• ETRI Journal
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• v.45 no.4
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• pp.603-614
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• 2023

Advancements in remote medical technologies and smart devices have led to expectations of contactless rehabilitation. Conventionally, rehabilitation requires clinicians to perform routine muscle function assessments with patients. However, assessment results are difficult to cross-reference owing to the lack of a gold standard. Thus, the application of remote smart rehabilitation systems is significantly hindered. This study analyzes the factors affecting the real-time evaluation of muscle function based on biometric sensor data so that we can provide a basis for a remote system. We acquired real clinical stroke patient data to identify the meaningful features associated with normal and abnormal musculature. We provide a system based on these emerging features that assesses muscle functionality in real time via streamed biometric signal data. A system view based on the amount of data, data processing speed, and feature proportions is provided to support the production of a rudimentary remote smart rehabilitation system.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.56-63
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• 2024

In high radiation fields, gamma cameras suffer from pulse pile-up, resulting in poor energy resolution, count losses, and image distortion. To overcome this problem, various methods have been introduced to reduce the size of the aperture or pixel, reject the pile-up events, and correct the pile-up events, but these technologies have limitations in terms of mechanical design and real-time processing. The purpose of this study is to develop a real-time gamma camera to evaluate the radioactive contamination in high radiation fields. The gamma camera is composed of a pinhole collimator, NaI(Tl) scintillator, position sensitive photomultiplier (PSPMT), signal processing board, and data acquisition (DAQ). The pulse pile-up is corrected in real-time with a field programmable gate array (FPGA) using the start time correction (STC) method. The STC method corrects the amplitude of the pile-up event by correcting the time at the start point of the pile-up event. The performance of the gamma camera was evaluated using a high dose rate ¹³⁷Cs source. For pulse pile-up ratios (PPRs) of 0.45 and 0.30, the energy resolution improved by 61.5 and 20.3%, respectively. In addition, the image artifacts in the ¹³⁷Cs radioisotope image due to pile-up were reduced.

• Journal of the Korea Safety Management & Science
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• v.8 no.4
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• pp.119-127
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• 2006

This paper deals with the middleware and S/W development of real time automatic attendance check management system using ubiquitous 900Mhz RFID(Radio Frequency Identification). This system supports the real time automatic attendance check and necessary data processing in class management. We expect to decrease the effort for class management and to upgrade the status of real time management of class.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.20-25
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• 2021

The target-object classification method was implemented using a deep-learning-based detection model in real-time images. The object detection model was a deep-learning-based detection model that allowed extensive data collection and machine learning processes to classify similar target-objects. The recognition model was implemented by changing the processing structure of the detection model and combining developed the vision-processing module. To classify the target-objects, the identity and similarity were defined and applied to the detection model. The use of the recognition model in industry was also considered by verifying the effectiveness of the recognition model using the real-time images of an actual soccer game. The detection model and the newly constructed recognition model were compared and verified using real-time images. Furthermore, research was conducted to optimize the recognition model in a real-time environment.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.300-307
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• 2010

According to growth of web, data processing technology is developing. In the Web of next generation, high-speed or high-volume data processing technologies for various wire-wireless users, USN and RFID are developing too. In this paper, we propose a high-volume data processing technology using Complex Event Processing(CEP) engine. CEP is the technology to process complex events. CEP Engine is the following characteristics. First it collects a high-volume event(data). Secondly it analyses events. Finally it lets event connect to new actions. In other words, CEP engine collects, analyses, filters high-volume events. Also it extracts events using pattern-matching for registered events and new events. As the results extracted. We use it by an input event of other work, real-time response for demanded event and can trigger to database for only valid data.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.517-524
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• 1998

This paper discusses the development of a reactive power controller using digital signal processing. Digital Signal Processing is the technique of using digital devices to Process continuous signals or data, often in real-time. And DSP algorithms are associated with a discrete time interval between input samples. When one designs a digital filter, one can use a Laplace transform to determine the continuous time frequency response. The corresponding discrete time transform is called Z transform and depends upon discrete samples of the input spaced equally in time. The objectives of this paper are to minimize real power losses and improve the power factor of a given system. Also, the implementation of a direct-form non recursive filter on the TMS320C31 has been described. The application of this microprocessor-based controller using DSP on test system reveals its numerous advantages. Performance and features of the controller for the reactive power control are analyzed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.59-63
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• 2016

Secondary damage to the user is a problem in biometrics. A brain-wave has no shape and a malicious user may not cause secondary damage to a user. However, if user sends brain-wave signals to an authentication system using a network, a malicious user could easily capture the brain-wave signals. Then, the malicious user could access the authentication system using the captured brain-wave signals. In addition, the dataset containing the brain-wave signals is large and the transfer time is long. However, user authentication requires a real-time processing, and an encryption scheme on brain-wave signals is necessary. In this paper, we propose an efficient encryption scheme using a chaos map and adaptive junk data on the brain-wave signals for user authentication. As a result, the encrypted brain-wave signals are produced and the processing time for authentication is reasonable in real-time.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1418-1432
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• 1996

In addition t improved availability, replication of data can enhance performance of distributed real-time transaction processing system by allowing transactions initiated at multiple node to be processed concurrently. To satisfy both the consistency and real-time constraints, it is necessary to integrate concurrency control and atomic commitment protocols with time-driven scheduling methods. blocking caused by existing concurrency control protocols is incompatible with time-driven scheduling because they cannot schedule transactions to meet given deadlines. To maintain consistency of replicated data and to provide a high degree of schedulability and predictability , the proposed time-driven scheduling methods integrate optimistic concurrency control protocols that minimize the duration of blocking and produce the serialization by reflecting the priority transactions. The atomicity of transactions is maintained to ensure successful commitment in distributed environment. Specific time-driven scheduling techniqueare discussed, together with an analysis of the performance of this scheduling.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.967-970
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• 2020

In a previous work we have done, we presented a monitoring system to automatically detect some dogs' behaviors from videos. However, the input video data used by that system was pre-trimmed to ensure it contained a dog only. In a real-life situation, the monitoring system would continuously receive video data, including frames that are empty and ones that contain people. In this paper, we propose a YOLOv4-based system for automatic object detection and trimming of dog videos. Sequences of frames trimmed from the video data received from the camera are analyzed to detect dogs and people frame by frame using a YOLOv4 model, and then records of the occurrences of dogs and people are generated. The records of each sequence are then analyzed through a rule-based decision tree to classify the sequence, forward it if it contains a dog only or ignore it otherwise. The results of the experiments on long untrimmed videos show that our proposed method manages an excellent detection performance reaching 0.97 in average of precision, recall and f-1 score at a detection rate of approximately 30 fps, guaranteeing with that real-time processing.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.626-631
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• 1997

This paper represents the design of a real-time image preprocessing system. The preprocessing system performs hardware-wise mask operations and thresholding operations at the speed of camera output single rate. The preprocessing system consists of the preprocessing board and the main processing board. The preprocessing board includes preprocessing unit that includes a $5\times5$ mask processor and LUT, and can perform mask and threshold operations in real-time. To achieve high-resolution image input data($20485\timesn$), the preprocessing board has a linescan camera interface. The main processing board includes the image processor unit and main processor unit. The image processor unit is equipped with TI's TMS320C32 DSP and can perform image processing algorithms at high speed. The main processor unit controls the operation of total system. The proposed system is faster than the conventional CPU based system.