• Food Science and Industry
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• v.54 no.3
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• pp.132-144
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• 2021

Along with the rise in the value of cryptocurrency, the interest of the blockchain is very high. However, most people do not understand cryptocurrency and blockchain very well. In addition, due to this lack of understanding of the technology, ideas about how blockchain technology can be applied in the food industry may not come up. Therefore, this content describes the advantages of blockchain technology in terms of security, starting with the understanding and operation method of cryptocurrency and blockchain technology, and briefly describes the development of a blockchain system. And simple examples of how this blockchain technology can be applied to other industries are summarized, and examples used in the food industry are summarized. Finally, it was insisted that using such a blockchain technology can provide safe food to consumers.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.111-121
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• 2021

As the main carrier of information, digital image is becoming more and more important. However, with the popularity of image acquisition equipment and the rapid development of image editing software, in recent years, digital image counterfeiting incidents have emerged one after another, which not only reduces the credibility of images, but also brings great negative impacts to society and individuals. Image copy-paste tampering is one of the most common types of image tampering, which is easy to operate and effective, and is often used to change the semantic information of digital images. In this paper, a method to protect the authenticity and integrity of image content by studying the tamper detection method of image copy and paste was proposed. In view of the excellent learning and analysis ability of deep learning, two tamper detection methods based on deep learning were proposed, which use the traces left by image processing operations to distinguish the tampered area from the original area in the image. A series of experimental results verified the rationality of the theoretical basis, the accuracy of tampering detection, location and classification.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.83-96
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• 2018

Electronic medical records in the hospital information system are the important evidence related to the crime and are subject to search and seizure. In the case of a large general hospital, it is possible to search for seizures through cooperation of the staff, but it is impossible in small hospitals. The investigation agency copies the database of electronic medical records and then selects relevant content. This approach has an issue of excessive search and seizure. In this paper, we propose field selection procedures and methods for electronic medical records while ensuring integrity, reproducibility, and chain of custody. Currently, it is necessary to study the procedures and methods of search and seizure of medical information system so that it can respond to next changing cloud hospital information system.

• Journal of the Korean Society of Food Culture
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• v.36 no.1
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• pp.1-27
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• 2021

Eumsikjeoljo (integrity with food) originally came from the Andong district, where the Goseong Yi clan inherited a cookbook from their ancestor Lee Jeong-Rong (1798~1871). The cookbook was written in an antiquated style and is estimated to have been written around the year 1865. Details of the era and authorship are seldom available for the extant ancient cookbooks. The authors of these books and the period during which these books were precisely written were studied through the Eumsikjeoljo which is a repository of 46 cooking disciplines. Of these 10 deal with the practice of traditional Korean crispy snack making, 4 with rice cake making, 3 of the yeonbyeong kind, 19 examples of Korean side dish making, 6 recipes of the kimchi variety, 2 examples of paste-based recipes, and 2 instances of instructions on how to make vinegar-based extracts. Also, in Eumsikjeoljo, there are descriptions of 29 different ways to brew rice wine. Of these, Danyang wine among the Leehwa wines and 13 others account for over 44% of the content. Leeyang wine and Sogok wine are represented by 10 different varieties and constitute around 34% of the entries. Samyang wine and Baek-il wine, along with 6 others, constitute 21% of the entries. The secret recipes of the Goseong Yi clan in the Andong district were recorded so that they could be transferred to the descendants of the clan. An inspection of the recipes and wine brewing techniques recorded in Eumsikjeoljo provides a clearer picture of the mid-1800s Andong noble family's traditional food habits and simultaneously sheds light on the late Joseon dynasty's food culture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3694-3722
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• 2022

In today's globalized world, there is no transparency in exchanging data and information between producers and consumers. However, these tasks experience many challenges, such as administrative barriers, confidential data leakage, and extensive time delays. To overcome these challenges, we propose a decentralized, secured, and verified smart chain framework using Ethereum Smart Contract which employs Inter Planetary File Systems (IPFS) and MongoDB as storage systems to automate the process and exchange information into blocks using the Tendermint algorithm. The proposed work promotes complete traceability of the product, ensures data integrity and transparency in addition to providing security to their personal information using the Lelantos mode of shipping. The Tendermint algorithm helps to speed up the process of validating and authenticating the transaction quickly. More so in this time of pandemic, it is easier to meet the needs of customers through the Ethermint Smart Chain, which increases customer satisfaction, thus boosting their confidence. Moreover, Smart contracts help to exploit more international transaction services and provide an instant block time finality of around 5 sec using Ethermint. The paper concludes with a description of product storage and distribution adopting the Ethermint technique. The proposed system was executed based on the Ethereum-Tendermint Smart chain. Experiments were conducted on variable block sizes and the number of transactions. The experimental results indicate that the proposed system seems to perform better than existing blockchain-based systems. Two configuration files were used, the first one was to describe the storage part, including its topology. The second one was a modified file to include the test rounds that Caliper should execute, including the running time and the workload content. Our findings indicate this is a promising technology for food supply chain storage and distribution.

• Journal of Pharmacopuncture
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• v.25 no.4
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• pp.369-381
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• 2022

Objectives: Hyperlipidemia (HL) is a major cause of ischemic heart diseases. The size-limiting effect of ischemic preconditioning (IPC), a cardioprotective phenomenon, is reduced in HL, possibly because of the opening of the mitochondrial permeability transition pore (MPTP). The objective of this study is to see what effect pretreatment with Inula racemose Hook root extract (IrA) had on IPC-mediated cardioprotection on HL Wistar rat hearts. An isolated rat heart was mounted on the Langendorff heart array, and then ischemia reperfusion (I/R) and IPC cycles were performed. Atractyloside (Atr) is an MPTP opener. Methods: The animals were divided into ten groups, each consisting of six rats (n = 6), to investigate the modulation of I. racemosa Hook extract on cardioprotection by IPC in HL hearts: Sham control, I/R Control, IPC control, I/R + HL, I/R + IrA + HL, IPC + HL, IPC + NS + HL, IPC + IrA+ HL, IPC + Atr + oxidative stress, mitochondrial function, integrity, and hemodynamic parameters are evaluated for each group. Results: The present experimental data show that pretreatment with IrA reduced the LDH, CK-MB, size of myocardial infarction, content of cardiac collagen, and ventricular fibrillation in all groups of HL rat hearts. This pretreatment also reduced the oxidative stress and mitochondrial dysfunction. Inhibition of MPTP opening by Atr diminished the effect of IrA on IPC-mediated cardioprotection in HL rats. Conclusion: The study findings indicate that pretreatment with IrA e restores IPC-mediated cardioprotection in HL rats by inhibiting the MPTP opening.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.139-148
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• 2023

Current food-traceability platforms suffer from problems such as inconsistent traceability standards, a lack of public credibility, and slow access to data. In this work, a combined code and identification method was designed that can achieve more secure product traceability using the dual anti-counterfeiting technology of a QR code and a hidden code. When the QR code is blurry, the hidden code can still be used to effectively identify food information. Based on this combined code, a food-safety traceability platform was developed. The platform follows unified encoding standards and provides standardized interfaces. Based on this innovation, the platform not only can serve individual food-traceability systems development, but also connect existing traceability systems. These will help to solve the problems such as non-standard traceability content, inconsistent processes, and incompatible system software. The experimental results show that the combined code has higher accuracy. The food-safety traceability platform based on the combined code improves the safety of the traceability process and the integrity of the traceability information. The innovation of this paper is invoking the combined code united the QR code's rapidity and the hidden code's reliability, developing a platform that uses a unified coding standard and provides a standardized interface to resolve the differences between multi-food-traceability systems. Among similar systems, it is the only one that has been connected to the national QR code identification platform. The project has made profits and has significant economic and social benefits.

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.314-314
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• 2022

In the production of rice flour, wet milling is a method of milling rice after soaking it in water, and it takes a lot of time and cost from milling to drying. To overcome this problem, the floury type rice was developed for dry milling and it is known to have round starch granules, low content of damaged starch after milling, and a starch structure similar to wheat. Because of its unique properties different from normal rice, it is necessary to research on processing and characteristics of floury-type rice to expand its utility in the food industry. Therefore, this study aimed to prepare the pregelatinized floury type rice (Baromi2) by autoclave and investigate their physicochemical properties. As the heat treatment time increased, the brightness decreased from 83.8 to 76.8, however, both redness and yellowness increased from 0.57 to 4.5 and from 14.58 to 21.13, respectively. Despite of same treatment time, soaking in water (10 min) before autoclaving increased the solubility and swelling power of Baromi2 over 2 times. The peak viscosity of native Baromi2 was over 2000 RVU, on the other hand, there was a significantly decrease to less than 1000 RVU of pregelatinized Baromi2. Heat treatment without immersion caused partial gelatinization of starch, resulting that some starch granules maintaining their integrity. Whereas there were no starch granules in heat treatment with soaking in water due to complete gelatinization. This study would be helpful to the suggestion of using heat-treated floury-type rice as an intermediate material in the food industry in the future.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.17-25
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• 2024

The Voids in the Mineral Aggregate (VMA) within asphalt mixtures play a crucial role in defining the mixture's structural integrity, durability, and resistance to environmental factors. Accurate prediction and optimization of VMA are essential for enhancing the performance and longevity of asphalt pavements, particularly in varying climatic and environmental conditions. This study introduces a novel machine learning framework leveraging ensemble machine learning model for predicting VMA in asphalt mixtures. By analyzing a comprehensive set of variables, including aggregate size distribution, binder content, and compaction levels, our framework offers a more precise prediction of VMA than traditional single-model approaches. The use of advanced machine learning techniques not only surpasses the accuracy of conventional empirical methods but also significantly reduces the reliance on extensive laboratory testing. Our findings highlight the effectiveness of a data-driven approach in the field of asphalt mixture design, showcasing a path toward more efficient and sustainable pavement engineering practices. This research contributes to the advancement of predictive modeling in construction materials, offering valuable insights for the design and optimization of asphalt mixtures with optimal void characteristics.