• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.59-79
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• 2005

Export containers in a container terminal are usually classified into a few weight groups and those belonging to the same group are placed together on a same stack. The reason for this stacking by weight groups is that it becomes easy to have the heavier containers be loaded onto a ship before the lighter ones, which is important for the balancing of the ship. However, since the weight information available at the time of container arrival is only an estimate, those belonging to different weight groups are often stored together on a same stack. This becomes the cause of extra moves, or rehandlings, of containers at the time of loading to fetch out the heavier containers placed under the lighter ones. In this paper, we use machine learning techniques to derive a classifier that can classify the containers into the weight groups with improved accuracy. We also show that a more useful classifier can be derived by applying a cost-sensitive learning technique, for which we introduce a scheme of searching for a good cost matrix. Simulation experiments have shown that our proposed method can reduce about 5$\sim$7% of rehandlings when compared to the traditional weight grouping method.

• Korean Journal of Applied Biomechanics
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• v.15 no.3
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• pp.143-152
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• 2005

The purpose of this study was to predict the failure or success of the Snatch-lifting trial as a consequence of the stand-up phase simulated in Kane's equation of motion that was effective for the dynamic analysis of multi-segment. This experiment was a case study in which one male athlete (age: 23yrs, height: 154.4cm, weight: 64.5kg) from K University was selected The system of a simulation included a multi-segment system that had one degree of freedom and one generalized coordinate for the shank segment angle. The reference frame was fixed by the Nonlinear Trans formation (NLT) method in order to set up a fixed Cartesian coordinate system in space. A weightlifter lifted a 90kg-barbell that was 75% of subject's maximum lifting capability (120kg). For this study, six cameras (Qualisys Proreflex MCU240s) and two force-plates (Kistler 9286AAs) were used for collecting data. The motion tracks of 11 land markers were attached on the major joints of the body and barbell. The sampling rates of cameras and force-plates were set up 100Hz and 1000Hz, respectively. Data were processed via the Qualisys Track manager (QTM) software. Landmark positions and force-plate amplitudes were simultaneously integrated by Qualisys system The coordinate data were filtered using a fourth-order Butterworth low pass filtering with an estimated optimum cut-off frequency of 9Hz calculated with Andrew & Yu's formula. The input data of the model were derived from experimental data processed in Matlab6.5 and the solution of a model made in Kane's method was solved in Matematica5.0. The conclusions were as follows; 1. The torque motor of the shank with 246Nm from this experiment could lift a maximum barbell weight (158.98kg) which was about 246 times as much as subject's body weight (64.5kg). 2. The torque motor with 166.5 Nm, simulated by angular displacement of the shank matched to the experimental result, could lift a maximum barbell weight (90kg) which was about 1.4 times as much as subject's body weight (64.5kg). 3. Comparing subject's maximum barbell weight (120kg) with a modeling maximum barbell weight (155.51kg) and with an experimental maximum barbell weight (90kg), the differences between these were about +35.7kg and -30kg. These results strongly suggest that if the maximum barbell weight is decided, coaches will be able to provide further knowledge and information to weightlifters for the performance improvement and then prevent injuries from training of weightlifters. It hopes to apply Kane's method to other sports skill as well as weightlifting to simulate its motion in the future study.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.169-179
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• 2017

Recently, due to global warming and climate change in Korea, local heavy storm occurs frequently. In this study, the risky areas for flooding in urban areas are analyzed for flood inundation based on two-dimensional urban flood runoff model (XP-SWMM) focusing on coastal high flood-risk urban areas. In addition, the MCDM (Multi-Criteria Decision Making) technique is utilized in order to establish the flood defense structural measures. The alternative flood reduction method are compared and the optimum flood defense measures are selected. A simulation model was used with three structural flood prevention measures (drainage pipe construction, water detention, flood pumping station). In order to decrease the flooding area, flood assessment criteria are suggested (flooded area, maximum inundation depth, damaged residential area, construction cost). Priorities of alternatives are determined by using compromise programming. As a result, the optimal flood defence alternative suggested for Janghang Zone 1 is flood pumping station and for Janghang Zone 2, 3 are drainage pipe construction.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.33-39
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• 2016

With recent advances in sensor technology, CMOS-based semiconductor devices and networking protocol, the areas for application of wireless sensor networks greatly expanded and diversified. Such diversification of uses for wireless sensor networks creates a multitude of beneficial possibilities for several industries. In the application of wireless sensor networks for monitoring systems' data transmission process from the sensor node to the sink node, transmission through multi-hop paths have been used. Also mobile sink techniques have been applied. However, high energy costs, unbalanced energy consumption of nodes and time gaps between the measured data values and the actual value have created a need for advancement. Therefore, this thesis proposes a new model which alleviates these problems. To reduce the communication costs due to frequent data exchange, a State Prediction Model has been developed to predict the situation of the peripheral node using a geographic autocorrelation of sensor nodes constituting the wireless sensor networks. Also, a Risk Analysis Model has developed to quickly alert the monitoring system of any fatal abnormalities when they occur. Simulation results have shown, in the case of applying the State Prediction Model, errors were smaller than otherwise. When the Risk Analysis Model is applied, the data transfer latency was reduced. The results of this study are expected to be utilized in any efficient communication method for wireless sensor network monitoring systems where all nodes are able to identify their geographic location.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.26-32
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• 2009

The multi-level storage architecture has been widely adopted in servers and data centers. However, while prefetching has been shown as a crucial technique to exploit sequentiality in accesses common for such systems and hide the increasing relative cost of disk I/O, existing multi-level storage studies have focused mostly on cache replacement strategies. In this paper, we show that prefetching algorithms designed for single-level systems may have their limitations magnified when applied to multi-level systems. Overly conservative prefetching will not be able to effectively use the lower-level cache space, while overly aggressive prefetching will be compounded across levels and generate large amounts of wasted prefetch. We design and implement a hierarchy-aware lower-level prefetching strategy called PMS(Prefetching strategy for Multi-level Storage system) that applicable to any upper level prefetching algorithms. PMS does not require any application hints, a priori knowledge from the application or modification to the va interface. Instead, it monitors the upper-level access patterns as well as the lower-level cache status, and dynamically adjusts the aggressiveness of the lower-level prefetching activities. We evaluated the PMS through extensive simulation studies using a verified multi-level storage simulator, an accurate disk simulator, and access traces with different access patterns. Our results indicate that PMS dynamically controls aggressiveness of lower-level prefetching in reaction to multiple system and workload parameters, improving the overall system performance in all 32 test cases. Working with four well-known existing prefetching algorithms adopted in real systems, PMS obtains an improvement of up to 35% for the average request response time, with an average improvement of 16.56% over all cases.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.11
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• pp.66-76
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• 2009

The motion estimation in video encoding system occupies the biggest part. So, we require the motion estimator with efficient structure for real-time operation. And for motion estimator's implementation, it is desired to design hardware module of an exclusive use that perform the encoding process at high speed. This paper proposes motion estimation detection block(MED), 41 SADs(Sum of Absolute Difference) calculation block, minimum SAD calculation and motion vector generation block based on parallel processing. The parallel processing can reduce effectively the amount of the operation. The minimum SAD calculation and MED block uses the pre-computation technique for reducing switching activity of the input signal. It results in high-speed operation. The MED and 41 SADs calculation blocks are composed of adder tree which causes the problem of critical path. So, the structure of adder tree has changed the most commonly used ripple carry adder(RCA) with carry skip adder(CSA). It enables adder tree to operate at high speed. In addition, as we enabled to easily control key variables such as control signal of search range from the outside, the efficiency of hardware structure increased. Simulation and FPGA verification results show that the delay of MED block generating the critical path at the motion estimator is reduced about 19.89% than the conventional strukcture.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.647-655
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• 2021

The IMO (International Maritime Organization) is discussing the improvement of energy ef iciency of ships in order to reduce greenhouse gas emissions from ships. Currently, by applying an ORC power generation system using waste heat generated from ships, high energy conversion efficiency can be expected from ships. This technology uses an organic medium based on Freon or hydrocarbons as the working fluid, which evaporates at a lower temperature range than water. Through this, it is possible to generate steam (gas) and generate power at a low and low temperature relatively. In this study, the analysis of heat flow between the refrigerant and waste heat in the ORC power generation system, which is an organic Rankine cycle, is analyzed using 3D simulation techniques to determine the temperature change, velocity change, pressure change, and mass change of the fluid flowing of the WHRU (Waste Heat Recovery Unit) inside and the outside the structure. The purpose of this study is to analyze how the mass change affects the structure, and this study analyzed the heat transfer of the heat exchanger from the refrigerant and the exhaust gas of the ship's main engine in the ORC power generation system using this technique.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1001-1010
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• 2021

Smart factories are complex systems which combine latest information technology (IT) with operation technology (OT). A smart factory aims to provide manufacturing capacity improvement, customized production, and resource reduction with these complex technologies. Although the smart factory is able to increase the efficiency through the technologies, the security level of the whole factory is low due to the vulnerability transfer from IT. In addition, the response and restoration of the business continuity plan are insufficient in case of damage due to the absence of factory security experts. The cope with the such problems, we propose an information security practice content for analyzing the damage by generating ransomware attacks in a digital twin-based smart factory similar to the real world. In our information security content, we introduce our conversion technique of physical devices into virtual machines or simulation models to build a practical environment for the digital twin. This content generates two types of the ransomware attacks according to a defined scenario in the digital twin. When the two generated attacks are successfully completed, at least 8 and 5 of the 23 virtual elements are take damage, respectively. Thus, our proposed content directly identifies the damage caused by the generation of two types of ransomware in the virtual world' smart factory.