• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.374-380
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• 2022

This paper shows the results of a study that predicts changes in seawater conditions in sea farms using machine learning-based long short term memory (LSTM) algorithms. Hardware was implemented using dissolved oxygen, salinity, nitrogen ion concentration, and water temperature measurement sensors to collect seawater condition information from sea farms, and transferred to a cloud-based Firebase database using LoRa communication. Using the developed hardware, seawater condition information around fish farms in Tongyeong and Geoje was collected, and LSTM algorithms were applied to learning results using these actual datasets to obtain predictive results showing 87% accuracy. Flask and REST APIs were used to provide users with predictive results for each of the four parameters, including dissolved oxygen. These predictive results are expected to help fishermen reduce significant damage caused by fish group death by providing changes in sea conditions in advance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.559-571
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• 2021

Along with the increase prevalence of computers, the number of malware distributions by attackers to ordinary users has also increased. Research to detect malware continues to this day, and in recent years, research on malware detection and analysis using AI is focused. However, the AI algorithm has a disadvantage that it cannot explain why it detects and classifies malware. XAI techniques have emerged to overcome these limitations of AI and make it practical. With XAI, it is possible to provide a basis for judgment on the final outcome of the AI. In this paper, we conducted malware group classification using XGBoost and Random Forest, and interpreted the results through SHAP. Both classification models showed a high classification accuracy of about 99%, and when comparing the top 20 API features derived through XAI with the main APIs of malware, it was possible to interpret and understand more than a certain level. In the future, based on this, a direct AI reliability improvement study will be conducted.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.71-78
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• 2023

In this paper, we analyze the structure of TV video software, one of the warship combat management system software, and propose a standard architecture that minimizes software modification due to the discontinuation replacement of warship hardware. The class structure was newly designed to minimize the class modified when replacing the warship hardware by separating the variable elements and common elements of TV video software through FORM(Feature-Oriented Reuse Method), the common part that communicates with the warship combat management system and displays the TV screen and the variable part that communicates between the operator and the TV camera. In addition, the Strategy design pattern is applied to efficiently add and modify classes that directly use hardware-dependent APIs when replacing hardware discontinuation, and to make both discontinued and replacements available software. Finally, the reliability testing time and functional testing time of the existing TV video software and the proposed software were measured and compared, and finally, it was confirmed that the hardware discontinuation replacement cost was reduced.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1091-1102
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• 2022

Robotic systems have developed very rapidly over the past decade. Robot Operating System is an open source-based software framework for the efficient development of robot operating systems and applications, and is widely used in various research and industrial fields. ROS applications may contain various vulnerabilities. Various studies have been conducted to monitor the excution of these ROS applications at runtime. In this study, we propose a real-time attack detection system using event-based runtime monitoring in ROS 2. Our attack detection system extends tracetools of ros2_tracing to instrument events into core libraries of ROS 2 middleware layer and monitors the events during runtime to detect attacks on the application layer through out-of-order execution of the APIs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.278-287
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• 2022

With the development of technology, driving simulators have been used in various ways. In driving simulator experiments, scenario creation is essential to increase fidelity, achieve research aims, and provide an immersive experience to the driver. However, challenges remain when creating realistic scenarios, such as developing a database and the execution of scenarios in real-time. Therefore, to create realistic scenarios, it is necessary to acquire real-time data. This study intends to develop a method of acquiring real-time weather and traffic speed information for actual, specific roads. To this end, this study suggests the concatenator for dynamic data obtained from Arduino sensors and public open APIs. Field tests are then performed on actual roads to evaluate the performance of the proposed solution. Such results may give meaningful information for driving simulator studies and for creating realistic scenarios.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.1-6
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• 2023

The purpose of this study is to research and develop so that users who are gradually progressing in the popularization of smartphones and the calculation of agricultural quality can use more active and flexible applications than existing application fields. People use event management applications to remember what they need to do, and maps applications to get to their appointments on time. You will need to build a glue-delivered application that leverages the Maps API to be able to recommend the glove's path for events so that the user can use the application temporarily. By comparing and analyzing currently used calendar, map, and schedule applications, several Open Maps APIs were compared to supplement the weaknesses and develop applications that converge the strengths. The results of application development by applying the optimal algorithm for recommending traffic routes according to time and place for the schedule registered by the user are described.

• Journal of Pharmacopuncture
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• v.25 no.4
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• pp.390-395
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• 2022

Objectives: Sweet bee venom (sBV) is purified from Apis mellifera, containing a high level of melittin-its main component. It has been used as a therapeutic agent for pain relief and anti-inflammation, as well as for treating neuronal abnormalities. Recently, there have been studies on the therapeutic application of sBV for anticancer treatment. In the present study, we investigated the pharmacological effect of sBV treatment in A549 human lung cancer cells. Methods: We used microscopic analysis to observe the morphological changes in A549 cells after sBV treatment. The MTT assay was used to examine the cytotoxic effect after dose-dependent sBV treatment. Molecular changes in sBV were evaluated by the expression of apoptosis marker proteins using western blot analysis. Results: Microscopic analysis suggested that the growth inhibitory effect occurred in a dose-dependent manner; however, cell lysis occurred at a concentration over 20 ㎍/mL of sBV. The MTT assay indicated that sBV treatment exhibited a growth inhibitory effect at a concentration over 5 ㎍/mL. On fluorescence activated cell sorting analysis, G0 dead cells were observed after G1 arrest at treatment concentrations up to 10 ㎍/mL. However, rapid cell rupture was observed at a concentration of 20 ㎍/mL. Western blot analysis demonstrated that sBV treatment modulated the expression of multiple cell death-related proteins, including cleaved-PARP, cleaved-caspase 9, p53, Bcl2, and Bax. Conclusion: sBV induced cell death in A549 human lung cancer cells at a pharmacological concentration, albeit causing hemolytic cell death at a high concentration.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.261-270
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• 2010

An integrated simulation engine provides tools, services, and standards to support various activities in the entire M&S from modeling and simulation to analysis of the simulation results. Many countries have developed integrated simulation engines to efficiently assist complex M&S activities. However, we do not have domestic simulation engines especially designed for defense M&S, therefore, developing M&S softwares still remains as a hard task with high cost and tine. OpenSIM(Open Simulation engine for Interoperable Models) is an integrated simulation engine and provides tools, services and standard interfaces for weapons analysis. OpenSIM's services are comprised of classes, member functions and data attributes which are commonly used in modeling, simulating and analyzing weapons systems. In this paper, we introduce OpenSIM's services in C++ APIs and illustrate them through an ASM example(Air to Surface Missile).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.183-188
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• 2023

Game object inheritance and multiple components allow for visualization of system architecture, good code reuse, and fast prototyping. On the other hand, objects are more likely to rely on high latency between game objects and components, static casts, and lots of references to things like null pointers. Therefore, It is important to design a game in such a way so that the dependency of objects on multiple classes could be reduced and existing codes could be reused. Therefore, we designed the game to make the classes more modular by applying Dependency Injection and the design patterns proposed by the Gang of Four. Since these dependencies are attributes of the game object and the injection occurs only in the initialization pass, there is little performance degradation or performance penalty in the game loop. Therefore, this paper proposed an efficient design method to effectively reuse APIs in the design and implementation of survival games.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.