Sang-Hyeon Kim

Comparative analysis of the anxiety-related behaviors in four inbred mice

An anxiety-related behavior is an emotional response of an organism, which is quantitatively measured by several behavioral paradigms. We employed two most frequently used behavioral tests, the open field and light-dark exploration, to comparatively analyze the anxiety-like behaviors in four inbred mice. For an accurate recording of movement, motion analysis software was developed that acquires a real-time video input to generate a behavioral path. Effects of the strains on the test results were evaluated by ANOVA with the Newman-Keuls post hoc comparison. Eight different behavioral indices, four from each tests, were grouped into two classes; the results of duration, center crossing, transition, rearing, and ambulation indicate strain differences of FVB/N>C57BL/6J>/=BALB/cA>/=CBA/N (I), while stretched-attend posture, peeping, and defecation show the tendency of FVB/N=C57BL/6J<CBA/N</=BALB/cA (II). The peeping is a novel type of behavior observed in this work. Although there is a variation among behavioral indices in their discrimination between inbred lines, the behaviors are highly correlated one another such that each class I or class II behaviors are clustered on two orthogonal factor planes as a result of the principal component analysis. The polarization of each inbred line toward these two behavioral biases may reflect genetic backgrounds of these strains.

Convolutional neural network-based spacecraft attitude control for docking port alignment

This paper proposes the spacecraft attitude control algorithm based on Convolutional Neural Networks (CNNs) for spacecrafts docking port alignment. the CNN model is used in order to recognize the attitude of target spacecraft and the attitude controller aligns the docking port of the target spacecraft using the target spacecrafts attitude information obtained from CNN. Three-Dimensional spacecraft simulator is developed for training CNN model and testing the algorithm. Experiments are conducted for demonstrating the target spacecrafts attitude recognition and attitude control performances of the proposed algorithm.

Distributed Observes for Cyberattack Detection and Isolation in Formation-Flying Unmanned Aerial Vehicles

In this paper, cyberattack detection and isolation is studied for a network of formation-flying unmanned aerial vehicles. As the unmanned aerial vehicles communicate to reach consensus on their sta...

An IMM-based method for reentry-phase tracking of unknown ballistic missiles

In this paper, the tracking system which is related to the ballistic missile defense (BMD) is considered. In BMD system, it is necessary to track the fast and unknown objects. Furthermore, priori information about the hostile missile is not provided. Without the priori information like aerodynamic parameters, it is hard to make the filter dynamic model of the hostile missile. To solve this problem, in many researches, IMM filter is selected as a tracking filter of BMD system. But IMM filter itself is not a perfect tool for tracking the unknown target. If the IMM filter mode set does not subsume the true dynamic model, the tracking filter may have large error. So, the mode revision method is suggested. With this method, the IMM mode set is adaptively changed and then subsumes the true dynamic model.

Comparative analysis of the responses to intruders with anxiety‐related behaviors of mouse

Anxiety in mice can be measured by behavioral reactivity to social or non‐social Stressors. These behaviors were compared by performing the resident‐intruder test (social) as well as the light‐dark transition and open‐field tests (non‐social) for the FVB, C57BL/6, and BALB/c lines of mouse. The three inbred lines showed significant differences in their responses to intruder mice. Three factors, accounting for about 68% of the total variance, were extracted from the scores obtained from the three behavioral tests. The first two major factors are primarily associated with the anxiety‐related behaviors. One includes anxiety behaviors with a locomotive basis, while the other includes defecation measured in both anxiety tests. The third factor explains the three social behaviors, facial investigation, ano‐genital investigation, and following, observed in the resident intruder test, although facial investigation is also moderately associated with the second factor. The results indicate that the behavioral responses to an intruder share a component distinct from anxiety‐related behaviors.

SVM-Based Fault Type Classification Method for Navigation of Formation Control Systems

In this paper, we propose a fault type classification algorithm for a networked multi-robot formation control. Both actuator and sensor faults of a robot are considered as node fault on the networked system. The Support Vector Machine (SVM) based classification scheme is proposed in order to classify the fault type accurately. Basically, the graph-theoretic approach is used for modeling the multi-agent communication and to generate the formation control law. A numerical simulation is presented to confirm the performance of proposed fault type classification method.