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Characteristics of Ankle Strategy Responses to Dynamic Tilting Perturbations
서한솔(Hansol Seo),정호현(Hohyun Jung),정덕영(Dukyoung Jung),임도형(Dohyung Lim) Korean Society for Precision Engineering 2018 한국정밀공학회지 Vol.35 No.2
Maintaining balance is a factor critical and integral to our effective physical function as it relates to the normal activities of daily living. Of the “hip strategy”, “stepping strategy” and “ankle strategy”, it is known and accepted that the “ankle strategy” is the first activated parameter to assist in the maintenance of balance in motor output. However, few studies actually evaluated or assessed the precise attributes of “ankle strategy” in relation to any therapeutic effort tocorrect and/or rehabilitate from physical imbalance caused by dynamic tilting perturbation. The aim of the study was to identify precise characteristics of the “ankle strategy” as they respond to dynamic tilting perturbations. Seven healthy male (aged 25.5 ± 1.7 years, average height of 173.9 ± 6.4 cm, average body mass of 71.3 ± 6.5 kg) were recruited to participate. The ankle joint motions were subjected to eight dynamic tilting perturbations generated by the customized tilting perturbation simulator, and the responses were measured by 3D motion capture system. Concurrently, foot pressure distribution and the corresponding centers of pressure (COP) trajectory were measured by a pressure measuring system, and the four main muscles’ activations related to the ankle joint motions were measured by wireless electromyogram system.
Hansol Seo(서한솔),Ohbyung Kwon(권오병) 한국지능정보시스템학회 2018 지능정보연구 Vol.24 No.1
Information technology improves the efficiency of humanities research. In humanities research, information technology can be used to analyze a given topic or document automatically, facilitate connections to other ideas, and increase our understanding of intellectual history. We suggest a method to identify and automatically analyze the relationships between arguments contained in unstructured data collected from humanities writings such as books, papers, and articles. Our method, which is called history mining, reveals influential relationships between arguments and the philosophers who present them. We utilize several classification algorithms, including a deep learning method. To verify the performance of the methodology proposed in this paper, empiricists and rationalism - related philosophers were collected from among the philosophical specimens and collected related writings or articles accessible on the internet. The performance of the classification algorithm was measured by Recall, Precision, F-Score and Elapsed Time. DNN, Random Forest, and Ensemble showed better performance than other algorithms. Using the selected classification algorithm, we classified rationalism or empiricism into the writings of specific philosophers, and generated the history map considering the philosopher’s year of activity.