This paper improves Collaborative Filtering Algorithms (CF) to recommend similar bookmarks for users of Social Bookmark Services. Standard CF algorithms have a problem with precision in multi-genre cases such as social bookmarks. We aim at solving this issue and propose a personal classification space-based collaborative filtering algorithm. Our interpretation is that users' bookmarks are disposed in their own classification space made by tags. The bookmark is transformed into a scalar as a similarity to a starting bookmark for a recommendation. We compare the personal classification space with others' space using the similarities. We handle the similarities as the rating to the bookmark in standard CF algorithms. The proposed algorithm is compared with other existing algorithms. In conclusion, our algorithm shows better precision than others.
In this paper, for an undirected network consisting of identical multi-dimensional linear subsystems in which the network structure is unknown and the number of input/output ports is less than that of subsystems, we propose a novel method to identify the strength of the connectivity between specified two subsystems. The proposed method is on the basis of the node knock-out procedure, and does not need any information on the other connectivities.
This paper proposes a formation control for multi robot systems. We give that the alternative error function can be modified to achieve relative state deviation between agents. Also, we show a formation control strategy of multi robot systems using simple control structure. Our proposed method does not contain a sign function, therefore, we can easily apply our method for the actual systems. Simulation and experimental results are given to show the effectiveness of our approach.
A conical CT system was used for the industrial X-ray CT system on this paper. It is known that this system has a missing cone problem, which causes a growth of image. We used an iterative phase retrieval algorithm as a proposal to solve this problem. We confirmed that this algorithm can recover a data of low frequency such as the approximate outline of the object. In addition, we tried to make a new constrain, boundary condition, which is implemented along the boundary of the missing cone. Through this search, it was found out that this algorithm offered the access to reducing the relative-error-rate by approximate 80%.
This paper presents a new broadcast control method for multi-agent systems. By restricting the objective functions to a class of functions, we derive simple broadcast controllers with constant-distance random movement. This enables us to construct high performance broadcast controllers with a small number of tuning parameters. The proposed controllers are proven to asymptotically achieve given tasks with probability one. The performance is demonstrated by numerical simulation.
This paper presents a fault diagnose method for event-driven systems based on probabilistic inference, Timed Markov Model (TMM). The TMM is one of semi-Markov process models wherein state transition probabilities depend on stay time at a state. The TMM requires numerous amount of learning data to establish a diagnosis system, and it is difficult to collect enough learning data in a large and complex system. This paper focuses on a diagnosis strategy based on sequential order of processes in the event-driven system, and the method can diagnose the fault even if the amount of learning data is not rich. Finally, the usefulness of the proposed strategy is verified through some experimental results of an automatic transfer line.
This paper describes a laser range finder based new fast self-localization algorithm for IGVC Auto-Nav challenge. In order to achieve fast real-time self-localization, we utilize shape of circular cone which exists as obstacles around the IGVC Auto-Nav challenge course. To detect accurate circular cone obstacle position regardless of observed direction of mobile robot, we apply circular Hough transform to detect center position of circular cone obstacles. In order to estimate mobile robot posture robustly, we formulate equations between geometric relation and traveling direction and to solve by applying singular value decomposition. To estimate fast and stable self-localization, we fuse between estimated mobile robot posture and absolute position from GPS by applying Complex type Kalman filter. Validity of proposed algorithm is confirmed by actual outdoor environments.
The present study aimed at assessing effects of daily piano practice on kinematics and muscular activity of the finger movements while musically-naive individuals played the piano. Six participants were asked to play a short melody with metronome with the non-dominant left hand (no explicit FB group). Another six participants were provided visual feedback regarding rhythmic accuracy (accuracy FB group). In no explicit FB group, the mean angle at the PIP and DIP joints became more extended with practicing. The amount of co-activation of the finger flexor and extensor muscles also decreased particularly at the late stage of the practice. In accuracy FB group, the amount of muscular co-activation did not changed with practice. The results provided evidence demonstrating that the daily piano practice reorganizes the hand posture in playing and economizes the muscular work for stiffening joints, and that explicit feedback regarding rhythmic accuracy of movements impedes the economization process.
In this paper, a robust tracking control law for multi-rotor UAVs is proposed based on sliding mode control. The dynamic model of the multi-rotor UAV is obtained via a Lagrange approach as a 4-input 4-output system. The proposed controller can achieve asymptotic convergence of the closed-loop system for the plant with uncertainty of moment of inertia of the body. To construct a controller, the model of the plant is decomposed into two parallel subsystems as a vertical and a horizontal systems. The vertical and horizontal subsystems are controlled by linear feedback and sliding mode controllers, respectively. We derive a condition that the proposed controller can ensure the stability of the closed-loop system. By numerical simulation, effectiveness of the proposed control is verified.
This paper considers the problem of controlling both the position and the attitude of a four-rotor mini helicopter. The four-rotor mini helicopter is described by a set of nonlinear equations and some parameters of the dynamics are subjected to uncertainies. This paper presents a new adaptive tracking controller based on backstepping technique using both a virtual attitude control and an on-line parameter estimation. This controller can make the tracking errors of the position and the yaw angle of a helicopter converge to zero exponentially. A numerical simulation is performed to evaluate the effectiveness of the proposed controller.
We developed a wireless sensor system that contains sensors for detecting the states of a television, a remote controller, the interior lighting and the illumination condition. After using the wireless sensor system for one month in the home of an elderly person, data showed habitual use of the TV and the interior lighting.