• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.197-202
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• 2019

A small millimeter-wave tracking radar power supply must provide stable power with minimal ripple noise and the switching frequency noise of the DC-DC converter must have a real-time self-test capability through on-the-fly monitoring without causing false alarms and ghost In this study, we developed a multi-output switching power supply with output power of more than 80% (@ 100% load) and 10 output power by adopting + 28VDC input for application to small millimeter wave tracking radar, DC-DC converter is applied for large power output and multi-output flyback method is applied for the remaining small power output. The test results show that 85% efficiency efficiency is achieved under 100% load condition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.139-143
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• 2019

Measurement of flow rate is required in various fields. Water meters are often used at home, and flow meters are used in water and sewage plants, petrochemical industries and so on.. A system is needed to monitor the flow rate in real time and notify immediately when flow rate is abnormal. Recently, with the development of the IoT it is possible to construct such devices at low cost. WeMos can be programmed with Arduino IDE as a mini wifii IoT module. The flow sensor can output a digital pulse proportional to the flow rate. In this paper, we developed the flow monitoring and warning system using WeMos and IoT technology. When the system operates, it calculates the flow rate, sends the value as JSON format to the server, monitors the flow rate as graph from the remote with the smartphone. We also implement the system to promptly send alert message to the smart phone using Pushbullet when the flow rate is abnormal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5568-5587
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• 2018

This research uses artificial intelligence methods for computer network intrusion detection system modeling. Primary classification is done using self-organized maps (SOM) in two levels, while the secondary classification of ambiguous data is done using Sugeno type Fuzzy Inference System (FIS). FIS is created by using Adaptive Neuro-Fuzzy Inference System (ANFIS). The main challenge for this system was to successfully detect attacks that are either unknown or that are represented by very small percentage of samples in training dataset. Improved algorithm for SOMs in second layer and for the FIS creation is developed for this purpose. Number of clusters in the second SOM layer is optimized by using our improved algorithm to minimize amount of ambiguous data forwarded to FIS. FIS is created using ANFIS that was built on ambiguous training dataset clustered by another SOM (which size is determined dynamically). Proposed hybrid model is created and tested using NSL KDD dataset. For our research, NSL KDD is especially interesting in terms of class distribution (overlapping). Objectives of this research were: to successfully detect intrusions represented in data with small percentage of the total traffic during early detection stages, to successfully deal with overlapping data (separate ambiguous data), to maximize detection rate (DR) and minimize false alarm rate (FAR). Proposed hybrid model with test data achieved acceptable DR value 0.8883 and FAR value 0.2415. The objectives were successfully achieved as it is presented (compared with the similar researches on NSL KDD dataset). Proposed model can be used not only in further research related to this domain, but also in other research areas.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.41-50
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• 2021

According to the progress of IT and data processing technology, the usage of internet increased rapidly and various smart devices are appearing. As such, modern people use smartphone to acquire informations they wish and also on daily life including leisure activity free of place. This study has designed and implemented schedule managing application that can help effective managing of our daily life, such as taking note of schedule and sharing appointments. The schedule managing application in this study offers diary taking, sharing the registrated schedule with other users on kakaotalk, saving the deleted schedule or diary to certain folder when users delete file, continuous alarm of daily schedule function together with schedule registration function. The application which is differentiated to other applications and raised usage is expected to effectively manage the busy everyday life.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.121-129
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• 2021

In addition to yellow dust occurring in China, fine dust has become a hot topic in Korea through news and media. Although there is fine dust generated from the outside, the purchase rate of air purifier products is increasing as external fine dust flows into the inside. The air purifier uses a filter internally, and the sensor notifies the user through the LED alarm whether the filter is replaced. However, there is currently no product measuring how much the filter rate is reduced and determining the pressure of the blower to operate. Therefore, in this paper, data are generated directly using Arduino, fine dust sensor, and differential pressure sensor. In addition, a program was developed using Python programming to calculate how old the filter is and to analyze the wind power of the blower according to the filter rate by calculating the measured dust and pressure values.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.85-92
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• 2022

Demand for big data analysis and AI developers is increasing, but there is a lack of an education base to supply them. In this paper, by developing a cloud-based artificial intelligence education platform, the goal was to establish an environment in which practical practical training can be efficiently learned at low cost at educational institutions and IT companies. The development of the education platform was carried out by planning scenarios for each user, architecture design, screen design, implementation of development functions, and hardware construction. This training platform consists of a containerized workload, service management platform, lecture and development platform for instructors and students, and secured cloud stability through real-time alarm system and age test, CI/CD development environment, and reliability through docker image distribution. The development of this education platform is expected to expand opportunities to enter new businesses in the education field and contribute to fostering working-level human resources in the AI and big data fields.

• Land and Housing Review
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• v.13 no.4
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• pp.105-114
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• 2022

Non-fire activated fire alarms caused by such actions as cigarette smoke, cooking, and high humidity are fire safety risk factors. In such instances, it is important to quickly locate and replace the actuated detector. However, it is difficult to locate those detectors because most do not have an address function. While new apartments can incorporate addressable fire alarm detectors, in existing apartments there are limitations in converting over to addressable detectors due to cost and power line issues. This study developed an efficient address function for fire alarms in existing apartments. The newly developed system consists of the existing receiver, and a proposed addressable repeater and detector. Utilizing an experimental setup, the performance of the proposed address monitoring system was confirmed to be stable and compatible with the receiver and existing detectors.

• Journal of Ocean Engineering and Technology
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• v.35 no.1
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• pp.91-97
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• 2021

Marine accidents caused by ships have brought about economic and social losses as well as human casualties. Most of these accidents are caused by small and medium-sized ships and are due to their poor conditions and insufficient equipment compared with larger vessels. Measures are quickly needed to improve the conditions. This paper discusses a video-integrated collision prediction and fall detection system to support the safe navigation of small- and medium-sized ships. The system predicts the collision of ships and detects falls by crew members using the CCTV, displays the analyzed integrated information using automatic identification system (AIS) messages, and provides alerts for the risks identified. The design consists of an object recognition algorithm, interface module, integrated display module, collision prediction and fall detection module, and an alarm management module. For the basic research, we implemented a deep learning algorithm to recognize the ship and crew from images, and an interface module to manage messages from AIS. To verify the implemented algorithm, we conducted tests using 120 images. Object recognition performance is calculated as mAP by comparing the pre-defined object with the object recognized through the algorithms. As results, the object recognition performance of the ship and the crew were approximately 50.44 mAP and 46.76 mAP each. The interface module showed that messages from the installed AIS were accurately converted according to the international standard. Therefore, we implemented an object recognition algorithm and interface module in the designed collision prediction and fall detection system and validated their usability with testing.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.994-1003
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• 2020

In this paper, we investigated the current issues on the KPAS(Korean Public Alert Service) by News analysis. News articles, from May 15, 2005 to April 30, 2020, were collected with the key word of 'KPAS' through the News Big-Data System provided by the Korea Press Foundation. The results of the content analysis are as follows. First, the issues on alert presentation were categorized by alarm sound, message content, alert level, transmission frequency, delay, reception range, time of alert, and language. Issues on inability to receive KPAS messages were categorized into authority, mobile, sending standard, mobile communication infra, etc. For the last two to three years, news on the inability issues had decreased, while news on the presentation issues had increased. This tells us that the public demand for improvement in the KPAS lies in the presentation issues. The demand for societal resolutions to the presentation issues especially on message content, transmission frequency, and reception range has soared.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.381-393
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• 2021

As part of the National Disaster Management Research Institute's Official Development Assistance (ODA) projects for transferring new technologies in the field of disaster-safety management, a flood forecasting and warning system was established in 2019 targeting the Borikhan in the Namxan River Basin in Bolikhamxai Province, Laos. In the target area, which is an ungauged small and medium river basin, observation stations for real-time monitoring of rainfall and runoff and alarm stations were installed, and a software that performs real-time data management and flood forecasting and warning functions was also developed. In order to establish a flood warning standard and develop a nomograph for flood prediction, hydraulic and hydrological analysis was performed based on the 30-year annual maximum daily rainfall data and river morphology survey results in the target area. This paper introduces the process and methodology used in this study, and presents the results of the system's applicability review based on the data observed and collected in 2020 after system installation.