• Food Science and Preservation
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• v.20 no.3
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• pp.348-355
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• 2013

This study was conducted to analyze the sensory profiles of commercial rice cookies and snacks in the market and to provide fundamental data on the development of rice cookies and snacks. The sensory characteristics of 10 kinds of Korean commercial rice cookies and snacks were evaluated using a sensory test and were analyzed via quantitative description analysis (QDA) and principal component analysis (PCA), depending on their rice contents and processing methods. The rice cookies and snacks with less than 30% rice contents and that were fried were preferred, and their grainy attribute was related to the preference for them. Then 27 kinds of commercial rice cookies and snacks from three countries, Japan, the U.S.A. and China, were also evaluated and compared with those from Korea. While the Korean commercial rice cookies and snacks were sweet, grainy and crispy, those of Japan were not sweet and instead, were salty and crispy.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.921-930
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• 2005

In this paper, a general purpose molecular simulation system which has been developed by the author, are described. One of the most advantageous features is that the molecular simulation system can handle a coarse-grained model as well as an all-atom mode. Therefore, we can simulate mesoscopic phenomena as well as microscopic phenomena with the help of Langevin dynamics simulation and dissipative particle dynamics simulation techniques. Thus we could study anesthesia, protein folding, biopolymer flow in microchannel with single framework, which spans from microscopic to mesoscopic scales. We expect that we can also simulate many other bio/nano systems of technological importance which are not feasible by means of molecular dynamics simulation technique. Finally, performance data are shown and a bottleneck is identified for future optimization.

• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.145-152
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• 2010

Most wearable system for mobile healthcare applications consists of three parts. The first part is the sensing elements based on bio-signal, the second is the circuit module for control, data acquisition and wireless communication and control and the third is garment with a built-in electrodes and circuits. The existing healthcare garment systems have to find a solution to signal-wire and uncomfortable and inappropriate electrode to long-term attachment. Even if the wireless communication is used for healthcare garment system, the interface between sensors and circuits have to use wires. To solve these problems, this paper use electrode using PEDOT coated PVDF nanoweb for ECG signal and PVDF film sensor for respiratory signal. And, we constructed garment network using digital yarn of 10um, and transmitted ECG and respiratory signal to mobile phone through the integrated circuit with bluetooth called station To evaluate feasibility of the proposed mobile healthcare garment system, we experimented with transmission and measurement of ECG and respiratory signal using nanoweb electrode and digital yarn. We got a successful result without noise and attenuation.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.211-214
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• 2003

Current VOD embodiment way is embodied using PC base. However, achieved research that embody this by Embedded System that PC base is not. OS of this system used WindowsCE.net and x86core used having built-ined SC1200(National company's Geode's familys) by CPU and memory used 128MByte SDRAM. Used Mpeg Decoder for processing of video data, and used Enthernet Controller for Internet. Composite, component, S-Video of video output section of this system is and select one of these and connect on TV and did so that get into action. Actuality implementation manufactured necessary BIOS, WinodwsCE.NET Porting, DeviceDriver in system development and necessary simple Application in action confirmation, and Video Player used Window Media Player had included to WindowsCE.net. Therefore, treatise that see to supplement shortcomings of VOD service been embodying in current PC in Embedded System's form embody that there is sense do can.

• The Journal of Industrial Distribution & Business
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• v.9 no.12
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• pp.23-29
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• 2018

Purpose - The purpose of this study is to apply a cost effective ultrasonic odor reduction method that generated micro-bubbles using ejector to the Southeast Asian wastewater market. Research design, data, and methodology - A leather maker located in Ansan-city, Gyunggi-do, South Korea was sampled from the collection tank to select experimental materials. Experimental setup consisted of circulating water tank-air ejector-ultrasonic device, and circulating wastewater. Sample analysis was performed by CODcr, T-N, T-P, and turbidity by the National Environmental Science Institute. Results - Experimental results show that it is most effective in removing odors when the frequency range of ultrasonic wave is 60~80 Khz and the output is 200 W. It showed that the concentration of complex odor dropped from a maximum of 14,422 times to a minimum of 120 times. Also, analysis of ammonia and hydrogen sulfide in specific odor substances has shown that they were reduced from 1.5 ppm to 0.4 ppm and from 0.6 ppm to 0.1 ppm, respectively. Conclusions - It is possible to shorten more than 12 hours in the treatment of micro-organisms. It can be seen that the processing time of odor after ultrasonic treatment in the pre-treatment facility is reduced by 25% when compared to the resultant micro-organisms after the chemical treatment, that is, the time of the bio-treatment of micro-organisms. Based on the results, it was confirmed that the pre-treatment method using the ultrasonic and the air ejector device of the experiment shows the effect of reducing the water pollutants and odor more effectively in a relatively short time than the conventional advanced oxidation method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.109-114
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• 2010

In this paper, the implementation of a human signal sensing module that has capabilities to check and restore the weak signals from the human body is presented. A module presented in this paper consists of processing and sensing elements related to human pulse and body temperature and a controller implemented with SoC design method. PPG data is detected by a noise filtering process toward the amplified signal which is from the operating frequency between 0.1Hz - 10Hz. A digital temperature sensor is used to check the body temperature. A sensor outputs the corresponding value of the electric voltage according to the body temperature. Moreover, this paper discusses the implementation of an enhanced microprocessor which is synthesized with VHDL as a part of the SoC development and used to control the entire module. The SoC processor is implemented on a Xilinx Spartan 3 XC3S1000 device and has the achieved operating frequency of 10MHz. The implemented SoC processor core is successfully tested with macro memories in FPGA and the experimental results are hereby shown.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.2
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• pp.129-138
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• 2023

The proportion of agricultural products handled through the Agricultural Products Processing Center (APC) is also steadily increasing every year, and in the case of Seongju Korean melon, a total of 10 APCs of Nonghyup and farming association corporations are in operation, and the distribution ratio is about 60% based on total production. In this study, Seongju Korean melon was selected as a target to analyze the environment load during carrying (production farm ~ APC) in the production area and the transport environment load during distribution of domestic fruits, and to analyze the environmental load for handling at APC. The vertical average vibration intensity (overall G_rms of 1~250 Hz) of truck transport measured at three transport routes from Seongju Korean melon producer ~ APC, Seongju ~ Seoul and Seongju ~ Jeju was about three times larger than that in the lateral direction and 4.5 times larger than that in the longitudinal direction, respectively. The frequency of occurrence of high-amplitude events (G) in the vertical direction compared to the measuring time was deeply related to pavement conditions in the order of unpaved farm-roads, concretepaved farm-roads, and asphalt-paved main-roads, but overall G_rms for the entire frequency band is believed to have a greater impact on vehicle traveling speed than road conditions. On the other hand, the difference in the size and direction of the vibration intensity measured by the forklift truck's main-body and the attachment (fork carrier) during handling at Seongju Korean melon APC was clear, and the vibration intensity of the forklift truck's main-body was largely affected by the stiffness of the fork and the mast according to the handling weight. Based on the field-data of the transport environment during domestic distribution measured through this study, it is believed that it is possible to develop a lab-based simulation protocol for appropriate packaging design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1310-1338
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• 2023

As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behave like the normal ones, thus it is difficult to recognize them. Several intelligent approaches have been introduced to improve the detection accuracy of this type of cyber-attack, including deep learning and machine learning techniques. Moreover, dimensionality reduction methods are implemented during the preprocessing stage. This research work proposes deep Autoencoder dimensionality reduction method combined with Artificial Neural Network (ANN) classifier as botnet detection system for IoT networks/systems. Experiments were carried out using 3- layer, 4-layer and 5-layer pre-processing data from the MedBIoT dataset. Experimental results show that using a 5-layer Autoencoder has better results, with details of accuracy value of 99.72%, Precision of 99.82%, Sensitivity of 99.82%, Specificity of 99.31%, and F1-score value of 99.82%. On the other hand, the 5-layer Autoencoder model succeeded in reducing the dataset size from 152 MB to 12.6 MB (equivalent to a reduction of 91.2%). Besides that, experiments on the N_BaIoT dataset also have a very high level of accuracy, up to 99.99%.

• The Korean Journal of Malacology
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• v.32 no.3
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• pp.185-188
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• 2016

PANM-DB (version 1.0) was constructed as a web-based interface for the analysis and annotation of Next-Generation Sequencing (NGS) data of Mollusca, Arthropoda, and Nematoda. The database collected the sequences of Protostomes (Mollusca, Arthropoda, and Nematoda) from the NCBI Taxonomy Browser, and the same were compiled in a multi-FASTA format and stored using the formatdb program. This improved the processing of the RNA-seq sequences in terms of speed and hit percentage. PANM-DB has been successfully used for the transcriptome annotation of butterfly, land snail, and other commercial mollusca. We have improved the database by updating the same with new sequences and version 2.0 contains a total of 7,571,246 protein sequences (two times more as compared to version 1.0). Furthermore, the updated version contains the Cephalopoda database. The constructed web interface is available that independently analyses following these updates that is an improvement of the mollusks BLAST server. The updated version of PANM-DB will be helpful for the analysis of the NGS based sequencing data of non-model species, especially Mollusca, Arthropoda, Nematoda.