• Title/Summary/Keyword: Time synchronization algorithm

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Development of a Power Management System for Efficient Power usage of Intelligent Ship (지능형 선박의 효울적인 전력사용을 위한 전력 관리 시스템 개발)

  • Park, Ji-Sang;Jeon, Min-Ho;Lee, Myung-Eui
    • Journal of Advanced Navigation Technology
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    • v.17 no.6
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    • pp.609-615
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    • 2013
  • As with any ships, adequate power provision is crucial, especially on the ocean navigating ships far from the land. In order to resolve the effective and economic power supply system of any ship in operation, in this paper, we propose a power management system that intelligently controls the power supply in ships. Power management systems in this design consist of a power load detection system, a generator configuration system, and a power monitoring system respectively. The CT / PT sensor is used to measure amount of current and power in the power detection system, and according to the collected information from various sensor, the generator configuration system will switch on and off the main / sub generator effectively. Finally, the power monitoring system will display all status information of this power management system at a glance for users. This power management systems implemented in this paper is evaluated via real-time experiments, which works well as designed, and certified by KSCIEC61892-1:2012 and KSCIEC60950-1:2008.

Development of Real-time based Hardware-In-Loop Simulator for performance evaluation of wind turbine control system (풍력발전기 제어시스템 성능평가를 위한 실시간 처리 기반의 Hardware-In-Loop 시뮬레이터 개발)

  • 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.

Gauss-Newton Based Emitter Location Method Using Successive TDOA and FDOA Measurements (연속 측정된 TDOA와 FDOA를 이용한 Gauss-Newton 기법 기반의 신호원 위치추정 방법)

  • Kim, Yong-Hee;Kim, Dong-Gyu;Han, Jin-Woo;Song, Kyu-Ha;Kim, Hyoung-Nam
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.7
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    • pp.76-84
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    • 2013
  • In the passive emitter localization using instantaneous TDOA (time difference of arrival) and FDOA (frequency difference of arrival) measurements, the estimation accuracy can be improved by collecting additional measurements. To achieve this goal, it is required to increase the number of the sensors. However, in electronic warfare environment, a large number of sensors cause the loss of military strength due to high probability of intercept. Also, the additional processes should be considered such as the data link and the clock synchronization between the sensors. Hence, in this paper, the passive localization of a stationary emitter is presented by using the successive TDOA and FDOA measurements from two moving sensors. In this case, since an independent pair of sensors is added in the data set at every instant of measurement, each pair of sensors does not share the common reference sensor. Therefore, the QCLS (quadratic correction least squares) methods cannot be applied, in which all pairs of sensor should include the common reference sensor. For this reason, a Gauss-Newton algorithm is adopted to solve the non-linear least square problem. In addition, to show the performance of the proposed method, we compare the RMSE (root mean square error) of the estimates with CRLB (Cramer-Rao lower bound) and derived the CEP (circular error probable) planes to analyze the expected estimation performance on the 2-dimensional space.

Duty Cycle Scheduling considering Delay Time Constraints in Wireless Sensor Networks (무선네트워크에서의 지연시간제약을 고려한 듀티사이클 스케쥴링)

  • Vu, Duy Son;Yoon, Seokhoon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.2
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    • pp.169-176
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    • 2018
  • In this paper, we consider duty-cycled wireless sensor networks (WSNs) in which sensor nodes are periodically dormant in order to reduce energy consumption. In such networks, as the duty cycle interval increases, the energy consumption decreases. However, a higher duty cycle interval leads to the increase in the end-to-end (E2E) delay. Many applications of WSNs are delay-sensitive and require packets to be delivered from the sensr nodes to the sink with delay requirements. Most of existing studies focus on only reducing the E2E delay, rather than considering the delay bound requirement, which makes hard to achieve the balanced performance between E2E delay and energy consumption. A few study that considered delay bound requirement require time synchronization between neighboring nodes or a specific distribution of deployed nodes. In order to address limitations of existing works, we propose a duty-cycle scheduling algorithm that aims to achieve low energy consumption, while satisfying the delay requirements. To that end, we first estimate the probability distribution for the E2E delay. Then, by using the obtained distribution we determine the maximal duty cycle interval that still satisfies the delay constraint. Simulation results show that the proposed design can satisfy the given delay bound requirements while achieving low energy consumption.

Power efficiency research for application of IoT technology (사물인터넷 기술 적용을 위한 소비전력 효율화 연구)

  • Seo, Younghoon;Park, Eun-Cheol;Kang, Sunghwan;Hwang, Jae-Mun;Yun, Junghwan;Eom, Junyoung;Gwon, Hyeong-Jun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.669-672
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    • 2015
  • Recent Internet of Things (IoT, Internet of Things) that can be applied to various fields as the development of technology has been developed a lot of service and has been developed with the service also for crop management. To manage the essential elements of soil moisture in the crop growth but existing a direct person measuring the fluid point to carry the measuring instrument, if you take advantage of the WPAN (Wireless Personal Area Network) in this paper to manage sensor data, a fixed 3 points (30, 60, 90 cm) and can be managed can be scientifically analyzed the state of growth of the crop. Open field environment is utilized as it is less disturbance of the interference and the frequency of the radio frequency signal of the structure provides a relatively comfortable environment. Therefore, WPAN building and data transmission scheme of the minimum cost is to be developed. In addition, the operation to enter low power mode, the algorithm is necessary because a lot of restrictions on the power supply applied to the sensor nodes and the gateway is constructed in the open field. In the experiment, verifying the effectiveness by using a network configuration of each of the sensor nodes and the gateway, and provides a method for time synchronization of the operation and a low power mode. The study protocol for the RF communication with the LoRa and to enhance communication efficiency is needed in the future.

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A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)

  • 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
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    • 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.

Frame Transmission and Channel Changing Methods of IEEE 802.15.4 Nodes in WiFi Traffic Interference Environment (WiFi 트래픽의 간섭환경에서 IEEE 802.15.4 노드의 프레임 전송 및 채널변경 방법)

  • Song, Myong Lyol
    • Journal of Internet Computing and Services
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    • v.15 no.1
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    • pp.179-191
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    • 2014
  • In this paper, a frame transmission method to make IEEE 802.15.4 nodes run at a new channel and its characteristics are studied when they experience difficulties in transmission of frames due to WiFi traffic. The researches on evaluating the interference from WiFi traffic, searching for a new channel with little interference or not, and changing the operating channel are analyzed. In an wireless channel overlapped with IEEE 802.11 network, the transmission delay of IEEE 802.15.4 frames, the collision of frames in sending IEEE 802.15.4 frames without applying CSMA-CA algorithm, and the operation of IEEE 802.11 nodes are explained. A transmission method of frames including frame-formated code blocks in order to use the rest part of collided IEEE 802.15.4 frame is proposed. In the experiments of the proposed method, it is observed that frame-formated code blocks are synchronized and received by receivers in case of collision, and then the collided positions in IEEE 802.15.4 frame and the characteristics of frame reception rate are analyzed. The experimental results show that the performance of the proposed method is improved in comparison to an existing method when we measure the time taken to send a channel change command and get the response in order to avoid the interference from WiFi traffic.

An accuracy analysis of Cyberknife tumor tracking radiotherapy according to unpredictable change of respiration (예측 불가능한 호흡 변화에 따른 사이버나이프 종양 추적 방사선 치료의 정확도 분석)

  • Seo, jung min;Lee, chang yeol;Huh, hyun do;Kim, wan sun
    • The Journal of Korean Society for Radiation Therapy
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    • v.27 no.2
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    • pp.157-166
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    • 2015
  • Purpose : Cyber-Knife tumor tracking system, based on the correlation relationship between the position of a tumor which moves in response to the real time respiratory cycle signal and respiration was obtained by the LED marker attached to the outside of the patient, the location of the tumor to predict in advance, the movement of the tumor in synchronization with the therapeutic device to track real-time tumor, is a system for treating. The purpose of this study, in the cyber knife tumor tracking radiation therapy, trying to evaluate the accuracy of tumor tracking radiation therapy system due to the change in the form of unpredictable sudden breathing due to cough and sleep. Materials and Methods : Breathing Log files that were used in the study, based on the Respiratory gating radiotherapy and Cyber-knife tracking radiosurgery breathing Log files of patients who received herein, measured using the Log files in the form of a Sinusoidal pattern and Sudden change pattern. it has been reconstituted as possible. Enter the reconstructed respiratory Log file cyber knife dynamic chest Phantom, so that it is possible to implement a motion due to respiration, add manufacturing the driving apparatus of the existing dynamic chest Phantom, Phantom the form of respiration we have developed a program that can be applied to. Movement of the phantom inside the target (Ball cube target) was driven by the displacement of three sizes of according to the size of the respiratory vertical (Superior-Inferior) direction to the 5 mm, 10 mm, 20 mm. Insert crosses two EBT3 films in phantom inside the target in response to changes in the target movement, the End-to-End (E2E) test provided in Cyber-Knife manufacturer depending on the form of the breathing five times each. It was determined by carrying. Accuracy of tumor tracking system is indicated by the target error by analyzing the inserted film, additional E2E test is analyzed by measuring the correlation error while being advanced. Results : If the target error is a sine curve breathing form, the size of the target of the movement is in response to the 5 mm, 10 mm, 20 mm, respectively, of the average $1.14{\pm}0.13mm$, $1.05{\pm}0.20mm$, with $2.37{\pm}0.17mm$, suddenly for it is variations in breathing, respective average $1.87{\pm}0.19mm$, $2.15{\pm}0.21mm$, and analyzed with $2.44{\pm}0.26mm$. If the correlation error can be defined by the length of the displacement vector in the target track is a sinusoidal breathing mode, the size of the target of the movement in response to 5 mm, 10 mm, 20 mm, respective average $0.84{\pm}0.01mm$, $0.70{\pm}0.13mm$, with $1.63{\pm}0.10mm$, if it is a variant of sudden breathing respective average $0.97{\pm}0.06mm$, $1.44{\pm}0.11mm$, and analyzed with $1.98{\pm}0.10mm$. The larger the correlation error values in both the both the respiratory form, the target error value is large. If the motion size of the target of the sine curve breathing form is greater than or equal to 20 mm, was measured at 1.5 mm or more is a recommendation value of both cyber knife manufacturer of both error value. Conclusion : There is a tendency that the correlation error value between about target error value magnitude of the target motion is large is increased, the error value becomes large in variation of rapid respiration than breathing the form of a sine curve. The more the shape of the breathing large movements regular shape of sine curves target accuracy of the tumor tracking system can be judged to be reduced. Using the algorithm of Cyber-Knife tumor tracking system, when there is a change in the sudden unpredictable respiratory due patient coughing during treatment enforcement is to stop the treatment, it is assumed to carry out the internal target validation process again, it is necessary to readjust the form of respiration. Patients under treatment is determined to be able to improve the treatment of accuracy to induce the observed form of regular breathing and put like to see the goggles monitor capable of the respiratory form of the person.

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