• Smart Media Journal
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• v.13 no.4
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• pp.48-56
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• 2024

In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.

• Smart Structures and Systems
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• v.18 no.5
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• pp.983-1004
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• 2016

Nowadays, there are two classes of methods for damage detection in structures consisting of static and dynamic. The dynamic methods are based on studying the changes in structure's dynamic characteristics. The theoretical basis of this method is that damage causes changes in dynamic characteristics of structures. The dynamic methods are divided into two categories: signal based and modal based. The modal based methods utilize the modal properties consisting of natural frequencies, modal damping and mode shapes. As the modal properties are sensitive to changes in the structure, these can be used for detecting the damages. In this study, using dynamic method and modal based approach (natural frequencies and mode shapes), the objective function is formulated. Then, detection of damages of truss structures is addressed by using Simplified Dolphin Echolocation algorithm and solving inverse optimization problem. Many scenarios are used to simulate the damages. To demonstrate the ability of the algorithm, different truss structures with several multiple elements scenarios are tested using a few runs. The influence of the two different levels of noise in the modal data for these scenarios is also considered. The last example of this article is investigated using a different mutation. This mutation obtains the exact answer with fewer loops and population by limited computational effort.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.19-25
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• 2017

Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1729-1736
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• 2004

This paper proposes an efficient collision detection method in the dynamic spatial subdivisions for the MMORPG engine which requires realtime interactions. An octree is a suitable structure for static scenes or terrain processing. An octree spatial subdivision enhances rendering speed of scenes. Current spatial subdivisions tend to be highly optimized for efficient traversal, but are difficult to update quickly for a changing geometry. When an object moves to the outside extent for the spatial subdivisions, the acceleration structure would normally have to be rebuilt. The OSP based on a tree is used to divide dynamically wide outside which is the subject of 3D MMORPG. TBV does not reconstruct all tree nodes of OSP and has reduced rebuilding times by TBV information of a target node. A collision detection is restricted to those objects contained in the visibility range of sight by using the information established in TBV. We applied the HBV and ray tracing for an efficient collision detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1301-1314
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• 2018

In this paper, we present a low-cost fire detection system using a thermal camera and a smartphone. The developed system collects thermal and RGB videos from the developed camera. To detect fire, candidate fire regions are extracted from videos obtained using a thermal camera. The block mean of variation of adjacent frames is measured to analyze the dynamic characteristics of the candidate fire regions. After analyzing the dynamic characteristics of regions of interest, a fire is determined by the candidate fire regions. In order to evaluate the performance of our system, we compared with a smoke detector, a heat detector, and a flame detector. In the experiments, our fire detection system showed the excellent performance in detecting fire with an overall accuracy rate of 97.8 %.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.102-108
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• Structural Engineering and Mechanics
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• v.53 no.2
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• pp.249-260
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• 2015

Damage detection based on a reference set of measured data usually has the problem of different environmental temperature in the two sets of measurements, and the effect of temperature difference is usually ignored in the subsequent model updating. This paper attempts to identify the structural damage including the temperature difference with artificial measurement noise. Both local damages and the temperature difference are identified in a gradient-based model updating method based on dynamic response sensitivity. The sensitivities of dynamic response with respect to the system parameters and temperature difference are calculated by direct integration method. The measured dynamic responses of the structure from two different states are used directly to identify the structural local damages and the temperature difference. A single degree-of-freedom mass-spring system and a planar truss structure are studied to illustrate the effectiveness of the proposed method.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.786-791
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• 2004

This study proposed the analysis of mass position detection and modified stiffness due to the change of the mass and stiffness of structure by using the original and modified dynamic characteristics. The method is applied to examples of a cantilever and 3 degree of freedom by modifying the mass. The predicted detection of mass positions and magnitudes are in good agreement with these from the structural reanalysis using the modified mass.

• Journal of Advanced Navigation Technology
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• v.17 no.5
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• pp.560-567
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• 2013

In this paper, it is proposed the fault detection method of the ASIC, without the Test Requirement Document(TRD), extracting internal logic circuit and analyzed the function of the ASIC using the multipurpose development program and simulation. If there don't have the TRD, it is impossible to analyze the operation of the circuit and find out the fault detection in any chip. Therefore, we make the TRD based on the analyzed logic data of the ASIC, and diagnose of the ASIC circuit at the gate level through the signal control of I/O pins using the Dynamic Pattern signal. According to the experimental results of the proposed method, we is confirmed the good performance of the fault detection capabilities which applied to the non-memory circuit.