• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.327-335
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• 2021

In this paper, we propose an embedded robot system based on "ROS2 on Yocto" that can support various robots. We developed a lightweight OS based on the Yocto Project as a next-generation robot platform targeting cloud robotics. Yocto Project was adopted for portability and scalability in both software and hardware, and ROS2 was adopted and optimized considering a low specification embedded hardware system. We developed SLAM, navigation, path planning, and motion for the proposed robot system validation. For verification of software packages, we applied it to home cleaning robot and indoor delivery robot that were already commercialized by LG Electronics and verified they can do autonomous driving, obstacle recognition, and avoidance driving. Memory usage and network I/O have been improved by applying the binary launch method based on shell and mmap application as opposed to the conventional Python method. Finally, we verified the possibility of mass production and commercialization of the proposed system through performance evaluation from CPU and memory perspective.

• Smart Structures and Systems
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• v.32 no.1
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• pp.61-81
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• 2023

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.77-82
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• 2022

GUI(Graphical User Interface)를 대신하는 차세대 인터페이스로서 NUI(Natural User Interace)에 기대가 모이는 것은 자연스러운 흐름이다. 본 연구는 NUI의 손가락 관절을 포함한 손동작 전체를 인식시키기 위해 웹캠과 카메라를 활용하여 다양한 배경과 각도의 손동작 데이터를 수집한다. 수집된 데이터는 전처리를 거쳐 데이터셋을 구축하며, ResNet50 모델을 활용하여 전이학습한 합성곱 신경망(Convolutional Neural Network) 알고리즘 분류기를 설계한다. 구축한 데이터셋을 입력시켜 분류학습 및 예측을 진행하며, 실시간 영상에서 인식되는 손동작을 설계한 모델에 입력시켜 나온 결과를 통해 가위바위보 게임을 구현한다.

• International Journal of Knowledge Content Development & Technology
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• v.14 no.3
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• pp. 7-18
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• 2024

The present study focuses on the activities and efforts of the National Mission for Manuscripts (NMM) in the Uttar Pradesh region, which is known for its vast area, population, and rich cultural heritage. The aim is to examine the digitization work carried out by the NMM in this area, as digitization plays a crucial role in preserving our country's rich ancient heritage. The importance of safeguarding cultural heritage is universally acknowledged, and digitization serves as a vital tool in this endeavour. Through digitization, we can protect and preserve our heritage for future generations. The government has implemented several commendable initiatives for manuscript digitization, and the NMM stands as a prominent organization dedicated to the conservation of cultural heritage. The NMM possesses a diverse range of cultural heritage resources, including photographic slides, photographs, digital images, photo-negatives, motion pictures, audio spools, microfiche, LP records, endangered manuscripts, audio and videotapes, digital images, microfilms, digital audio and video files, and more. The mission has undertaken extensive digitization efforts to conserve and provide access to a significant portion of its collection. This study is unique as it explores the digital conservation and digitization practices of a premier institute working in the field of art and cultural heritage in Uttar Pradesh. With its extensive network of institutions, the mission aims to cover all manuscripts, digitize them, and consolidate them on a common platform for easy access and utilization.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.93-98
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• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.403-412
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• 2019

The characteristics of the manoeuvring motion of a ship are dependent on the ship type, as well as draft or speed in the same ship. In recent years, the number of extra-large vessels has increased significantly, which can cause enormous material and environmental damage in the event of a marine accident. Thus, the importance of ship maneuvering is increasing. The IMO has forced the officers to be trained in simulators through the STCW 95 amendment. However, FMSS is costly and difficult to access and the PC-based simulator has the disadvantage that only one person can engage in simulation. The purpose of this study was to solve the shortcomings of the FMSS and PC-based simulators by enabling multiple people to use their PCs to simulate based on a network. The simulator is implemented through the analysis and numerical calculation of the Nomoto model, Radar function mounting, data transfer protocol design, and GUI building. To verify the simulator, the simulation results were compared and analyzed with the test results of T.S. HANBADA according to the criteria of the Korean Register of Shipping(KR) and IMO standards for ship maneuverability. As a result, It showed a relative error of 0%~ 32.1% with an average of 13.7%, and it satisfied the IMO criteria for ship maneuverability.

• Journal of The Korean Association For Science Education
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• v.40 no.1
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• pp.41-50
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• 2020

Looking at the understanding of scientific concepts from a linguistic perspective, it is very important for students to develop a deep and sophisticated understanding of words used in scientific concept as well as the ability to use them correctly. This study intends to provide the basis for productive knowledge education of scientific words by noting that the foundation of productive knowledge teaching on scientific words is not well established, and by exploring ways to teach the relationship among words that constitute scientific concept in a productive and effective manner. To this end, we extracted the relationship among the words that make up the scientific concept from the text of science textbook by using quantitative text analysis methods, second, qualitatively examined the meaning of the word relationship extracted as a result of each method, and third, we proposed a writing activity method to help improve the productive knowledge of scientific concept words. We analyzed the text of the "Force and motion" unit on first grade science textbook by using four methods of quantitative linguistic analysis: word cluster, co-occurrence, text network analysis, and word-embedding. As results, this study suggests four writing activities, completing sentence activity by using the result of word cluster analysis, filling the blanks activity by using the result of co-occurrence analysis, material-oriented writing activities by using the result of text network analysis, and finally we made a list of important words by using the result of word embedding.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.426-432
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• 2021

Continuous wave (CW) Doppler radar has the advantage of being able to solve the privacy problem unlike camera and obtains signals in a non-contact manner. Therefore, this paper proposes a human activity recognition (HAR) system using CW Doppler radar, and presents the hardware design and implementation results for acceleration. CW Doppler radar measures signals for continuous operation of human. In order to obtain a single motion spectrogram from continuous signals, an algorithm for counting the number of movements is proposed. In addition, in order to minimize the computational complexity and memory usage, binarized neural network (BNN) was used to classify human motions, and the accuracy of 94% was shown. To accelerate the complex operations of BNN, the FPGA-based BNN accelerator was designed and implemented. The proposed HAR system was implemented using 7,673 logics, 12,105 registers, 10,211 combinational ALUTs, and 18.7 Kb of block memory. As a result of performance evaluation, the operation speed was improved by 99.97% compared to the software implementation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.799-808
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• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.398-407
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• 2016

We cooperated with four domestic educational astronomical observatories to construct a baseline and perform simultaneous observations to determine the geocentric parallax, distance, and motion of 1036 Ganymed, an Amor asteroid near the Earth. Observations were made on the day when simultaneous observations were possible from September to November 2011. Measured distances of 1036 Ganymed were 0.394 AU on Sept. 26, 0.365 AU on Oct. 11, and 0.340 AU on Oct. 25, respectively, which were within the error range as compared with the measured distances proposed by the US Jet Propulsion Laboratory. The 1036 Ganymed showed a tilting motion during the observation period, and the tangential angular velocities were measured at $0.037-0.052^{{\prime {\prime}}\;sec^{-1}$. Through this study, it was shown that the simultaneous observations among educational astronomical observations can obtain distance measurements with an error range of about 5% for asteroids near 0.4 AU. And it expected to be used as a research & education program emphasizing collaborative observation activities based on a network between observatories.