• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.77-83
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• 2022

Nand flash memory requires an Erase-Before-Write operation structurally. In order to solve this problem, it can be solved by classifying a page (hot data page) where data update operation occurs frequently and storing it in a separate block. The MHF (Multi Hash Function Framework) technique records the frequency of data update requests in the system memory, and when the recorded value exceeds a certain standard, the data update request is judged as hot data. However, the method of simply counting only the frequency of the data update request has a limit in judging it as accurate hot data. In addition, in the case of a technique that determines the persistence of a data update request, the fact of the update request is recorded sequentially based on a time interval and then judged as hot data. In the case of such a persistence-based method, its implementation and operation are complicated, and there is a problem of inaccurate judgment if frequency is not considered in the update request. This paper proposes a lightweight hot data determination technique that considers both frequency and persistence in data update requests.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1180-1187
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• 2022

As the likelihood of occurrence of the localized microbursts or severe flooding is increased due to the unusual weather changes, it is the very urgent problem to detect these weather hazards with a local weather radar. For a local weather radar of this purpose, it is essential to detect the low altitude and the fast varying weather conditions. Therefore, the very fast update of the weather information and the efficient clutter removal is very important. To achieve this goal, the appropriate method should be applied which does not need the mechanical elevation scanning and has the capability of the efficient clutter removal. Therefore, in this paper, the usefulness of the implementation of elevational filter banks with the spatial FFT algorithm was analyzed and investigated using a simple array antenna. It is shown that the suggested method can be used for both the minimization of the ground clutter and the fast update of weather information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.76-86
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• 2023

Radars used by air-crafts have two important characteristics; First, they should have a real-time signal processing system finishing signal processing before deadline while getting and processing successive in-phase and quadrature data. Second, they can cover a lot of modes including A2A(Air to Air), A2G(Air to Gound), A2S(Air to Sea), and Ground Map(GM). So the structure of radar signal processing SWs in modern airborne radars are becoming more complicate. Also, the implementation of radar signal processing SW needs to reuse common code blocks between other modes for efficiency or change some of the code blocks into alternative algorithm blocks. These are the reason why the radar signal processing SW framework suggested in this paper is taking advantage of modular programming. This paper proposes an modular framework applicable on the airborne radar signal processing SW maintaining the real-time characteristic using the signal processing procedures for A2G/A2S as examples.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.117-124
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• 2021

Livestock behavioral analysis is a factor that has a great influence on livestock health management and agricultural productivity increase. However, most digital devices introduced for behavioral analysis of livestock do not provide raw data and also provide limited analysis results. Such a closed system makes it more difficult to integrate data and build big data, which are essential for the introduction of advanced IT technologies. Therefore, it is necessary to supply farm-scale data collection devices that can be easily used at low cost. This study presents a data collection system for analyzing the behavior of livestock. The system consists of a number of miniature computing units that operate wirelessly, and collects livestock body temperature and acceleration data, location information, and livestock environment data. In addition, this study presents an algorithm for estimating the behavior of livestock based on the collected acceleration data. For the experiment, a system was built in a Korean cattle farm in Icheon, Gyeonggi-do, and data were collected for 20 Korean cattle, and based on this, the empirical and analysis results were presented.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.149-155
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• 2022

The popularity of e-commerce systems on the Internet is increasing day by day, and the recommendation system, as a core function of these systems, greatly reduces the effort to search for desired products by recommending products that customers may prefer. The collaborative filtering technique is a recommendation algorithm that has been successfully implemented in many commercial systems, but despite its popularity and usefulness in academia, the memory-based implementation has inaccuracies in its reference neighbor. To solve this problem, this study proposes a new time-aware collaborative filtering technique that integrates and utilizes the neighbors of each item and each user, weighting the recent similarity more than the past similarity with them, and reflecting it in the recommendation list decision. Through the experimental evaluation, it was confirmed that the proposed method showed superior performance in terms of prediction accuracy than other existing methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.977-984
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• 2022

Recently, with the economic development of Southeast Asia, the use of information devices is widely spreading, and the demand for application services using intelligent character recognition is increasing. This paper discusses deep learning-based feature extraction and recognition of Myanmar, one of the Southeast Asian countries. Myanmar alphabet (33 letters) and Myanmar numerals (10 numbers) are used for feature extraction. In this paper, the number of nine features are extracted and more than three new features are proposed. Extracted features of each characters and numbers are expressed with successful results. In the recognition part, convolutional neural networks are used to assess its execution on character distinction. Its algorithm is implemented on captured image data-sets and its implementation is evaluated. The precision of models on the input data set is 96 % and uses a real-time input image.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1059-1068
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• 2022

A Post-Quantum Cryptographic algorithm NTRU, which is designed by considering the computational power of quantum computers, satisfies the mathematically security level. However, it should consider the characteristics of side-channel attacks such as power analysis attacks in hardware implementation. In this paper, we verify that the private key can be recovered by analyzing the power signal generated during the decryption process of NTRU. To recover the private keys, the Simple Power Analysis (SPA), Correlation Power Analysis (CPA) and Differential Deep Learning Analysis (DDLA) were all applicable. There is a shuffling technique as a basic countermeasure to counter such a power side-channel attack. Neverthe less, we propose a more effective method. The proposed method can prevent CPA and DDLA attacks by preventing leakage of power information for multiplication operations by only performing addition after accumulating each coefficient, rather than performing accumulation after multiplication for each index.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.751-757
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• 2021

In this paper, we proposed a pipeline system for holographic image production in a web server-based environment. There are time and spatial constraints for the existing holographic image production. The purpose of the proposed system is to obtain high-quality holographic images by reducing accessibility to users. It is a structure in which a video captured by a user in a web environment is transmitted to a server and converted into a frame for holographic image production through post-production. For high-quality holographic image acquisition, post-processing uses a deep learning-based algorithm. The proposed system provides various service tools in the web environment for user convenience. Through this method, the user's accessibility is improved when producing holographic images because images are taken in a web environment rather than in a limited space.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.79-85
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• 2022

Internet of Things (IoT) connects devices with various platforms, computing power, and functions. Due to the diversity of networks and the ubiquity of IoT devices, demands for security and privacy are increasing. Therefore, cryptographic mechanisms must be strong enough to meet these increased requirements, while at the same time effective enough to be implemented in devices with long-range specifications. In this paper, we present the performance and memory limitations of modern cryptographic primitives and schemes for different types of devices that can be used in IoT. In addition, detailed performance evaluation of the performance of the most commonly used encryption algorithms in low-spec devices frequently used in IoT networks is performed. To provide data protection, the binary ring uses encryption asymmetric fully homomorphic encryption and symmetric encryption AES 128-bit. As a result of the experiment, it can be seen that the IoT device had sufficient performance to implement a symmetric encryption, but the performance deteriorated in the asymmetric encryption implementation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.77-82
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• 2022

The effect of indoor air pollution on the human body is greater and more dangerous than outdoor air pollution. In general, a person stays indoors for a long time, and in a closed room, pollutants are continuously accumulated and the polluted air is better delivered to the lungs. Especially in the case of young children, it is very sensitive to indoor air and it is fatal. In addition, methods to reduce indoor air pollution, which cannot be ventilated with more frequent indoor activities and continuously increasing external fine dust due to Covid 19, are becoming more important. In order to improve the problems of the existing autonomous driving air purifying robot, this paper divided the map and Upper Confidence bounds applied to Trees(UCT) based algorithm to solve the problem of the autonomous driving robot not sterilizing a specific area or staying in one space continuously, and the problem of children who are vulnerable to indoor air pollution. We propose a space-adaptive autonomous driving air purifying robot for a green smart school that can be improved.