• Proceedings of the KSRS Conference
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• v.1
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• pp.126-129
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• 2006

The marine environment is under considerable threat from intentional or accidental oil spills, ballast water discharged, dredging and infilling for coastal development, and uncontrolled sewage and industrial wastewater discharges. Monitoring spills and illegal oil discharges is an important component in ensuring compliance with marine protection legislation and general protection of the coastal environments. For the monitoring task an image processing system is needed that can efficiently perform the detection and the tracking of oil spills and in this direction a significant amount of research work has taken place mainly with the use of radar (SAR) remote sensing data. In this paper the level set image segmentation technique was tested for the detection of oil spills. Level set allow the evolving curve to change topology (break and merge) and therefore boundaries of particularly intricate shapes can be extracted. Experimental results demonstrated that the level set segmentation can be used for the efficient detection and monitoring of oil spills, since the method coped with abrupt shape’s deformations and splits.

• Proceedings of the KSRS Conference
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• v.2
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• The Journal of Information Systems
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• v.26 no.2
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• pp.123-142
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• 2017

Purpose The development of the Fintech industry can be on the basis of the development in IT technologies such as Big data, IoT, cloud computing, it can be considered that the financial industry is repeating the evolution into Fintech. But the awareness of the consumers is still very low. Therefore the current dissertation, tries to deduce the suggestions for invigoration measures for Fintech by conducting an empirical study on the factors that influence the intention of reuse of Fintech on the consumer's point of view. Design/methodology/approach This study made a design of the research model by integrating the factors deducted from the Expectation Confirmation Theory. This paper empirically analyzes the impact of Continuous Usage Intention for Improvement of Fintech. The 302 survey responses were used to verify research hypotheses through covariate structural equation model. Findings According to the empirical analysis result, this study confirmed that the ultimate purpose of the Fintech service is to eliminate the social cost's waste element occurring from issue of money by not using or reducing the usage of cash. Since many Fintech users have pointed out security as the priority task, a direction for the related institutions has been proposed. Second, the content of the current dissertation will be the opportunity of broadening the perception of the current consumers that perceive Fintech as only a NFC simple payment service.

• Journal of architectural history
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• v.26 no.3
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• pp.7-18
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• 2017

This research focuses on the cadastre and cartographic tradition regarding the representation of Rome that had lasted until the middle of 18th Century. Since the early period of Roman Republic until the early 18th Century, map was considered as a effective medium to record the status of urban facts and also a manifestation of changing perception of reality. These facts allow to diagnose social and conventional changes that had occurred in the field of representation techniques and methodologies derived from diverse intention and objective in elaboration of each map. Cartography also has affinity to architectural drawing as many categories of individuals are involved, clients, researchers, craftsmen, publisher and collectors. Fundamental task of documenting the contemporary physical reality was given to the map, however, as architects had practiced through the drawings, cartographers also reconstruct in subjective way specific buildings and urban aspects according to various needs and demands. As such, philology and imagination play important role as two constitute extreme poles in the evolution of the cadastre. Through analysis of paradigmatic examples in the genealogy of cartography of Rome, it was possible to understand the changing episteme that testify the mentality and custom in the field of visual representation.

• Transactions of Materials Processing
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• v.8 no.5
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• pp.471-481
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• 1999

The properties of deformed products are generally dependent upon the distribution of microstureture. It is, therefore, necessary to make the distribution of microstureture uniform in order to achieve the best balance of properties in the final product. This is often a demanding task, even for conventional materials. It is become essential to achieving mechanical integrity and a desired combination of microstructure and properties. The objective mechanical integrity and a desired combination of microsttucture and properties. The objective of this study is to design the optimal die profile which can yield more uniform microstructure in hot extruded product. The microstructure evolution, such as dynamic and static recrystallization as well as grain growth, is investigated using the program com-bined with yada and Senuma's empirical equations and rigid-thermoviscoplastic finite element method. The die profile of hot extrusion is represented by Bezier-curve to define all available profile. In order to obtain the optimal die profile which yields uniform microstructure in the product the FPS(Flexible Polyhedron Search) method is applied to the present study. To validate the result of present study the experimental hot extrusion is performed and the result is compared with that of simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2815-2839
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• 2020

In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.

• Smart Structures and Systems
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• v.5 no.4
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• pp.483-494
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• 2009

Damage detection has been proven to be a challenging task in structural health monitoring (SHM) due to the fact that damage cannot be measured. The difficulty associated with damage detection is related to electing a feature that is sensitive to damage occurrence and evolution. This difficulty increases as the damage size decreases limiting the ability to detect damage occurrence at the micron and submicron length scale. Damage detection at this length scale is of interest for sensitive structures such as aircrafts and nuclear facilities. In this paper a new photonic sensor based on photonic crystal (PhC) technology that can be synthesized at the nanoscale is introduced. PhCs are synthetic materials that are capable of controlling light propagation by creating a photonic bandgap where light is forbidden to propagate. The interesting feature of PhC is that its photonic signature is strongly tied to its microstructure periodicity. This study demonstrates that when a PhC sensor adhered to polymer substrate experiences micron or submicron damage, it will experience changes in its microstructural periodicity thereby creating a photonic signature that can be related to damage severity. This concept is validated here using a three-dimensional integrated numerical simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.327-336
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• 2004

In distributed autonomous mobile robot system, each robot (predator or prey) must behave by itself according to its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot have both learning and evolution ability to adapt to dynamic environment. This paper proposes a pursuing system utilizing the artificial life concept where virtual robots emulate social behaviors of animals and insects and realize their group behaviors. Each robot contains sensors to perceive other robots in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used for behavior decision controller. The input of the neural network is decided by the existence of other robots and the distance to the other robots. The output determines the directions in which the robot moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation. Besides, in this paper, we could have observed the robots' emergent behaviors during simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.441-446
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• 2010

Each robot decides and behaviors themselves surrounding circumstances in the swarm robot system. Robots have to conduct tasks allowed through cooperation with other robots. Therefore each robot should have the ability to learn and evolve in order to adapt to a changing environment. In this paper, we proposed learning based on Q-learning algorithm and evolutionary using Harmony Search algorithm and are trying to improve the accuracy using Harmony Search Algorithm, not the Genetic Algorithm. We verify that swarm robot has improved the ability to perform the task.

• Smart Structures and Systems
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• v.26 no.6
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• pp.753-763
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• 2020

The early prediction of Compressive Strength of Concrete (CSC) is a significant task in the civil engineering construction projects. This study, therefore, is dedicated to introducing two novel hybrids of neural computing, namely Shuffled Complex Evolution (SCE) and Teaching-Learning-Based Optimization (TLBO) for predicting the CSC. The algorithms are applied to a Multi-Layer Perceptron (MLP) network to create the SCE-MLP and TLBO-MLP ensembles. The results revealed that, first, intelligent models can properly handle analyzing and generalizing the non-linear relationship between the CSC and its influential parameters. For example, the smallest and largest values of the CSC were 17.19 and 58.53 MPa, and the outputs of the MLP, SCE-MLP, and TLBO-MLP range in [17.61, 54.36], [17.69, 55.55] and [18.07, 53.83], respectively. Second, applying the SCE and TLBO optimizers resulted in increasing the correlation of the MLP products from 93.58 to 97.32 and 97.22%, respectively. The prediction error was also reduced by around 34 and 31% which indicates the high efficiency of these algorithms. Moreover, regarding the computation time needed to implement the SCE-MLP and TLBO-MLP models, the SCE is a considerably more time-efficient optimizer. Nevertheless, both suggested models can be promising substitutes for laboratory and destructive CSC evaluative models.