• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.17-22
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• 2012

Convolution filtering methods have been widely applied to various digital signal processing fields for image blurring, sharpening, edge detection, and noise reduction, etc. According to their application purpose, the filter mask size or shape and the mask value are selected in advance, and the designed filter is applied to input image for the convolution processing. In this paper, we proposed an image processing acceleration method for the convolution processing by using two-dimensional Look-up table (LUT) and overlap-region buffering technique. First, based on the fixed convolution mask value, the multiplication operation between 8 or 10 bit pixel values of the input image and the filter mask values is performed a priori, and the results memorized in LUT are referred during the convolution process. Second, based on symmetric structural characteristics of the convolution filters, inherent duplicated operation region is analysed, and the saved operation results in one step before in the predefined memory buffer is recalled and reused in current operation step. Through this buffering, unnecessary repeated filter operation on the same regions is minimized in sequential manner. As the proposed algorithms minimize the computational amount needed for the convolution operation, they work well under the operation environments utilizing embedded systems with limited computational resources or the environments of utilizing general personnel computers. A series of experiments under various situations verifies the effectiveness and usefulness of the proposed methods.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.89-112
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• 2015

Recently, the business environment of healthcare has changed rapidly due to the entering the mobile era, the intensifying global competition, and the explosion of healthcare needs. Despite of necessity in expanding new IT-based medical services and investing IT resources to respond environmental changes, the small and medium sized hospitals could not realize these requirements due to the limited management resources. CHISSMH is designed and presented in this research to provide high valued clouding medical services with reasonable price. CHISMH is designed and presented in this research to provide high valued medical services with reasonable price through cloud computing. CHISME is designed to maximize resource pooling and sharing through the visualization. By doing so, Cloud Service provider could minimize maintenance cost of cloud data center, provide high level services with reasonable pay-per-use price. By doing so, Cloud Service provider could minimize maintenance cost of cloud data center, and could provide high level services with reasonable pay-per-use price. CHISME is expected to be base framework of cloud HIS services and be diffusion factor of cloud HIS services Operational experience in CHISSMH with 15 hospitals is analyzed and presented as well.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.151-164
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• 2009

The importance of sensor networks as a base of ubiquitous computing realization is being highlighted, and espicially the security is recognized as an important research isuue, because of their characteristics.Several efforts are underway to provide security services in sensor networks, but most of them are preventive approaches based on cryptography. However, sensor nodes are extremely vulnerable to capture or key compromise. To ensure the security of the network, it is critical to develop security Intrusion Detection System (IDS) that can survive malicious attacks from "insiders" who have access to keying materials or the full control of some nodes, taking their charateristics into consideration. In this perper, we design a distributed and adaptive IDS architecture on sensor networks, respecting both of energy efficiency and IDS efficiency. Utilizing a modified HEED algorithm, a clustering algorithm, distributed IDS nodes (dIDS) are selected according to node's residual energy and degree. Then the monitoring results of dIDSswith detection codes are transferred to dIDSs in next round, in order to perform consecutive and integrated IDS process and urgent report are sent through high priority messages. With the simulation we show that the superiorities of our architecture in the the efficiency, overhead, and detection capability view, in comparison with a recent existent research, adaptive IDS.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.436-442
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• 2020

ESS(energy storage system) has recently become an important power source in various areas due to increased renewable energy resources. The more ESS is used, the less the effective capacity of the ESS. Therefore, it is important to manage the remaining useful lifetime(RUL). RUL can be checked regularly by inspectors, but it is common to be monitored and estimated by an automated monitoring system. The accurate state estimation is important to ESS operator for economical and efficient operation. RUL estimation model usually requires complex mathematical calculations consisting of cycle aging and calendar aging that are caused by the operation frequency and over time, respectively. A lightweight RUL estimation model is required to be embedded in low-performance processors that are installed on ESS. In this paper, a lightweight ESS RUL estimation model is proposed to operate on low-performance micro-processors. The simulation results show less than 1% errors compared to the original RUL model case. In addition, a performance analysis is conducted based on ATmega 328. The results show 76.8 to 78.3 % of computational time reduction.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.484-498
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• 2004

In this paper. we propose a novel performance monitoring scheme for heterogeneous SOAP nodes. The scheme is basically based on two-level (kernel-level and user-level) packet filtering of TCP flows. By TCP flow, we mean a sequence of raw packet streams on a TCP transaction. In this scheme, we detect and extract SOAP operations embedded in SOAP messages from TCP flows. Therefore, it becomes possible to monitor heterogeneous SOAP nodes deployed on diverse SOAP-based middlewares such as .Net and Apache AXIS. We present two implementation mechanisms for the proposed scheme. The first mechanism tries to identify SOAP operations by analyzing all fragmented SOAP messages on TCP flows. However, a naive policy would incur untolerable overhead since it needs to copy all packets from kernel to user space. The second mechanism overcomes this problem by selectively copying packets from kernel to user space. For selective copying, we use a kernel-level packet filtering method that makes use of some representative TCP flags.(e.g. SIN, FIN and PSH). In this mechanism, we can detect SOAP operations only from the last fragment of SOAP messages in most cases. Finally, we implement a SOAP monitoring system using a component ca]led SOAP Sniffer that realizes our proposed scheme, and show experimental results. We strongly believe that our system will play a vital role as a tool for various services such as transaction monitoring and load balancing among heterogeneous SOAP nodes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2334-2339
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• 2009

In case of an embedded system having an LCD panel with touch-screen capability, various figures such as rectangles, pentagons, circles, and arrows are frequently used for the delivery of user-input commands. In such a case, it is necessary to have an algorithm that can recognize whether a touched location is within a figure on which a specific user-input command is assigned. Such algorithms, however, impose a considerable amount of overhead for embedded systems with restricted amount of computing resources. This paper first describes a method for initializing and driving a touch-screen LCD and a coordinate-calibration method that converts touch-screen coordinates into LCD panel coordinates. Then it introduces methods that can be used for recognizing touched areas of rectangles, many-sided figures like pentagons, and circles; they are a range checking method for rectangles, a crossing number checking method for many-sided figures, a distance measurement method for circles, and a color comparison method that can be applied to all figures. In order to evaluate the performance of these methods, we implement two-dimensional graphics functions for drawing figures like triangles, rectangles, circles, and images. Then, we draw such figures and measures times spent for the touched-area recognition of these figures. Measurements show that the range checking is the most suitable method for rectangles, the distance measurement for circles, and the color comparison for many-sided figures and images.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.846-850
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• 2009

Recently, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics such as environmental monitoring, smart spaces, medical applications, and precision agriculture. The sensor nodes are battery powered. Therefore, the energy is the most precious resource of a wireless sensor network since periodically replacing the battery of the nodes in large scale deployments is infeasible. Energy efficient mechanisms for gathering sensor readings are indispensable to prolong the lifetime of a sensor network as long as possible. There are two energy-efficient approaches to prolong the network lifetime in sensor networks. One is the compression scheme to reduce the size of sensor readings. When the communication conflict is occurred between two sensor nodes, the sender must try to retransmit its reading. The other is the MAC protocol to prevent the communication conflict. In this paper, we propose a novel approaches to reduce the size of the sensor readings in the MAC layer. The proposed scheme compresses sensor readings by allocating the time slots of the TDMA schedule to them dynamically. We also present a mathematical model to predict latency from collecting the sensor readings as the compression ratio is changed. In the simulation result, our proposed scheme reduces the communication cost by about 52% over the existing scheme.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.271-284
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• 2008

Self-healing is an approach to evaluating constraints defined in target system and to applying an appropriate strategy when violating he constrains. Today, the computing environment is very complex, so researches that endow a system with the self-healing's ability that recognizes problem arising in a target system are being an important issues. However, most of the existing researches are that self-healing developers need much effort and time to analyze and model constraints. Thus, this paper proposes an automated approach to determine problem arising in external and internal system environment. The approach proposes: 1) Specifying the target system through the models created in design phase of target system. 2) Automatically creating constraints for external and internal system environment, by using the specified contents. 3) Deriving a dependency model of a component based on the created internal state rule. 4) Translating the constraints and dependency model into code evaluating behaviors of the target system, and determinating problem level. 5) Monitoring an internal and external status of system based on the level of problem determination, and applying self-healing strategy when detecting abnormal state caused in the target system. Through these, we can reduce the efforts of self-healing developers to analyze target system, and heal rapidly not only abnormal behavior of target system regarding external and internal problem, but also failure such as system break down into normal state. To evaluate the proposed approach, through video conference system, we verify an effectiveness of our approach by comparing proposed approach's self-healing activities with those of the existing approach.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.115-124
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• 2013

In this paper, we suggest a secure data dissemination by Lightweight Individual Encryption Multicast scheme over wireless sensor networks using the individual encryption method with Forward Error Correction instead of the group key encryption method. In wireless sensor networks, a sink node disseminates multicast data to the number of sensor nodes to update the up to date software such as network re-programming and here the group key encryption method is the general approach to provide a secure transmission. This group key encryption approach involves re-key management to provide a strong secure content distribution, however it is complicated to provide group key management services in wireless sensor networks due to limited resources of computing, storage, and communication. Although it is possible to control an individual node, the cost problem about individual encryption comes up and the individual encryption method is difficult to apply in multicast data transmission on wireless sensor networks. Therefore we only use 0.16% of individually encrypted packets to securely transmit data with the unicast to every node and the rest 99.84% non-encrypted encoded packets is transmitted with the multicast for network performance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.892-903
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• 2020

The rapid and accurate prediction of storm-surge height during typhoon attacks is essential in responding to coastal disasters. Most methods used for predicting typhoon data are based on numerical modeling, but numerical modeling takes significant computing resources and time. Recently, various studies on the expeditious production of predictive data based on artificial intelligence have been conducted, and in this study, artificial intelligence-based storm-surge height prediction was performed. Several learning data were needed for artificial intelligence training. Because the number of previous typhoons was limited, many synthesized typhoons were created using the tropical cyclone risk model, and the storm-surge height was also generated using the storm surge model. The comparison of the storm-surge height predicted using artificial intelligence with the actual typhoon, showed that the root-mean-square error was 0.09 ~ 0.30 m, the correlation coefficient was 0.65 ~ 0.94, and the absolute relative error of the maximum height was 1.0 ~ 52.5%. Although errors appeared to be somewhat large at certain typhoons and points, future studies are expected to improve accuracy through learning-data optimization.