• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.11
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• pp.1217-1223
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• 2007

Advanced microwave absorbers for wide oblique incidence angles are required in many applications including wireless communication or vehicle identification in ITS(Intelligent Transport System) where 5.8 GHz DSRC(Dedicated Short Range Communication) system is applied. In this study, two-layered microwave absorber(with a laminate structure of dielectric/magnetic composites) has been designed for the achievement of low reflection coefficient over wide incidence angles at 5.8 GHz. Iron flake particles are used as the filler in the absorbing layer, and the magnetic composite sheet exhibits high magnetic loss due to ferromagnetic resonance in gigahertz frequencies. The surface layer of low dielectric constant containing small amount of carbon black is used as the impedance transformer. On the basis of transmission line theory, the reflection loss has been calculated for the two-layer structure with variation of incident angles for both TE(Transverse Electric) and TM(Transverse Magnetic) polarizations. At the optimum thickness of the composite layers, a low value of reflection loss(less than -10 dB) has been predicted for wide incidence angles up to $55^{\circ}$ which is in good agreement with the measured value determined by free-space measurement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.209-220
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• 2022

With the worldwide spread of African swine fever, interest in livestock epidemics has increased. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but there are no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted the trajectory of livestock-related vehicles using the facility-visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority. The results are presented as exposure indices aggregating the link-time occupancy of each vehicle. As a result, 274,519 livestock-related vehicle trajectories were extracted, and the exposure values by link and zone were derived quantitatively. This study highlights the need for prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.5
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• pp.641-648
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• 2013

A beam is a major load-carrying member in many engineering structures. Beams with properly designed cross sections and stiffeners are required to enhance the structural properties. Such a design may cause various coupling behaviors, and therefore, an accurate analysis is essential for the proper design of beams. In this research, we manufactured box-beams with stiffeners, which mimic the out-of-plane composite bending-shear coupling behavior reported in literature. A modal test is carried out to obtain the dynamic characteristics, such as natural frequencies and mode shapes, of the box-beam. The obtained results are compared with those of 3D FEM, which confirm that the out-of-plane bending-shear coupling behavior reported in literature is possible. The coupling behavior can be controlled by the proper design of the stiffeners.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.379-385
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• 2012

This paper developes the navigation visual aid supporting a watch officer's situation awareness and analyzes its performance test result. Developing the equipment made from composite video sensor which transfer video signal, ranger laser measurement model which search out distance, Pan/ Tilt, center control device. The developed equipment with Pan/Tilt was made from high performance video sensor and ranger laser measurement. To make a real ship test, we carried on setting the developed equipment on ship, observed a danger factor and analyzed a image, and from that we can evaluate marine environment awareness. Through this result, the developed equipment can show effective ability of the awareness of the clearer check and resolution situation when compare with the binocular.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.689-694
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• 2009

In this paper an approach to building fuzzy models for predicting daily and weekly stock prices is presented. Predicting stock prices with traditional time series analysis has proven to be difficult. Fuzzy logic based models have advantage of expressing the input-output relation linguistically, which facilitates the understanding of the system behavior. In building a stock prediction model we bear a burden of selecting most effective indicators for the stock prediction. In this paper information used in traditional candle stick-chart analysis is considered as input variables of our fuzzy models. The fuzzy rules have the premises and the consequents composed of trapezoidal membership functions and nonlinear equations, respectively. DE(Differential Evolution) identifies optimal fuzzy rules through an evolutionary process. The fuzzy models to predict daily and weekly open, high, low, and close prices of KOSPI(KOrea composite Stock Price Index) are built, and their performances are demonstrated.

• Steel and Composite Structures
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• v.31 no.6
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• pp.629-640
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• 2019

The investigation of retaining wall structures behavior under dynamic loads is considered as one of important parts for designing such structures. Generally, the performance of these structures is under the influence of the environment conditions and their geometry. The aim of this research is to design retaining wall structures based on smart and optimal systems. The use of accuracy and speed to assess the structures under different conditions is one of the important parts sought by designers. Therefore, optimal and smart systems are able to have better addressing these problems. Using numerical and coding methods, this research investigates the retaining wall structure design under different dynamic conditions. More than 9500 models were constructed and considered for modelling design. These designs include height and thickness of the wall, soil density, rock density, soil friction angle, and peak ground acceleration (PGA) variables. Accordingly, a neural network system was developed to establish an appropriate relationship between data to obtain safety factor (SF) of retaining walls under different seismic conditions. Different parameters were analyzed and the effect of each parameter was assessed separately. According to these analyses, the structure optimization was performed to increase the SF values. The optimal and smart design showed that under different PGA conditions, the structure performance can be appropriately improved while utilization of the initial (or basic) parameters leads to the structure failure. Therefore, by increasing accuracy and speed, smart methods could improve the retaining structure performance in controlling the wall failure. The intelligent design process of this study can be applied to some other civil engineering applications such as slope stability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.167-178
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• 2023

Our society is rapidly changing, and there is a growing demand for various convenience services in our daily lives. Among these services, railway and subway stations require tailored wayfinding services to accommodate individuals with disabilities. Currently, signage and information desks are the primary means of navigation. However, individuals with disabilities often rely on assistance from others due to physical discomfort or cognitive impairments. In this paper, we propose a customized wayfinding system within railway stations to assist individuals with disabilities. This system aims to ensure safe and convenient mobility in complex indoor environments, including transfer facilities.

• Steel and Composite Structures
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• v.49 no.4
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• pp.457-471
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• 2023

To make up for the performance weaknesses of recycled aggregate concrete (RAC), expand the application range of RAC, and alleviate the environmental problems caused by excessive exploitation of natural coarse aggregates (NCA), this study proposes a basalt fiber-reinforced recycled aggregate concrete (BFRRAC)-filled square steel tubular columns that combines two modification methods of steel tube and fiber, which may greatly enhance the mechanical properties of RAC. The axial compression performance for BFRRAC-filled square steel tubular columns was reported during this study. Seven specimens with different replacement ratios of recycled coarse aggregate (RCA), length-diameter ratios, along with basalt fiber (BF) contents were designed as well as fabricated for performing axial compression test. For each specimen, the whole failure process as well as mode of specimen were discovered, subsequently the load-axial displacement curve has obtained, after which the mechanical properties was explained. A finite element analysis model for specimens under axial compression was then established. Subsequently, based on this model, the factors affecting axial compression performance for BFRRAC-filled square steel tubes were extended and analyzed, after which the corresponding design suggestion was proposed. The results show that in the columns with length-diameter ratios of 5 and 8, bulging failure was presented, and the RAC was severely crushed at the bulging area of the specimen. The replacement ratio of RCA as well as BF content little affected specimen's peak load (less than 5%). As the content of BF enhanced from 0 kg/m³ to 4 kg/m³, the dissipation factor and ductility coefficients increased by 10.2% and 5.6%, respectively, with a wide range.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.35-51
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• 2012

Cloud computing is internet-based computing where computing resources are offered over the Internet as scalable and on-demand services. In particular, in case a number of various cloud services emerge in accordance with development of internet and mobile technology, to select and provide services with which service users satisfy is one of the important issues. Most of previous works show the limitation in the degree of user satisfaction because they are based on so called concept similarity in relation to user requirements or are lack of versatility of user preferences. This paper presents cloud service selection reasoning which can be applied to the general cloud service environments including a variety of computing resource services, not limited to web services. In relation to the service environments, there are two kinds of services: atomic service and composite service. An atomic service consists of service attributes which represent the characteristics of service such as functionality, performance, or specification. A composite service can be created by composition of atomic services and other composite services. Therefore, a composite service inherits attributes of component services. On the other hand, the main participants in providing with cloud services are service users, service suppliers, and service operators. Service suppliers can register services autonomously or in accordance with the strategic collaboration with service operators. Service users submit request queries including service name and requirements to the service management system. The service management system consists of a query processor for processing user queries, a registration manager for service registration, and a selection engine for service selection reasoning. In order to enhance the degree of user satisfaction, our reasoning stands on basis of the degree of conformance to user requirements of service attributes in terms of functionality, performance, and specification of service attributes, instead of concept similarity as in ontology-based reasoning. For this we introduce so called a service attribute graph (SAG) which is generated by considering the inclusion relationship among instances of a service attribute from several perspectives like functionality, performance, and specification. Hence, SAG is a directed graph which shows the inclusion relationships among attribute instances. Since the degree of conformance is very close to the inclusion relationship, we can say the acceptability of services depends on the closeness of inclusion relationship among corresponding attribute instances. That is, the high closeness implies the high acceptability because the degree of closeness reflects the degree of conformance among attributes instances. The degree of closeness is proportional to the path length between two vertex in SAG. The shorter path length means more close inclusion relationship than longer path length, which implies the higher degree of conformance. In addition to acceptability, in this paper, other user preferences such as priority for attributes and mandatary options are reflected for the variety of user requirements. Furthermore, to consider various types of attribute like character, number, and boolean also helps to support the variety of user requirements. Finally, according to service value to price cloud services are rated and recommended to users. One of the significances of this paper is the first try to present a graph-based selection reasoning unlike other works, while considering various user preferences in relation with service attributes.