• Journal of information and communication convergence engineering
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• v.15 no.4
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• pp.244-249
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• 2017

Wearable sensor-based gait analysis has been widely conducted to analyze various aspects of human ambulation abilities under the free-living condition. However, there have been few research efforts on using wearable sensors to analyze human walking on an unstable surface such as on a ship during a sea voyage. Since the motion of a ship on the unstable sea surface imposes significant differences in walking strategies, investigation is suggested to find better performing wearable sensor-based gait analysis algorithms on this unstable environment. This study aimed to compare two representative gait event algorithms including time domain and frequency domain analyses for detecting heel strike on an unstable platform. As results, although two methods did not miss any heel strike, the frequency domain analysis method perform better when comparing heel strike timing. The finding suggests that the frequency analysis is recommended to efficiently detect gait event in the unstable walking environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1860-1875
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• 2013

In this paper, we present a comparative performance evaluation of the sampling frequency synchronization method that eliminates the initial sampling frequency offset (SFO) to reduce the overall synchronization time in Digital Radio Mondiale (DRM) receivers. To satisfy the advanced synchronization performance requirements of DRM receivers, we introduce the conventional DRM synchronization method (Method 1) and another method (Method 2), which does not perform the initial sampling frequency synchronization in the conventional synchronization method (both methods are mentioned later in this paper). To demonstrate the effectiveness of the performance evaluation, analytical expressions for frame detection are derived and simulations are provided. Based on the simulations and numerical analysis, our result shows that Method 2, with a negligible performance loss, is robust to the effects of the initial sampling frequency synchronization even if SFO is present in the DRM signal. In addition, we verify that the inter-cell differential correlation used between reference cells is robust to the effect of the initial SFO.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3756-3777
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• 2019

Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.

• Food Science of Animal Resources
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• v.41 no.1
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• pp.85-94
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• 2021

A pig-specific real-time PCR assay based on the mitochondrial ND5 gene was developed to detect porcine material in food and other products. To optimize the performance of assay, seven commercial TaqMan master mixes and two real-time PCR platforms (Applied Biosystems StepOnePlus and Bio-rad CFX Connect) were used to evaluate the limit of detection (LOD) as well as the PCR efficiency and specificity. The LODs and PCR efficiencies for the seven master mixes on two platforms were 0.5-5 pg/reaction and 84.96%-108.80%, respectively. Additionally, non-specific amplifications of DNA from other animal samples (human, dog, cow, and chicken) were observed for four master mixes. These results imply that the sensitivity and specificity of a real-time PCR assay may vary depending on master mix and platform used. The best combination of master mix and real-time PCR platform can accurately detect 0.5 pg porcine DNA, with a PCR efficiency of 100.49%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2414-2433
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• 2021

This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.76-79
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• 2014

Face recognition is very challenging because of the unexpected changes of pose, expression, and illumination. Facial detection in the mobile environments has additional difficulty since the computational resources are very limited. This paper discusses face detection based on frequency domain matched filtering in the mobile environments. Face detection is performed by a linear or phase-only matched filter and sequential verification stages. The candidate window regions are selected by a number of peaks of the matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering tests, which aim to remove false alarms among selected candidate windows. The algorithms are built with JAVA language on the mobile device operated by the Android platform. The simulation and experimental results show that real-time face detection can be performed successfully in the mobile environments.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.302-309
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• 2020

Early-detection and monitoring of toxic chemical gas cloud with chemical detector is essential for reducing the number of casualties. Conventional method for chemical detection and reconnaissance has the limitation in approaching to chemically contaminated site and prompt understanding for the situation. Stand-off detector can detect and identify the chemical gas at a long distance but it cannot know exact distance and position. Chemical detection UAV is an emerging platform for its high mobility and operation safety. In this study, we have conducted chemical gas cloud detection with the stand-off chemical detector and the chemical detection UAV. DMMP vapor was generated in the area where the cloud can be detected through the field of view(FOV) of stand-off chemical detector. Monitoring the vapor cloud with standoff detector, the chemical detection UAV moved back and forth at the area DMMP vapor being generated to detect the chemical contamination. The hybrid detection system with standoff cloud detection and point detection by chemical sensors with UAV seems to be very efficient as a new concept of chemical detection.

• Journal of the Korean Geographical Society
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• v.50 no.5
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• pp.473-483
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• 2015

In a coastal area, a plenty of research has adopted remotely sensed data. This is because longterm interaction between land and ocean makes continuous geographical changes in a broad extent and unaccessible areas. However, conventional remote sensing platforms such as satellite or airplane has several disadvantages including limited temporal resolution and high operational costs. Hence, this study uses a UAV system to detect a coastline and its movement. Result of coastline detection shows how the coastline moves in a day. Time-series coastlines were derived from UAV aerial images through digital image processing. There is a drawback in the stability of UAV compared to the conventional remote sensing platform, but the advantage appears on the economical efficiency. Since the latest studies shows an improvement of UAV for a variety of purposes in many fields, a UAV can also be utilized for regional study and spatial data acquisition platform. geography can also utilize a UAV as a spatial data acquisition platform for regional study.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.101-112
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• 2010

The recent trend of the hacking deals with all the IT infrastructure related to the profit of the companies. Presently, they attack the service itself, the source of the profit, while they tried to access to the service infrastructure through the non-service port in the past. Although they affect the service directly, it is difficult to block them with the old security solution or the old system and they threaten more and more companies with the demand of money menacing the protection of customers and the sustainable management. This paper aims to design and implement multi-platform network packet scanner targeting the exception handling network intrusion detection system which determines normal, abnormal by traffic. Linux and unix have the various network intrusion detection and packet management tools like ngrep, snort, TCPdump, but most of them are based on CUI (Character based User Interface) giving users discomfort who are not used to it. The proposed system is implemented based on GUI(Graphical User Interface) to support the intuitive and easy-to-use interface to users, and using Qt(c++) language that supports multi-platform to run on any operating system.

• Annals of Laboratory Medicine
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• v.38 no.6
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• pp.569-577
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• 2018

Background: The increasing prevalence of drug-resistant tuberculosis (TB) infection represents a global public health emergency. We evaluated the usefulness of a newly developed multiplexed, bead-based bioassay (Quantamatrix Multiplexed Assay Platform [QMAP], QuantaMatrix, Seoul, Korea) to rapidly identify the Mycobacterium tuberculosis complex (MTBC) and detect rifampicin (RIF) and isoniazid (INH) resistance-associated mutations. Methods: A total of 200 clinical isolates from respiratory samples were used. Phenotypic anti-TB drug susceptibility testing (DST) results were compared with those of the QMAP system, reverse blot hybridization (REBA) MTB-MDR assay, and gene sequencing analysis. Results: Compared with the phenotypic DST results, the sensitivity and specificity of the QMAP system were 96.4% (106/110; 95% confidence interval [CI] 0.9072-0.9888) and 80.0% (72/90; 95% CI 0.7052-0.8705), respectively, for RIF resistance and 75.0% (108/144; 95% CI 0.6731-0.8139) and 96.4% (54/56; 95% CI 0.8718-0.9972), respectively, for INH resistance. The agreement rates between the QMAP system and REBA MTB-MDR assay for RIF and INH resistance detection were 97.6% (121/124; 95% CI 0.9282-0.9949) and 99.1% (109/110; 95% CI 0.9453-1.0000), respectively. Comparison between the QMAP system and gene sequencing analysis showed an overall agreement of 100% for RIF resistance (110/110; 95% CI 0.9711-1.0000) and INH resistance (124/124; 95% CI 0.9743-1.0000). Conclusions: The QMAP system may serve as a useful screening method for identifying and accurately discriminating MTBC from non-tuberculous mycobacteria, as well as determining RIF- and INH-resistant MTB strains.