• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.19-26
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• 2021

In fine-particle injection processing, hard fine particles, such as silicon carbide or aluminum oxide, are injected - using high-pressure air, and a small amount of material is removed by applying an impact to the workpiece by spraying at high speeds. In this study, a two-axis stage device capable of sequence control was developed to spray various shapes, such as circles and squares, on the surface during the micro-particle jetting process to understand the surface-shape micro-particle-processing characteristics. In the experimental device, two stepper motors were used for the linear movement of the two degree-of-freedom mechanism. The signal output from the microcontroller is - converted into a signal with a current sufficient to drive the stepper motor. The stepper motor rotates precisely in synchronization with the pulse-signal input from the outside, eliminating the need for a separate rotation-angle sensor. The major factors of the processing conditions are fine particles (silicon carbide, aluminum oxide), injection pressure, nozzle diameter, feed rate, and number of injection cycles. They were identified using the ANOVA technique on the design of the experimental method. Based on this, the surface roughness of the spraying surface, surface depth of the spraying surface, and radius of the corner of the spraying surface were measured, and depending on the characteristics, the required spraying conditions were studied.

• Nutrition Research and Practice
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• v.13 no.2
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• pp.105-114
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• 2019

BACKGROUND/OBJECTIVES: Several previous studies have investigated whether regular walnut consumption positively changes heart-health-related parameters. The aim of this study was to investigate the effects of daily walnut intake on metabolic syndrome (MetS) status and other metabolic parameters among subjects with MetS. SUBJECTS/METHODS: This study was a two-arm, randomized, controlled crossover study with 16 weeks of each intervention (45 g of walnuts or iso-caloric white bread) with a 6 week washout period between interventions. Korean adults with MetS (n = 119) were randomly assigned to one of two sequences; 84 subjects completed the trial. At each clinic visit (at 0, 16, 22, and 38 weeks), MetS components, metabolic parameters including lipid profile, hemoglobin A1c (HbA1c), adiponectin, leptin, and apolipoprotein B, as well as anthropometric and bioimpedance data were obtained. RESULTS: Daily walnut consumption for 16 weeks improved MetS status, resulting in 28.6%-52.8% reversion rates for individual MetS components and 51.2% of participants with MetS at baseline reverted to a normal status after the walnut intervention. Significant improvements after walnut intake, compared to control intervention, in high-density lipoprotein cholesterol (HDL-C) (P = 0.028), fasting glucose (P = 0.013), HbA1c (P = 0.021), and adiponectin (P = 0.019) were observed after adjustment for gender, age, body mass index, and sequence using a linear mixed model. CONCLUSION: A dietary supplement of 45 g of walnuts for 16 weeks favorably changed MetS status by increasing the concentration of HDL-C and decreasing fasting glucose level. Furthermore, consuming walnuts on a daily basis changed HbA1c and circulating adiponectin levels among the subjects with MetS. This trial is registered at ClinicalTrials.gov as NCT03267901.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2277-2298
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• 2019

Adaptive learning in e-learning has garnered researchers' interest. In it, learning resources could be recommended automatically to achieve a personalized learning experience. There are various ways to realize it. One of the realistic ways is adaptive learning path recommendation, in which learning resources are provided according to learners' requirements. This paper summarizes existing works and proposes an innovative approach. Firstly, a learner-centred concept map is created using graph theory based on the features of the learners and concepts. Then, the approach generates a linear concept sequence from the concept map using the proposed traversal algorithm. Finally, Learning Objects (LOs), which are the smallest concrete units that make up a learning path, are organized based on the concept sequences. In order to realize this step, we model it as a multi-objective combinatorial optimization problem, and an improved immune algorithm (IIA) is proposed to solve it. In the experimental stage, a series of simulated experiments are conducted on nine datasets with different levels of complexity. The results show that the proposed algorithm increases the computational efficiency and effectiveness. Moreover, an empirical study is carried out to validate the proposed approach from a pedagogical view. Compared with a self-selection based approach and the other evolutionary algorithm based approaches, the proposed approach produces better outcomes in terms of learners' homework, final exam grades and satisfaction.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.277-286
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• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1052-1061
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• 2019

Objective: This study was conducted to identify duck liver-expressed antimicrobial peptide 2 (LEAP-2) and demonstrate its antimicrobial activity against various pathogens. Methods: Tissue samples were collected from 6 to 8-week-old Pekin ducks (Anas platyrhynchos domesticus), total RNA was extracted, and cDNA was synthesized. To confirm the duck LEAP-2 transcript expression levels, quantitative real-time polymerase chain reaction was conducted. Two kinds of peptides (a linear peptide and a disulfide-type peptide) were synthesized to compare the antimicrobial activity. Then, antimicrobial activity assay and fluorescence microscopic analysis were conducted to demonstrate duck LEAP-2 bactericidal activity. Results: The duck LEAP-2 peptide sequence showed high identity with those of other avian species (>85%), as well as more than 55% of identity with mammalian sequences. LEAP-2 mRNA was highly expressed in the liver with duodenum next, and then followed by lung, spleen, bursa and jejunum and was the lowest in the muscle. Both of LEAP-2 peptides efficiently killed bacteria, although the disulfide-type LEAP-2 showed more powerful bactericidal activity. Also, gram-positive bacteria was more susceptible to duck LEAP-2 than gram-negative bacteria. Using microscopy, we confirmed that LEAP-2 peptides could kill bacteria by disrupting the bacterial cell envelope. Conclusion: Duck LEAP-2 showed its antimicrobial activity against both gram-positive and gram-negative bacteria. Disulfide bonds were important for the powerful killing effect by disrupting the bacterial cell envelope. Therefore, duck LEAP-2 can be used for effective antibiotics alternatives.

• Journal of Microbiology and Biotechnology
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• v.31 no.1
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• pp.8-15
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• 2021

More and more available fungal genome sequence data reveal a large amount of secondary metabolite (SM) biosynthetic 'dark matter' to be discovered. Heterogeneous expression is one of the most effective approaches to exploit these novel natural products, but it is limited by having to clone entire biosynthetic gene clusters (BGCs) without errors. So far, few effective technologies have been developed to manipulate the specific large DNA fragments in filamentous fungi. Here, we developed a fungal BGC-capturing system based on CRISPR/Cas9 cleavage in vitro. In our system, Cas9 protein was purified and CRISPR guide sequences in combination with in vivo yeast assembly were rationally designed. Using targeted cleavages of plasmid DNAs with linear (8.5 kb) or circular (8.5 kb and 28 kb) states, we were able to cleave the plasmids precisely, demonstrating the high efficiency of this system. Furthermore, we successfully captured the entire Nrc gene cluster from the genomic DNA of Neosartorya fischeri. Our results provide an easy and efficient approach to manipulate fungal genomic DNA based on the in vitro application of Cas9 endonuclease. Our methodology will lay a foundation for capturing entire groups of BGCs in filamentous fungi and accelerate fungal SMs mining.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.35-42
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• 2001

The primitive polynomial on GF(q) is used in the area of the scrambler, the error correcting code and decode, the random generator and the cipher, etc. The algorithm that generates efficiently the primitive polynomial on GF(q) was proposed by A.D. Porto. The algorithm is a method that generates the sequence of the primitive polynomial by repeating to find another primitive polynomial with a known primitive polynomial. In this paper, we propose the algorithm that is improved in the A.D. Porto algorithm. The running rime of the A.D. Porto a1gorithm is O($\textrm{km}^2$), the running time of the improved algorithm is 0(m(m+k)). Here, k is gcd(k, $q^m$-1). When we find the primitive polynomial with m odor, it is efficient that we use the improved algorithm in the condition k, m>>1.

• Smart Media Journal
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• v.11 no.4
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• pp.19-29
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• 2022

Recently, with the development of IoT technology, the number of farms using smart farms is increasing. Smart farms monitor the environment and optimise internal environment automatically to improve crop yield and quality. For optimized crop cultivation, researches on predict crop productivity are actively studied, by using collected agricultural digital data. However, most of the existing studies are based on statistical models based on existing statistical data, and thus there is a problem with low prediction accuracy. In this paper, we use various predition models for predicting the production and sales profits, and compare the performance results through models by using the agricultural digital data collected in the facility horticultural smart farm. The models that compared the performance are multiple linear regression, support vector machine, artificial neural network, recurrent neural network, LSTM, and ConvLSTM. As a result of performance comparison, ConvLSTM showed the best performance in R2 value and RMSE value.

• Journal of Veterinary Science
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• v.21 no.4
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• pp.52.1-52.11
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• 2020

Background: Intradural-intramedullary intervertebral disc extrusion (IIVDE) is a rare condition of intervertebral disc disease. However, the diagnosis of IIVDE is challenging because the prognosis and imaging characteristics are poorly characterized. Objectives: We aimed to describe the clinical and imaging characteristics of tentatively diagnosed IIVDE in dogs to assess the prognostic utility of neurological grade and magnetic resonance imaging (MRI) findings. Methods: Twenty dogs were included in this retrospective cohort study. Results: Nonchondrodystrophic breeds (n = 16) were more predisposed than chondrodystrophic breeds. Most dogs showed acute onset of clinical signs. Neurological examination at admission showed predominant non-ambulatory paraparesis (n = 9); paresis (n = 16) was confirmed more frequently than paralysis (n = 4). Follow-up neurological examination results were only available for 11 dogs, ten of whom showed neurological improvement and 8 showed successful outcomes at 1 month. The characteristic MRI findings include thoracic vertebra (T)2 hyperintense, T1 hypointense, intramedullary linear tracts with reduced disc volume, and cleft of the annulus fibrosus. None of the MRI measurements were significantly correlated with neurological grade at admission. Neurological grade did not differ according to the presence of parenchymal hemorrhage, parenchymal contrast enhancement, and meningeal contrast enhancement. Neurological grades at admission showed a statistical correlation with those observed at the 1-month follow-up (r = 0.814, p = 0.02). Conclusions: IIVDE is a rare form of disc extrusion commonly experienced after physical activity or trauma and most frequently affects the cranial-cervical and thoracolumbar regions of nonchondrodystrophic dog breeds. Neurological score at admission emerged as a more useful prognostic indicator than MRI findings in dogs with suspected IIVDE.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.157-162
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• 2023

To NP-complete 3-SAT problem, this paper proposes a O(nm) polynomial time algorithm, where n is the number of literals and m is the total frequency of all literals in equation f. The algorithm firstly decides a truth value of a literal in sequence of previously-set priority. The priority order is as follows: a literal whose occurrence in a clause is 1(k=1), a literal which is k≥2 and whose truth value is either 0 or 1, and a literal with the minimum frequency. Then, literals whose truth value is determined are then deleted from clause T and the remaining clauses. This process is repeated l times, the number of literals. As a result, the proposed algorithm has been successful in accurately determining the satisfiability of a given equation f and in deciding the truth value of all the literals. This paper, therefore, provides not only a linear-time algorithm as a viable solution to the SAT problem, but also a basis for solving the P versus NP problem.