7564297
Problem-Independent Schema Synthesis for Genetic Algorithms
As a preprocessing for genetic algorithms, static reordering helps genetic algorithms effectively create and preserve high-quality schemata, and consequently improves the performance of genetic algorithms. In this paper, we propose a static reordering method independent of problem-specific knowledge. One of the novel features of our reordering method is that it is applicable to any problem with no information about the problem. The proposed method constructs a weighted complete graph from the gene distances calculated from solutions with relatively high fitnesses, transforms them into a gene-interaction graph, and finds a gene rearrangement. Extensive experimental results showed significant improvement for a number of applications.
19448510
A Genetic Approach for Gene Selection on Microarray Expression Data
Microarrays allow simultaneous measurement of the expression levels of thousands of genes in cells under different physiological or disease states. Because the number of genes exceeds the number of samples, class prediction on microarray expression data leads to an extreme “curse of dimensionality” problem. A principal goal of these studies is to identify a subset of informative genes for class prediction to reduce the curse of dimensionality. We propose a novel genetic approach that selects a subset of predictive genes for classification on the basis of gene expression data. Our genetic algorithm maximizes correlation between genes and classes and minimizes intercorrelation among genes. We tested the genetic algorithm on leukemia data sets and obtained improved results over previous results.
12076
Multi-attractor gene reordering for graph bisection
We propose a new gene reordering scheme for the graph bisection problem. Our gene reordering starts with two or more vertices to capture the clustering structure of graphs effectively. We devised a chromosome repairing method for hybrid genetic search, which helps exploit clusters when combined with gene reordering. Experimental tests showed that the suggested reordering scheme significantly improves the performance of genetic algorithms over previous reordering methods.
15089682
Lagrange Multiplier Method for Multi-campaign Assignment Problem
It is crucial to maximize marketing efficiency and customer satisfaction in personalized marketing. In this paper, we raise the multiple recommendation problem which occurs when performing several personalized campaigns simultaneously. We formulate the multi-campaign assignment problem to solve this issue and propose methods for solving the problem. The most notable element is the Lagrange multiplier method. Roughly speaking, Lagrange multiplier reduces problem complexity with a minor impact on optimality. However, it is not easy to find Lagrange multipliers in exact accord with problem constraints. We use a genetic algorithm for finding optimal Lagrange multipliers. Through the experiments, we verify the effectiveness of the problem formulation and our genetic approach.
17681470
New Usage of Sammon's Mapping for Genetic Visualization
It is a hard problem to understand the fitness landscape of a problem as well as the evolution of genetic algorithms. For the purpose, we adopt Sammon's mapping for the investigation. We demonstrate its usefulness by applying it to the graph partitioning problem which is a well-known NP-hard problem. Also, through the investigation of schema traces, we explain the genetic process and the reordering effect in the genetic algorithm.
10542004
Investigation of the Fitness Landscapes and Multi-parent Crossover for Graph Bipartitioning
An empirical study is performed on the local-optimum space of graph bipartitioning. We examine some statistical features of the fitness landscape. They include the cost-distance correlations and the properties around the central area of local optima. The study revealed some new notable results about the properties of the fitness landscape; e.g., the central area yielded fairly good quality in the local-optimum space. We performed an experiment on a spectrum of different exploitation strengths of the central areas. From the results, it seems attractive to exploit the central area, but excessive or insufficient exploitation is not desirable.
61949387
Quantizer design and distributed encoding algorithm for source localization in sensor networks
In this paper, we propose a quantizer design algorithm that is optimized for source localization in sensor networks. For this application, the goal is to minimize the amount of information that the sensor nodes have to exchange in order to achieve a certain source localization accuracy. We show that this goal can be achieved more efficiently when "application-specific" quantizers are used. Our proposed quantizer design algorithm uses a cost function that takes into account the distance between the actual source position and the position estimated based on quantized data. We also propose a distributed encoding algorithm that is applied after quantization and achieves rate savings by merging quantization bins without any degradation of localization performance. The merging technique in the encoding algorithm exploits the fact that certain combinations of quantization bins at each node cannot occur because the corresponding spatial regions have an empty intersection. We apply these algorithms to a system where an acoustic sensor model is employed for localization. For this case, we introduce the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations show the improved performance of our quantizer over traditional quantizer designs. In addition, they show rate savings (32.8%, 5 nodes, 4 bits per node) when our novel bin-merging algorithms are used. Our results also show that an optimized bit allocation leads to significant improvements in localization performance with respect to a bit allocation that uses the same number of bits for each node.
15453065
Device-Aware Cache Replacement Algorithm for Heterogeneous Mobile Storage Devices
Hard disks, most prevalent mass-storage devices, have high power consumption and high response time for random I/O requests. Recent remarkable technology improvement of flash memory has made it a rising secondary storage device but flash memory still has high cost per bit. Usage of heterogeneous storage devices such as a pair of a hard disk and a flash memory can provide reasonable cost, relatively acceptable response time, and low-power consumption. In this paper, we propose a novel buffer cache replacement algorithm which targets a mobile computing system with a heterogeneous storage pair of a hard disk and a flash memory. The algorithm partitions the cache per each device and adjusts the size of each partition based on the performance indices of the devices, and manages each partition according to workload patterns. Simulations show that the proposed algorithm yields a hit rate up to two times higher than LRU on the typical mobile traces according to the cache size and achieves also better system I/O response time and energy consumption.
7461874
Face and Facial Expression Recognition with an Embedded System for Human-Robot Interaction
In this paper, we present an embedded system in which face recognition and facial expression recognition for Human-Robot Interaction are implemented. To detect face with a fast and reliable way, AdaBoost algorithm is used. Then, Principal Component Analysis is applied for recognizing the face. Gabor wavelets are combined with Enhanced Fisher Model for facial expression recognition. Performance of the facial expression recognition reaches to 93%. The embedded system runs on 150MHz and the processing speed is 0.6 frames / second. Experimental result demonstrates that face detection, recognition and facial expression can be implemented with an embedded system for the Human-Robot Interaction.
6477815
An Affective User Interface Based on Facial Expression Recognition and Eye-Gaze Tracking
This paper describes a pipeline by which facial expression and eye-gaze of the user are tracked, and then 3D facial animation is synthesized in the remote place based upon timing information of the facial and eye movement information. The system first detects a facial area within the given image and then classifies its facial expression into 7 emotional weightings. Such weighting information, transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. It turns out that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method. The emotional avatar embedded on a mobile platform has some potential in conveying emotion between peoples via Internet.
13345946
Efficient Implementation of Image Warping on a Multimedia Processor
The spatial transformation of images, commonly known as image warping, is fundamental to many applications, e.g. remote sensing, medical imaging, computer vision, and computer graphics. Computational demands in image warping are high, requiring a geometric transformation, address and coefficient generation, and some form of interpolation. However, unlike most image processing algorithms, the data flow for image warping can be highly irregular, which makes any efficient implementation challenging.This paper describes an efficient algorithm which addresses these challenges by making use of the capabilities of a single-chip multiprocessing microprocessor, the Texas Instruments TMS320C80 MVP (multimedia video processor). the MVP's advanced digital signal processors (ADSPs) offer tremendous computational power through instruction-level parallelism and several key features designed for image processing. The MVP's intelligent input/output interface via the transfer controller (TC) permits efficient irregular memory accesses.Affine and perspective warps have been implemented for 8-bit, 16-bit and and RGB color data using bilinear interpolation.The affine warp can generate 512 × 512 warped output images faster than real-time video rates require. For 8-bit images, the performance is 14.1 ms. Although the amount of computation necessary is the same for 16-bit images, the execution time increases to 15.2 ms since twice as many bytes need to be transferred. For RGB color images, it takes 28.0 ms. The perspective warp requires 46.3 ms for 8-bit and 16-bit images, and 60.4 ms for RGB color images. This unprecedented performance for software-based image warping exceeds many hardware approaches reported in the literature.