• Korean Journal of Remote Sensing
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• 제20권6호
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• pp.419-425
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• 2004

This study has proposed a data fusion method based on the Dempster-Shafer evidence theory The Dempster-Shafer fusion uses mass functions obtained under the assumption of class-independent Gaussian assumption. In the Dempster-Shafer approach, uncertainty is represented by 'belief interval' equal to the difference between the values of 'belief' function and 'plausibility' function which measure imprecision and uncertainty By utilizing the Dempster-Shafer scheme to fuse the data from multiple sensors, the results of classification can be improved. It can make the users consider the regions with mixed classes in a training process. In most practices, it is hard to find the regions with a pure class. In this study, the proposed method has applied to the KOMPSAT-EOC panchromatic image and LANDSAT ETM+ NDVI data acquired over Yongin/Nuengpyung. area of Kyunggi-do. The results show that it has potential of effective data fusion for multiple sensor imagery.

• Journal of the Korea Society for Simulation
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• 제19권4호
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• pp.209-218
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• 2010

The aim of the study on the tactical object representation techniques in synthetic environment is on acquiring fundamental techniques for detection and tracking of tactical objects, and evaluating the strategic situation in the virtual ground. In order to acquire these techniques, there need the tactical objects' position tracking and evaluation, and an inter-sharing technique between tactical models. In this paper, we study the algorithms on the sensor data fusion and coordinate conversion, proportional navigation guidance(PNG), and pursuit-evasion technique for engineering and higher level models. Additionally, we simulate the position evaluation of tractical objects using the pursuit and evasion maneuvers between a submarine and a torpedo.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제48권2호
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• pp.127-137
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• 2011

We have developed a wearable device that can convert sensor data into real-time step counts and activity levels. Sensor data on gait were acquired using a triaxial accelerometer. A test was performed according to a test protocol for different walking speeds, e.g., slow walking, walking, fast walking, slow running, running, and fast running. Each test was carried out for 36 min on a treadmill with the participant wearing a portable gas analyzer (K4B2), an Actical device, and the device developed in this study. The signal vector magnitude (SVM) was used to process the X, Y, and Z values output by the triaxial accelerometer into one representative value. In addition, for accurate step-count detection, we used three algorithms: an heuristic algorithm (HA), the adaptive threshold algorithm (ATA), and the adaptive locking period algorithm (ALPA). A regression equation estimating the energy expenditure (EE) was derived by using data from the accelerometer and information on the participants. The recognition rate of our algorithm was 97.34%, and the performance of the activity conversion algorithm was better than that of the Actical device by 1.61%.

• Ecology and Resilient Infrastructure
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• 제6권4호
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• pp.243-249
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• 2019

The purpose of this study is to analyze the reflectance of bed materials according to changes in the water level using a drone-based hyperspectral sensor. For this purpose, we took hyperspectral images of bed materials such as soil, gravel, cobble, reed, and vegetation to compare and analyze the spectral data of each material. To adjust the water level, we constructed an experimental channel to control the discharge and installed the bed materials within the channel. In this study, we configured 3 cases according to the water level (0.0 m, 0.3 m, 0.6 m). After the imaging process, we used the mean value of 10 points for each bed material as analytical data. According to the analysis, each material showed a similar reflectance by wavelength and the intrinsic reflectance characteristics of each material were shown in the visible and near-infrared region. Also, the deeper the water level, the lower the peak reflectance in the visible and near-infrared region, and the rate of decrease differed depending on the bed material. We expect the intrinsic properties of these bed materials to be used as basic research data to evaluate river environments in the future.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• 제6권1호
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• pp.37-42
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• 2010

The stay cylinder weld at the steam generator of Korean Standard Nuclear Power Plants is safety class I component and is subjected to be inspected by the volumetric examination such as ultrasonic method. As accessibility of this area is limited due to the narrow space and high radiation, the existing manual inspection method involves various difficulties. Moreover operators may be exposed to internal contamination by contaminated dust during the surface buffing process to improve the inspection reliability of this area. Recently the new automatic inspection system for stay cylinder welds has been developed. The inspection system basically consists of a driving assembly, data acquisition device and signal processing units. The driving assembly is classified by 1) the scanner for inspecting and buffing the weld, 2) pillars for guiding the scanner and 3) the base frame for loading and supporting pillars. The scanner has 4 sensor modules to inspect in 4 refracted angles and 4 incident directions. These components can be inserted into the skirt of the stay cylinder through the manway hole and assembled easily by one-touch in the skirt. Data acquisition device and signal processing units developed in previous works are also newly upgraded for better processing of data analysis and evaluation. The system has been successfully demonstrated not only in the mock-up but also in the field. In this paper, newly developed inspection system for the stay cylinder weld of the steam generator is introduced and their field applications are discussed.

• Journal of Advanced Navigation Technology
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• 제13권3호
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• pp.319-326
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• 2009

In this paper, the key technologies of Navigation receiver for GNSS sensor station are presented as a development result of a GNSS ground station in ETRI. A wide-band antenna and RF/IF components and SW signal processing unit to cover the GPS and Galileo signals for GNSS receiver are developed and its performance is verified by using GPS live signal and GNSS RF signal simulator from SpirentTM. We also gather GIOVE-A signal by using H/W antenna and RF/IF units in IF-level as sampling frequency and bit number, 112MHz and 8bits, respectively by using the developed wide-band antenna and RF/IF components. Data acquisition is done by using commercial data acquisition device from National Instrument TM. The gathered data is fed into SW receiver to process Galileo E1 to verify Galileo signal processing by Galileo live signal from GIOVE-A.

• IEMEK Journal of Embedded Systems and Applications
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• 제11권2호
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• pp.97-105
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• 2016

Microcontrollers (MCUs) for endpoint smart sensor devices of internet-of-thing (IoT) are being implemented as system-on-chip (SoC) with on-chip instruction flash memory, in which user firmware is embedded. MCUs directly fetch binary code-based instructions through bit-line sense amplifier (S/A) integrated with on-chip flash memory. The S/A compares bit cell current with reference current to identify which data are programmed. The S/A in reading '0' (erased) cell data consumes a large sink current, which is greater than off-current for '1' (programmed) cell data. The main motivation of our approach is to reduce the number of accesses of erased cells by binary code level transformation. This paper proposes a built-in write/read path architecture using binary code inversion method based on hot-spot region detection of instruction code access to reduce sensing current in S/A. From the profiling result of instruction access patterns, hot-spot region of an original compiled binary code is conditionally inverted with the proposed bit-inversion techniques. The de-inversion hardware only consumes small logic current instead of analog sink current in S/A and it is integrated with the conventional S/A to restore original binary instructions. The proposed techniques are applied to the fully-custom designed MCU with ARM Cortex-M0$^{TM}$ using 0.18um Magnachip Flash-embedded CMOS process and the benefits in terms of power consumption reduction are evaluated for Dhrystone$^{TM}$ benchmark. The profiling environment of instruction code executions is implemented by extending commercial ARM KEIL$^{TM}$ MDK (MCU Development Kit) with our custom-designed access analyzer.

• Journal of Biosystems Engineering
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• 제40권3호
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• pp.165-177
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• 2015

Purpose: Accurate monitoring of soil strength is a key technology applicable to various precision agricultural practices. Soil strength has been traditionally measured using a cone penetrometer, which is time-consuming and expensive, making it difficult to obtain the spatial data required for precision agriculture. To improve the current, inefficient method of measuring soil strength, our objective was to develop and evaluate an in-situ system that could measure horizontal soil strength in real-time, while moving across a soil bin. Methods: Multiple cone-shape penetrometers were horizontally assembled at the front of a vertical plow blade at intervals of 5 cm. Each penetrometer was directly connected to a load cell, which measured loads of 0-2.54 kN. In order to process the digital signals from every individual transducer concurrently, a microcontroller was embedded into the measurement system. Wireless data communication was used between a data storage device and this real-time horizontal soil strength (RHSS) measurement system travelling at 0.5 m/s through an indoor experimental soil bin. The horizontal soil strength index (HSSI) measured by the developed system was compared with the cone index (CI) measured by a traditional cone penetrometer. Results: The coefficient of determination between the CI and the HSSI at depths of 5 cm and 10 cm ($r^2=0.67$ and 0.88, respectively) were relatively less than those measured below 20 cm ($r^2{\geq}0.93$). Additionally, the measured HSSIs were typically greater than the CIs for a given numbers of compactor operations. For an all-depth regression, the coefficient of determination was 0.94, with a RMSE of 0.23. Conclusions: A HSSI measurement system was evaluated in comparison with the conventional soil strength measurement system, CI. Further study is needed, in the form of field tests, on this real-time measurement and control system, which would be applied to precision agriculture.

• Korean Journal of Construction Engineering and Management
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• 제14권5호
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• pp.153-163
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• 2013

As recent buildings have been more higher and larger, construction vertical lifting planning and operation is a key factor for successful project in tall building. Although many studies have been trying to set up a construction lifting planning system at early stage, there's not existing a control real-time lift operation control system with respect to during construction stage. Therefore, In this study, we use the sensor device to collect the lift operating data for improvement of lift operation efficiency and develope optimum lift operating system which can perform real-time analysis. Finally, we verify the efficiency of proposed system through comparison between realtime operating data and simulated data using proposing system. In this paper, the proposed system show more efficient moving line compared with previous system. This can contribute to development of unmanned lift system.