• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.140-147
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• 2014

In this paper, we propose a method for real-time depth image refinement. In order to improve the quality of the depth map acquired from Kinect camera, we employ constant memory and texture memory which are suitable for a 2D image processing in the graphics processing unit (GPU). In addition, we applied the joint bilateral filter (JBF) in parallel to accelerate the overall execution. To enhance the quality of the depth image, we applied the JBF hierarchically using the compute unified device architecture (CUDA). Finally, we obtain the refined depth image. Experimental results showed that the proposed real-time depth image refinement algorithm improved the subjective quality of the depth image and the computational time was 260 frames per second.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.1
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• pp.48-59
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• 2015

In recent years, there are increasing threats of rootkits that undermine the integrity of a system by manipulating OS kernel. To cope with the rootkits, in Vigilare, the snoop-based monitoring which snoops the memory traffics of the host system was proposed. Although the previous work shows its detection capability and negligible performance loss, the problem is that the proposed design is not acceptable in recent commodity mobile application processors (APs) which have become de facto the standard computing platforms of smart devices. To mend this problem and adopt the idea of snoop-based monitoring in commercial products, in this paper, we propose a snoop-based monitor design called S-Mon, which is designed for the AP platforms. In designing S-Mon, we especially consider two design constraints in the APs which were not addressed in Vigilare; the unified memory model and the crossbar switch interconnect. Taking into account those, we derive a more realistic architecture for the snoop-based monitoring and a new hardware module, called the region controller, is also proposed. In our experiments on a simulation framework modeling a productionquality device, it is shown that our S-Mon can detect the rootkit attacks while the runtime overhead is also negligible.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.417-423
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• 2017

Recently, many embedded devices that have the computing capability required for deep learning have become available; hence, many new applications using these devices are emerging. However, these embedded devices have an architecture different from that of PCs and high-performance servers. In this paper, we propose a method that improves the performance of deep-learning framework by considering the architecture of an embedded device that shares memory between the CPU and the GPU. The proposed method is implemented in Caffe, an open-source deep-learning framework, and is evaluated on an NVIDIA Jetson TK1 embedded device. In the experiment, we investigate the image recognition performance of several state-of-the-art deep-learning networks, including AlexNet, VGGNet, and GoogLeNet. Our results show that the proposed method can achieve significant performance gain. For instance, in AlexNet, we could reduce image recognition latency by about 33% and energy consumption by about 50%.

• Nuclear Engineering and Technology
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• v.31 no.3
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• pp.344-363
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• 1999

A multi-dimensional thermal-hydraulic system analysis code, MARS 1.3.1, has been developed in order to have the realistic analysis capability of two-phase thermal-hydraulic transients for pressurized water reactor (PWR) plants. As the backbones for the MARS code, the RELAP5/MOD3.2.1.2 and COBRA-TF codes were adopted in order to take advantages of the very general, versatile features of RELAP5 and the realistic three-dimensional hydrodynamic module of COBRA-TF. In the MARS code, all the functional modules of the two codes were unified into a single code first. Then, the source codes were converted into the standard Fortran 90, and then they were restructured using a modular data structure based on "derived type variables" and a new "dynamic memory allocation" scheme. In addition, the Windows features were implemented to improve user friendliness. This paper presents the developmental work of the MARS version 1.3.1 including the hydrodynamic model unification, the heat structure coupling, the code restructuring and modernization, and their verifications.their verifications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.593-600
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• 2007

Small computer systems such as mobile devices adopt NAND flash memories as their storage media. However, DBMS running on such systems are optimized to hard disks. When small computer systems use DBMS they usually use additional system layer, like FTL, that emulates flash memories as normal hard disks and DBMS cannot control flash memories directly. In this paper, we propose unified storage system that DBMS controls flash memories directly. We implemented the system in a real environment and proved the proposed system outperforms legacy systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.436-447
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• 2014

The major elements of avionics system architecture are requirements, Real Time Operating System, message communication, memory, and data format etc. Herein describes a state-of-the-art development trend for the avionics system architecture, system requirements and data bus among the major elements of avionics system. While, domestic technology has been tried to Integrated Modular Avionics(IMA) system based on the Avionics Full Duplex Switched Ethernet(AFDX) technology during Light Attack Helicopter(LAH) project in Korea, but not yet proved as the product case in Full Scale Development Phase. The avionics system architecture considering the domestic inexperience of the IMA system architecture are suggested for the Next-generation Corps Unmanned Aircraft System.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• The Korean Journal of Emergency Medical Services
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• v.25 no.1
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• pp.105-124
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• 2021

Purpose: This study aims to identify the present handover status and the difference in performance and importance of handover between 119 paramedics and emergency department (ED) staff to improve the quality of handover. Methods: The study involved a questionnaire survey of 171 paramedics and 108 ED staff in four regions from August 28 to September 23, 2020. Subsequently, 279 questionnaires were collected and 277 copies were used for this study. Data were analyzed by SPSS 26.0 version. Results: The results showed that most of the paramedics and the ED staff rely on memory and verbally handover, without formal education about the handover process. And there were significant differences in performance in important information of prehospital. Some of the handover items were a difference in performance and importance between the paramedics and the ED staff. Conclusion: The unified education based on required and optional items is necessary to reduce the loss of information between the paramedics and ED staff, and standardized tools need to be developed in the handover process.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.493-499
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• 2009

Three methods frequently used for Hangul display in computer systems are Standard Johab Code in which each of Hangul consonants and vowels is given a 5-bit code and each syllable created by combining them forms a 2-byte code, Standard Wansung Code in which each of all the syllables generally used for Hangul presentation forms a 2-byte code, and Unicode in which each syllable in most of the world's language systems is given a unique code so that it allows computers to consistently represent and manipulate them in a unified manner. An embedded system in general has a lower processing power and a limited amount of storage space, compared to a personal compute(PC) system. According to its usage, however, the former may have a processing power equal to that of the latter. Hence, when Hangul display needs to be adopted, an embedded system must choose a display method suitable for its own resource environment. This paper introduces a TFT LCD initialization method and pixel display functions of an LN2440SBC embedded board on which an LP35, a 3.5" TFT LCD kit, is attached. Using the initialization and pixel display functions, in addition, we compare three aforementioned Hangul display methods, in terms of their processing speeds and amounts of memory space required. According to experiments, Standard Johab Code requires less amount of memory space but more processing time than Standard Wansung Code, and Unicode requires the largest amount of memory space but the least processing time.