Magnetic compass fault detection method for GPS/INS/magnetic compass integrated navigation systems

This paper proposes a magnetic compass fault detection method for GPS/INS/Magnetic compass integrated navigation systems. The fault is assumed to be caused by the hard iron and soft iron effect and modeled as an abrupt change in the magnetic compass output. In order to detect the fault, a test statistic related with only azimuth error measurement is determined. When a fault is detected, the GPS/INS/Magnetic compass integrated navigation system is changed into a GPS/INS integrated navigation system mode. In order to show the validity of the proposed method, computer simulation and van testing are carried out. The simulation and van test results show that the proposed navigation system gives more accurate outputs than the GPS/INS/Magnetic compass without the proposed method.     

Localization algorithm using a virtual label for a mobile robot in indoor and outdoor environments

Scanning laser range sensors provide range data consisting of a set of point measurements. The laser sensor URG-04LX has a distance range of approximately 0.02–4 m and a scanning angle range of 240°. Usually, such an image range is acquired from one viewpoint by “moving” the laser beam using rotating mirrors/prisms. The orientation of the laser beam can easily be measured and converted into the coordinates of the image. This article conducts localization using virtual labels with data about distances in the environment obtained from 2D distance laser sensors. This method puts virtual labels on special features and points which are along the mobile robot’s path. The current location is calculated by combining the virtual label and the range image of the laser range finder.     

Latent semantic analysis for vector space expansion and fuzzy logic-based genetic clustering

This paper proposes an improved latent semantic analysis (LSA) model to represent textual document and takes advantage of a fuzzy logic based genetic algorithm (FLGA) for clustering. The standard genetic algorithm (GA) in conventional vector space model is rather difficult to deal with because the high dimensional encoding of GA makes it explore the optimal solution in a complicated space which is prone to cause an overflow problem. The LSA-based corpus model not only reduces the dimensions drastically, but also creates an underlying semantic structure which enhances its ability of distinguishing documents in terms of concepts and indirectly improves the ability of GA for clustering (genetic clustering). A novel FLGA is proposed in conjunction with this semantic model in this study. According to the nature of biological evolution, several fuzzy controllers are given to adaptively adjust and optimize the behaviors of the GA which can effectively prevent the premature convergence to a suboptimum solution. The experiment results show that the fuzzy logic controllers enhance the ability of the GA to explore the global optimum solution, and the utilization of the LSA-based text representation method to FLGA further improves its clustering performance.     

Consumer perceptions on web advertisements and motivation factors to purchase in the online shopping

The principal objective of this study was to investigate the mediating and moderating effects of product involvement and trust toward websites in relation to the effects of the attributes of web advertisements on customers’ purchase intentions. We collected data consisting of a total of 264 responses from individuals with previous experience with purchasing products from online shopping mall sites, and utilized the PLS (partial least squares) method to analyze the collected data.     

Efficient RNTS system for privacy of banking off-line customer

With the development in IT technology and with growing demands of users, a ubiquitous environment is being made. Because individual identification is important in ubiquitous environment, RFID technology would be used frequently. RFID is a radio frequency identification technology to replace bar code. The reader transmits query (request of user information) and tag-provides user information. RFID has various advantages, such as high speed identification rates, mass memory storages. However, eavesdropping is possible as well as a problem that user information is exposed (Juels et al. in Conference on Computer and Communications Security—ACM CCS, pp. 103–111, 2003; Ohkubo et al. in RFID Privacy Workshop 2003; Weis et al. in International Conference on Security in Pervasive Computing, pp. 201–212, 2003; Weis et al. in Cryptographic Hardware and Embedded Systems—CHES, pp. 454–469, 2002). Therefore, when off-line customer had visited bank for banking service, RNTS (RFID number ticket service) system provides both anonymity in customer identification and efficiency of banking service. In addition, RNTS system protects privacy of an off-line user visiting the bank and it is an efficient method offering service in order of arriving in the bank.     

Genetic algorithm for text clustering based on latent semantic indexing

In this paper, we develop a genetic algorithm method based on a latent semantic model (GAL) for text clustering. The main difficulty in the application of genetic algorithms (GAs) for document clustering is thousands or even tens of thousands of dimensions in feature space which is typical for textual data. Because the most straightforward and popular approach represents texts with the vector space model (VSM), that is, each unique term in the vocabulary represents one dimension. Latent semantic indexing (LSI) is a successful technology in information retrieval which attempts to explore the latent semantics implied by a query or a document through representing them in a dimension-reduced space. Meanwhile, LSI takes into account the effects of synonymy and polysemy, which constructs a semantic structure in textual data. GA belongs to search techniques that can efficiently evolve the optimal solution in the reduced space. We propose a variable string length genetic algorithm which has been exploited for automatically evolving the proper number of clusters as well as providing near optimal data set clustering. GA can be used in conjunction with the reduced latent semantic structure and improve clustering efficiency and accuracy. The superiority of GAL approach over conventional GA applied in VSM model is demonstrated by providing good Reuter document clustering results.     

Design of micromirror actuator by ionic polymer metal composites

Microactuators for micromirror system have found many applications in various areas including projection displays, optical switches, RF switches and so on. In this paper we demonstrated micromirror actuator using ionic polymer metal composites (IPMC) that is a suitable candidate, since it has many attractive qualities such as durability, aquatic, miniature and light-weighted. Specially, IPMC has extraordinary advantages which are simple bending motion for low driving voltage (1–2 V), low power consumption, and simple structure. The IPMC actuator is made of Nafion NE-1110 (Dupont Co, Ltd., 260 µm thick) layer and electrode (platinum) layers and driven by 1–4 V. The displacement measured vertically is 0.25 mm and tilting angle is 11.3°. The angular motion, which is more than 10°, is a good advantage in the field of display module. This paper shows that the IPMC actuator has enough possibility for other applications.     

A method of stepwise benchmarking for inefficient DMUs based on the proximity-based target selection

DEA is a useful nonparametric method of measuring the relative efficiency of a DMU and yielding a reference target for an inefficient DMU. However, it is very difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually.The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.     

Team THOR's Entry in the DARPA Robotics Challenge Finals 2015

This paper describes Team THOR's approach to human‐in‐the‐loop disaster response robotics for the 2015 DARPA Robotics Challenge (DRC) Finals. Under the duress of unpredictable networking and terrain, fluid operator interactions and dynamic disturbance rejection become major concerns for effective teleoperation. We present a humanoid robot designed to effectively traverse a disaster environment while allowing for a wide range of manipulation abilities. To complement the robot hardware, a hierarchical software foundation implements network strategies that provide real‐time feedback to an operator under restricted bandwidth using layered user interfaces. Our strategy for humanoid locomotion includes a backward‐facing knee configuration paired with specialized toe and heel lifting strategies that allow the robot to traverse difficult surfaces while rejecting external perturbations. With an upper body planner that encodes operator preferences, predictable motion plans are executed in unforeseen circumstances. These plans are critical for manipulation in unknown environments. Our approach was validated during the DRC Finals competition, where Team THOR scored three points in 18 min of operation time, and the results are presented along with an analysis of each task.