• Convergence Security Journal
• /
• v.17 no.5
• /
• pp.153-161
• /
• 2017

The gain a decision by a prediction supposition future combat. Take a future combat by the method fighting of U.S. Army in the Irak war. A make combat progress is from real time information to precision bombing for a guided weapon by GPS, a intelligence satellite, a pilotless scout plane, real time simultaneous and unification combat power are the kernel element of gain a decision fighting power by network in the ground, sky, marine, universe, cyberspace. The NCW is in a sense network center war organic be connected by networking a factor of operation. Any where networking information collection, command and decision, blow system. The Study on the improvement plan for Military combat power by base of NCW abainst the future War. Construct an integrate intelligence network apply to future combat.

• The Korean Journal of Applied Statistics
• /
• v.37 no.1
• /
• pp.13-38
• /
• 2024

As economic uncertainties have increased recently due to COVID-19, there is a growing need to quickly grasp private consumption trends that directly reflect the economic situation of private economic entities. This study proposes a method of estimating private consumption in real-time by comprehensively utilizing big data as well as existing macroeconomic indicators. In particular, it is intended to improve the accuracy of private consumption estimation by comparing and analyzing various machine learning methods that are capable of fitting ultra-high-dimensional big data. As a result of the empirical analysis, it has been demonstrated that when the number of covariates including big data is large, variables can be selected in advance and used for model fit to improve private consumption prediction performance. In addition, as the inclusion of big data greatly improves the predictive performance of private consumption after COVID-19, the benefit of big data that reflects new information in a timely manner has been shown to increase when economic uncertainty is high.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.2
• /
• pp.102-111
• /
• 2023

Automatic Music Transcription (AMT) is a task that detects and recognizes musical note events from a given audio recording. In this paper, we focus on reducing the latency of real-time AMT systems on piano music. Although neural AMT models have been adapted for real-time piano transcription, they suffer from high latency, which hinders their usefulness in interactive scenarios. To tackle this issue, we explore several techniques for reducing the intrinsic latency of a neural network for piano transcription, including reducing window and hop sizes of Fast Fourier Transformation (FFT), modifying convolutional layer's kernel size, and shifting the label in the time-axis to train the model to predict onset earlier. Our experiments demonstrate that combining these approaches can lower latency while maintaining high transcription accuracy. Specifically, our modified model achieved note F1 scores of 92.67 % and 90.51 % with latencies of 96 ms and 64 ms, respectively, compared to the baseline model's note F1 score of 93.43 % with a latency of 160 ms. This methodology has potential for training AMT models for various interactive scenarios, including providing real-time feedback for piano education.

• Journal of KIISE
• /
• v.44 no.3
• /
• pp.232-238
• /
• 2017

Application response time is critical to end-user response time in Android smartphones. Due to the plentiful resources of recent smartphones, storage I/O response time becomes a major key factor in application response time. However, existing storage I/O trace tools for Android and Linux give limited information only for a specific I/O layer which makes it difficult to combine I/O information from different I/O layers, because not helpful for application developer and researchers. In this paper, we propose a novel storage I/O trace tool for Android, called AIOPro (Android I/O profiler). It traces storage I/O from application - Android platform - system call - virtual file system - native file system - page cache - block layer - SCSI layer and device driver. It then combines the storage I/O information from I/O layers by linking them with file information and physical address. Our evaluations of real smartphone usage scenarios and benchmarks show that AIOPro can track storage I/O information from all I/O layers without any data loss under 0.1% system overheads.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.643-661
• /
• 2018

This paper proposes a novel algorithm for lane detection based on inverse perspective transformation and Kalman filter. A simple inverse perspective transformation method is presented to remove perspective effects and generate a top-view image. This method does not need to obtain the internal and external parameters of the camera. The Gaussian kernel function is used to convolute the image to highlight the lane lines, and then an iterative threshold method is used to segment the image. A searching method is applied in the top-view image obtained from the inverse perspective transformation to determine the lane points and their positions. Combining with feature voting mechanism, the detected lane points are fitted as a straight line. Kalman filter is then applied to optimize and track the lane lines and improve the detection robustness. The experimental results show that the proposed method works well in various road conditions and meet the real-time requirements.

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.5
• /
• pp.480-485
• /
• 2013

Enhancing energy efficiency of machine tools causes substantial impacts on the manufacturing industries, to cope with the competitive introduction of the total energy management strategies. Real-time energy monitoring is essential to identify energy consumption patterns of the machine tools and correlate them with the energy management strategy. Integrated analysis of machine tool's operation status and the corresponding energy usage is most important to accurately evaluate the energy efficiency under the various machining process environments. This paper proposes a system architecture to realize the online energy monitoring system and the embedded energy monitoring approach interconnected with the CNC kernel. The shop-floor operation management system is presented to integrate the proposed online energy monitoring approach.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.6
• /
• pp.1301-1306
• /
• 2011

RTOS in the embedded system is a powerful tool for the design of multi-tasking. However, previous RTOS has large proportion in the MCU with limited memory. So it is difficult to apply RTOS. In this paper, I removed less frequently used features from the traditional RTOS, and designed lightweight RTOS that schedules and manages the resources with minimal code. I used techniques to obtain user memory using sharing stack, and to reduce the overhead at context. Considering ratio of kernel and applications, the RTOS designed in this paper is available on the MCU with more than 4KB of program memory.

• The Journal of Korea Robotics Society
• /
• v.15 no.4
• /
• pp.375-384
• /
• 2020

Today's robots consist of many hardware and software subsystems, depending on the functions needed for specific tasks. Integration of subsystems can require a great deal of effort, as both the communication method and protocol of the subsystem can vary. This paper proposes an expandable robotic system in which all subsystems are integrated under Robot Operation System (ROS) framework. To achieve this, the paper presents a software library, ROS_M, developed to implement the TCP/IP-based ROS communication protocol in different control environments such as MCU and RT kernel based embedded system. Then, all the subsystem including hardware can use ROS protocol consistently for communication, which makes adding new software or hardware subsystems to the robotic system easier. A latency measurement experiment reveals that the system built for loop control can be used in a soft real-time environment. Finally, an expandable mobile manipulator robot is introduced as an application of the proposed system. This robot consists of four subsystems that operate in different control environments.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.1
• /
• pp.214-221
• /
• 2007

This paper presents a myoelectric hand prosthesis(MHP) with two degree of freedom(2-DOF), which consists of a mechanical hand, a surface myoelectric sensor(SMES) for measuring myoelectric signal, a control system and a charging battery. The actuation for the 2-DOF hand functions such as grasping and wrist rotation was performed by two DC-motors, and controlled by myoelectric signal measured from the residual forearm muscle. The grip force of the MHP was automatically changed by a mechanical automatic speed reducer mounted on the hand. The skin interface of SMES was composed of the electrodes using the SUS440 metal in order to endure a wet condition due to the sweat. The sensor was embedded with a amplifier and a filter circuit for rejecting the offset voltage caused by power line noises. The control system was composed of the grip force sensor, the slip sensor, and the two controllers. The two controllers were made of a RISC-type microprocessor, and its software was executed on a real-time kernel. The control system used Force Sensing Resistors, FSR, as slip pick-ups at the fingertip of a thumb and the grip force information was obtained from a strain-gauge on the lever of the MHP. The experimental results were showed that the proposed control system is feasible for the MHP.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.26 no.8B
• /
• pp.1119-1128
• /
• 2001

본 논문에서는 이차원(2-D) 이산 웨이블릿 면환(Discrete Wavelet Transform, DWT)을 이용한 연상압축기를 FPGA 칩에서 실시간으로 동작 가능하도록 하는 효율적인 메모리 스케줄링 방법(E$^2$M$^2$)을 제안하였다. S/W적으로 위의 메모리 사상 방법을 검증한 후, 실제로 상용화된 SFRAM을 선정하여 메모리 제어기를 구현하였다. 본 논문에서는 Mallet-tree를 이용한 2-D DWT 영상압축 칩을 구현할 경우를 가정하였다. 이 알고리즘은 연산 과정에서 많은 데이터를 정장하여야 하는데, FPGA는 많은 데이터를 저장할 수 있는 메모리가 내장되어 있지 않으므로 외부 메모리를 사용하여야 한다. 외부메모리는 열(row)에 대해서만 연속(burst) 읽기, 쓰기 동작이 가능하기 때문에 Mallet-tree 알고리즘의 데이터 입출력을 그대로 적용할 경우 실시간 동작을 수행하는 DWT 압축 칩을 구현할 수 없다. 본 논문에서는 데이터 쓰기를 수행할 경우에는 메모리 셀(cell)의 수직 방향을 저장시키고 읽기를 수행할 때는 수평으로 데이터의 연속 읽기를 수행함으로써 필터가 항상 수평 방향에 위치하게 하는 방법을 제안하였다. 입방법을 C-언어로 DWT 커넬(Kernel)과 메모리의 에뮬레이터(emulator)를 구현하여 실험한 결과, Mallat-tree 이론을 그대로 적용시켰을 때와 동일한 필터링을 수행할 수 있음을 검증하였다. 또한, 상용화된 SDRAM의 메모리 제어기를 H/W로 구현하여 시뮬레이션 함으로써 본 논문에서 제안한 방법이 실제적인 하드웨어로 실시간 동작을 할 수 있음을 보였다.