• Journal of IKEEE
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• v.23 no.3
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• pp.954-961
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• 2019

This paper suggests an advanced 8T SRAM which can operate properly in subthreshold voltage regime. The memory cell consists of symmetric 8 transistors, in which the latch storing data is controlled by a column-wise assistline. During the read, the data storage nodes are temporarily decoupled from the read path, thus eliminating the read disturbance. Additionally, the cell keeps the noise-vulnerable 'low' node close to the ground, thereby improving the dummy-read stability. In the write, the boosted wordline facilitates to change the contents of the memory bit. At 0.4 V supply, the advanced 8T cell achieves 65% higher dummy-read stability and 3.7 times better write-ability compared to the commercialized 8T cell. The proposed cell and circuit techniques have been verified in a 16-kbit SRAM array designed with an industrial 180-nm low-power CMOS process.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.35-40
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• 2019

Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and replace the current detection methods. Data must collected continuously in order to learn malicious code patterns that change over time. However, the process of storing and processing a large amount of malware files is accompanied by high space and time complexity. In this paper, an HDFS-based distributed processing system is designed to reduce space complexity and accelerate feature extraction time. Using a distributed processing system, we extract two API features based on filtering basis, 2-gram feature and APICFG feature and the generalization performance of ensemble learning models is compared. In experiments, the time complexity of the feature extraction was improved about 3.75 times faster than the processing time of a single computer, and the space complexity was about 5 times more efficient. The 2-gram feature was the best when comparing the classification performance by feature, but the learning time was long due to high dimensionality.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.6
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• pp.3-12
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• 2019

Current risk assessment methods typically determine accident risks embedded in construction projects by combining severity and frequency; however, they do not reflect the characteristics of construction projects. To solve the problem, this study aims to develop a novel risk assessment method that combines severity, frequency, and disaster influence factors (i.e., weather conditions and worker's characteristics) for assessing risks of activities occurring on a construction site actually. In this study, a severity was estimated by death against victims, and a frequency was estimated by the victim rate. The frequency was then converted to probability taking disaster influence factors into account. Thus, instead of considering severity and frequency for assessing the original risks (RO), the proposed method uses severity and probability to yield adjusted risks (RA) for each activity. A case study was conducted to determine if the proposed method works as intended in a real setting. The results show that RA is more sensitive to disaster influence factors than RO and, therefore, is able to assess the actual risks reflecting the working environment and conditions of a construction site. This study contributes to risk management of construction projects by offering a risk assessment method that measures a possibility of potential disasters from the probabilistic perspective. This method would help project managers assess accident risks in a more systematic and quantitative manner.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.593-600
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• 2020

The equipment for marine IoT service have to overcome the effect of seawater. Furthermore, the free floating transmitter in seawater will be less affected by the seawater environment. The results of the design and fabrication of antenna, which is embedded in buoy, are shown in this research. The proposed antenna is used to supervise the states of fishing gears in monitoring system for real-name system of electric fishing gear. The selected frequency band of the proposed antenna is 920 MHz, and PCB pattern type is selected for subminiature and light weight. It is confirmed that RF characteristics is more degraded, however, the radiation is gradually upward as the contact surface of buoy with seawater is more broaden through the simulation results. That is, the RF performance of the proposed antenna is more deteriorated but beam radiation characteristics is more suited the marine IoT, the seawater effect is more increased. It is expected that the proposed antenna will contribute the implementation of IoT network based on low power wide area (LPWA) when the degradation of RF performance will be settled.

• Journal of IKEEE
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• v.25 no.4
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• pp.762-765
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• 2021

In this paper, an automotive ECU (electronic control unit) with Kalman filter accelerator is designed and implemented. RISC-V is exploited as a processor core. Accelerator for Kalman filter matrix operation, CAN (controller area network) controller for in-vehicle network, and LIN (local interconnect network) controller are designed and embedded. Kalman filter operation consists of time update process and measurement update process. Current state variable and its error covariance are estimated in time update process. Final values are corrected from input measurement data and Kalman gain in measurement update process. Usually floating-point multiplication is exploited in software implementation, but fixed-point multiplier considering accuracy analysis is exploited in this paper to reduce hardware area. In 28nm silicon fabrication, its operating frequency, area, and gate counts are 100MHz, 0.37mm², and 760k gates, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Journal of Korea Trade
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• v.23 no.6
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• pp.131-144
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• 2019

Purpose - The purpose of this study was to investigate market power of soybeans exported by the United States to Korea. Particularly, this paper considered dichotomous characteristics of genetically modified (GM) soybeans and non-GM soybeans and conducted empirical analysis of these two segregated soybean markets to understand key tenets of market power in international soybean trade. Design/methodology - The difference in market power between GM and non-GM soybeans was analyzed using Residual Demand Elasticity (RDE) and Residual Supply Elasticity (RSE) models over the period of 2008~2018. RDE and RSE models under an imperfect competition condition were used to estimate market margins and determine whether GM and non-GM exporters or importers exercised market power in the destination market. Findings - Empirical results suggested that the U.S. had a market power on both GM and non-GM soybean exports. GM exports had greater market power than non-GM exports (14% vs. 9%). By contrast, Korea showed an inability to grab market margin or exert market power in soybean imports. Both export supply by the U.S. and import demand by Korea were found to be more responsive to price changes of GM soybeans than to prices changes of non-GM soybeans. This might be due to a self-interested, profit-seeking strategy by the exporter and many concerned consumers regarding potential adverse effects of GMOs in the importing country. Originality/value - This paper fills the literature gap by exploiting market power in both GM and non-GM markets with explicit consideration of price correlations between GM and non-GM soybeans in Korea. A number of existing studies have provided evidence for market power broadly embedded in international commodity trade. However, studies focusing on Korean markets are limited. No study has explored the country's soybean trade. Furthermore, the majority of prior studies have almost exclusively focused on the market power from a standpoint of exporting countries without discussing importers' market structure. This paper also sought to understand potentially distinguished patterns of market power between GM and non-GM markets.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.89-97
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• 2023

In this paper, we propose factors that make log analysis difficult and design technique for detecting various objects embedded in the logs which helps in the subsequent analysis. In today's IT systems, logs have become a critical source data for many advanced AI analysis techniques. Although logs contain wealth of useful information, it is difficult to directly apply techniques since logs are semi-structured by nature. The factors that interfere with log analysis are various objects such as file path, identifiers, JSON documents, etc. We have designed a BERT-based object pattern recognition algorithm for these objects and performed object identification. Object pattern recognition algorithms are based on object definition, GROK pattern, and regular expression. We find that simple pattern matchings based on known patterns and regular expressions are ineffective. The results show significantly better accuracy than using only the patterns and regular expressions. In addition, in the case of the BERT model, the accuracy of classifying objects reached as high as 99%.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.1-8
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• 2020

The similarity detection to plagiarism or duplication of computer programs requires a different type of analysis methods and tools according to the programming language used in the implementation and the sort of code to be analyzed. In recent years, the similarity appraisal for the object code in the embedded system, which requires a considerable resource along with a more complicated procedure and advanced skill compared to the source code, is increasing. In this study, we described a method for analyzing the similarity of functional units in the assembly language through the conversion of object code using the reverse engineering approach, such as the reverse assembly technique to the object code. The instruction and operand table for comparing the similarity is generated by using the syntax analysis of the code in assembly language, and a tool for detecting the similarity is designed.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.379-396
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• 2021

Purpose - The purpose of this paper is to study the rational payoff from the standpoint of foreign investors and the government when the government issues GDP-linked bonds to foreign investors. Design/methodology/approach - In this paper, the prices of 12 types of GDP-linked bond structures, which are classified according to the calculation cycle of the rate of change of linked GDP, the currency issued, and whether options are embedded, were evaluated. The Fama-French 3-factor model and the GMM-SDF model are used in the asset pricing model, and domestic and overseas investors used different basis assets. Findings - The KRW premium for US investors is estimated to be 43bp on a quarterly basis and 30bp on an annual basis, respectively, meaning that when the government issues bonds in KRW, the interest rate paid to US investors will be reduced by 30bp to 160bp (annually converted). Using the Fama-French 3 factor model, the KRW premium is the risk premium for the US market beta, meaning that if US investors do not intend to invest in US market beta, it is advantageous to receive an additional interest rate by investing in USD-denominated GDP-linked bonds. Korea's GDP- linked bond give US investors diversified investment utility, so they are willing to incorporate Korean GDP-linked bonds even if -150bp of interest is deducted from the structure issued to Korean investors. And as a result of estimating the value of the option through the GDP-linked bond with options that provides a floor for guaranteeing the principal, the value of the option linked to the annual GDP issued in dollars was the lowest. Research implications or Originality - Issuing dollar-denominated GDP-linked bonds linked to annual GDP with the option of guaranteeing the principal by the government is a way to increase investment opportunities for US investors and achieve financial stability of the government.