• Advances in aircraft and spacecraft science
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• v.4 no.2
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• pp.185-202
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• 2017

In a flexible airvehicle, an assessment of the structural coupling levels through analysis and experiments provides structural data for the design of notch filters which are generally utilized in the flight control system to attenuate the flexible response pickup. This is necessitated as during flight, closed loop control actuation driven with flexible response inputs could lead to stability and performance related problems. In the present work, critical parameters influencing servoelastic response have been identified. A sensitivity study has been carried out to assess the extent of influence of each parameter. A multi-parameter tuning approach has been implemented to achieve an enhanced analytical model for improved predictions of aircraft servoelastic response. To illustrate the model updation approach, initial and improved test analysis correlation of lateral servoelastic responses for a generic flexible airvehicle are presented.

• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.29-38
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• 2018

Through process quality information, the time required for process quality analysis has been drastically shortened, the process defect rate has been reduced, and the manufacturing lead time has been shortened and the on-time delivery rate has been improved. Therefore, The purpose of this study is to develop a quality information analysis system model that effectively shortens the time required for process quality analysis in automobile safety belt parts manufacturing process. As a result of experiments on communication operation between manufacturing execution system (MES) quality server, injection machine control computer, injection machine programmable logic controller (PLC) and terminal, in analyzing quality information, the conventional handwriting input method took an average of 20 minutes, but the new multi-network method took about 2 minutes on average. In addition, the process defect rate was reduced by 13% and the manufacturing lead time was shortened from 28 hours to 20 hours. The delivery compliance rate improved from 96 to 99%.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.23-28
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• 2021

The gripper with a soft pneumatic actuator uses a soft material, unlike the gripper that uses a rigid body, so it is safer and lighter to interact with objects without advanced control technology. Among the soft pneumatic actuators that have been studied, PneuNets actuators have bellows shape, which enable quick operation and complete bending with only small material deformation at low pressure. In this study, we suggested improved form of PneuNets actuators to obtain the performance of the soft actuator that a larger bending angle and larger bending force at a small pressure. An experiment was designed and conducted to measure the bending angle and bending force according to the pressure. As a result, it was confirmed through experiments that the improved model has a maximum bending angle at a pressure of 5 kPa lower than that of the previous model, and a maximum bending force of 1.97 times at the same pressure.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1309-1323
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• 2020

Crowd evacuation simulation is an important research issue for designing reasonable building layouts and planning more effective evacuation routes. The social force model (SFM) is an important pedestrian movement model, and is widely used in crowd evacuation simulations. The model can effectively simulate crowd evacuation behaviors in a simple scene, but for a multi-obstacle scene, the model could result in some undesirable problems, such as pedestrian evacuation trajectory oscillation, pedestrian stagnation and poor evacuation routing. This paper analyzes the causes of these problems and proposes an improved SFM for complex multi-obstacle scenes. The new model adds navigation points and walking shortest route principles to the SFM. Based on the proposed model, a crowd evacuation simulation system is developed, and the crowd evacuation simulation was carried out in various scenes, including some with simple obstacles, as well as those with multi-obstacles. Experiments show that the pedestrians in the proposed model can effectively bypass obstacles and plan reasonable evacuation routes.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.110-117
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• 2022

This paper describes a localization algorithm utilizing relative observations for multiple autonomous underwater vehicles (Multiple-AUVs). In order to maximize the efficiency of operation and mission accomplishment and to prevent problems such as collision and interference, the locations and directions of Multiple-AUVs must be precisely estimated. To estimate the locations and directions, we designed a localization algorithm utilizing relative observations and verified it with simulations based on sensor data sets acquired through real sea experiments. Also, an optimal combination of relative observation information for efficient localization is figured out through combining various relative observations. The proposed method shows improved localization results compared to those only using the navigation algorithm. The performance of localization is improved up to 58% depending on the combination of relative observations.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.141-151
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• 1993

For navigation of a mobile robot, it is one of the essential tasks to find out its current position. Dead reckonining is the most frequently used method to estimate its position. Hpwever conventional dead reckoner is prone to give us false information on the robot position especially when the wheels are slipping. This paper proposes an improved dead reckoning scheme using neural networks. The network detects the instance of wheel slopping and estimates the linear velocity of the wheel; thus it calculates current position and heading angle of a mobile robot. The structure and variables of the nerual network are chosen in consideration of slip motion characteristics. A series of experiments are performed to train the networks and to investigate the performance of the improved dead reckoning system.

• Advances in aircraft and spacecraft science
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• v.10 no.5
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• pp.393-418
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• 2023

Drones are increasingly used in logistics delivery due to their low cost, high-speed and straight-line flight. Considering the small cargo capacity, limited endurance and other factors, this paper optimized the pickup and delivery vehicle routing problem with time windows in the mode of "truck+drone". A mixed integer programming model with the objective of minimizing transportation cost was proposed and an improved adaptive large neighborhood search algorithm is designed to solve the problem. In this algorithm, the performance of the algorithm is improved by designing various efficient destroy operators and repair operators based on the characteristics of the model and introducing a simulated annealing strategy to avoid falling into local optimum solutions. The effectiveness of the model and the algorithm is verified through the numerical experiments, and the impact of the "truck+drone" on the route cost is analyzed, the result of this study provides a decision basis for the route planning of "truck+drone" mode delivery.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.83-88
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• 2024

In this paper we used classification algorithms on social networking. We are proposing, a new classification algorithm called the improved Decision Tree (IDT). Our model provides better classification accuracy than the existing systems for classifying the social network data. Here we examined the performance of some familiar classification algorithms regarding their accuracy with our proposed algorithm. We used Support Vector Machines, Naïve Bayes, k-Nearest Neighbors, decision tree in our research and performed analyses on social media dataset. Matlab is used for performing experiments. The result shows that the proposed algorithm achieves the best results with an accuracy of 84.66%.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.692-695
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• 2024

With the recent advancements in artificial intelligence (AI), the performance of deep learning-based audio deepfake technology has significantly improved. This technology has been exploited for criminal activities, leading to various cases of victimization. To prevent such illicit outcomes, this paper proposes a deep learning-based audio deepfake detection model. In this study, we propose CoNSIST, an improved audio deepfake detection model, which incorporates three additional components into the graph-based end-to-end model AASIST: (i) Squeeze and Excitation, (ii) Positional Encoding, and (iii) Reformulated HS-GAL, This incorporation is expected to enable more effective feature extraction, elimination of unnecessary operations, and consideration of more diverse information, thereby improving the performance of the original AASIST. The results of multiple experiments indicate that CoNSIST has enhanced the performance of audio deepfake detection compared to existing models.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.272-283
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• 2017

In this paper, an improved predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) control system is proposed, on account of the standard PFC method cannot provides a satisfying disturbance rejection performance in the case of strong disturbances. The PFC-based method is first introduced in the control design of speed loop, since the good tracking and robustness properties of the PFC heavily depend on the accuracy of the internal model of the plant. However, in orthodox design of prediction model based control method, disturbances are not considered in the prediction model as well as the control design. A minimum-order observer (MOO) is introduced to estimate the disturbances, which structure is simple and can be realized at a low computational load. This paper adopted the MOO to observe the load torque, and the observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC strategy with torque compensation, called the PFC+MOO method, is presented. The validity of the proposed method was tested via simulation and experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.