• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.107-113
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• 2018

With the rapid development of big data and Internet technologies among IT technologies, it is being changed into an environment where data stored in the cloud environment can be used wherever the Internet is connected, without storing important data in an external storage device such as USB. However, protection of users' privacy information is becoming increasingly important as the data being processed in the cloud environment is changed into an environment that can be easily handled. In this paper, we propose a user-reserving management model that can improve the user 's service quality without exposing the information used in the cloud environment to a third party. In the proposed model, user group is grouped into virtual environment so that third party can not handle user's privacy information among data processed in various cloud environments, and then identity property and access control policy are processed by block chain.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.88-99
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• 2020

This study aimed to explore the effects of perceived family stress, supportive resources, intentional rumination, and coping behaviors on posttraumatic growth of cancer survivors based on the Double ABCX Family Stress Model. Data were collected from 200 cancer survivors currently living with their spouses and analyzed by path analysis using AMOS program. The results of this study were as follows. First, perceived family stress of cancer survivors had direct effects on supportive resources, intentional rumination, and coping behaviors, and had indirect effects on posttraumatic growth mediated by supportive resources, intentional rumination, and coping behaviors. Second, supportive resources, intentional rumination, and coping behaviors had direct effects on posttraumatic growth. Third, supportive resources and intentional rumination had direct effects on coping behaviors and had an indirect effect on posttraumatic growth mediated by coping behaviors. The current study supported the applicability of the Double ABCX Family Stress Model to the posttraumatic growth process of cancer survivors.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.123-127
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• 2020

In order to obtain the overall fire line information of medium and large forest fires at night, the ground control system was developed to determine whether forest fires occurred through real-time video clips and to calculate the location of the forest fires determined using the location of drones, angle information of video cameras, and altitude information on the map to reduce the time required for regular video matches obtained after the completion of the mission. To verify the reliability of the developed function, the error distance of the aiming position information of the flight altitude star and the image camera was measured, and the location information within the reliable range was displayed on the map. As the function developed in this paper allows real-time identification of multiple locations of forest fires, it is expected that overall fire line information for the establishment of forest fire extinguishing measures will be obtained more quickly.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.9-14
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• 2020

With the distribution modernization policy advanced by the government and consumers preference toward it, the so called "modern market" has undergone rapid growth. Conversely, traditional market is losing popularity with consumers as a result of inadequate modern structures, small market size, convoluted relationships, inefficient operation and disordered transactions, among others. Therefore, this study seeks to utilize ubiquitous computing, that is, the upgrade of context aware information to 6W1H and promote the market through the interface with Smartphone and provide advanced information through the augmented reality technology. For the construction of context-aware system using user context, the results may significantly differ according to how reference rules are applied to and implemented on knowledge base. In light of above, through the use of RFID technology and 6W1H context awareness, we seek to promote traditional markets.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.135-142
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• 2020

In the recent farming industry, there is a growing diffusion of drones, which are recognized as a crucial technology of the 4 th industrial revolution to cope with aging. Especially, filming and pest control using drones are representative fields that have different age groups for obtaining a national license of multicopter that is a ultra-light flying device, and can create profits after getting a license. However, pest control technology using drones has different spray effects depending on levels of operational proficiency, since this highly relies on an operator's operating skills. It is anticipated that if this issue is supplemented, the use of drones for pest control in the farming industry will diversify. For analysis of spraying characteristics of agricultural pest control drones, this study aims to formulate effective spraying hours and effective spraying intervals and suggest an algorithm, which facilitates an accurate calculation of pest control area depending on the kinds of pest control drones. This algorithm can be used in the field of pest control by improving scatterling issues caused by drone flight methods of drone pest controllers and building an optimum pest control manual in future.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.40-46
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• 2020

With the development of the Internet, users share their experiences and opinions. Since related keywords are used witho0ut considering information such as the general emotion or genre of an unstructured document such as a movie review, the sensitivity accuracy according to the appropriate emotional situation is impaired. Therefore, we propose a system that predicts emotions based on information such as the genre to which the unstructured document created by users belongs or overall emotions. First, representative keyword related to emotion sets such as Joy, Anger, Fear, and Sadness are extracted from the unstructured document, and the normalized weights of the emotional feature words and information of the unstructured document are trained in a system that combines CNN and LSTM as a training set. Finally, by testing the refined words extracted through movie information, morpheme analyzer and n-gram, emoticons, and emojis, it was shown that the accuracy of emotion prediction using emotions and F-measure were improved. The proposed prediction system can predict sentiment appropriately according to the situation by avoiding the error of judging negative due to the use of sad words in sad movies and scary words in horror movies.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.65-70
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• 2020

With the appearance of Bitcoin that builds peer-to-peer networks for transaction of digital content and issuance of cryptocurrency, lots of blockchain networks have been developed to improve transaction performance. Recently, Joseph Lubin discussed Decentralization Transaction per Second (DTPS) against alleviating the value of biased TPS. However, this Lubin's trust model did not enough consider a security issue in scalability trilemma. Accordingly, we proposed a trust metric based on blockchain size, stale block rate, and average block size, using a sigmoid function and convex optimization. Via numerical analysis, we presented the optimal blockchain size of popular blockchain networks and then compared the proposed trust metric with the Lubin's trust model. Besides, Bitcoin based blockchain networks such as Litecoin were superior to Ethereum for trust satisfaction and data volume.

• Journal of Convergence for Information Technology
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• v.10 no.5
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• pp.60-74
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• 2020

The purpose of this study is to review articles related to disaster training for nursing students and nurses by investigating the contents and effects of research. Electronic databases, including CINAHL, Pubmed and RISS were searched. Papers published only in English or Korean were included. Twelve studies were selected from the 3,588 references screened. Most training programs took less than 8 hours, focusing mostly on the response phase of disaster. Intervention methods included simulation, debriefing, action learning, role play, problem based learning and so on. It was found that disaster training programs have significant positive effects on disaster management competency, disaster knowledge, disaster nursing related self-confidence, and disaster response competency. It was also revealed that multidisciplinary practice would help learners enhance cooperation and collaboration with other team members and foster a positive professional identity. Among the selected articles, the randomized controlled trial(RCT) study was just one. Therefore, RCTs are further needed to verify the effects of such an disaster training. Also, further studies considering the characteristics of department and nursing interventions based on all phases of disaster are needed.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.49-58
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• 2020

This study was conducted to identify the changes in academic self-efficacy and self-directed learning ability after applying flipped learning using media convergence to the basic nursing practice courses. It is offering flipped learning to 22 students from the experimental group and 26 students from the control group. Data were collected from August 27 to December 3, 2019. The difference in academic self-efficacy before and after the flipped learning was no significant difference between the two groups. However, the difference in self-directed learning ability was 11.32 points in the experimental group and 0.23 points in the control group (t=2.32, p=.027). According to the results of this study, flipped learning using media convergence was found to be an effective teaching method to improve self-directed learning ability of students. Therefore, it is necessary to study the expanded application of flipped learning using media convergence to various nursing subjects.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.140-146
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• 2020

Since the current crime prevention systems have a standard mechanism that victims request for help by themselves or ask for help from a third party nearby, it is difficult to obtain appropriate help in situations where a prompt response is not possible. In this study, we proposed and developed an automatic rescue request model and system using Deep Learning and OpenCV. This study is based on the prerequisite that immediate and precise threat detection is essential to ensure the user's safety. We validated and verified that the system identified by more than 99% of the object's accuracy to ensure the user's safety, and it took only three seconds to complete all necessary algorithms. We plan to collect various types of threats and a large amount of data to reinforce the system's capabilities so that the system can recognize and deal with all dangerous situations, including various threats and unpredictable cases.