• International Area Studies Review
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• v.22 no.3
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• pp.255-292
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• 2018

This paper evaluates the new food policy adopted by the European Union to enhance the food safety after the mad cow crisis occurred in 1990's. Newly introduced rules at the EU level are characterized by two features. Firstly, an important part of them have the form of Regulation which is a binding legislative to all member countries. Secondly, most of them are horizontally applied to the whole food industry, irrespective of their kinds of performance, hygiene or labelling. According to theoretical studies on this topic, any food safety regulation for solving adverse selection problem or reducing negative externality in food consumption should be fine-tuning depending on the concrete demand and costs conditions of the food sector concerned. In this theoretical perspective, the food safety laws introduced at EU level after mad cow crisis have been over-regulated for improving social welfare. The true motivation for the transfer of the policy competence on food safety to the Union level is political rather than economic. Our analysis with a political economic perspective shows that how the EU food regulations have been embraced not only by the governments of member countries, but also by diverse interest groups like food processor & distributors, consumers and agro-livestock groups, and that they have been used as protectionist purpose specially against non-member developing countries. Taking into account the fact that the basic aim to form the Union is to establish a single market to enhance economic efficiency at the Union level, the EU is required to adopt some policy actions to reduce negative effects of too restrictive food safety regulations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.5
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• pp.17-30
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• 2001

In this paper, we implemented a scalar multiplier needed at an elliptic curve cryptosystem over standard basis in $GF(2^{163})$. The scalar multiplier consists of a radix-16 finite field serial multiplier and a finite field inverter with some control logics. The main contribution is to develop a new fast finite field inverter, which made it possible to avoid time consuming iterations of finite field multiplication. We used an algorithmic transformation technique to obtain a data-independent computational structure of the Extended Euclid GCD algorithm. The finite field multiplier and inverter shown in this paper have regular structure so that they can be easily extended to larger word size. Moreover they can achieve 100% throughput using the pipelining. Our new scalar multiplier is synthesized using Hyundai Electronics 0.6$\mu\textrm{m}$ CMOS library, and maximum operating frequency is estimated about 140MHz. The resulting data processing performance is 64Kbps, that is it takes 2.53ms to process a 163-bit data frame. We assure that this performance is enough to be used for digital signature, encryption & decryption and key exchange in real time embedded-processor environments.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.4
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• pp.553-561
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• 2020

Water-soluble rubber asphalt-based waterproofing material, which is one of the waterproofing materials for building structures, is mainly used indoors (toilet, kitchen, balcony, etc.). In general, asphalt-based materials are used for non-exposed installation, rather than as exposed type as they do not deviate from their usual basic black pigmentation, and water-soluble rubber asphalt-based coating waterproofing materials are basically limited to indoors because of their low physical properties. Accordingly, in order to improve the tensile and elongation properties, a silane coupling agent, an inorganic filler, and a processor oil w ere added to improve the physical properties, and accordingly, the basic physical properties of the outdoor coating waterproofing material quality standard were analyzed. As a result, the water-soluble rubber asphalt coating waterproofing material compared with the exposure quality standard showed a result that exceeded the basic physical property quality standard of silicone rubber in all items under test evaluation, but the tensile strength and tear strength of the first class of urethane rubber were chloroprene. It was found that the performance compared to the quality standards of rubber-based tear strength was about 34.2% to about 40.8%.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.251-263
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• 2022

This paper presents an idea of ScanSAR image formation. For image formation of ScanSAR that utilizes the burst mode for raw signal acquisition, most conventional single burst methods essentially require a step of azimuth stitching which contributes to radiometric and phase distortions to some extent. Time-domain cross correlation could replace SPECAN which is most popularly used for ScanSAR processing. The core idea of the proposed method is that it is possible to relieve the necessity of azimuth stitching by an extension of Doppler bandwidth of the reference function to the burst cycle period. Performance of the proposed method was evaluated by applying it to the raw signals acquired by a spaceborne SAR system, and results satisfied all image quality requirements including 3 dB width, peak-to-sidelobe ratio (PSLR), compression ratio,speckle noise, etc. Image quality of ScanSAR is inferior to that of Stripmap in all aspects. However, it is also possible to improve the quality of ScanSAR image competitive to that of Stripmap if focused on a certain parameter while reduced qualities of other parameters. Thus, it is necessary for a ScanSAR processor to offer a great degree of flexibility complying with different requirements for different applications and techniques.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.109-117
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• 2021

Recently, the use of speech-based interfaces is increasing as a means for human-computer interaction (HCI). Accordingly, interest in post-processors for correcting errors in speech recognition results is also increasing. However, a lot of human-labor is required for data construction. in order to manufacture a sequence to sequence (S2S) based speech recognition post-processor. To this end, to alleviate the limitations of the existing construction methodology, a new data construction method called Back TranScription (BTS) was proposed. BTS refers to a technology that combines TTS and STT technology to create a pseudo parallel corpus. This methodology eliminates the role of a phonetic transcriptor and can automatically generate vast amounts of training data, saving the cost. This paper verified through experiments that data should be constructed in consideration of text style and domain rather than constructing data without any criteria by extending the existing BTS research.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.167-177
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• 2022

In order to obtain satellite image products using the image transmitted to the ground station after capturing the satellite images, many image pre/post-processing steps are involved. During the pre/post-processing, when converting from level 1R images to level 1G images, geometric correction is essential. An interpolation method necessary for geometric correction is inevitably used, and the quality of the level 1G images is determined according to the accuracy of the interpolation method. Also, it is crucial to speed up the interpolation algorithm by the level processor. In this paper, we proposed a lightweight CNN-based interpolation method required for geometric correction when converting from level 1R to level 1G. The proposed method doubles the resolution of satellite images and constructs a deep learning network with a lightweight deep convolutional neural network for fast processing speed. In addition, a feature map fusion method capable of improving the image quality of multispectral (MS) bands using panchromatic (PAN) band information was proposed. The images obtained through the proposed interpolation method improved by about 0.4 dB for the PAN image and about 4.9 dB for the MS image in the quantitative peak signal-to-noise ratio (PSNR) index compared to the existing deep learning-based interpolation methods. In addition, it was confirmed that the time required to acquire an image that is twice the resolution of the 36,500×36,500 input image based on the PAN image size is improved by about 1.6 times compared to the existing deep learning-based interpolation method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.181-192
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• 2022

Active vibration control system(AVCS) for helicopter enables to control the vibration generated from the main rotor and has the superb vibration reduction performance with low weight compared passive vibration reduction device. In this paper, FxLMS algorithm-based vibration control software of the light civil helicopter tansmits the control command calculated using the signals of the tachometer and accelerometers to the circular force generator(CFG) is developed and verified. According to the RTCA DO-178C/DO-331, the vibration control software is developed through the model based design technique, and real-time operation performance is evaluated in PILS(processor in-the loop simulation) and HILS(hardware in-the loop simulation) environments. In particular, the reliability of the software is improved through the LDRA-based verification coverage in the PIL environments. In order to AVCS to light civil helicopter(LCH), the dynamic response characteristic model is obtained through the ground/flight tests. AVCS configuration which exhibits the optimal performance is determined using system optimization analysis and flight test and obtain STC certification.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.