• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.537-539
• /
• 2016

Recently, unmanned technologies interest increased. An unmanned boat is not directly on people and radio can be controlled by boat. Used for military unmanned boat was first developed in the United States Navy. In recent years, for hobby, for pesticide application, for water activities, expanding exploration in various ways, including for use. The role of a variety of unmanned boat above, In the case of a variety of unmanned probe of the role of unmanned boat on the boat people who don't be able to come to the vision of the advantage can not be exploring places like blind spot. In this paper, The Blind Spot are explorations of places such as streaming real-time as possible, an unmanned boat using Raspberry Pi that support implementation. Receiver input signals of an unmanned boat to the transmitter under the manipulation of, using smartphones hotspot feature Raspberry Pi and smartphones, network connection. Via Raspberry Pi motion of using real-time streaming using unmanned boat.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.20 no.3
• /
• pp.113-120
• /
• 2010

Content security and privacy protection are important issues in emerging network-based video surveillance applications. Especially, satisfying both real-time constraint and energy efficiency with embedded system-based video sensors is challenging since the battery-operated sensors need to compress and protect video content in real-time. In this paper, we propose a multicore-based solution to compress and protect video surveillance data, and evaluate the effectiveness of the solution in terms of both real-time constraint and energy efficiency. Based on the experimental results with MPEG2/AES software, we confirm that the multicore-based solution can improve the energy efficiency of a singlecore-based solution by a factor of 30 under the real-time constraint.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.10A
• /
• pp.886-895
• /
• 2005

As the networked media technology have been grown in recent, there have been many research works to deliver high-quality video such as HDV and HDTV over the Internet. To realize high-quality media service over the Internet, however, the network adaptive streaming scheme is required to adopt to the dynamic fluctuation of underlying networks. In this paper, we design and implement the network-adaptive HD(high definition) MPEG-2 streaming system employing the frame-based prioritized packetization. Delivered video is inputted from the JVC HDV camera to the streaming sewer in real-time. It has a bit-rate of 19.2 Mbps and is multiplexed to the MPEG-2 TS (MPEG-2 MP@HL). For the monitoring of network status, the packet loss rate and the average jitter are measured by using parsing of RTP packet header in the streaming client and they are sent to the streaming server periodically The network adaptation manager in the streaming server estimates the current network status from feedback packets and adaptively adjusts the sending rate by frame dropping. For this, we propose the real-time parsing and the frame-based prioritized packetization of the TS packet. The proposed system is implemented in software and evaluated over the LAN testbed. The experimental results show that the proposed system can enhance the end-to-end QoS of HD video streaming over the best-effort network.

• Journal of Biomedical Engineering Research
• /
• v.19 no.5
• /
• pp.469-476
• /
• 1998

In the case of acquisition and displaying medical Images such as ultrasonography and endoscopy on VGA monitor of PC system, image degradation of tear-drop appears through scan conversion. In this study, we compare several methods which can solve this degradation and implement the hardware system that resolves this problem in real-time with PC. It is possible to represent high quality image display and real-time processing and acquisition with specific de-interlacing device and PCI bridge on our hardware system. Image quality is improved remarkably on our hardware system. It is implemented as PC-based system, so acquiring, saving images and describing text comment on those images and PACS networking can be easily implemented.metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

• The KIPS Transactions:PartC
• /
• v.18C no.4
• /
• pp.265-278
• /
• 2011

The objective of this paper is to analyze and characterize end-to-end packet statistics after modeling and simulation of WiFi (IEEE 802.11g) and WiMAX (IEEE 802.16e) of a virtual wireless network using OPNET Modeler Wireless Suite. Wireless internal and external network simulators such as Remcom's Wireless InSite Real Time (RT) module, WinProp: W-LAN/Fixed WiMAX/Mobile WiMAX, and SMI system, are designed to consider data transfer rate based on wireless propagation signal strength. However, we approached our research in a different perspective without support for characteristic of these wireless network simulators. That is, we will discuss the purpose of a visual analysis for these packets, how to receive each point packets (e.g., wireless user, base station or access point, and http server) through end-to-end virtual network modeling based on integrated wired and wireless network without wireless propagation signal strength. Measuring packet statistics is important in QoS metric analysis among wireless network performance metrics. Clear packet statistics is an especially essential metric in guaranteeing QoS for WiMAX users. We have found some interesting results through modeling and simulation for virtual wireless network using OPNET Modeler Wireless Suite. We are also able to analyze multi-view efficiency through experiment/observation result.

• International Journal of Highway Engineering
• /
• v.12 no.4
• /
• pp.61-70
• /
• 2010

The purpose of this study is to analyze the accuracy of traffic volume forecast by comparing an estimated to real traffic volume. For this study, total 10 sections of national highways, which are planned in 1980s and 1990s, were selected and traffic analysis data for highway construction were collected. In addition, targeted 10 sections were categorized into network-related and -unrelated sections. In the analysis of inaccuracy between the estimated and real traffic, for network-related sections, appeared to have lower inaccuracy. As time goes on after traffic open, inaccuracy between the estimated and real traffic appeared to be lower. In various section lengths, the longer the section length, the higher the inaccuracy is. Using 3 years passed data after traffic open, national highway have lower inaccuracy than expressway. However, the traffic analysis according to traffic open time resulted in little change of the inaccuracy.

• International Journal of Computer Science & Network Security
• /
• v.23 no.7
• /
• pp.186-192
• /
• 2023

Malwares are becoming a major problem nowadays all around the world in android operating systems. The malware is a piece of software developed for harming or exploiting certain other hardware as well as software. The term Malware is also known as malicious software which is utilized to define Trojans, viruses, as well as other kinds of spyware. There have been developed many kinds of techniques for protecting the android operating systems from malware during the last decade. However, the existing techniques have numerous drawbacks such as accuracy to detect the type of malware in real-time in a quick manner for protecting the android operating systems. In this article, the authors developed a hybrid model for android malware detection using a decision tree and KNN (k-nearest neighbours) technique. First, Dalvik opcode, as well as real opcode, was pulled out by using the reverse procedure of the android software. Secondly, eigenvectors of sampling were produced by utilizing the n-gram model. Our suggested hybrid model efficiently combines KNN along with the decision tree for effective detection of the android malware in real-time. The outcome of the proposed scheme illustrates that the proposed hybrid model is better in terms of the accurate detection of any kind of malware from the Android operating system in a fast and accurate manner. In this experiment, 815 sample size was selected for the normal samples and the 3268-sample size was selected for the malicious samples. Our proposed hybrid model provides pragmatic values of the parameters namely precision, ACC along with the Recall, and F1 such as 0.93, 0.98, 0.96, and 0.99 along with 0.94, 0.99, 0.93, and 0.99 respectively. In the future, there are vital possibilities to carry out more research in this field to develop new methods for Android malware detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.1
• /
• pp.109-118
• /
• 2016

Traffic congestions are rapidly increasing in urban areas. In order to reduce these problems, it needs real-time data and intelligent techniques to quickly identify traffic activities with useful information. This paper proposes a Fuzzy Domain Ontology(FDO)-based opinion mining system to monitor the transportation network in real-time as well to make a city polarity map for travelers. The proposed system retrieves tweets and reviews related to transportation activities and a city. The feature opinions are extracted from these tweets and reviews and then used FDO to identify transportation and city features polarity. This FDO and intelligent prototype are developed using $Prot{\acute{e}}g{\acute{e}}$ OWL (Web Ontology Language) and JAVA, respectively. The experimental result shows satisfactory improvement in tweets and review's analyzing and opinion mining.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.1-6
• /
• 2008

Data grid shares distributed large data via wide-band network. Such grid environment consumes much time for large data transmission. Because it is implemented on internet as physical network. Many replication strategies were proposed for solving this problem, but they are not optimal in real Data grid environments. Because they were proposed that based on logical topology without consideration of real internet architecture. Grid data access time is largely influenced by internet architecture as physical network of Data grid. In this paper, we propose a new data replication strategy RSIA(Replication Strategy based on Internet Architecture) based on internet architecture. The RSIA places replicas considering structural hierarchy in each element of internet, and avoid the performance bottlenecks to reduce system performance degradation when a data transfer. Through simulation, we show that the proposed RSIA data replication strategy improves the performance of Data Grid environment compared with previous strategies.

• Journal of Hydrogen and New Energy
• /
• v.24 no.3
• /
• pp.264-274
• /
• 2013

Piping systems play an important role in gas and oil transferring system. In the piping system, there are many elements, such as valves and flow meters. In order to check their normal operating conditions, each signal from each element is displayed on the monitor in the pipe control room. By the way, there are several accidental cases in the piping system even if all signals from the local elements are judged to be normal on the monitor in the control room. Further, opposite cases often happen even the monitor shows abnormal while the local elements work normal. To overcome this abnormal functions, it is not so easy to construct the environment in which sensors detecting the working states of all elements installed in the piping system. In this paper, a new non-contact measurement technique which can calculate the elements' delicate displacements by using a PIV(particle image velocimetry) and diagnose their working states by using a neural network is proposed. The measurement system consists of a host computer, a micro system, a telescope and a high-resolution camera. As a preliminary test, the constructed measurement system was applied to measure delicate vibrations of mobile phones. For practical application, a pneumatic system was measured by the constructed system.