• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.37-48
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• 1994

In spatial information processing, particularly in non-renewable resource exploration, the spatial data sets, including remote sensing, geophysical and geochemical data, have to be geocoded onto a reference map and integrated for the final analysis and interpretation. Application of a computer based GIS(Geographical Information System of Geological Information System) at some point of the spatial data integration/fusion processing is now a logical and essential step. It should, however, be pointed out that the basic concepts of the GIS based spatial data fusion were developed with insufficient mathematical understanding of spatial characteristics or quantitative modeling framwork of the data. Furthermore many remote sensing and geological data sets, available for many exploration projects, are spatially incomplete in coverage and interduce spatially uneven information distribution. In addition, spectral information of many spatial data sets is often imprecise due to digital rescaling. Direct applications of GIS systems to spatial data fusion can therefore result in seriously erroneous final results. To resolve this problem, some of the important mathematical information representation techniques are briefly reviewed and discussed in this paper with condideration of spatial and spectral characteristics of the common remote sensing and exploration data. They include the basic probabilistic approach, the evidential belief function approach (Dempster-Shafer method) and the fuzzy logic approach. Even though the basic concepts of these three approaches are different, proper application of the techniques and careful interpretation of the final results are expected to yield acceptable conclusions in cach case. Actual tests with real data (Moon, 1990a; An etal., 1991, 1992, 1993) have shown that implementation and application of the methods discussed in this paper consistently provide more accurate final results than most direct applications of GIS techniques.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.452-455
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• 2000

There are increasingly important financial incentives and environmental consideration to improve the effluent quality of wastewater from domestic and industrial users. The activated sludge process is a widely used biological wastewater treatment process. The activated sludge process is complicated due to the many factors such as the variation of influent flowrate and concentration, the complexity of biological reactions and the various operation conditions. Nowadays, not only suspended solids and residual carbon, but also nitrogen and phosphorous concentration of the effluent water must be taken into account for the design and operation of wastewater treatment plants. Also, the effluent quality to be met are more stringent. Therefore, an intelligent control approach is required in order to successful biological nitrogen removal. In this paper, the strategies for dosage of extra carbon in the anoxic zone and DO concentration in the aerobic zone are presented and evaluated through the simulation using the denitrification layout of the IWA simulation benchmark implemented by Matlab$\^$/5.3/Simulink$\^$/3.0. The control strategy to achieve sufficient denitrification rates in an anoxic zone. Methanol is used as an external extra carbon source. The external extra carbon source is required for the nitrogen removal process because nitrogen and organic concentration are fluctuated in the influent flowrate. The dissolved oxygen is calculated by So concentration in the activated sludge model NO.1. The air flowrate of each aerobic reactor is intelligently controlled to achieve the predefined setpoints. Air flowrate is adjusted by the fuzzy logic controller that includes two inputs and one output. The objective function for the optimization procedure is designed to improve effluent quality and reduce the operating cost.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.127-131
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• 2007

The control of electrical appliances residing in the home network can be accomplished via Internet with the UPnP expansion without modifying an existing UPnP. In this paper, we propose the Internet Gateway that consists of an UPnP IGD(Internet Gateway Device) DCP(Device Control Protocol) and an UPnP Bridge as a system to control electrical appliances of home network. UPnP IGD DCP is to enable the configurable initiation and sharing of Internet connections as well as assuring advanced connection-management features and management of host configuration service. It also supports transparent Internet access by non-UPnP-certified devices. UPnP Bridge searches for local home network devices by sending control messages, while control point of UPnP Bridge looks up devices of interest on the Internet, subsequently furnishing the inter-networking controlling among devices which belong to different home network systems. With our approach, devices on one home network can control home electrical appliances on the other home network via Internet through IGD DCP with control commands of UPnP.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.306-316
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• 2013

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.50-58
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• 2013

Estimating a driver's head pose is an important task in driver-assistance systems because it can provide information about where a driver is looking, thereby giving useful cues about the status of the driver (i.e., paying proper attention, fatigued, etc.). This study proposes a system for estimating the head pose using monocular images, which includes a novel use of backprojection. The system can use a single image to estimate a driver's head pose at a particular time stamp, or an image sequence to support the analysis of a driver's status. Using our proposed system, we compared two previous pose estimation approaches. We introduced an approach for providing ground-truth reference data using a mannequin model. Our experimental results demonstrate that the proposed system provides relatively accurate estimations of the yaw, tilt, and roll angle. The results also show that one of the pose estimation approaches (perspective-n-point, PnP) provided a consistently better estimate compared to the other (pose from orthography and scaling with iterations, POSIT) using our proposed system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.167-173
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• 2002

In this paper, we propose an interactive genetic algorithm (IGA) to implement an automated 2D avatar synthesis. The IGA technique is capable of expressing user's personality in the avatar synthesis by using the user's response as a candidate for the fitness value. Our suggested IGA method is applied to creating avatars automatically. Unlike the previous works, we introduce the concepts of 'hidden population', as well as 'primitive avatar' and 'simplified genotype', which are used to overcome the shortcomings of IGA such as human fatigue or reliability, and reasonable rates of convergence with a less number of iterations. The procedure of designing avatar models consists of two steps. The first step is to detect the facial feature points and the second step is to create the subjectively optimal avatars with diversity by embedding user's preference, intuition, emotion, psychological aspects, or a more general term, KANSEI. Finally, the combined processes result in human-friendly avatars in terms of both genetic optimality and interactive GUI with reliability.