc were obtained for frequency and percentage analysis. The study found that 72.7 percent of students had experience to blood or body fluids exposure during the clinical practicum. Except for any needle injury, 70.4 percent of student were exposed to blood or body fluids. 28.8 percent of them which was the highest percentage of injection injury were exposed during the venous blood draw. 36.5 percent of exposure were related to wound dressings which was the highest percentage related to clinical procedures. 71.2 percent of students mentioned that they did not report this exposure because 68.5 percent students thought that it has no danger. According to the survey on hepatitis B, 50.6% of students had antibodies, but 31.8 percent of students did not confirm that the antibodies were formed. Even though paramedic students do practical training in a hazardous environment with repeated exposure to blood and body fluids due to the nature of job characteristics, the systemic infection control education program is insufficient. In order to prevent exposure and to protect paramedic students who do practical training with patients, it is necessary to make more systematic and active efforts in the continuous monitoring and the preventive education.

Today, in the information society, since the government administration of all countries places importance on clarity and efficiency, the authority concentration of the administration is inevitable. Therefore, the Parliament, which is a legislative body, is at a time when the policy control function to check and monitor it is becoming more important. In particular, due to the emergence of parliamentary democracy, in the reality that the people must elect representatives and represent their own opinions, the parliamentary inspection system is very valuable in that it satisfies the right of the people to know and ultimately enables the people to democratically control the administration. The role of the Parliament moves from the inherent legislative function to the information collection and disclosure of government administration, discussion and resolution of political issues, and observation and supervision of the administration. And it can be seen as the global trend. As a result of this trend, status and role of the National Assembly is being strengthened from the legislative body to the control agency of government administration. Thus, the most substantive authority of Article 61 of the Constitution can be deemed the parliamentary inspection system. The parliamentary inspection system is a system that let exercise the legislation, budget, and authority to control of state administration by identify the challenges and policy implementation of each country's institutions through the audit of the executive administration's overall government administration performance outside the National Assembly. However, due to the amendment of Constitution in 1988, the parliamentary inspection right and investigation of state administration right had reinstated and the parliamentary inspection system, which is being implemented annually, is the 31st year of the year in 2019. However, the general evaluation of the public is negative and insufficient time for inspections, lack of sanctions on nonattendance witnesses, excessive data submission, and refusal to submit materials by the administration were pointed out as the problem. Therefore, in this paper, the researcher tries to point out the overall problems of the parliamentary inspection system and to summarize the effective improvement plans.

This study is about online purchases of foods that have been reluctant to deal with distribution processes and reliability issues. We find out that attributes of the online food market affects behavior intention and whether it differs according to consumption tendency. A survey was conducted on consumers who had ever purchased food online for hypothesis testing. Reliability and feasibility were reviewed for the collected data and the hypothesis was verified through structural equation model analysis. While product diversity, product information and customer service factors of the online food market significantly affect behavior intention, price is not. We identified differences in the impact of behavior intention on consumption tendencies. For the Gaseongbi group, only the product information factors have significant effect on behavior, and for the Gasimbi group, the price and customer service factors have a significant effect on behavior intention. The findings provide theoretical and practical implications for marketers to study various marketing method based on consumer tendencies.

The government has proposed a development model for universities to strengthen the capacity of the College of Humanities as part of the university restructuring policy in line with the trend of the times, and encouraged each university to voluntarily induce the establishment of the humanities development plan through financial support under their own individual conditions. With the decline in the school-age population due to the declining fertility rate, the rapid change in the industrial structure has highlighted the decline in the employment rate of the students of the humanities. Therefore, the government is implementing university grading based on the results of the university structural reform evaluation, and pressing low-grade universities through reduction of capacity and reduction of support. In the course of this change, universities have designated the College of Humanities as the primary target of integration with other majors or and its disintegration. This study examines the direction of the government's attempt to change the humanities in the era of the Fourth Industrial Revolution, and suggests a precedent example during the reform of the humanities college. If the humanities college is integrated with practical studies such as management, design, IT, CT, and engineering, the strengths of the humanities can be highlighted. However, the results of this study suggest that many variables such as consideration of students' aptitudes and interests in the integration process of majors, autonomy in major selection, understanding between departments integrated, and demand for a single major before integration or disintegration should be considered. In addition, an example of a local private university shows that the hasty attempt to integrate or disintegrate the humanities can rather lead to various educational harms.