• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.15-20
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• 2021

The imprecise real-time scheduling can be used for minimizing the bad effects of timing faults by leaving less important tasks unfinished if necessary when a transient overload occured. In the imprecise scheduling, every time-critical task can be logically decomposed into two tasks : a mandatory task and an optional task. Recently, some studies in this field showed good schedulability performance and minimum total error by deferring the optional tasks. But the schedulability performance of the studies can be shown only when the execution time of each optional task was less than or equal to the execution time of its corresponding mandatory task. Therefore, in this paper, a new deferring strategy is proposed under the reverse execution time restriction to the previous studies. Nevertheless, the strategy produces comparable or superior schedulability performance to the previous studies and can minimize the total error also.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.31-38
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• 2021

In this paper, in order to obtain the optimization of the RNN model used for sentiment analysis, the correlation of each model was studied by observing the trend of loss and accuracy according to hyperparameter tuning. As a research method, after configuring the hidden layer with LSTM and the embedding layer that are most optimized to process sequential data, the loss and accuracy of each model were measured by tuning the unit, batch-size, and embedding size of the LSTM. As a result of the measurement, the loss was 41.9% and the accuracy was 11.4%, and the trend of the optimization model showed a consistently stable graph, confirming that the tuning of the hyperparameter had a profound effect on the model. In addition, it was confirmed that the decision of the embedding size among the three hyperparameters had the greatest influence on the model. In the future, this research will be continued, and research on an algorithm that allows the model to directly find the optimal hyperparameter will continue.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.43-48
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• 2021

One of the effective ways to increase data transmission rate is to use massive antenna technique where tens or hundreds of antennas are deployed in base station and spatial diversity gain is improved by multiuser method. If multiuser method is applied, there will be inter-user interference and maximal ratio combiner (MRC) is conventionally used to reduce the complexity of the receiver and to eliminate interference. However, as the number of mobile devices increases, the performance of the conventional receiver becomes deteriorated. To solve this problem, we propose a new detector that completely eliminates the interference from the registered devices and reduces that from the unregistered devices. Then, to reduce the complexity of the proposed scheme, we propose adaptive algorithm of the proposed scheme. Through simulation, we show that the proposed scheme has better bit error rate performance than the conventional scheme.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.127-132
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• 2020

The Smart Music Learning Device(SMLD) presented in this paper constructs the display part by attaching the touch panel to both sides of the transparent panel. The main processing unit uses raspberry pie, and the operating system uses Android. On the transparent panel, music education contents are displayed, and on the touch panels 1 and 2, the inputs of learners and instructors are accepted. The signal input from the touch panels 1 and 2 controls the progress of the music education contents through a process in the main processing unit. This control process design and implement a two - sided panel - based interactive training algorithm. This device aims at musical education based on mutual understanding. Therefore, it conducts face-to-face education using music education contents presented through transparent panel. This allows the instructor to know in real time the response to the learner, thus improving the understanding of the learning and the quality of the education. Also, the learner's concentration can be improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.225-230
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• 2020

Machine learning is an algorithm which learns a computer based on the data so that the computer can identify the trend of the data and predict the output of new input data. Machine learning can be classified into supervised learning, unsupervised learning, and reinforcement learning. Supervised learning is a way of learning a machine with given label of data. In other words, a method of inferring a function of the system through a pair of data and a label is used to predict a result using a function inferred about new input data. If the predicted value is continuous, regression analysis is used. If the predicted value is discrete, it is used as a classification. A result of analysis, no. 8 (5, 3.4, setosa), 27 (5, 3.4, setosa), 41 (5, 3.5, setosa), 44 (5, 3.5, setosa) and 40 (5.1, 3.4, setosa) in Table 3 were classified as the most similar Iris flower. Therefore, theoretical practical are suggested.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.1-6
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• 2021

In the modern society, traffic problems are occurring as vehicle ownership increases. In particular, the incidence of highway traffic accidents is low, but the fatality rate is high. Therefore, a technology for detecting an abnormality in a vehicle is being studied. Among them, there is a vehicle anomaly detection technology using deep learning. This detects vehicle abnormalities such as a stopped vehicle due to an accident or engine failure. However, if an abnormality occurs on the road, it is possible to quickly respond to the driver's location. In this study, we propose a deep learning-based vehicle anomaly detection using road CCTV data. The proposed method preprocesses the road CCTV data. The pre-processing uses the background extraction algorithm MOG2 to separate the background and the foreground. The foreground refers to a vehicle with displacement, and a vehicle with an abnormality on the road is judged as a background because there is no displacement. The image that the background is extracted detects an object using YOLOv4. It is determined that the vehicle is abnormal.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1551-1565
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• 2020

On April 4, 2019, a forest fire started in Goseong County and lasted for three days, burning the neighboring areas of Sokcho. The strong winds moved the blaze from one region to another region and declared the worst wildfire in South Korea in years. More than 1,880 facilities, including 400 homes, were burnt down. The fire burned a total area of 529 hectares (1,307 acres), which involved 13,000 rescuers and 16,500 military troops to control the fire occurrence. Thousands of people were evacuated, and two people are dead. This study generated post-wildfire maps to provide necessary data for evacuation and mitigation planning to respond to this destructive wildfire, also prevent further damage and restore the area affected by the wildfire. This study used KOMPSAT-3A and Sentinel-2 imagery to map the post-wildfire condition. The SVM showed higher accuracy (overall accuracy 95.29%) compared with ANN (overall accuracy of 94.61%) for the KOMPSAT-3A. Moreover, for Sentinel-2, the SVM attained a higher accuracy (overall accuracy of 91.52%) than the ANN algorithm (overall accuracy 90.11%). In total, four post-wildfire burned area maps were generated; these results can be used to assess the area affected by the Sokcho wildfire and wildfire mitigation planning in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.1-8
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• 2022

In this paper, we design and implement a GPU-based parallel algorithm to effectively solve the traveling salesman problem through an ant color system. The repetition process of generating hundreds or thousands of tours simultaneously in TSP utilizes GPU's task-level parallelism, and the update process of pheromone trails data actively exploits data parallelism by 32x32 thread blocks. In particular, through simultaneous memory access of multiple threads, the coalesced accesses on continuous memory addresses and concurrent accesses on shared memory are supported. This experiment used 127 to 1002 city data provided by TSPLIB, and compared the performance of sequential and parallel algorithms by using Intel Core i9-9900K CPU and Nvidia Titan RTX system. Performance improvement by GPU parallelization shows speedup of about 10.13 to 11.37 times.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.1-8
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• 2022

With the development of communication infrastructure, the number of network equipment owned by one person is gradually increasing. General-purpose devices such as smartphones can implement theft/loss prevention function by implementing S/W. However, other small devices lack practicality such as long-distance communication problems due to standard communication technology specifications or H/W limitations, and lack of functions(authentication and security). This study combines the Lora communication protocol in the LPWA standard environment and the blockchain technology. Anti-theft and security functions were added to the protocol, and the PBFT consensus algorithm was applied to build a blockchain network. As a result of the test, the effectiveness of safety(authentication and trust network) and performance(blockchain processing performance) were confirmed. This study aims to contribute to the future development of portable or small device anti-theft products as a 4th industrial convergence research.

• Journal of KIBIM
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• v.12 no.2
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• pp.49-59
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• 2022

The main idea of this study is to propose a BIM-based automation system drawing up a report of energy conservation plan in the architecture division. In order to obtain a building permit, an energy conservation plan must be prepared for buildings with a total floor area of 500m² or more under the current law. Currently, it is adopted as a general method to complete a report by obtaining data and drawings necessary for an energy conservation plan through manual work and input them directly into the verification system. This method takes a lot of effort and time in the design phase which ultimately increases the initial cost of the business, including the services of companies specialized in the environmental field. However, in preparation for mandatory BIM work process in the future, it is necessary to introduce BIM-based automatic creation system that has an advantage for shortening the whole process to enable rapid permission of energy-saving designs for buildings. There may be many methods of automation, but this study introduces how to build an application using Dynamo of Revit, in terms of utilizing BIM, and write an energy conservation plan by automatic completion of report through Dynamo and Excel's VBA algorithm, which can save time and cost in preparing the report of energy conservation plan compared with the manual process. Also we have insisted that the digital transformation of architectural process is a necessary for an efficient use of our automation system in the current energy conservation plan workflow.