• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1471-1492
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• 2015

The rapid development of smartphone technologies have resulted in the evolution of mobile botnets. The implications of botnets have inspired attention from the academia and the industry alike, which includes vendors, investors, hackers, and researcher community. Above all, the capability of botnets is uncovered through a wide range of malicious activities, such as distributed denial of service (DDoS), theft of business information, remote access, online or click fraud, phishing, malware distribution, spam emails, and building mobile devices for the illegitimate exchange of information and materials. In this study, we investigate mobile botnet attacks by exploring attack vectors and subsequently present a well-defined thematic taxonomy. By identifying the significant parameters from the taxonomy, we compared the effects of existing mobile botnets on commercial platforms as well as open source mobile operating system platforms. The parameters for review include mobile botnet architecture, platform, target audience, vulnerabilities or loopholes, operational impact, and detection approaches. In relation to our findings, research challenges are then presented in this domain.

• Smart Structures and Systems
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• v.7 no.2
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• pp.133-152
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• 2011

System identification is a fundamental step towards the application of structural health monitoring and damage detection techniques. On this respect, the development of evolved identification strategies is a priority for obtaining reliable and repeatable baseline modal parameters of an undamaged structure to be adopted as references for future structural health assessments. The paper presents the identification of the modal parameters of the Guangzhou New Television Tower, China, using a data-driven stochastic subspace identification (SSI-data) approach complemented with an appropriate automatic mode selection strategy which proved to be successful in previous literature studies. This well-known approach is based on a clustering technique which is adopted to discriminate structural modes from spurious noise ones. The method is applied to the acceleration measurements made available within the task I of the ANCRiSST benchmark problem, which cover 24 hours of continuous monitoring of the structural response under ambient excitation. These records are then subdivided into a convenient number of data sets and the variability of modal parameter estimates with ambient temperature and mean wind velocity are pointed out. Both 10 minutes and 1 hour long records are considered for this purpose. A comparison with finite element model predictions is finally carried out, using the structural matrices provided within the benchmark, in order to check that all the structural modes contained in the considered frequency interval are effectively identified via SSI-data.

• Smart Structures and Systems
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• v.6 no.4
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• pp.405-421
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• 2010

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.41-49
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• 2014

Pig chronic wasting disease, including porcine reproductive and respiratory syndrome (PRRS) and postweaning multisystemic wasting syndrome (PMWS), have made a continuous economic damage in pig farms. Airborne spread of livestock viruses are an important spread factor which is difficult to analyze due to invisible airflow and limitation of measurement. The objective of this study is to analyze airborne disease spread between buildings in the experimental pig farm by means of field experiment and computational fluid dynamics (CFD). The field experiments were conducted to capture airborne virus using air sampler and teflon filter along multi points in the experimental pig farm. The samples were tested in terms of virus detection resulting in positive reaction for PRRS and PCV-2 viruses, which can be a firm evidence of airborne virus spread. The CFD simulation model was developed by considering complex topography, wind conditions, building arrangement, and ventilation systems and was used to analyze airborne virus spread according to different wind conditions. The CFD computed result showed a possibility of airborne virus spread via livestock aerosol from infected pig house to neighboring pig houses according to wind directions. The CFD simulation technique is expected to provide significant data for estimating and making a counterplan against airborne disease spread.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.153-162
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• 2014

We show that carbon nanotube sensors with gold particles on the single-walled carbon nanotube (SWNT) network operate as Schottky barrier transistors, in which transistor action occurs primarily by varying the resistance of Au-SWNT junction rather than the channel conductance modulation. Transistor characteristics are calculated for the statistically simplified geometries, and the sensing mechanisms are analyzed by comparing the simulation results of the MOSFET model and Schottky junction model with the experimental data. We demonstrated that the semiconductor MOSFET effect cannot explain the experimental phenomena such as the very low limit of detection (LOD) and the logarithmic dependence of sensitivity to the DNA concentration. By building an asymmetric concentric-electrode model which consists of serially-connected segments of CNTFETs and Schottky diodes, we found that for a proper explanation of the experimental data, the work function shifts should be ~ 0.1 eV for 100 pM DNA concentration and ~ 0.4 eV for $100{\mu}M$.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.1
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• pp.27-33
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• 2017

GPS provides the positioning solution in most areas of the world. However, the position error largely occurs in the urban area due to signal attenuation, signal blockage, and multipath. Although many studies have been carried out to solve this problem, a definite solution has not yet been proposed. Therefore, research is being conducted to solve the vehicle localization problem in the urban environment by converging sensors such as cameras and Light Detection and Ranging (LIDAR). In this paper, the precise vehicle localization using 3D LIDAR (Velodyne HDL-32E) is performed in the urban area. As there are many tall buildings in the urban area and the outer walls of urban buildings consist of planes generally perpendicular to the earth's surface, the outer wall of the building meets at a vertical corner and this vertical corner can be accurately extracted using 3D LIDAR. In this paper, we describe the vertical corner extraction method using 3D LIDAR and perform the precise localization by combining the extracted corner position and GPS/DR information. The driving test was carried out in an about 4.5 km-long section near Teheran-ro, Gangnam. The lateral and longitudinal RMS position errors were 0.146 m and 0.286 m, respectively and showed very accurate localization performance.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.91-114
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• 2016

In this paper, recent research trends and activities on structural health monitoring (SHM) of civil infrastructure in Korea are reviewed. Recently, there has been increasing need for adopting smart sensing technologies to SHM, so this review focuses on smart sensing, monitoring, and assessment for civil infrastructure. Firstly, the research activities on smart sensor technology is reviewed including optical fiber sensors, piezoelectric sensors, wireless smart sensors, and vision-based sensing system. Then, a brief overview is given to the recent advances in smart monitoring and assessment techniques such as vibration-based global monitoring techniques, local monitoring with piezoelectric materials, decentralized monitoring techniques for wireless sensors, wireless power supply and energy harvest. Finally, recent joint SHM activities on several test beds in Korea are discussed to share the up-to-date information and to promote the smart sensors and monitoring technologies for applications to civil infrastructure. It includes a Korea-US joint research on test bridges of the Korea Expressway Corporation (KEC), a Korea-US-Japan joint research on Jindo cable-stayed bridge, and a comparative study for cable tension measurement techniques on Hwamyung cable-stayed bridge, and a campaign test for displacement measurement techniques on Sorok suspension bridge.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.256-263
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• 2002

Optical Multistage Interconnection Networks(OMINs) comprising photonic switches have been studied extensively as important interconnecting building blocks for communication networks and parallel computing systems. A basic element of photonic switching networks is a 2$\times$2 directional coupler with two inputs and two outputs. This paper is concerned with the diagnosis of cross-talk-faults in OMINs. As the size of today's network becomes very large, the conventional diagnosis methods based on tests and simulation have become inefficient, or even more, impractical. In this paper, we propose a simple and easily implementable algorithm for detection and isolation of the single crosstalk-fault in OMINs. Specifically, we develope an algorithm fur the isolation of the source fault in switching elements whenever the single crosstalk-fault is detected in OMINS. The proposed algorithm is illustrated by an example of 16$\times$16 banyan network.

• Tunnel and Underground Space
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• v.14 no.1
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• pp.35-42
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• 2004

Impact-echo is a method for non-destructive testing of concrete structure. This method is based on the use of impact-generated stress wave which is propagated and reflected from internal flaws within concrete structure and external surface. In this study, we performed non-destructive testing using impact-echo methods for safety diagnosis of civil engineering and building structures. There are testing cases for the three models having one-dimensional form ; The first case is the measurement of thickness change of the model, the second is the detection of cavity in the model, and the third is the predictions of the lining thickness and the position of the cavity under tunnel lining condition.

• Agribusiness and Information Management
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• v.3 no.1
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• pp.11-22
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• 2011

This study describes the development of a web-based system that collects all data generated in the research conducted to set pre-harvest residue limits (PHRLs) for agricultural product safety control. These data, including concentrations of pesticide residues, limit of detection, limit of quantitation, recoveries, weather charts, and growth rates, are incorporated into a database, a regression analysis of the data is performed using statistical techniques, and the PHRL for an agricultural product is automatically computed. The development and establishment of this system increased the efficiency and improved the reliability of the research in this area by standardizing the data and maintaining its accuracy without temporal or spatial limitations. The system permits automatic computation of the PHRL and a quick review of the goodness of fit of the regression model. By building and analyzing a database, it also allows data accumulated over the last 10 years to be utilized.