• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1A
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• pp.25-33
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• 2011

The impact damage behavior of steel-strengthened concrete panels exposed to explosive loading is investigated. Since real explosion experiments require the vast costs to facilities as well as the blast and impact damage mechanisms are too complicated, numerical analysis has lately become a subject of special attention. However, for engineering problems involving blast wave and fragment impact, there is no single numerical method that is appropriate to the various problems. In order to evaluate the retrofit performance of a steel-strengthened concrete panel subject to blast wave and fragment impact loading, an explicit analysis program, AUTODYN is used in this work. The multi-solver coupling methods such as Euler-Lagrange and SPH-Lagrange coupling method in order to improve efficiency and accuracy of numerical analysis is implemented. The simplified and idealized two dimensional and axisymmetric models are used in order to obtain a reasonable computation running time. As a result of the analysis, concrete panels subject to either blast wave or fragment impact loading without the steel plate are shown the scabbing and perforation. The perforation can be prevented by concrete panels reinforced with steel plate. The numerical results show good agreement with the results of the experiments.

• Journal of IKEEE
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• v.24 no.2
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• pp.638-648
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• 2020

Currently, the method of user-follwoing in intelligent cooperative robots usually based in vision system and using Lidar is common and have excellent performance. But in the closed space of Corona 19, which spread worldwide in 2020, robots for cooperation with medical staff were insignificant. This is because Medical staff are all wearing protective clothing to prevent virus infection, which is not easy to apply with existing research techniques. Therefore, in order to solve these problems in this paper, the ultrasonic sensor is separated from the transmitting and receiving parts, and based on this, this paper propose that estimating the user's position and can actively follow and cooperate with people. However, the ultrasonic sensors were partially applied by improving the Median filter in order to reduce the error caused by the short circuit in communication between hard reflection and the number of light reflections, and the operation technology was improved by applying the curvature trajectory for smooth operation in a small area. Median filter reduced the error of degree and distance by 70%, vehicle running stability was verified through the training course such as 'S' and '8' in the result.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.35-46
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• 2011

Future Internet should support more efficient mobility management, flexible traffic engineering and various emerging new services. So, lots of traffic engineering techniques have been suggested and developed, but it's impossible to apply them on the current running commercial Internet. To overcome this problem, OpenFlow protocol was proposed as a technique to control network equipments using network controller with various networking applications. It is a software defined network, so researchers can verify their own traffic engineering techniques by applying them on the controller. In addition, for high-speed packet processing in the OpenFlow network, programmable NetFPGA card with four 1G-interfaces and commercial Procurve OpenFlow switches can be used. In this paper, we implement an OpenFlow test-bed using hardware-accelerated NetFPGA cards and Procurve switches on the KREONET, and implement CSPF (Constraint-based Shortest Path First) algorithm, which is one of popular QoS routing algorithms, and apply it on the large-scale testbed to verify performance and efficiency of multimedia traffic engineering scheme in Future Internet.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.107-117
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• 2004

The growing demand for customer-response, made-to-order manufacturing and satisfactory delivery are stimulating the importance of commercial fleet management problem. Moreover, the rapid transformation to the customer-oriented multi-frequency, relatively small fleet, such as home delivery and Perishable goods, requiring prompt delivery and advanced real-time operation of vehicle fleets. In this paper we consider the vehicle routing problem(VRP) to minimize delivery completion time which is equal to the time that last customer wait for the vehicle in fleet operation. The mathematical formulation is different from those for the classical VRP which is minimizing cost/distance/time by running vehicles in manager's point of view. The key aspect of this model is not considering the return time from the last customer to depot in every vehicle path. Thereby, the vehicle dispatcher can afford to dynamically respond to customer demand and vehicle availability. The customer's position concerned with minimizing waiting time that may be applied for the delivery of product required freshness or delivery time. Extensive experiments are carried out to compare the performance of minimizing delivery completion time by using the ILOG Solver which has the advantage of solving quickly an interim solution very near an optimal solution. The experimental results show that the suggested model can easily find near optimal solution in a reasonable computational time under the various combination of customers and vehicles.

• Journal of IKEEE
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• v.22 no.3
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• pp.829-835
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• 2018

Recently, studies have been actively conducted to reduce spare power that is unnecessarily generated or wasted in existing power systems and to improve energy use efficiency. In this study, smart meter, which is one of the element technologies of smart grid, is implemented to improve the efficiency of energy use by controlling power of electric devices, and predicting trends of energy usage based on deep learning. We propose and develop an algorithm that controls the power of the electric devices by comparing the predicted power consumption with the real-time power consumption. To verify the performance of the proposed smart meter based on the deep running, we constructed the actual power consumption environment and obtained the power usage data in real time, and predicted the power consumption based on the deep learning model. We confirmed that the unnecessary power consumption can be reduced and the energy use efficiency increases through the proposed deep learning-based smart meter.

• Journal of Korean Home Economics Education Association
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• v.4 no.1
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• pp.87-95
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• 1992

The purpose of this study is to suggest how we can get over the difficulties of practical drill under experimentation concerning the units of making clothes in the curriculum of home economics. The import of this study was based on the results of the preceding studies the field of the making Korean clothes, from the standpoint of the teaching tools and teaching materials by the use of VTR, is one of the most insufficient. On the one hand, the teaching procedure here a VTR, running 34 minutes or so, was made up with the process of making Korean men’s slacks, and was led by the researcher’s own. The contents of the lesson are as follows： the shape of Korean clothes, the name of each part, the process of drawing, cutting and sewing, and the items of evaluation and arrangement. On the other hand, the two comparative groups were made to compare one with the other： One group was taught by help of VTR media, and the other by the model performance and explanation of the instructor’s own. All of the statistical data were analyzed in terms of SPSS/PC, and t-verification was made, to make difference between the two, after standard deviation was calculated according to the classified domains. The consequences of the test research are shown as below： 1. The difference of understanding was obviously made in considering that the group made a better score than the comparative one in understanding to process of making Korean clothes. 2. The difference of skill was highly made in considering that the group made a better score than the comparative one in the practical drill of making Korean clothes. 3. The difference of interests was evidentally made in considering that the group made a better score than the comparative one in the stage of making Koran clothes. Such means that the motivation and attitude of the learners was made stimulate by the Audio-Visual material than by the traditional cramming method. 4. The difference of frequency was fairly made in considering that the experimeatal group made a better score than the comparative one in the frequency of individual teaching. 5. The difference of the efficiency of time-consumption was clearly made in considering that the experimental group made a better score than the comparative one. As the results of the research above, the medium of VTR proved to more effective to the achievement of schoolwork and the strategies of teaching. Therefore, more use of VTR media will help the instructors with the difficulties of practical drill in the whole process of making Korean clothes； Widely use of VTR media in teaching will be surely more fruitfull to the unit of making Korean clothes than teaching by explanation.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.15-25
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• 2005

Embedded systems have a set of tasks to execute. These tasks can be implemented either on application specific hardware or as software running on a specific processor. The design of an embedded system involves the selection of hardware software resources, Partition of tasks into hardware and software, and performance evaluation. An accurate estimation of execution time for extreme cases (best and worst case) is important for hardware/software codesign. A tighter estimation of the execution time bound nay allow the use of a slower processor to execute the code and may help lower the system cost. In this paper, we consider an ARM-based embedded system and developed a tool to estimate the tight boundary of execution time of a task with loop bounds and any additional program path information. The tool we developed is based on an exiting timing analysis tool named 'Cinderella' which currently supports i960 and m68k architectures. We add a module to handle ARM ELF object file, which extracts control flow and debugging information, and a module to handle ARM instruction set so that the new tool can support ARM processor. We validate the tool by comparing the estimated bound of execution time with the run-time execution time measured by ARMulator for a selected bechmark programs.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.319-326
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• 2004

To help network intrusion detection systems(NIDSs) keep up with the demands of today's networks, that we the increasing network throughput and amount of attacks, a radical new approach in hardware and software system architecture is required. In this paper, we propose a Network Processor(NP) based In-Line mode NIDS that supports the packet payload inspection detecting the malicious behaviors, as well as the packet filtering and the traffic metering. In particular, we separate the filtering and metering functions from the deep packet inspection function using two-level searching scheme, thus the complicated and time-consuming operation of the deep packet inspection function does not hinder or flop the basic operations of the In-line mode system. From a proto-type NP-based NIDS implemented at a PC platform with an x86 processor running Linux, two Gigabit Ethernet ports, and 2.5Gbps Agere PayloadPlus(APP) NP solution, the experiment results show that our proposed scheme can reliably filter and meter the full traffic of two gigabit ports at the first level even though it can inspect the packet payload up to 320 Mbps in real-time at the second level, which can be compared to the performance of general-purpose processor based Inspection. However, the simulation results show that the deep packet searching is also possible up to 2Gbps in wire speed when we adopt 10Gbps APP solution.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.221-228
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• 2017

With the recent development of IoT technology, medical services using IoT technology are increasing in many medical institutions providing health care services. However, as the number of IoT sensors attached to the user body increases, the healthcare information transmitted to the server becomes complicated, thereby increasing the time required for analyzing the user's healthcare information in the server. In this paper, we propose a deep learning based health care information management method to collect and process healthcare information in a server for a large amount of healthcare information delivered through a user - attached IoT device. The proposed scheme constructs a subnet according to the attribute value by assigning an attribute value to the healthcare information transmitted to the server, and extracts the association information between the subnets as a seed and groups them into a hierarchical structure. The server extracts optimized information that can improve the observation speed and accuracy of user's treatment and prescription by using deep running of grouped healthcare information. As a result of the performance evaluation, the proposed method shows that the processing speed of the medical service operated in the healthcare service model is improved by 14.1% on average and the server overhead is 6.7% lower than the conventional technique. The accuracy of healthcare information extraction was 10.1% higher than the conventional method.