• Journal of IKEEE
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• v.25 no.4
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• pp.625-633
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• 2021

This paper describes a scalable architecture for flexible hardware implementation of Montgomery modular multiplication. Our scalable modular multiplier architecture, which is based on a one-dimensional array of processing elements (PEs), performs word parallel operation and allows us to adjust computational performance and hardware complexity depending on the number of PEs used, N_PE. Based on the proposed architecture, we designed a scalable Montgomery modular multiplier (sMM) core supporting eight field sizes defined in SEC2. Synthesized with 180-nm CMOS cell library, our sMM core was implemented with 38,317 gate equivalents (GEs) and 139,390 GEs for N_PE=1 and N_PE=8, respectively. When operating with a 100 MHz clock, it was evaluated that 256-bit modular multiplications of 0.57 million times/sec for N_PE=1 and 3.5 million times/sec for N_PE=8 can be computed. Our sMM core has the advantage of enabling an optimized implementation by determining the number of PEs to be used in consideration of computational performance and hardware resources required in application fields, and it can be used as an IP (intellectual property) in scalable hardware design of elliptic curve cryptography (ECC).

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.48-48
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• 2010

Sound quality and NVH-issues(Noise, Vibration and Harshness) of vehicles has become very important for car manufacturers. It is interpreted as among the most relevant factors regarding perceived product quality, and is important in gaining market advantage. The general sound quality of vehicles was gradually improved over the years. However, today the development cycles in the automotive industry are constantly reduced to meet the customers' demands and to react quickly to market needs. In addition, new drive and fuel concepts, tightened ecological specifications, increase of vehicle classes and increasing diversification(increasing market for niche vehicles), etc. challenge the acoustic engineers trying to develop a pleasant, adequate, harmonious passenger cabin sound. Another aspect concerns the general pressure for reducing emission and fuel consumption, which lead to vehicle weight reductions through material changes also resulting in new noise and vibration conflicts. Furthermore, in the context of alternative powertrains and engine concepts, the new objective is to detect and implement the vehicle sound, tailored to suit the auditory expectations and needs of the target group. New questions must be answered: What are appropriate sounds for hybrid or electric vehicles? How are new vehicle sounds perceived and judged? How can customer-oriented, client-specific target sounds be determined? Which sounds are needed to fulfil the driving task, and so on? Thus, advanced methods and tools are necessary which cope with the increasing complexity of NVH-problems and conflicts and at the same time which cope with the growing expectations regarding the acoustical comfort. Moreover, it is exceedingly important to have already detailed and reliable information about NVH-issues in early design phases to guarantee high quality standards. This requires the use of sophisticated simulation techniques, which allow for the virtual construction and testing of subsystems and/or the whole car in early development stages. The virtual, testing is very important especially with respect to alternative drive concepts(hybrid cars, electric cars, hydrogen fuel cell cars), where complete new NVH-problems and challenges occur which have to be adequately managed right from the beginning. In this context, it is important to mention that the challenge is that all noise contributions from different sources lead to a harmonious, well-balanced overall sound. The optimization of single sources alone does not automatically result in an ideal overall vehicle sound. The paper highlights modern and innovative NVH measurement technologies as well as presents solutions of recent NVH tasks and challenges. Furthermore, future prospects and developments in the field of automotive acoustics are considered and discussed.

• Journal of Platform Technology
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• v.10 no.4
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• pp.47-55
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• 2022

Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• Smart Media Journal
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• v.11 no.7
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• pp.76-84
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• 2022

In Korea, where rice is the staple food, there are many cases in which the nutritional composition of food is different at the same weight, even though the same ingredients are used and the food or food name is the same. The cause is closely related to the moisture content of the food according to the cooking method and cooking process. In order to design a diet tailored to individual health and supply accurate calories and nutrients, a method of expressing food data that is not affected by the cooking process or cooking method is required. Usually, the same ingredients or foods show a lot of deviation from the nutritional components presented in the standard food database due to the difference in moisture content. For this reason, there are problems that increase the complexity of the food ingredient database and the difficulty in using it. As a method to improve these problems, we would like to propose a food data expression method based on dry weight. As an example of this, the characteristics of rice as a food material and changes in major nutritional components according to the change in moisture of various rice-processed foods made from rice were considered. In addition, as an example of how to normalize food data through this, the dry weight-based nutrition label of rice was presented.

• Convergence Security Journal
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• v.24 no.1
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• pp.51-57
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• 2024

Although industrial control systems (ICSs) recently keep evolving with the introduction of Industrial IoT converging information technology (IT) and operational technology (OT), it also leads to a variety of threats and vulnerabilities, which was not experienced in the past ICS with no connection to the external network. Since various control command messages are sent to field devices of the ICS for the purpose of monitoring and controlling the operational processes, it is required to guarantee the message integrity as well as control center authentication. In case of the conventional message integrity codes and signature schemes based on symmetric keys and public keys, respectively, they are not suitable considering the asymmetry between the control center and field devices. Especially, compromised node attacks can be mounted against the symmetric-key-based schemes. In this paper, we propose message authentication scheme based on double hash chains constructed from cryptographic hash function without introducing other primitives, and then propose extension scheme using Merkle tree for multiple uses of the double hash chains. It is shown that the proposed scheme is much more efficient in computational complexity than other conventional schemes.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.501-506
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• 2024

Humans have been shown to engage in multitasking behavior when searching for information on two or more topics or searching an information system at the same time. When processing multiple information tasks, priorities must be established as there are cognitive and physical limitations in processing multiple information tasks at once. The level of cognitive attention involved in multitasking behavior can vary depending on the complexity and importance of the information task. The objectives of this study are to understand: (a) the relationship between attention and information task prioritization behavior when people interact with information retrieval systems to find information for multiple tasks; (b) The effect of the degree of attention on information task prioritization behavior when people interact with an IR system to find information for multiple tasks. A review of the relevant literature shows that when people interact with information retrieval systems to find information for multiple tasks, their level of attention affects how they prioritize multiple information tasks. It should be noticed that people pay more attention to things they find interesting or important. Human-centered system design based on a conceptual understanding of multitasking is discussed.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.165-174
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• 2010

The numerical modeling of a coal gasification reaction occurring in an entrained flow coal gasifier is presented in this study. The purposes of this study are to develop a reliable evaluation method of coal gasifier not only for the basic design but also further system operation optimization using a CFD(Computational Fluid Dynamics) method. The coal gasification reaction consists of a series of reaction processes such as water evaporation, coal devolatilization, heterogeneous char reactions, and coal-off gaseous reaction in two-phase, turbulent and radiation participating media. Both numerical and experimental studies are made for the 1.0 ton/day entrained flow coal gasifier installed in the Korea Institute of Energy Research (KIER). The comprehensive computer program in this study is made basically using commercial CFD program by implementing several subroutines necessary for gasification process, which include Eddy-Breakup model together with the harmonic mean approach for turbulent reaction. Further Lagrangian approach in particle trajectory is adopted with the consideration of turbulent effect caused by the non-linearity of drag force, etc. The program developed is successfully evaluated against experimental data such as profiles of temperature and gaseous species concentration together with the cold gas efficiency. Further intensive investigation has been made in terms of the size distribution of pulverized coal particle, the slurry concentration, and the design parameters of gasifier. These parameters considered in this study are compared and evaluated each other through the calculated syngas production rate and cold gas efficiency, appearing to directly affect gasification performance. Considering the complexity of entrained coal gasification, even if the results of this study looks physically reasonable and consistent in parametric study, more efforts of elaborating modeling together with the systematic evaluation against experimental data are necessary for the development of an reliable design tool using CFD method.