• Resources Recycling
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• v.32 no.6
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• pp.45-53
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• 2023

This study discussed the trend and future strategy of adsorption technology R&D to effectively recover ammonia emitted from the livestock fields. A proper ammonia adsorbent should incorporate acidic or hydrogen bonding functional groups on the surface, as well as a high specific surface area and a good surface structure appropriate for ammonia adsorption. Activated carbon and minerals such as zeolite have widely been used as ammonia adsorbents, but their adsorption effects are generally low, so any improvement through surface modification should be necessary. For example, incorporation of metal chloride included in a porous adsorbent can promote ammonia adsorption effectiveness. Recently, new types of adsorbents such as MOFs (Metal-Organic Frameworks) and POPs (Porous Organic Polymers) have been developed and utilized. They have shown very high ammonia adsorption capacity because of adjustable and high specific surface area and porosity. In addition, Prussian Blue exhibited high ammonia adsorption and desorption performance and selectivity. This looks relatively advantageous in relation to the recovery of ammonia from livestock waste discharge. In the future, further research should be made to evaluate ammonia adsorption/desorption efficiency and purity using various adsorbents under conditions suitable for livestock sites. Also, effective pre- and/or post-treatment processes should be integrated to maximize ammonia recovery.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Informatization Policy
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• v.30 no.4
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• pp.40-61
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• 2023

The adoption of smart factories and smart manufacturing as strategies to enhance competitiveness and stimulate growth in the manufacturing sector is vital for a country's future competitiveness and industrial transformation. The government has consistently pursued smart manufacturing innovation policies starting with the Manufacturing Innovation 3.0 strategy in the Ministry of Industry. This study aims to identify policy areas for smart factories and smart manufacturing based on technical standards. Analyzing policy areas at the current stage where the establishment and support of domestic standards aligning with international technical standards are required is crucial. By prioritizing smart manufacturing process areas within the industry, policymakers can make well-informed decisions to advance smart manufacturing without blindly following international standardization in already well-established areas. To achieve this, the study utilizes a hierarchical analysis method including expert interviews and importance-performance analysis for the five major process areas. The findings underscore the importance of proactive participation in standardization for emerging technologies, such as data and security, instead of solely focusing on areas with extensive international standardization. Additionally, policymakers need to consider carbon emissions, energy costs, and global environmental challenges to address international trends in export and digital trade effectively.

• Informatization Policy
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• v.30 no.4
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• pp.3-39
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• 2023

With the growing importance of information/information system, information security is emphasized, and the significance of information security audit as a tool for maintaining the proper security level is increasing as well. The objectives of the study are to identify the overall research trends and to propose future research areas by analyzing domestic and overseas research in the area. To achieve the objectives, 103 research papers were analyzed based on both general and subject-related criteria. The following are the major research results : In terms of research approach, more empirical studies are needed; For subject "Auditor," studies to develop a framework for related variables (e.g., capability) are needed; For subject "Audit Activities/Procedures," future research should focus on the process/results of detailed audit activities; Future domestic research for "Audit Areas" should look for the new technology/industry/security areas covered by foreign studies; For "Audit Objective/Impact," studies to define the variables (e.g., performance and quality) systematically and comprehensively are needed; For "Audit Standard/Guidelines," research on model/guideline needs to be continued.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.576-583
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• 2023

This study aimed to investigate the impact of enhancing the electrode conductivity and mitigating the production of hydrogen peroxide - a by-product arising from lactate oxidation - on the performance of lactate electrodes. The electrical conductivity of the electrode was improved by modifying the surface of carbon paper with single-walled carbon nanotubes. Catalase was introduced to effectively eliminate the hydrogen peroxide produced during the lactate oxidation reaction. The carbon paper electrode, with simultaneous immobilization of both lactate oxidase and catalase, yielded a current 1.7 times greater than the electrode where only lactate oxidase was immobilized. The electrode in which lactate oxidase and catalase were co-immobilized on the surface of carbon paper modified with single-walled carbon nanotubes, produced a current of 171 µA, which was more than twice as much current as the carbon paper with only lactate oxidase immobilized. The optimized electrode showed a linear response up to lactate concentration of 20 mM, confirming that it can be used as a sensor electrode.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.239-246
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• 2023

In this paper, we propose an open-loop algorithm to classify speech and music signals using the spectral flux parameters and Mel Frequency Cepstral Coefficients(MFCC) parameters for the audio coder. To increase responsiveness, the MFCC was used as a short-term feature parameter and spectral fluxes were used as a long-term feature parameters to improve accuracy. The overall voice/music signal classification decision is made by combining the short-term classification method and the long-term classification method. The Gaussian Mixed Model (GMM) was used for pattern recognition and the optimal GMM parameters were extracted using the Expectation Maximization (EM) algorithm. The proposed long-term and short-term combined speech/music signal classification method showed an average classification error rate of 1.5% on various audio sound sources, and improved the classification error rate by 0.9% compared to the short-term single classification method and 0.6% compared to the long-term single classification method. The proposed speech/music signal classification method was able to improve the classification error rate performance by 9.1% in percussion music signals with attacks and 5.8% in voice signals compared to the Unified Speech Audio Coding (USAC) audio classification method.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.113-123
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• 2023

This paper introduces the Cherry system, a user-independent blockchain donation system. This is a procedure that is delivered to the beneficiary's bank account through a virtual account when a donor makes a donation, so there is no difference from the existing donation delivery method from the user's point of view However, within the blockchain, Cherry Points, a virtual currency based on the user ID, are issued and delivered to the beneficiary, while all transactions and the beneficiary's usage history are managed on the blockchain. By adopting this method, there was an improvement in blockchain performance, with transaction processing exceeding 1,000 TPS in typical transaction condition and service completion within 21.3 seconds. By applying the automatic influence control algorithm to this system, the influence according to stake, which is an individual donation, is greatly reduced to 0.3 after 2 months, thereby concentrating influence could be controlled automatically. In addition, it was designed to enable micro tracking by adding a tracking function by timestamp to the donation ledger for each individual ID, which greatly improved the transparency in the use of donations. From a service perspective, existing blockchain donation systems were handled as limited donation delivery methods. Since it is a direct service in a user-independent method, convenience has been greatly improved by delivering donations in various forms.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1693-1705
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• 2023

Rural areas, which account for about 90% of the country's land area, are increasing in importance and value as a space that performs various public functions. However, facilities that adversely affect residents' lives, such as livestock facilities, factories, and solar panels, are being built indiscriminately near residential areas, damaging the rural environment and landscape and lowering the quality of residents' lives. In order to prevent disorderly development in rural areas and manage rural space in a planned manner, detection and monitoring of hazardous facilities in rural areas is necessary. Data can be acquired through satellite imagery, which can be acquired periodically and provide information on the entire region. Effective detection is possible by utilizing image-based deep learning techniques using convolutional neural networks. Therefore, U-Net model, which shows high performance in semantic segmentation, was used to classify potentially hazardous facilities in rural areas. In this study, KOMPSAT ortho-mosaic optical imagery provided by the Korea Aerospace Research Institute in 2020 with a spatial resolution of 0.7 meters was used, and AI training data for livestock facilities, factories, and solar panels were produced by hand for training and inference. After training with U-Net, pixel accuracy of 0.9739 and mean Intersection over Union (mIoU) of 0.7025 were achieved. The results of this study can be used for monitoring hazardous facilities in rural areas and are expected to be used as basis for rural planning.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.91-97
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• 2023

Electrochemical (EC) CO₂ reduction is a promising method to convert CO₂ into valuable hydrocarbon fuels and chemicals ecofriendly. Here, we report on a facile method to synthesize surface-controlled SnO₂/Cu(OH)₂ nanowires (NWs) and its EC reduction of CO₂ to HCOOH and CO. The SnO₂/Cu(OH)₂ NWs (-16 mA/cm²) showed superior electrochemical performance compared to Cu(OH)2 NWs (-6 mA/cm²) at -1.0 V (vs. RHE). SnO₂/Cu(OH)₂ NWs showed the maximum Faradaic efficiency for conversion to HCOOH (58.01 %) and CO (29.72 %). The optimized catalyst exhibits a high C1 Faradaic efficiency stable electrolysis for 2 h in a KHCO₃ electrolyte. This study facilitates the potential for the EC reduction of CO₂ to chemical fuels.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1139-1147
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• 2023

The purpose of this paper is to present and evaluate the performance of a method for controlling the dose for optimal image acquisition while minimizing patient exposure by applying a small-sized Photomultiplier(SiPM) sensor inside a portable detector. Portable detectors have the advantage of being able to quickly access the patient's location for rapid diagnosis, but this mobility comes with the challenge of dose control. This paper presents a method to identify the dose that can have the DQE and optimal image quality of the detector through image evaluation based on IEC62220-1-1, an international standard for X-ray imaging devices, and to identify the optimal dose by matching the ADU of the image and the output of the SiPM Sensor. The Skull AP image was acquired by implementing the detector manufacturer's reference dose. The optimal dose was 342.8 µGy, and the optimal controlled dose was 148.3 µGy, which is 57 % of the manufacturer's reference dose. The Chest AP image was 81.9 µGy and the optimal controlled dose was 27.9 µGy, which is a high dose reduction effect of 66 %. In addition, the two images were analyzed by five radiologists and found to have no clinically significant difference in anatomical delineation.