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As the security threat and crime rate have been increased all over the globe, the video surveillance system using closed-circuit television (CCTV) has become an essential tool for many security-related applications and is widely used in many areas as a monitoring system. However, most of the data collected by the video surveillance system is used as evidence of objective data after crime and disaster have occurred. And, often time, video surveillance systems tend to be used in a passive manner due to the high cost and human resources. The video surveillance system should actively respond to detect crime and accidents in advance through real-time monitoring and immediately transmit data in case of an accident. This study proposes developing an intelligent video surveillance system that can actively monitor in real-time without human input. In solving the problems of the existing video surveillance system, deep learning technology will be carried through the data processing model design to visualize data for crime detection after building an artificial intelligence server and video surveillance camera. In addition, this design proposes an intelligent surveillance system to quickly and effectively detect crimes by sending a video image and notification message to the web through real-time processing.

An amendment to this paper has been published and can be accessed via the original article.

Health information systems use technologies in health care to improve the overall effectiveness of patient care and become important part in health care services. Among other diseases, pressure ulcers, a skin disease arise from prolonged exposure to high pressure points, is required to check patient’s body state and an electronic monitoring system enables to support constant body check with sharing accurate data with professionals. Although technological perspectives have advanced for better prevention of pressure ulcer, only few studies have reported experimental results and clinical responses on the preventive methods in terms of its effectiveness and comfort, and most preventive systems for pressure ulcer risk do not fulfill basic requirements such as sufficient reliability, unobtrusiveness, long-term usage and easy monitoring at various types of equipment. The purpose of this study is to examine a monitoring sensor-based eHealth image system to support pressure ulcer treatment and identify the effectiveness of the system presenting the system architecture. The result of this study would provide support and insight of using the eHealth monitoring system to professionals who need to manage and care of patients.

Smart devices such as smart phone play an important role in networked environments as connecting to other network devices and Internet Things. Smart phone combines the features of cell phone and a personal computer operating system. And it has become one of vital elements for modern people and society. However, smartphone has drawbacks like spam and security. Globally, people are exposed to spam call that they receive promotion calls from twice to dozens of times a day, spam call and voice phishing due to hacking and personal information leak in the internet environment. This phenomenon can cause personal stress, anxiety due to phone bank fraud, waste of time for receiving spam call, disturbance during work, criminal and the other serious social problems. In the present study, Humming Call system has been studied and developed to provide the measurement for evaluation and activation of service to prevent spam call in advance as a solution for the aforementioned problem. Hamming call is a service which receives information to help call through differentiation from existing service related to anti-spam system from DB (Internal DB) and Server. Then it provides the information for incoming call and outgoing call. To measure the actual performance by utilizing the system of this present study, DB has used CUBRID DBMS for 6 months and data stored in DB have been extracted through SQL Statement. The results indicate that this system prevents such problem for over 30%. If main function among various functions of this system is specialized and developed focusing on management of spam call from phone number, the system would perform more effectively.

Lipid-based carriers, including liposomes and emulsions, have been studied as antigen delivery systems to improve humoral and cellular immune responses. Lipid-based delivery systems have been tailored based on the physicochemical properties of antigens and administration routes. Non-covalent encapsulation or chemical conjugation of antigens onto the surface of nanocarriers has been reported to load high amounts of antigen, protect antigens from degradation, and enhance cellular uptake by immune cells. Moreover, active targeting to antigen-presenting cells can be achieved through surface modification of lipid-based nanostructures. Antigens, which include proteins, peptides and nucleic acids, have been delivered by appropriate lipid-based delivery systems, and antigen-loaded lipid nanoparticles have been shown to cause greater immune responses compared with naked antigens. For in vivo applications, both invasive and non-invasive routes have been adopted for vaccination with antigen-loaded lipid nanocarriers. In this review, we address recent progress, current status, and clinical applications of lipid-based antigen delivery systems.

Background For understanding and evaluating a more realistic and accurate assessment of ecosystem carbon balance related with environmental change or difference, it is necessary to analyze the various interrelationships between soil respiration and environmental factors. However, the soil temperature is mainly used for gap filling and estimation of soil respiration (Rs) under environmental change. Under the fact that changes in precipitation patterns due to climate change are expected, the effects of soil moisture content (SMC) on soil respiration have not been well studied relative to soil temperature. In this study, we attempt to analyze relationship between precipitation and soil respiration in temperate deciduous broad-leaved forest for 2 years in Gwangneung. Results The average soil temperature (Ts) measured at a depth of 5 cm during the full study period was 12.0 °C. The minimum value for monthly Ts was − 0.4 °C in February 2015 and 2.0 °C in January 2016. The maximum monthly Ts was 23.6 °C in August in both years. In 2015, annual precipitation was 823.4 mm and it was 1003.8 mm in 2016. The amount of precipitation increased by 21.9% in 2016 compared to 2015, but in 2015, it rained for 8 days more than in 2016. In 2015, the pattern of low precipitation was continuously shown, and there was a long dry period as well as a period of concentrated precipitation in 2016. 473.7 mm of precipitation, which accounted for about 51.8% of the precipitation during study period, was concentrated during summer (June to August) in 2016. The maximum values of daily Rs in both years were observed on the day when precipitation of 20 mm or more. From this, the maximum Rs value in 2015 was 784.3 mg CO2 m−2 h−1 in July when 26.8 mm of daily precipitation was measured. The maximum was 913.6 mg CO2 m−2 h−1 in August in 2016, when 23.8 mm of daily precipitation was measured. Rs on a rainy day was 1.5~1.6 times higher than it without precipitation. Consequently, the annual Rs in 2016 was about 12% higher than it was in 2015. It was shown a result of a 14% increase in summer precipitation from 2015. Conclusions In this study, it was concluded that the precipitation pattern has a great effect on soil respiration. We confirmed that short-term but intense precipitation suppressed soil respiration due to a rapid increase in soil moisture, while sustained and adequate precipitation activated Rs. In especially, it is very important role on Rs in potential activating period such as summer high temperature season. Therefore, the accuracy of the calculated values by functional equation can be improved by considering the precipitation in addition to the soil temperature applied as the main factor for long-term prediction of soil respiration. In addition to this, we believe that the accuracy can be further improved by introducing an estimation equation based on seasonal temperature and soil moisture.