• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.27-33
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• 2023

Recently, water shortages have occurred due to climate change, and the need for water management of agricultural water has increased due to the occurrence of algal blooms in reservoirs. Existing algae prevention is operated by putting many people on site and misses the optimal spraying time due to movement through boats. In order to solve this problem, it is necessary to block contamination in advance and move within time to uniformly spray complex microorganisms uniformly. Control drones are used for pesticide spraying and can be applied to algae prevention work by utilizing control drones. In this paper, basic research for the establishment of a marine control system was conducted for application to the reservoir environment, and as one of the results, the characteristics of a drone nozzle, a core technology that can be used for control drones, were calculated. In particular, it was found that the existing agricultural control drones had a disadvantage that the concentration was non-uniform within the suggested spraying interval, and to compensate for this, nozzle positioning and nozzle spraying uniformity were calculated. Based on the experimental results, we develop a core algorithm for establishing an algal bloom monitoring system in the reservoir environment and propose a precision control technology that can be used for marine control work in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.166-171
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• 2023

Efficient energy management is a very important factor in sensor networks with limited resources, and cluster techniques have been studied a lot in this respect. However, a problem may occur in which energy use of the cluster header is concentrated, and when the cluster header is not evenly distributed over the entire area but concentrated in a specific area, the transmission distance of the cluster members may be large or very uneven. The transmission distance can be directly related to the problem of energy consumption. Since the energy of a specific node is quickly exhausted, the lifetime of the sensor network is shortened, and the efficiency of the entire sensor network is reduced. Thus, balanced energy consumption of sensor nodes is a very important research task. In this study, factors for balanced energy consumption by cluster headers and sensor nodes are analyzed, and a balancing distribution clustering method in which cluster headers are balanced distributed throughout the sensor network is proposed. The proposed cluster method uses multi-hop routing to reduce energy consumption of sensor nodes due to long-distance transmission. Existing multi-hop cluster studies sets up a multi-hop cluster path through a two-step process of cluster setup and routing path setup, whereas the proposed method establishes a hierarchical cluster routing path in the process of selecting cluster headers to minimize the overhead of control messages.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.236-241
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• 2023

Water quality problems in rivers, lakes, and estuaries have become serious in Korea. In order to overcome eutrophication of freshwater lakes and river basins, systematic management of water quality is necessary. To manage water quality in freshwater lakes and basins, apply hydrological models suitable for the basin and water quality models such as rivers and lakes to reduce water pollution based on the prediction results of these models. Improvement measures must be presented. In order to apply appropriate water pollution improvement measures in the watershed, accurate pollution sources must be identified and pollution loads must be predicted and presented. Based on GIS, the connection between the pollutant database and the hydrological and water quality prediction model will be integrated based on spatial location, making it possible to provide systematic support to improve watershed water quality by comprehensively including the water quality modeling process. In this paper, in order to accurately predict water pollution in freshwater lakes and river basins, a water quality model system is established using GIS-based spatial information to present a comprehensive water quality management method for freshwater lake basins in the future, and to systematically manage pollution sources through water quality modeling. This study was conducted to easily and efficiently operate hydrological and water quality models using automated spatial information.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.178-185
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• 2023

Rapid urbanization and advancements in technology have led to a surge in the number of automobiles, resulting in frequent traffic accidents, and consequently, an increase in human casualties and economic losses. Therefore, there is a need for technology that can predict the risk of traffic accidents to prevent them and minimize the damage caused by them. Traffic accidents occur due to various factors including traffic congestion, the traffic environment, and road conditions. These factors give traffic accidents spatiotemporal characteristics. This paper analyzes traffic accident data to understand the main characteristics of traffic accidents and reconstructs the data in a time series format. Additionally, an LSTM-MLP based model that excellently captures spatiotemporal characteristics was developed and utilized for traffic accident prediction. Experiments have proven that the proposed model is more rational and accurate in predicting the risk of traffic accidents compared to existing models. The traffic accident risk prediction model suggested in this paper can be applied to systems capable of real-time monitoring of road conditions and environments, such as navigation systems. It is expected to enhance the safety of road users and minimize the social costs associated with traffic accidents.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.94-99
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• 2024

Recently, wind power has been gaining attention as a highly efficient renewable energy source, leading to various technological developments worldwide. Typically, wind power is operated in the form of large wind farms with many wind turbines installed in areas rich in wind resources. However, in developing countries or regions isolated from the power grid, off-grid small wind power systems are emerging as an efficient solution. To efficiently operate and expand off-grid small-scale power systems, the development of real-time monitoring systems is required. For the efficient operation of small wind power systems, it is essential to develop real-time monitoring systems that can actively respond to excessive wind speeds and various environmental factors, as well as ensure the stable supply of produced power to small areas or facilities through an Energy Storage System (ESS). The implemented system monitors turbine RPM, power generation, brake operation, and more to create an optimal operating environment. The developed small wind power system can be utilized in remote road lighting, marine leisure facilities, mobile communication base stations, and other applications, contributing to the development of the RE100 industry ecosystem.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.113-118
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• 2024

Recently, advancements in artificial intelligence and computer graphics technology have led to the emergence of various virtual humans across multiple media such as movies, advertisements, broadcasts, games, and social networking services (SNS). In particular, in the advertising marketing sector centered around virtual influencers, virtual humans have already proven to be an important promotional tool for businesses in terms of time and cost efficiency. In Korea, the virtual influencer market is in its nascent stage, and both large corporations and startups are preparing to launch new services related to virtual influencers without clear boundaries. However, due to the lack of public disclosure of the development process, they face the situation of having to incur significant expenses. To address these requirements and challenges faced by businesses, this paper implements a photogrammetry-based facial capture system for creating realistic virtual humans and explores the use of these models and their application cases. The paper also examines an optimal workflow in terms of cost and quality through MetaHuman modeling based on Unreal Engine, which simplifies the complex CG work steps from facial capture to the actual animation process. Additionally, the paper introduces cases where virtual humans have been utilized in SNS marketing, such as on Instagram, and demonstrates the performance of the proposed workflow by comparing it with traditional CG work through an Unreal Engine-based workflow.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.77-85
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• 2024

The suspension device that connects the prosthetic leg and the residual limb allows lower limb amputees to wear prosthetic limbs, and is the most sensitive part when using prosthetic limbs as it is always in contact with the residual limb not only while walking but also in everyday life. In this paper, using the principles of attraction and repulsion of permanent magnets, we developed a magnetic lock suspension device that can fix the amputees and prosthetic legs of lower limb amputees by changing the polarity of the magnet. The operation method of the magnetic lock is that when neodymium magnets are placed on the left and right as NNSS based on a non-magnetic brass core, the magnetic force flows outward beyond the brass core using the adsorption member as a medium to generate bonding force. When rotated 90 degrees, the magnet moves to NSNS. The principle is that as the position moves, the magnetic force flows inward and cancels out.Based on this, we conducted a bonding test using tensile strength and a short-term comparative evaluation of the prosthesis with the shuttle lock suspension system, which was a comparison group, to verify reliability and evaluate satisfaction with the prototype. As a result, the tensile strength exceeding the appropriate bonding strength was confirmed, and the magnetic lock showed higher satisfaction than the shuttle lock. In the future, we plan to conduct long-term ADL clinical trials for commercialization and develop a product that can be distributed to actual amputees.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.321-326
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• 2015

In this paper, we proposed an algorithm which could transmit reliable data between smart devices by using inaudible high frequency of audible frequency range and cyclic redundancy check method. The proposed method uses 18 kHz~22 kHz as high frequency which inner speaker of smart device can make a sound in audible frequency range (20 Hz~22 kHz). To increase transmission quantity of data, we send mixed various frequencies at high frequency range 1 (18.0 kHz~21.2 kHz). At the same time, to increase accuracy of transmission data, we send some mixed frequencies at high frequency range 2 (21.2 kHz~22.0 kHz) as checksum. We did experiments about data transmission between smart devices by using the proposed method to confirm data transmission speed and accuracy of the proposed method. From the experiments, we showed that the proposed method could transmit 32 bits data in 235 ms, the transmission success rate was 99.47%, and error detection by using cyclic redundancy check was 0.53%. Therefore, the proposed method will be a useful for wireless transmission technology between smart devices.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.187-192
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• 2007

Conference focus maintains and manages SIP(Session Initiation Protocol) signal connections with total conference participants, and it plays core functions of conference server. When the number of conference participants increases, conference focus restricts scalability of conference as increasing quantify of messages for processing. In this paper, to solve this problem. we propose a user system(conference information agent), which receives conference information from the conference focus and transfers them to the participants it manages. And we design and implement the total system including conference focus. When the conference information agent subscribe to the conference focus, it shows its possession of agent capability and capacity by using SIP SUBSCRIBE message. The conference focus informs to the other party by SIP response message that it was chosen as a conference information agent, and after that the conference focus sends all conference notification messages to it. So load of the conference focus can be reduced by this method. Finally, we have analyzed the performance of our system by experiments.