• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1204-1227
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• 2020

The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.6
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• pp.648-653
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• 2012

Cavity pressure, an important factor in injection molding process, should be minimized to enhance injection molding quality. In this study, we decided the locations of valve gates to minimize the maximum cavity pressure. To solve this problem, we integrated MAPS-3D (Mold Analysis and Plastic Solution-3Dimension), a commercial injection molding analysis CAE tool, using the file parsing method of PIAnO (Process Integration, Automation and Optimization) as a commercial process integration and design optimization tool. In order to reduce the computational time for obtaining the optimal design solution, we performed an approximate optimization using a meta-model that replaced expensive computer simulations. To generate the meta-model, computer simulations were performed at the design points selected using the optimal Latin hypercube design as an experimental design. Then, we used micro genetic algorithm equipped in PIAnO to obtain the optimal design solution. Using the proposed design approach, the maximum cavity pressure was reduced by 17.3% compared to the initial one, which clearly showed the validity of the proposed design approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5231-5248
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• 2016

As a service-oriented paradigm, web service composition has obtained great attention from both academia and industry, especially in the area of cloud service. Nowadays more and more web services providing the same function but different in QoS are available in cloud, so an important mission of service composition strategy is to select the optimal composition solution according to QoS. Furthermore, the selected composition solution should satisfy the service level agreement (SLA) which defines users' request for the performance of composite service, such as price and response time. A composite service is feasible only if its QoS satisfies user's request. In order to obtain composite service with the optimal QoS and avoid SLA violations simultaneously, in this paper we first propose a QoS evaluation method which takes the SLA satisfaction into account. Then we design a service selection algorithm based on our QoS evaluation method. At last, we put forward a parallel running strategy for the proposed selection algorithm. The simulation results show that our approach outperforms existing approaches in terms of solutions' optimality and feasibility. Through our running strategy, the computation time can be reduced to a large extent.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5459-5473
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• 2017

Recently, a tracking algorithm called the spatial-temporal context model has been proposed to locate a target by using the contextual information around the target. This model has achieved excellent results when the target undergoes slight occlusion and appearance changes. However, the target location in the current frame is based on the location in the previous frame, which will lead to failure in the presence of fast motion because of the lack of a prediction mechanism. In addition, the spatial context model is updated frame by frame, which will undoubtedly result in drift once the target is occluded continuously. This paper proposes two improvements to solve the above two problems: First, four possible positions of the target in the current frame are predicted based on the displacement between the previous two frames, and then, we calculate four confidence maps at these four positions; the target position is located at the position that corresponds to the maximum value. Second, we propose a target reliability criterion and design an adaptive threshold to regulate the updating speed of the model. Specifically, we stop updating the model when the reliability is lower than the threshold. Experimental results show that the proposed algorithm achieves better tracking results than traditional STC and other algorithms.

• Korean Journal of Construction Engineering and Management
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• v.13 no.1
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• pp.77-86
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• 2012

Progress measurement provides project participants with valuable information in terms of 'current status', 'corrective countermeasure', and 'forecast of future risks'. However, the managerial effort (or workload) required to acquire and maintain detailed progress data has been the major barrier to practical implementation. Even though recent efforts in utilizing data acquisition technologies (DATs) have actively attempted to automate the progress measurement process, previous DAT research has only been focused on limited construction tasks or selected technologies. This paper proposes a DAT selection algorithm that automatically assign an appropriate DAT for every commodity item for an entire constriction project. Five different criteria were identified and developed in order to comprehend specific requirements for automating the progress measurement of each commodity group. A case-study and also a survey from practitioners were conducted in order to validate the proposed methodology.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.55-60
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• 2008

Inspection of steel columns which is one of the most critical elements in construction requires trained surveyor(s). Also it takes time to handle survey device(s) delicately for accurate measurements. To improve the inspection process of steel columns, the previous studies developed the AR prototype system, ARCam, and showed that ARCam is a promising inspection device that can reduce inspection time. However, ARCam still requires a surveyor to make measurements based on his visual perception and judgment This study proposes an algorithm for automatic inspection based on ARCam. The algorithm is based on image processing and computer vision and focuses on the inspection of steel column plumbness. This method will make measurements without a surveyor's judgment. The ultimate purpose of the automatic inspection is to minimize the surveying labor, thus reducing inspection time and cost.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.918-922
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• 1998

With the development of industry, the qualitical advancement of power is needed. Since it is placed in the end step of power system, the fault at the distribution system causes some users blackout directly. So if the fault occurs, quick restoration is very important subject and, for the reason, induction of the distribution automation system is now being progressed briskly. For the quick restoration of the faulted distribution system, the load shedding of the blackout-area must be followed, and the other problems like the shedded load, faulted voltage and the rest may cause other accident. Accordingly load shedding must be based on the precise calculation technique during the distribution system load flow(dist flow) calculation. In these days because of its superior convergence characteristic the Newton-Raphson method is most widely used. The number of buses in the distribution system amounts to thousands, and if the fault occurs at the distribution system, the speed for the dist flow calculation is to be improved to apply to the On-Line system. However, Newton-Raphson method takes much time relatively because it must calculate the Jacobian matrix and inverse matrix at every iteration, and in the case of huge load, the equation is hard to converge. In this thesis. matrix equation is used to make algebraical expression and then to solve load flow equation and to modify above defects. Then the complex matrix is divided into real part and imaginary part to keep sparcity. As a result time needed for calculation diminished. Application of mentioned algorithm to 302 bus, 700 bus, 1004 bus system led to almost identical result got by Newton-Raphson method and showed constant convergence characteristic. The effect of time reduction showed 88.2%, 86.4%, 85.1% at each case of 302 bus, 700 bus system 86.4%, and 1004 bus system.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.543-550
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• 2019

In 2006, Janet Wing defined computational thinking and operated SW education as a formal curriculum in the UK in 2013. This study collected related research papers by using computational thinking, which has recently increased in importance, and analyzed it using text mining. In the first, CONCOR analysis was conducted with the keyword of computational thinking. In the second, text mining of the components of computational thinking was selected by the repr23esentative academic journals at domestic and foreign. As a result of the two-time analysis, first, abstraction, algorithm, data processing, problem decomposition, and pattern recognition were the core of the study of computational thinking component. Second, research on convergence education centered on computational thinking and science and mathematics subjects was actively conducted. Third, research on computational thinking has been expanding since 2010. Research and development of the classification and definition of computational thinking and components and applying them to education sites should be conducted steadily.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.109-119
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• 2015

The interaction between wireless sensors such as Internet of Things (IoT) and Cloud is a new paradigm of communication virtualization to overcome resource and efficiency restriction. Cloud computing provides unlimited platform, resources, services and also covers almost every area of computing. On the other hand, Wireless Sensor Networks (WSN) has gained attention for their potential supports and attractive solutions such as IoT, environment monitoring, healthcare, military, critical infrastructure monitoring, home and industrial automation, transportation, business, etc. Besides, our virtual groups and social networks are in main role of information sharing. However, this sensor network lacks resource, storage capacity and computational power along with extensibility, fault-tolerance, reliability and openness. These data are not available to community groups or cloud environment for general purpose research or utilization yet. If we reduce the gap between real and virtual world by adding this WSN driven data to cloud environment and virtual communities, then it can gain a remarkable attention from all over, along with giving us the benefit in various sectors. We have proposed a Pub/Sub-based sensor virtualization framework Cloud environment. This integration provides resource, service, and storage with sensor driven data to the community. We have virtualized physical sensors as virtual sensors on cloud computing, while this middleware and virtual sensors are provisioned automatically to end users whenever they required. Our architecture provides service to end users without being concerned about its implementation details. Furthermore, we have proposed an efficient content-based event matching algorithm to analyze subscriptions and to publish proper contents in a cost-effective manner. We have evaluated our algorithm which shows better performance while comparing to that of previously proposed algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.2
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• pp.71-76
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• 2016

Digital image processing is being utilized in various fields including medical industry, satellite photos, and factory automation image recognition. However, this kind of image data produces heat by an external cause in the course of being processed, transmitted, and stored. Most typical noises added in the images are AWGN and salt and pepper. MF, CWMF, and AWMF are methods used to restore images damaged by AWGN and the existing methods are likely to damage detailed information such as an edge. Therefore, this paper suggests an algorithm applying weight of average filter, average filter depending on pixel, and spatial weight filter based on edge size of local mask in an AWGN environment, in a different way. Also, this paper compares functions of existing methods by using PSNR to prove excellence of the suggested algorithm.