• IE interfaces
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• v.22 no.1
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• pp.17-25
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• 2009

In mobile device's user interface, menu organization is very important as well as menu structure because small display of mobile device. Menu items should be organized based on user knowledge structure to design user-centered interface. Traditionally, MDS (Multidimensional Scaling) have been most often used to expose users' perceived organization of menu items. But, information that MDS reveals is just relative spatial location of concepts and not relevant to concepts connection. Unlike MDS, Trajectory Mapping explicitly finds users' cognitive links between perceived concepts. This study proposes a Trajectory Mapping technique for eliciting knowledge structure, especially a set of cognitive pathways linking menu items, from end user. With twelve participants, MDS and Trajectory Mapping were conducted using cellular phone's menu items. And user knowledge structure was analyzed through Visual Concept Map that combination of results of MDS and Trajectory Mapping. After then, menu items were organized according to users' perceived organization. Empirical usability test was also conducted. The results of usability test showed that usability, in terms of task performance time, number of errors, and satisfaction, for newly organized interface was significantly improved compare to original interface. The methodology of this study is expected to be applicable to design a user-centered interface. In other words, Trajectory Mapping technique can be used as a design tool of user interface for imposing user knowledge structure on the interface.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.399-404
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• 2008

사용자 중심의 메뉴 기반 인터페이스를 설계하기 위해서는 인간의 지식 구조를 이해하는 것이 중요하다. 인간의 지식 구조를 이해하게 되면, 인터페이스를 통해서 전달된 자극들이 만들어낸 개념들이 어떠한 관계를 가지고 정신 모형(mental model)을 형성하고 있는지 알 수 있다. 인간의 지식 구조는 MDS (Multidimensional Scaling)과 Trajectory Mapping을 이용하여 Visual Concept Map 으로 나타낼 수 있고, 이것을 바탕으로 인간의 지식구조를 시각적으로 이해할 수 있다. MDS 는 인간의 머릿속에 자리잡고 있는 개념들의 상대적 위치를 알려주고, Trajectory Mapping 은 개념들 간의 연결 상태를 보여준다. 즉, Trajectory Mapping 을 통하여 개념들 간악 인지적 정보를 알 수 있다. 본 연구에서는 MDS 와 Trajectory Mapping 을 이용하여 핸드폰 메뉴로부터 전달 받은 시각적 자극들에 악해 형성된 개념들에 대한 인간의 지식 구조를 Visual Concept Map 으로 시각화하였다. 그리고 이렇게 시각화된 지식 구조를 바탕으로 메뉴 구조를 개발하였다. 본 연구 결과, MDS 와 Trajectory Mapping 을 이용한 인간의 지식 구조의 시각화는 사용자 중심의 메뉴 기반 인터페이스를 설계하는데 유용하게 쓰일 수 있을 것으로 보인다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.465-470
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• 2015

This paper proposes a robust 3D mapping system for a UAV (Unmanned Aerial Vehicle) that carries a LRF (Laser Range Finder) using the sinusoidal trajectory algorithm. In the case of previous 3D mapping research, the UAV usually takes off vertically and flights up and down while the LRF is measuring horizontally. In such cases, the measuring range is limited and it takes a long time to do mapping. By using the sinusoidal trajectory algorithm proposed in this research, the 3D mapping can be time-efficient and the measuring range can be widened. The 3D mapping experiments have been done to evaluate the performance of the sinusoidal trajectory algorithm by scanning indoor walls.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.102-105
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• 2005

A Effective wall following plays important role for the mapping behaviors which determine the entire memory size and the shape of map before building a map. In case of wall following, attacking those cause by curved wall or obstacles brings a bad stuff that makes ripples on the moving trajectory. These types of ripples come to an end with problems that increase the load of calculation and sensing errors. In this paper, a new sensing method and its corresponding controller are suggested for problems. It minimizes the occurrence of the trajectory ripples.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.230-235
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• 1992

We propose a method of generating data to train a neural network controller. The data can be prepared directly by an iterative learning technique which repeatedly adjusts the control input to improve the tracking quality of the desired trajectory. Instead of storing control input data in memory as in iterative learning control, the neural network stores the mapping between the control input and the desired output. We apply this concept to the trajectory control of a two link robot manipulator with a feedforward neural network controller and a feedback linear controller. Simulation results show good generalization of the neural network controller.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• Communications of the Korean Mathematical Society
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• v.11 no.1
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• pp.71-79
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• 1996

In this paper, we prove for a nonexpansive mapping T that under certain conditions the trajectory $t \to G_t(x), t \in [0,1]$, defined by the equation $G_t(x) = (1 - t)x + tTG_t(x)$ strongly converges to a fixed point of T as $t \to 1^{-1}$.

• Communications of the Korean Mathematical Society
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• v.17 no.1
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• pp.37-51
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• 2002

Let X be a reflexive Banach space with a uniformly Gateaux differentiable norm, C a nonempty bounded open subset of X, and T a continuous mapping from the closure of C into X which is locally pseudo-contractive mapping on C. We show that if the closed unit ball of X has the fixed point property for nonexpansive self-mappings and T satisfies the following condition: there exists z $\in$ C such that ∥z-T(z)∥<∥x-T(x)∥ for all x on the boundary of C, then the trajectory tlongrightarrowz$_{t}$$\in$C, t$\in$[0, 1) defined by the equation z$_{t}$ = tT(z$_{t}$)+(1-t)z is continuous and strongly converges to a fixed point of T as t longrightarrow 1￣.ow 1￣.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.479-484
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• 1992

The resolved motion rate control (RMRC) is converting to Joint space trajectory from given Cartesian space trajectory. The RMRC requires the inverse of Jacobian matrix. Since the Jacobian matrix of the redundant robot is generally not square, the pseudo-inverse must be introduced. However the pseudo-inverse is not easy to be implemented on a digital computer in real time as well as mathematically complex. In this paper, a simple fuzzy resolved motion rate control (FRMRC) that can replace the RMRC using pseudo-inverse of Jacobian is proposed. The proposed FRMRC with appropriate fuzzy rules, membership functions and reasoning method can solve the mapping problem between the spaces without complexity. The mapped Joint space trajectory is sufficiently accurate so that it can be directly used to control redundant manipulators. Simulation results verify the efficiency of the proposed idea.