Innovations in Individual Feature History Management—The Significance of Feature-based Temporal Model

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO’s temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO’s temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure.

The impact of process standardization on business process outsourcing success

What is the impact of business process standardization on business process outsourcing (BPO) success? This paper argues that there is a direct impact of process standardization on BPO success, due to production cost economies, and also an indirect effect via improved contractual and relational governance resulting from better monitoring opportunities and facilitated communication and coordination. This threefold impact of standardization on BPO success is empirically confirmed using data from 335 BPO ventures in 215 German banks.     

Adaptive robust fuzzy control for path tracking of a wheeled mobile robot

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Suboptimal filter for continuous‐time linear systems with unknown parameters

The filtering problem for continuous‐time linear systems with unknown parameters is considered. A new suboptimal filter is herein proposed. It is based on the optimal mean‐square linear combination of the local Kalman filters. In contrast to the optimal weights, the suboptimal weights do not depend on current observations; thus, the proposed filter can easily be implemented in real‐time. Examples demonstrate high accuracy and efficiency of the suboptimal filter. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Solving shortest path problem using particle swarm optimization

This paper presents the investigations on the application of particle swarm optimization (PSO) to solve shortest path (SP) routing problems. A modified priority-based encoding incorporating a heuristic operator for reducing the possibility of loop-formation in the path construction process is proposed for particle representation in PSO. Simulation experiments have been carried out on different network topologies for networks consisting of 15–70 nodes. It is noted that the proposed PSO-based approach can find the optimal path with good success rates and also can find closer sub-optimal paths with high certainty for all the tested networks. It is observed that the performance of the proposed algorithm surpasses those of recently reported genetic algorithm based approaches for this problem.     

Vector control for loss minimization of induction motor using GA–PSO

This paper deals with the GA–PSO (genetic algorithm–particle swarm optimization) based vector control for loss minimization operation of induction motor. It is estimated that more than around 50% of the world electric energy generated is consumed by electric machines such as induction motor, dc motor. So, improving efficiency in electric drives is important and control strategy for minimum energy loss is needed as one of optimal operation strategies. The vector control of induction motor has been widely used to operate in a wide speed range by using flux weakening at rated speed. However, it is still necessary to advance because of coupling is behavior between fluxes in motor. In this paper, vector control approach is suggested for an optimal operation of induction motor using variable acceleration and GA–PSO tuning method through simulation. We can obtain satisfactory results for energy saving control.     

Proteomics in diabetic nephropathy

Diabetes mellitus (DM) is currently one of the principal causes of end stage renal disease (ESRD). Approximately 40% of all diabetic patients eventually develop diabetic nephropathy (DN). The complexity of diabetes and its complications require a broad-based, unbiased, scientific approach, such as proteomics, in order to understand the progression of DN. Proteomic techniques have been applied extensively to explore the complexity of the mechanisms associated with DN, and to identify novel biomarkers and therapeutic targets. This review provides insights into how proteomics can be applied to DN, and how experimental data can be linked to clinical applications. In addition, recent proteome studies of DN are summarized. The rapid rate of development of the relevant technologies, along with the combination of classic physiological and biochemical techniques with proteomics will facilitate new discoveries.     

Evaluation of the critical stroke of an earthworm-like robot for capsule endoscopes

Recently, the capsule endoscope has been highlighted for the patient's convenience and the possibility of application in the small intestine. However, the capsule endoscope has some limitations in obtaining an image of the digestive organ because its movement depends only on the peristaltic motion. In order to solve these problems, it is necessary to determine the locomotive mechanism of the capsule endoscope. Therefore, the present authors have already proposed an earthworm-like robot, which has a locomotive mechanism. However, this mechanism should be designed so that the earthworm-like robot has a larger stroke than the critical stroke required to perform motion inside the small intestine. In this study, therefore, not only is the modelling of the locomotive process based on a biomechanical study presented but also the movement of the earthworm-like robot in the small intestine is simulated. Through the simulation process, the variation in the critical stroke with regard to the elastic modulus of the mesentery is investigated. Finally, from an in vitro test of the proposed robot, it is found that the experimental result is very similar to that of the simulation. Consequently, the present work will provide guidelines for designing an earthworm-like robot for diagnosis of the small intestine.     

Arthemis: annotation software in an integrated capturing and analysis system for colonoscopy

Colonoscopy is an endoscopic technique that allows physicians to inspect the inside of the human colon. During a colonoscopic procedure, a tiny video camera at the tip of the endoscope generates a video signal of the internal mucosa of the colon. In current practice, the entire colonoscopic procedure is not routinely captured. Software tools providing easy access to important contents of videos that are digitally captured during colonoscopy are not available. Hence, it is very time consuming to review an entire video, locate important contents, annotate them, and extract the annotated contents for research, teaching, and training purposes. Arthemis, a software application, was developed to facilitate this process. For convenient data sharing, Arthemis allows annotation according to the European Gastrointestinal Society for Endoscopy (ESGE) Minimal Standard Terminology (MST), an internationally accepted standard for digestive endoscopy. Arthemis is part of our integrated capturing and content analysis system for colonoscopy called Endoscopic Multimedia Information System (EMIS). This paper presents Arthemis as a component of EMIS, the design and implementation of Arthemis, and key lessons learned from the development process.