Due to COVID-19, many paradigm shifts in existing manufacturing facilities and the expansion of non-face-to-face services are accelerating worldwide. A representative technology is digital twin technology. Such digital twin technology, which existed only conceptually in the past, has recently become feasible with the construction of a 5G-based network. Accordingly, this paper designed and implemented a part of the USB process to enable digital twins based on OPC UA communication, which is a standard interlocking structure, between real object objects and virtual reality-based USB process in accordance with this paradigm change. By reflecting the physical characteristics of real objects together, it is possible to simulate real-time synchronization of these with real objects. In the future, this can be applied to various industrial fields, and it is expected that it will be possible to reduce costs for decision-making and prevent dangerous accidents.
The prevalence of stress and depression among emotional workers is increasing due to the rapid increase in emotional labor and service workers. However, the current mental health management of emotional workers is difficult to consider the emotional response at the time of stress situations, and the existing mental health management is limited because the individual's base state is not reflected. In this study, we present mental healthcare digital twin solution technology, a personalized stress risk management solution. For mental health risk management due to emotional labor, a solution simulation is performed to accurately predict stress risk through synchronization/modeling of dynamic objects in virtual space by extracting individual stress risk factors such as emotional/physical response and environment into various modalities. It provides a mental healthcare digital twin solution for predicting personalized mental health risks that can be configured with modalities and objects tailored to the environment of emotional workers and improved according to user feedback.
Journal of the Korean Association of Geographic Information Studies
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v.27
no.3
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pp.30-42
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2024
In this paper, we presented the processing process of the sea floor mapping system using multi-beam echo-sounding data through actual measurements and the results of processing the multi-beam echo-sounding data obtained by exploring some waters of Yeosu Bay. Simultaneously and continuously observe the location and water depth of the sea using GNSS and multi-beam echo sounder, synchronization of the two data, depth correction process considering the tide level at the time of observation, 3D model of the seafloor, contour map, and longitudinal and cross-section data of the seafloor topography. In addition, by extracting efficiently the dredging volume according to the dredging area and planned water depth required for dredging construction management of submarine projects, it can be used for maintenance and management of marine construction sites and ports.
An environmental radiation monitoring system based on high pressurized ionization chamber has been used for on-line gamma monitoring surrounding the KAERI (Korea Atomic Energy Research Institute), which transmits the dose data measured from ion chamber on the site via radio frequency to a central processing computer and stores the transmitted real-time data. Although communication using radio frequency has several advantages such as effective and economical transmission, storage, and data process, there is one main disadvantage that data loss during transmission often happens because of unexpected communication problems. It is possible to restore the loss data by off-line such as floppy disk but the simultaneous process and display of current data as well as the backup data are very difficult in the present on-line system. In this work, a new electronic circuit board and the operation software applicable to the conventional environmental radiation monitoring system are developed and the automatical synchronization of the ion chamber unit and the central processing computer is carried out every day. This system is automatically able to restore the backup data within 34 hours without additional equipments and also display together the current data as well as the transmitted backup data after checking time flag.
The aim of the present recent study was to compare the protein patterns in the vaginal mucus of Hanwoo cattles during spontaneous and CIDR induced-estrus. Ten cattles, who had been observed in estrus, received no treatment and served as the group of cattles with normal spontaneous estrus. Thirteen cattles in the CIDR received an CIDR insert on day 14 were removed and cattles were injected GnRH on day 15. Vaginal mucus samples were collected from all cattles at the same time the single AI in cattles with spontaneous estrus and the AI in cattles with induced estrus. Spontaneous and CIDR-induced estrus vaginal mucus samples were analyzed on two different array surfaces: cation-exchange (CM10), anion-exchange (Q10). In addition, using the NaCl solution by which the proteins combined after washing are 0.5, 1 and 2 M, it was fractionated and a protein was collected successively. The results are summarized as follows: 1) Ionic surfaces chemistries (Q10 and CM10) gave the best results in terms of detectable protein peaks, with more than 100 protein peaks in the two fractions and under each condition. 2) Protein mass spectrometer using 11 different proteins in protein identification of 7 were able to determine the protein. List of identified proteins as follows; Ribosome-binding protein 1, GRIP 1-associated protein 1, Katanin p60 ATPase-containing subunit A-like 1, Protein FAM44A, DUF729 domain-containing protein 1, Prolactin precursor, Dihydrofolate erductase. Conclusively, on the basis of this study, protein expression in the vaginal mucus could be used as an indicator for time of estrus manifestation in order to increase conception rates by applying AI at an optional time.
Kim, Dae-Jin;Ryu, Kyung-Sang;Kim, Byungki;Jang, Moon-Seok;Ko, Hee-Sang;Yoo, Cheol
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.10
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pp.794-805
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2017
This paper proposes a Hardware-In-Loop(HIL) Simulator for a Wind Turbine and an operational control algorithm to evaluate the performance of a wind turbine control system. It provides not only for the validation of the control logics, safety functions and H/W failure, but also for the high reliability of the wind turbines (by reducing/and the reduction of the operating expense(OPEX) through performance evaluation tests with complex scenarios. On the other hand, the proposed simulator uses MATLAB, CODER, and the PLC library to operate in synchronization with the hardware, and a real-time processing-based wind turbine module including a dynamic model and control system, wind module, grid module and host PC to manage the HIL-simulator. Several experiments were carried out under the above concept to verify the effectiveness of the proposed WT HIL-simulator.
Youn, Tak;Park, Hae-Jeong;Kang, Do-Hyung;Kim, Myung-Sun;Kim, Jae-Jin;Kwon, Jun Soo
Korean Journal of Biological Psychiatry
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v.8
no.2
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pp.251-257
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2001
Backgrounds : Gamma band oscillatory activity is considered to be related to cognitive functions and illustrates that the concept of event-related oscillations bridges the gap between single neurons and neural assemblies. An event-related gamma oscillation is the time-locked responses of specific frequency, and can be identified by computing the amplitude frequency characteristics of the averaged event-related potentials(ERPs) after stimulation. Objectives : We purposed to present experimental paradigm to investigate ${\gamma}$-band oscillation activities from the recording of ERPs by using auditory oddball paradigm and investigate the difference of ${\gamma}$-band activity between schizophrenia and normal controls. Methods : The ERPs resulting from auditory stimuli with oddball paradigm in a group of schizophrenics(n=11), and also a group of age-, sex-, and handedness matched normal controls, were recorded by 128 channel EEG. The ${\gamma}$-band oscillatory activities were calculated by using time-frequency wavelet decomposition of the signal between 20 and 80Hz. The ${\gamma}$-band oscillatory activities of both groups were compared by t-test. Results : The ${\gamma}$-band oscillatory of the leads Fz, Cz, and Pz of both groups were represented well in the time-frequency maps. Significant increases of the ${\gamma}$-band activity in normal controls compared with schizophrenics were observed around 160 msec, 350 msec, and 800 msec after stimulation. Conclusions : Our results suggested that the increment in ${\gamma}$-band oscillatory activity during cognitive operations and decreased ${\gamma}$-band activity in schizophrenics may be associated with the cognitive dysfunctions and the pathophysiology of the schizophrenia.
Here we aimed to date the year and season of the resin collection from Korean red pines at Worak mountain and investigate the natural healing ability of the wounds using the tree-ring analysis technique. We determined the dating of the resin collection based on the synchronization between the ring-width time series from the wound surface of the experimental trees and the local master chronology, which is the mean time series from the sound surface on the opposite side of the wounds. For the dating of resin collection, we selected thirteen Korean red pines with resin wounds. For the investigation on the annual healing ability of the wounds, we sampled three dead trees out of 13 trees as disks. Through the comparison of the individual ring-width time series from the wounds with the local master chronology, it was verified that the resin collection was undertaken between the spring of 1962 and the autumn of 1975. The mean healing length of the wounds was 15.8 cm over the preceding 42 years, making their annual mean healing 0.38 cm. Through our study we successfully verified the healing ability of the wounded Korean red pines for the resin collection as well as the undocumented resin collection history.
Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
Journal of Intelligence and Information Systems
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v.25
no.1
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pp.163-177
/
2019
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
The Journal of Korean Institute of Communications and Information Sciences
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v.22
no.6
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pp.1210-1230
/
1997
In this paper, we suggest an architecture of DS/CDMA tranceiver composed of one pilot channel used as reference and multiple traffic channels. The pilot channel-an unmodulated PN code-is used as the reference signal for synchronization of PN code and data demondulation. The coherent demodulation architecture is also exploited for the reverse link as well as for the forward link. Here are the characteristics of the suggested DS/CDMA system. First, we suggest an interlaced quadrature spreading(IQS) method. In this method, the PN coe for I-phase 1st channel is used for Q-phase 2nd channels and the PN code for Q-phase 1st channel is used for I-phase 2nd channel, and so on-which is quite different from the eisting spreading schemes of DS/CDMA systems, such as IS-95 digital CDMA cellular or W-CDMA for PCS. By doing IQS spreading, we can drastically reduce the zero crossing rate of the RF signals. Second, we introduce an adaptive threshold setting for the synchronization of PN code, an initial acquistion method that uses a single PN code generator and reduces the acquistion time by a half compared the existing ones, and exploit the state machines to reduce the reacquistion time Third, various kinds of functions, such as automatic frequency control(AFC), automatic level control(ALC), bit-error-rate(BER) estimator, and spectral shaping for reducing the adjacent channel interference, are introduced to improve the system performance. Fourth, we designed and implemented the DS/CDMA MODEM to be used for variable transmission rate applications-from 16Kbps to 1.024Mbps. We developed and confirmed the DS/CDMA MODEM architecture through mathematical analysis and various kind of simulations. The ASIC design was done using VHDL coding and synthesis. To cope with several different kinds of applications, we developed transmitter and receiver ASICs separately. While a single transmitter or receiver ASC contains three channels (one for the pilot and the others for the traffic channels), by combining several transmitter ASICs, we can expand the number of channels up to 64. The ASICs are now under use for implementing a line-of-sight (LOS) radio equipment.
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