An Evolutionary Algorithm Approach to Optimal Ensemble Classifiers for DNA Microarray Data Analysis

In general, the analysis of microarray data requires two steps: feature selection and classification. From a variety of feature selection methods and classifiers, it is difficult to find optimal ensembles composed of any feature-classifier pairs. This paper proposes a novel method based on the evolutionary algorithm (EA) to form sophisticated ensembles of features and classifiers that can be used to obtain high classification performance. In spite of the exponential number of possible ensembles of individual feature-classifier pairs, an EA can produce the best ensemble in a reasonable amount of time. The chromosome is encoded with real values to decide the weight for each feature-classifier pair in an ensemble. Experimental results with two well-known microarray datasets in terms of time and classification rate indicate that the proposed method produces ensembles that are superior to individual classifiers, as well as other ensembles optimized by random and greedy strategies.     

HERMES: embedded file system design for A/V application

Embedded systems such as PVR, set-top box, HDTV put unique demand on I/O subsystem design. Underlying software, particularly file system, needs to be elaborately designed so that it can meet tight constraints of consumer electronics platform: performance, price, reliability, and etc. In this work, we develop state-of-art file system elaborately tailored for A/V workload. There are two design objectives in our file system: performance and support for logical level abstraction. For performance, we develop a number of novel features: extent based allocation, single level file structure with block index augmentation scheme, aggressive free block allocation to minimize disk fragmentation, elaborate file system meta data layout, separation of name space data and file data and etc. HERMES enables the user to view file as a collection of semantic units (frame or audio samples). HERMES file system encompasses most of state-of-the-art file system technologies published in preceding works. Via extensive physical experiment, we verify that HERMES file system successfully addresses the original issues: good scalability, predictable I/O latency (minimizing variability in I/O latency), efficient disk head movement and etc. This is the result of harmonious effort of large I/O size, aggressive free block allocation algorithm, data block placement strategy, file organization, layout of HERMES file system and etc. The result of performance experiments indicate that HERMES file system prototype successfully meets the file system constraints for high volume and high bandwidth multimedia application. HERMES file system exhibits superior performance to EXT2 file system (Linux) and XFS file system (SGI).

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.