• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.101-106
• /
• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

• The Korean Journal of Air & Space Law and Policy
• /
• v.28 no.1
• /
• pp.3-54
• /
• 2013

Nowadays, major advanced countries in aviation technology are putting their effort to develop commercial and civil Unmanned Aircraft System(UAS) due to its highly promising market demand in the future. The market scale of commercial and civil UAS is expected to increase up to approximately 8.8 billon U.S. dollars by the year 2020. The usage of commercial and civil UAS covers various areas such as remote sensing, relaying communications, pollution monitoring, fire detection, aerial reconnaissance and photography, coastline monitoring, traffic monitoring and control, disaster control, search and rescue, etc. With the introduction of UAS, changes need to be made on current Air Traffic Management Systems which are focused mainly manned aircrafts to support the operation of UAS. Accordingly, the legislation for the UAS operation should be followed. Currently, ICAO's Unmanned Aircraft System Study Group(UASSG) is leading the standardization process of legislation for UAS operation internationally. However, some advanced countries such as United States, United Kingdom, Australia have adopted its own legislation. Among these countries, United States is most forth going with President Obama signing a bill to integrate UAS into U.S. national airspace by 2015. In case of Korea, legislation for the unmanned aircraft system is just in the beginning stage. There are no regulations regarding the operation of unmanned aircraft in Korea's domestic aviation law except some clauses regarding definition and permission of the unmanned aircraft flight. However, the unmanned aircrafts are currently being used in military and under development for commercial use. In addition, the Ministry of Land, Infrastructure and Transport has a ambitious plan to develop commercial and civil UAS as Korea's most competitive area in aircraft production and export. Thus, Korea is in need of the legislation for the UAS operation domestically. In this regards, I personally think that Korea's domestic legislation for UAS operation will be enacted focusing on following 12 areas : (1)use of airspace, (2)licenses of personnel, (3)certification of airworthiness, (4)definition, (5)classification, (6)equipments and documents, (7)communication, (8)rules of air, (9)training, (10)security, (11)insurance, (12)others. Im parallel with enacting domestic legislation, korea should contribute to the development of international standards for UAS operation by actively participating ICAO's UASSG.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.77-85
• /
• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• The Journal of Society for e-Business Studies
• /
• v.20 no.4
• /
• pp.103-126
• /
• 2015

Compared to other countries, cloud computing in Korea is not popular especially in the government sector. One of the reasons for the current not-fully-blossomed situation is partly by early investment in huge government datacenters under Korea's e-government initiative; let alone, there was no strong control tower as well as no enforcing law and ordinances for driving such cloud computing initiative. However, in 2015 March 'Cloud Computing and Privacy Security Act' (hereinafter, Cloud Act) had been passed in the Parliament and from September 2015 Cloud Act was deployed in Korea. In U.S., FedRAMP (Federal Risk Assessment and Management Program) along with Obama Adminstration's 'Cloud First' strategy for U.S. federal institutions is the key momentum for federal cloud computing adoption. In 2015 January, U.S. Congressional Research Service (CRS) has published an extensive monitoring report for cloud computing in U.S. federal institutions. The CRS report which monitored U.S. government cloud computing implementation is indeed a good guideline for Korean government cloud computing services. For this reason, the purpose of the study is to (1) identify important aspects of the enacted Korean Cloud Act, (2) describe recent U.S. federal government cloud computing status, (3) suggest strategy and key strategy factors for facilitating cloud adoption in public organizations reflecting SDLC strategy, wherein.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.12
• /
• pp.1959-1970
• /
• 2013

Attempts were made in this paper to compare the practice of protective actions for information of patients' medical treatment between hospital administrators who do not make direct contact with patients and occupational therapists who usually do. The comparison between jobs in charge showed that occupational therapists did not practice much protective actions for information of patients' medical treatment ($3.52{\pm}.809$) compared to hospital administrators ($3.92{\pm}.724$), even though the former had received regular education about protection, management and supervision of patients' medical information more often ($3.17{\pm}1.129$) than the latter ($3.16{\pm}1.037$). In spite of the fact that occupational therapists were exposed frequently to the danger of revealing medical information in the process of their job performance through talks and communications with patients, they displayed relatively little concern for and awareness of keeping information of medical treatment from being leaked by them. It is thus suggested to promote awareness of medical staff to protect medical information by means of flexible educational system for each occupational group, periodical monitoring, continuing public relation, training and quality control for protection of medical information, as well as routine self-examination of such practice.

• Journal of Radiation Protection and Research
• /
• v.39 no.3
• /
• pp.127-133
• /
• 2014

North Korea's uranium enrichment facility is a matter of international concern. It is of particular alarming to South Korea with regard to the security and safety of the country. This situation requires continuous monitoring of the DPRK and emergency preparedness on the part of the ROK. To assess the detectability of an undeclared uranium enrichment plant in North Korea, uranium concentrations in the air at both a short and a long distance from the enrichment facility were estimated. $UF_6$ source terms were determined by using existing information on North Korean facility and data from the operation experience of enrichment plants from other countries. Using the calculated source terms, two atmospheric dispersion models (Gaussian Plume Model and HYSPLIT models) and meteorological data were used to estimate the uranium particle concentrations from the Yongbyon enrichment facility. A maximum uranium concentration and its location are dependent upon the meteorological conditions and the height of the UF6 release point. This study showed that the maximum uranium concentration around the enrichment facility was about $1.0{\times}10^{-7}g{\cdot}m^{-3}$. The location of the maximum concentration was within about 0.4 km of the facility. It has been assumed that the uranium sample of about a few micrograms (${\mu}g$) could be obtained; and that few micrograms of uranium can be easily measured with current measurement instruments. On the contrary, a uranium concentration at a distance of more than 100 kilometers from the enrichment facility was estimated to be about $1.0{\times}10^{-13}{\sim}1.0{\times}10^{-15}g{\cdot}m^{-3}$, which is less than back-ground level. Therefore, based on the results of our paper, an air sample taken within the vicinity of the Yongbyon enrichment facility could be used to determine as to whether or not North Korea is carrying out an undeclared nuclear program. However, the air samples taken at a longer distance of a few hundred kilometers would prove difficult in detecting a clandestine nuclear activities.

• The Korean Journal of Archival Studies
• /
• no.25
• /
• pp.3-46
• /
• 2010

Digital records management is one whole system in which many social and technical elements are interacting. To maintain the trustworthiness, the repository needs periodical audit and certification. Thus, individual electronic records management agency needs toolkit that can be used to self-evaluate their trustworthiness continuously, and self-assess their atmosphere and system to recognize deficiencies. The purpose of this study is development of self-certification toolkit for repositories, which synthesized and analysed such four international standard and best practices as OAIS Reference Model(ISO 14721), TRAC, DRAMBORA, and the assessment report conducted and published by TNA/UKDA, as well as MoRe2 and current national laws and standards. As this paper describes and demonstrate the development process and the framework of this self-certification toolkit, other electronic records management agencies could follow the process and develop their own toolkit reflecting their situation, and utilize the self-assessment results in-house. As a result of this research, 12 areas for assessment were set, which include (organizational) operation management, classification system and master data management, acquisition, registration and description, storage and preservation, disposal, services, providing finding aids, system management, access control and security, monitoring/audit trail/statistics, and risk management. In each 12 area, the process map or functional charts were drawn and business functions were analyzed, and 54 'evaluation criteria', consisted of main business functional unit in each area were drawn. Under each 'evaluation criteria', 208 'specific evaluation criteria', which supposed to be implementable, measurable, and provable for self-evaluation in each area, were drawn. The audit and certification toolkit developed by this research could be used by digital repositories to conduct periodical self-assessment of the organization, which would be used to supplement any found deficiencies and be used to reflect the organizational development strategy.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.