• Journal of KIISE
• /
• v.42 no.1
• /
• pp.54-67
• /
• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.20 no.9
• /
• pp.914-923
• /
• 2009

Helix antennas have been widely applied to satellite TT&C, data communication and GPS receiver systems onboard military, remote sensing and communication purpose satellites. The helix antennas are known to be convenient to control impedance and radiation coverage characteristics with a maximum directivity in satellite z-axis. Waveguide horn is commonly used for radar system that needs ultra-wideband pulse for exploration ground radar and electromagnetic disability measurement etc. It has high efficiency and low reflection characteristics provided by the low-profile shape and suppressed radiation distortion. In this paper, a waveguide horn structure incorporated with helix antenna design is proposed for satellite applications that require ultra-wideband pulse radar and high rate RF data communication link to ground station over wide coverage area. The main design concern is to synthesize variable beam forming pattern based on modified horn-helix combination helicone structure such that multi-mission antenna is implemented applicable for TT&C, earth observation, high data rate transmission. Waveguide horn helps to reduce the overall antenna structure size by introduction fold type reflector connected to the tapered helix antenna. The next generation KOMPSAT satellite currently under development requires high-performance precision attitude control system. We present an initial design of a hybrid hern-helix antenna structure suitable for efficient RF communication module design of multi-purpose satellite systems.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.7
• /
• pp.11-20
• /
• 2024

In this paper, we propose the BAG (Bit-width Aware Generator) and the Intermediate Layer Knowledge Distillation using Channel-wise Attention to reduce the knowledge gap between a quantized network, a full-precision network, and a generator in GDFQ (Generative Data-Free Quantization). Since the generator in GDFQ is only trained by the feedback from the full-precision network, the gap resulting in decreased capability due to low bit-width of the quantized network has no effect on training the generator. To alleviate this problem, BAG is quantized with same bit-width of the quantized network, and it can generate synthetic images, which are effectively used for training the quantized network. Typically, the knowledge gap between the quantized network and the full-precision network is also important. To resolve this, we compute channel-wise attention of outputs of convolutional layers, and minimize the loss function as the distance of them. As the result, the quantized network can learn which channels to focus on more from mimicking the full-precision network. To prove the efficiency of proposed methods, we quantize the network trained on CIFAR-100 with 3 bit-width weights and activations, and train it and the generator with our method. As the result, we achieve 56.14% Top-1 Accuracy and increase 3.4% higher accuracy compared to our baseline AdaDFQ.

• 한국HCI학회:학술대회논문집
• /
• 2006.02a
• /
• pp.859-864
• /
• 2006

Mean shift 는 데이터의 특징을 잘 살려내는 None-parametric 방법으로, 특히 영상처리분야에서 많은 각광을 받아왔다. 하지만 좋은 결과를 보장하는 뛰어난 성능에도 불구하고, 높은 메모리소요와 긴 처리시간에 기인하여, 비디오처리 등의 분야에 적용하기엔 현실적인 제약점이 있다. 상기한 제약점을 극복하기 위해, 본 시스템은 비디오를 분석하여 전경과 후경으로 나눈다. 본 논문은 전경으로 분류된 부분에 대해 각 분리된 개체를구분하고, 좌표변환(coordinate shift)을 실행하여 연산을 할 비디오의 연산의 규모를 줄이는 방법론을 제시한다. 이러한 처리로 매우 많은 처리시간이 단축됨을 실험을 통해 알 수 있었다. 다음으로, 나뉘어진 전경에 3D mean shift를 적용하여 생성된 결과물에 대하여 3D cluster data structure 를 생성하고, 이를 이동하여 인터랙티브 에디팅이 가능하도록 하였다. 후경으로 나뉜 데이터는 이미지 한 장으로 축약이 되며, 2D mean shift 기반의 interactive cartooning system 을 통하여 만화화가 된다. 본 논문은 만화 특유의 단순한 톤을 표현하기 위해, 세밀한 분할이 필요한 부분과 그렇지 않은 부분을 따로 구분하여 처리하는 레이어처리방법을 제안한다. 위의 과정을 여러 실사이미지에 적용, 실험해본 결과 기존의 연구결과에 비해 매우 짧은 시간 내에 대상의 특징이 잘 나타낸 양질의 결과물이 생성되었다. 이러한 결과물은 출판, 영상편집분야 등 여러 분야에서 요긴하고 간편하게 사용될 수 있을 것으로 생각된다.

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.3
• /
• pp.1-6
• /
• 2004

there needs a new Geographic information system development Technology of the abstraction, encapsulation, modulation and hierarchy using Graphic representation of object modeling Technique. The method is based on composite object of Graphic data with the hierarchy concepts and abstraction of Graphic information in order to improve data abstraction of the graphic data file and described concept of multiple inheritance and classification that supports a wide variety of graphic class such as mesh unit, layer. segment and so on. in simple case of software development using SPICE model and object modeling techniques. this thesis suggested object representation of Graphic data which can reduce software development life cycle and the cost of software maintenance.

• The KIPS Transactions:PartD
• /
• v.10D no.3
• /
• pp.439-446
• /
• 2003

A crucial limitation in environments where data is broadcast to very large client populations is the low bandwidth available for clients to communicate with servers. Many advanced applications are developed in mobile computing environments, but conventional concurrency controls are not suitable because of the low bandwidth of wireless network. In this paper, we propose a new optimistic concurrency control protocol for mobile transactions. In this protocol, mobile read-only transactions can be completed locally at the clients without additional communication, only mobile update transactions are sent to the server for global validation. Our protocol reduces unnecessary aborts occurred in the previous study using only conflict information. In addition to, our algorithm can detect and resolve non-serializable execution using by data table maintained in a server.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.2
• /
• pp.187-196
• /
• 2017

The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.8C
• /
• pp.655-662
• /
• 2012

In this work, we propose an airborne cognitive radio system that searches a new spectrum band to avoid a communication interruption due to the interference from many radar signals. We develop a method of fast spectrum sensing based on an effective frequency by recognizing the interfering radar as well as geographical information. This effective frequency is calculated by the free-space path loss between a base station and a fighter with the speed parameter. From our analysis, it is verified that the maximum frequency searching time is reduced by half by using our method.

• Journal of IKEEE
• /
• v.24 no.2
• /
• pp.523-528
• /
• 2020

With a widespread of sensor-rich mobile devices, the analysis of human activities becomes more general and simpler than ever before. In this paper, we propose two deep neural networks that efficiently and accurately perform human activity recognition (HAR) using tri-axial accelerometers. In combination with powerful modern deep learning techniques like batch normalization and LSTM networks, our model outperforms baseline approaches and establishes state-of-the-art results on WISDM dataset.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.15 no.9
• /
• pp.906-913
• /
• 2004

FFT algorithm is the most popular ISAR imaging technique from radar data. It requires polar formatting technique to make a focused image of the target as MTRC(Moving Through Resolution Cell) causes a blurred image when the data is from the wide azimuth angle. But there exits the angle limit for the application of the polar formatting and we cannot obtain clear images if the range of the azimuth angle is too wide to process with polar, formatting. This paper analyses the relative merits of the polar formatting algorithm accompanied by interpolation to the CDT algorithm that needs not the interpolation.