• The Journal of the Acoustical Society of Korea
• /
• v.15 no.6
• /
• pp.16-25
• /
• 1996

In this paper, we designed the chip which can classify the Korean characters using CAM(Content Addressable Memory). A high-speed OCR has been implemented by software to recognize the characters. However, it is difficult to process in real-time. The pipelined hardware implementation is one of the solution to recognize the characters in real-time by using the parallel processing techniques. We used the CAM which has the function of high-speed parallel-match to implement easily and twenty reference patterns are used for comparison. The chip has been evaluated result using DLAB of DAZIX. The simulation results have shown that the process speed was $1.6{\mu}s$ per character. Also, we programed using C-language and compared the results.

• Journal of Oriental Neuropsychiatry
• /
• v.19 no.2
• /
• pp.15-39
• /
• 2008

Objective : The objective of this study was to investigate the effects of breath meditation with neurofeedback on memory, concentration of healthy adult volunteers Method 25 healthy adult volunteers were divided into two groups. One group was treated with breath meditation and real neurofeedback, but the other group was administered with breath meditation and sham neurofeedback three times a week for 10 sessions, Before and after 10 sessions neurofeedback, all subjects were measured by cognitive functions assessment, heart rate variability, BDI, STAI, K-WAIS, HRSD, VAS about amnesia. Results : 1. Breath Meditation decreased error rate and increased concentration, cognition strength, and success rate of Cognitive Functions Assessment. Also, Breath Medication elevated IQ score of K-WAIS short form. 2. Sham : neurofeedback increased concentration, cognition strength compared to Real neurofeedback. Conclusion : The results suggest that breath meditation might effect cognitive function of healthy adult positively, but neurofeedback is not clear. In order to prove whether neurofeedback is effective or not, it should be studied more.

• Journal of Integrative Natural Science
• /
• v.14 no.4
• /
• pp.189-196
• /
• 2021

Recently, as a countermeasure for cyber breach attacks and confidential leak incidents on PC hard disk memory storage data of the metaverse industry, it is required when reviewing and developing a remote-based regular/real-time monitoring and analysis security system. The reason for this is that more than 90% of information security leaks occur on edge-end PCs, and tangible and intangible damage, such as an average of 1.20 billion won per metaverse industrial security secret leak (the most important facts and numerical statistics related to 2018 security, 10.2018. the same time as responding to the root of the occurrence of IT WORLD on the 16th, as it becomes the target of malicious code attacks that occur in areas such as the network system web due to interworking integration when building IT infrastructure, Deep-Access-based regular/real-time remote. The concept of memory analysis and audit system is key.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.49 no.7
• /
• pp.71-79
• /
• 2012

As advances in computer technology, dissemination of smartphones and tablet PCs has increased and digital media has become easily accessible. The performance of computer hardware is improved and the form of hardware is changed, but basically the change in mechanism was not occurred. Typically, the data used in the program is resident in memory during the operation because of the operating system efficiency. So, these data in memory is accessible through the memory dumps or real-time memory analysis. The user's personal information or confidential data may be leaked by exploiting data; thus, the countermeasures should be provided. In this paper, we proposed the method that minimizes user's data leakage through finding the physical memory address of the process using virtual memory address, and initializing memory data of the process.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.3
• /
• pp.304-315
• /
• 2001

In this paper, we peformed the real-time implementation of AMR(Adaptive Multi-Rate) speech coding algorithm which is adopted for IMT-2000 service using TMS320C6201, i.e., a Texas Instrument´s fixed-point DSP. With the ANSI C source code released from ETSI, optimization is performed to make it run in real-time with memory as small as possible using the C compiler and assembly language. Implemented AMR speech codec has the size of 32.06 kWords program memory, 9.75 kWords data RAM memory, and 19.89 kWords data ROM memory. And, The time required for processing one frame of 20 ms length speech data is about 4.38 ms, and it is short enough for real-time operation. It is verified that the decoded result of the implemented speech codec on the DSP is identical with the PC simulation result using ANSI C code for test sequences. Also, actual sound input/output test using microphone and speaker demonstrates its proper real-time operation without distortions or delays.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.11
• /
• pp.3077-3085
• /
• 1999

Conventional caching system doesn't support Real-Time attributes and load balance. To solve these problems, this paper describes the design and implementation of the RIOP(Real-Time Inter-ORB Protocol) to provide QoS guarantees mechanism integrating RSVP and TAO ORB. Futhermore, it provides fast XCSLS(Extended Caching System for Load Balance) implementing main memory cache in Primary Server using locality of objects. In this paper, a key feature is presented : QoS enforcement, PS(Primary Server) and RS(Replicated Server)

• Transactions of the Korean Society of Automotive Engineers
• /
• v.2 no.1
• /
• pp.106-115
• /
• 1994

A parallel integration approach is proposed for real-time simulation of controlled mechanical systems. The proposed approach, which employs the dual-rate integration method in a parallel computing environment, is developed to deal with stiffness and high frequency characteristics of the controlled mechanical systems effectively. Numerical experiments are performed to demonstrate the effectiveness of the approach in shared memory multiprocessors, Alliant FX/8 and Alliant FX/80.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.3
• /
• pp.151-158
• /
• 2024

Although on-device artificial intelligence (AI) has gained attention to diagnosing machine faults in real time, most previous studies did not consider the model retraining and redeployment processes that must be performed in real-world industrial environments. Our study addresses this challenge by proposing an on-device AI-based real-time machine fault diagnosis system that utilizes continual learning. Our proposed system includes a lightweight convolutional neural network (CNN) model, a continual learning algorithm, and a real-time monitoring service. First, we developed a lightweight 1D CNN model to reduce the cost of model deployment and enable real-time inference on the target edge device with limited computing resources. We then compared the performance of five continual learning algorithms with three public bearing fault datasets and selected the most effective algorithm for our system. Finally, we implemented a real-time monitoring service using an open-source data visualization framework. In the performance comparison results between continual learning algorithms, we found that the replay-based algorithms outperformed the regularization-based algorithms, and the experience replay (ER) algorithm had the best diagnostic accuracy. We further tuned the number and length of data samples used for a memory buffer of the ER algorithm to maximize its performance. We confirmed that the performance of the ER algorithm becomes higher when a longer data length is used. Consequently, the proposed system showed an accuracy of 98.7%, while only 16.5% of the previous data was stored in memory buffer. Our lightweight CNN model was also able to diagnose a fault type of one data sample within 3.76 ms on the Raspberry Pi 4B device.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.2E
• /
• pp.38-46
• /
• 1997

The objective of the paper is to compare the computational complexity of five algorithms for computing time-domain second-order Volterra filter outputs in terms of number of real multiplication and addition operations required for implementation. This study shows that if the filter memory length is greater that or equal to 16, the fast algorithm using the overlap-save method and the frequency-domain symmetry properties of the quadratic coefficients is the most efficient among the algorithms investigated in this paper, When the filter memory length is less than 16, the algorithm using the time-domain symmetry properties is better than any other algorithm.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.921-924
• /
• 1999

By controlling the pixels of a liquid crystal display (LCD) electronically, we fabricated a real-time moving window on a LCD, through which light passes. Using the moving window and hi-focusing lens, we suggested a non-mechanical spatio-angular multiplexed holographic memory system and demonstrated its feasibility through optical experiments. The principle of the proposed method and optical experimental results are also presented.