• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.435-442
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• 2018

Outlier detection means to detect data samples that deviate significantly from the distribution of normal data. Most outlier detection methods calculate an outlier score that indicates the extent to which a data sample is out of normal state and determine it to be an outlier when its outlier score is above a given threshold. However, since the range of an outlier score is different for each data and the outliers exist at a smaller ratio than the normal data, it is very difficult to determine the threshold value for an outlier score. Further, in an actual situation, it is not easy to acquire data including a sufficient amount of outliers available for learning. In this paper, we propose a clustering-based outlier detection method by constructing a model representing a normal data region using only normal data and performing binary classification of outliers and normal data for new data samples. Then, by dividing the given normal data into chunks, and constructing a clustering model for each chunk, we expand it to the ensemble method combining the decision by the models and apply it to the streaming data with dynamic changes. Experimental results using real data and artificial data show high performance of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.627-635
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• 2019

A programmable drone is a drone developed not only to experience the basic principles of flight but also to control drones through Arduino-based programming. Due to the nature of the training drones, the main users are students who are inexperienced in controlling the drones, which often cause frequent collisions with external objects, resulting in high damage to the drones' frame. In this study, the structural stability of the drone was evaluated by means of a structural dynamics based collision simulation for educational drone frame. Collision simulations were performed on three cases according to the impact angle of $0^{\circ}$, $+15^{\circ}$ and $-15^{\circ}$, using an analytical model with approximately 240,000 tetrahedron elements. Using ANSYS LS-DYNA, which provides excellent functions for the simulation of the dynamic behavior of three-dimensional structures, the stress distribution and strain generated on the drone upper, the drone lower, and the ring assembly were analyzed when the drones collided against the wall at a rate of 4 m/s. Safety factors resulting from the equivalent stress and the yield strain were calculated in the range of 0.72 to 2.64 and 1.72 to 26.67, respectively. To ensure structural stability for areas where stress exceeds yield strain and ultimate strain according to material properties, the design reinforcement is presented.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.6
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• pp.253-262
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• 2018

Oscillating Water Column (OWC) Wave Energy Converters (WEC) harness electricity through a Power-Take-Off (PTO) system from the induced-airflow by seawater oscillating inside a chamber. In general, an air chamber with a relatively small cross-sectional area is required compared to seawater chamber to obtain high-velocity air in the PTO system, and in order to simulate an accurate air flow rate in the air chamber, a three-dimensional study is required. In this study, the dynamic response of OWC-WEC that is equipped with the channel of seawater exchange for the case of irregular waves has been numerically studied. The open source CFD software, OLAFLOW for the simulation of wave dynamics to the openFOAM and FOAM-extend communities, was used to simulate the interaction between the device and irregular waves. Based on the numerical simulation results, we discussed the fluctuation characteristics of three dimensional air flow in the air-chamber, wave deformation around the structure and the seawater flow inside the channel of seawater exchange. The numerical results the maximum air flow velocity in the air-chamber increases as the Ursell value of the significant wave increases, and the velocity of airflow flowing out from the inside of air chamber to the outside is greater than the speed of flowing into the air chamber from the outside.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.1
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• pp.109-115
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• 2019

In arc-welding applying to the present automobile part manufacturing process, a wrist-hollow type arc welding robot can shorten the welding cycle time, because feedability of a welding wire is not affected by a robot posture and thus facilitates high-quality arc welding, based on stable feeding with no entanglement. In this paper, we will propose the optimization of wrist design for a wrist-hollow type 6-Axis articulated robot. Specifically, we will perform the investigation on the optimized design of inner diameter of hollow arms (Axis 4 and Axis 6) and width of the upper arm by using the simulation of robot motion characteristics, using a Genetic Algorithm (i.e., GA). Our simulations are based on $SolidWorks^{(R)}$ for robot modeling, $MATLAB^{(R)}$ for GA optimization, and $RecurDyn^{(R)}$ for analyzing dynamic characteristics of a robot. Especially $RecurDyn^{(R)}$ is incorporated in the GA module of $MATLAB^{(R)}$ for the optimization process. The results of the simulations will be verified by using $RecurDyn^{(R)}$ to show that the driving torque of each axis of the writs-hollow 6-axis robot with the optimized wrist design should be smaller than the rated output torque of each joint servomotor. Our paper will be a guide for improving the wrist-hollow design by optimizing the wrist shape at a detail design stage when the driving torque of each joint for the wrist-hollow 6-axis robot (to being developed) is not matched with the servomotor specifications.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.926-931
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• 2011

Among various techniques for hydrogen production from organic wastewater, a dark fermentation is considered to be the most feasible process due to the rapid hydrogen production rate. However, the main drawback of it is the low hydrogen production yield due to intermediate products such as organic acids. To improve the hydrogen production yield, a co-culture system of dark and photo fermentation bacteria was applied to this research. The maximum specific growth rate of R. sphaeroides was determined to be $2.93h^{-1}$ when acetic acid was used as a carbon source. It was quite high compared to that of using a mixture of volatile fatty acids (VFAs). Acetic acid was the most attractive to the cell growth of R. sphaeroides, however, not less efficient in the hydrogen production. In the co-culture system with glucose, hydrogen could be steadily produced without any lag-phase. There were distinguishable inflection points in the accumulation of hydrogen production graph that resulted from the dynamic production of VFAs or consumption of it by the interaction between the dark and photo fermentation bacteria. Lastly, the hydrogen production rate of a repeated fed-batch run was $15.9mL-H_2/L/h$, which was achievable in the sustainable hydrogen production.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.449-460
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• 2021

ASVspoof 2017 deals with detection of replay attacks and aims to classify real human voices and fake voices. The spoofed voice refers to the voice that reproduces the original voice by different types of microphones and speakers. data augmentation research on image data has been actively conducted, and several studies have been conducted to attempt data augmentation on voice. However, there are not many attempts to augment data for voice replay attacks, so this paper explores how audio modification through data augmentation techniques affects the detection of replay attacks. A total of 7 data augmentation techniques were applied, and among them, dynamic value change (DVC) and pitch techniques helped improve performance. DVC and pitch showed an improvement of about 8% of the base model EER, and DVC in particular showed noticeable improvement in accuracy in some environments among 57 replay configurations. The greatest increase was achieved in RC53, and DVC led to an approximately 45% improvement in base model accuracy. The high-end recording and playback devices that were previously difficult to detect were well identified. Based on this study, we found that the DVC and pitch data augmentation techniques are helpful in improving performance in the voice spoofing detection problem.

• Korean Journal of Applied Biomechanics
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• v.31 no.1
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• pp.1-15
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• 2021

Objective: The aim of this study was to investigate 1) the difference in static lower extremity alignment (SLEA) according to a history of lateral ankle sprain (LAS), 2) to identify SLEA factors affecting LAS, and 3) to present the cut-off value and 4) the usefulness and limitations of the SLEA measurement. Method: This case-control study recruited 88 men (age: 27.78±4.69 yrs) and 39 women (age: 24.62±4.20 yrs) subjects with and without LAS. SLEA measurement protocol included Q angle, tibiofemoral angle, genu recurvatum, rear foot (RF) angle, tibal varum and torsion, navicular drop, ankle dorsiflexion range of motion (DF ROM). Independent t-test, logistic regression and receiver operating characteristic (ROC) curve were used for statistical analysis. Results: Men with a history of LAS had significantly smaller Q angles both in standing and in supine position, while women with a history of LAS had significantly greater DF ROM in non-weight bearing (NWB; p < 0.05). Logistic regression model suggests tibial varum (OR = 0.779, p = 0.021) and WB DF ROM (OR = 1.067, p = 0.045) were associated with LAS in men. In case of women, there were no significant SLEA factors for LAS, however, ROC curve analysis revealed standing RF angle (AUC = 0.647, p = 0.028) and NWB DF ROM (AUC = 0.648, p = 0.026) could be affecting factors for LAS. Conclusion: There are differences in SLEA according to the history of LAS, furthermore, the identified items were different by sex. In case of men, tibial varum and WB DF ROM affect LAS occurrence. Standing RF angle and NWB DF ROM of women could be a predictor for LAS. However, since the sensitivity and specificity in most of the SLEA measurements are low, kinematic in dynamic tasks should be considered together for a more accurate evaluation of LAS risk.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.2
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• pp.89-94
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• 2021

The mechanical reliability of flexible devices has become a major concern on their commercialization, where the importance of reliable bonding is highlighted. In terms of component materials' properties, it is important to consider thermal damage of polymer substrates that occupy large area of the flexible device. Therefore, room temperature bonding process is highly advantageous for implementing flexible device assemblies with mechanical reliability. Conventional epoxy resins for the bonding still require curing at high temperatures. Even after the curing procedure, the bonding joint loses flexibility and exhibits poor fatigue durability. To solve this problems, low-temperature and adhesive-free bonding are required. In this work, we develop a room temperature bonding process for polymer substrates using carbon nanotube heated by microwave irradiations. After depositing multiple-wall carbon nanotubes (MWNTs) on PET polymer substrates, they are heated locally with by microwave while the entire bonding specimen maintains room temperature and the heating induces mechanical entanglement of CNT-PET. The room temperature bonding was conducted for a PET/CNT/PET specimen at 600 watt of microwave power for 10 seconds. Thickness of the CNT bonding joint was very thin that it obtains flexibility as well. In order to evaluate the mechanical reliability of the joint specimen, we performed lap shear test, three-point bending test, and dynamic bending test, and confirmed excellent joint strength, flexibility, and bending durability from each test.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.