• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.1-6
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• 1999

This paper is on the analysis for the real-time software requirement. This method can be used for TNPN(Timed Numerical Peri Net) as a easy communication means with real-users. It is based on the RTTL(Real Time Temporal Logic) for correctness the system. TNPN is used to represent a behavior specification language, the validity of specified behaviors in TNPN is expressed in RTTL, and analyzed through the teachability graph. Thus, the requirement between user and system is satisfied Using the example of shared track, the validity of the property of real-time(safetiness, responsiveness, liveness, priority) is verified. Also this framework if given to connection with a object, natually.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.75-83
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• 2018

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.1-9
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• 2018

With developments in science and technology and improvement in living standards, human life expectancy is steadily increasing worldwide. For effective healthcare, it is necessary to check health conditions according to individuals' behavior and acquire prior knowledge on possible diseases. In this study, we classified the diseases that are major causes of death in Korea by referring to data provided by the Korea National Health and Nutrition Examination Survey. We selected indexes that could be used as indicators of major diseases and created the LCBB-SC. In the LCBB-SC, the data are systematically subdivided into related fields to provide integrated data related to each disease and to provide an infrastructure that can be used by researchers. In addition, by developing a web interface allowing for self-symptom assessments, this resource will be beneficial to people who want to check their own health condition using a list of diseases that might be caused by their behaviors.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.115-119
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• 2020

Recently, CCTV installations are rapidly increasing in the public and private sectors to prevent various crimes. In accordance with the increasing number of CCTVs, video-based abnormal behavior detection in control systems is one of the key technologies for safety. This is because it is difficult for the surveillance personnel who control multiple CCTVs to manually monitor all abnormal behaviors in the video. In order to solve this problem, research to recognize abnormal behavior using deep learning is being actively conducted. In this paper, we propose a model for detecting abnormal behavior based on the deep learning model that is currently widely used. Based on the abnormal behavior video data provided by AI Hub, we performed a comparative experiment to detect anomalous behavior through violence learning and fainting in videos using 2D CNN-LSTM, 3D CNN, and I3D models. We hope that the experimental results of this abnormal behavior learning model will be helpful in developing intelligent CCTV.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.120-123
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• 2020

The surveillance system to prevent crime and accidents in advance has become a necessity, not an option in real life. Not only public institutions but also individuals are installing surveillance cameras to protect their property and privacy. However, since the installed surveillance camera cannot be monitored for 24 hours, the focus is on the technology that tracks the video after an accident occurs rather than prevention. In this paper, we propose a system model that monitors abnormal behaviors that may cause crimes through real-time video, and when a specific behavior occurs, the surveillance system automatically detects it and responds immediately through an alarm. We are a model that analyzes real-time images from surveillance cameras and uses I3D models from analysis servers to analyze abnormal behavior and deliver notifications to web servers and then to clients. If the system is implemented with the proposed model, immediate response can be expected when a crime occurs.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.159-165
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• 2021

Electronic devices used in the mobile environments fabricated under the plasma conditions in high vacuum system. Especially for the development of advanced electronic devices, high quality plasma as the process conditions are required. For this purpose, the variable conductance throttle valves for controllable plasma employed to the high vacuum system. In this study, we analyzed the effects of throttle valve applications on vacuum characteristics simulated to obtain the optimum design modelling for plasma conditions of high vacuum system. We used commercial simulator of vacuum system, VacSim(multi) on this study. Reliability of simulator verified by simulation of the commercially available models of high vacuum system. Simulated vacuum characteristics of the proposed modelling agreed with the observed experimental behaviour of real systems. Pressure limit valve and normally on-off control valve schematized as the modelling of throttle valve for the constant process-pressure of below 10-3 torr. Simulation results plotted as pump down curve of chamber, variable valve conductance and conductance logic of throttle valve. Simulated behaviors showed the applications of throttle valve sustained the process-pressure constantly, stably, and reliably in plasma process.

• Asia Marketing Journal
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• v.24 no.2
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• pp.39-50
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• 2022

Live streaming has become one of the most important communication tools for influencers to synchronously interact with viewers. It is critical to understand the effect of the reciprocal and synchronously interactive relations built between influencers and viewers, so-called trans-parasocial relations, in the context of live streaming. In this study, we investigate how trans-parasocial relations impact viewers' stickiness and purchase intention on live streaming platforms. Furthermore, we investigate fanship as a mediating factor in the relationship between trans-parasocial relations and viewers' behaviors. Overall, the results reveal significant direct and indirect effects of trans-parasocial relations on viewers' stickiness and purchase intention. Higher trans-parasocial relations further lead to stronger viewers' fanship toward influencers and increases their willingness to stay longer or make purchases on live streaming platforms. These findings further the understanding of influencer-viewer relations and viewers' behavior on live streaming platforms and provide valuable insights into influencer marketing and live streaming.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.88-93
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• 2023

In software engineering, requirement analysis is an important task throughout the process and takes up a high proportion. However, factors that fail to analyze requirements include communication failure, different understanding of the meaning of requirements, and failure to perform requirements normally. To solve this problem, we derived actors and behaviors using morpheme analysis and BERT algorithms in the Korean requirement document and constructed them as ontologies. A chatbot system with ontology data is constructed to derive a final system event list through Q&A with users. The chatbot system generates the derived system event list as a requirement diagram and a requirement specification and provides it to the user. Through the above system, diagrams and specifications with a level of coverage complied with Korean requirement documents were created.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.34 no.2
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• pp.117-124
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• 2023

Savant syndrome was described before autism. However, they soon became closely associated, as many of their symptoms (intellectual disability, repetitive behaviors, alterations in social communication, and islets of abilities) overlap. Only a few women with autism have been diagnosed with savant syndrome. The theories or hypotheses that attempt to explain savant syndrome, which are common in autism, present differential treatment according to sex. We postulate that savant syndrome associated with autism as well as autism in general is underdiagnosed in women.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.1-16
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• 2023

Influencer advertising, which has gained significant attention in academia and industry, is widely adopted as a digital marketing strategy. This study empirically analyzes the impact of perceived influencer channel attributes and ad attributes on the suitability of advertisements and their effects on consumers' positive and negative advertising behaviors. The research aims to identify various factors that can enhance the effectiveness of influencer advertising. The results reveal that among the influencer channel attributes, informativeness and intimacy have a positive impact on ad suitability, while ad clutter has a negative impact. Additionally, ad-influencer fit positively affect ad attention and negatively influences ad avoidance. Based on these findings, companies can enhance the effectiveness of influencer advertising by first selecting influencers who align well with the advertisement and emphasizing informativeness and emotional bonding to improve ad suitability. Moreover, the study suggests that influencer advertising strategies can be effective as long as they avoid excessive ad clutter, as it diminishes ad suitability. Marketing practitioners and advertising planners can utilize these insights to formulate more effective influencer advertising strategies.