ART Neural Networks: Distributed Coding and ARTMAP Applications

ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, financial forecasting, machine tool monitoring, digital circuit design, chemical analysis, and robot vision. Supervised ART architectures, called ARTMAP systems, feature internal control mechanisms that create stable recognition categories of optimal size by maximizing code compression while minimizing predictive error in an on-line setting. Special-purpose requirements of various application domains have led to a number of ARTMAP variants, including fuzzy ARTMAP, ART-EMAP, Gaussian ARTMAP, and distributed ARTMAP. ARTMAP has been used for a variety of applications, including computer-assisted medical diagnosis. Medical databases present many of the challenges found in general information management settings where speed, efficiency, ease of use, and accuracy are at a premium. A direct goal of improved computer-assisted medicine is to help deliver quality emergency care in situations that may be less than ideal. Working with these problems has stimulated a number of ART architecture developments, including ARTMAP-IC [1]. This paper describes a recent collaborative effort, using a new cardiac care database for system development, has brought together medical statisticians and clinicians at the New England Medical Center with researchers developing expert systems and neural networks, in order to create a hybrid method for medical diagnosis. The paper also considers new neural network architectures, including distributed ART {dART), a real-time model of parallel distributed pattern learning that permits fast as well as slow adaptation, without catastrophic forgetting. Local synaptic computations in the dART model quantitatively match the paradoxical phenomenon of Markram-Tsodyks [2] redistribution of synaptic efficacy, as a consequence of global system hypotheses.Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657

Finding What You Need, and Knowing What You Can Find: Digital Tools for Palaeographers in Musicology and Beyond

This chapter examines three projects that provide musicologists with a range of resources for managing and exploring their materials: DIAMM (Digital Image Archive of Medieval Music), CMME (Computerized Mensural Music Editing) and the software Gamera. Since 1998, DIAMM has been enhancing research of scholars worldwide by providing them with the best possible quality of digital images. In some cases these images are now the only access that scholars are permitted, since the original documents are lost or considered too fragile for further handling. For many sources, however, simply creating a very high-resolution image is not enough: sources are often damaged by age, misuse (usually Medieval ‘vandalism’), or poor conservation. To deal with damaged materials the project has developed methods of digital restoration using mainstream commercial software, which has revealed lost data in a wide variety of sources. The project also uses light sources ranging from ultraviolet to infrared in order to obtain better readings of erasures or material lost by heat or water damage. The ethics of digital restoration are discussed, as well as the concerns of the document holders. CMME and a database of musical sources and editions, provides scholars with a tool for making fluid editions and diplomatic transcriptions: without the need for a single fixed visual form on a printed page, a computerized edition system can utilize one editor’s transcription to create any number of visual forms and variant versions. Gamera, a toolkit for building document image recognition systems created by Ichiro Fujinaga is a broad recognition engine that grew out of music recognition, which can be adapted and developed to perform a number of tasks on both music and non-musical materials. Its application to several projects is discussed

Image Processing Techniques: A Review

In today’s scenario image processing is one of the vast growing fields. It is a method which is commonly used to improve raw images which are received from various resources. It is a kind of signal processing. This paper provides an overview of image processing methods. The main concern of this paper is to define various techniques used in different phases of image processing.   Most Searchable Keywords on Web image processing techniques, image processing methods, image processing techniques pdf, image processing papers, types of image processing techniques, image processing technique, digital image processing techniques pdf, digital image processing techniques, latest image processing techniques, research papers on image processing, analog image processin

A multi-view approach to cDNA micro-array analysis

The official published version can be obtained from the link below.Microarray has emerged as a powerful technology that enables biologists to study thousands of genes simultaneously, therefore, to obtain a better understanding of the gene interaction and regulation mechanisms. This paper is concerned with improving the processes involved in the analysis of microarray image data. The main focus is to clarify an image's feature space in an unsupervised manner. In this paper, the Image Transformation Engine (ITE), combined with different filters, is investigated. The proposed methods are applied to a set of real-world cDNA images. The MatCNN toolbox is used during the segmentation process. Quantitative comparisons between different filters are carried out. It is shown that the CLD filter is the best one to be applied with the ITE.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the National Science Foundation of China under Innovative Grant 70621001, Chinese Academy of Sciences under Innovative Group Overseas Partnership Grant, the BHP Billiton Cooperation of Australia Grant, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050 and the Alexander von Humboldt Foundation of Germany

Design and application of reconfigurable circuits and systems

Open Acces

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area

Depth Segmentation Method for Cancer Detection in Mammography Images

Breast cancer detection remains a subject matter of intense and also a stream that will create a path for numerous debates. Mammography has long been the mainstay of breast cancer detection and is the only screening test proven to reduce mortality. Computer-aided diagnosis (CAD) systems have the potential to assist radiologists in the early detection of cancer. Many techniques were introduced based on SVM classifier, spatial and frequency domain, active contour method, k-NN clustering method but these methods have so many disadvantages on the SNR ratio, efficiency etc. The quality of detection of cancer cells is dependent with the segmentation of the mammography image. Here a new method is proposed for segmentation. This algorithm focuses to segment the image depth wise and also coloured based segmentation is implemented. Here the feature identification and detection of malignant and benign cells are done more easily and also to increase the efficiency to detect the early stages of breast cancer through mammography images. In which the relative signal enhancement technique is also done for high dynamic range images. Markovian random function can be used in the depth segmentation. Markov Random Field (MRF) is used in mammography images. It is because this method can model intensity in homogeneities occurring in these images. This will be helpful to find the featured tumor DOI: 10.17762/ijritcc2321-8169.15023

Advanced avionics concepts: Autonomous spacecraft control

A large increase in space operations activities is expected because of Space Station Freedom (SSF) and long range Lunar base missions and Mars exploration. Space operations will also increase as a result of space commercialization (especially the increase in satellite networks). It is anticipated that the level of satellite servicing operations will grow tenfold from the current level within the next 20 years. This growth can be sustained only if the cost effectiveness of space operations is improved. Cost effectiveness is operational efficiency with proper effectiveness. A concept is presented of advanced avionics, autonomous spacecraft control, that will enable the desired growth, as well as maintain the cost effectiveness (operational efficiency) in satellite servicing operations. The concept of advanced avionics that allows autonomous spacecraft control is described along with a brief description of each component. Some of the benefits of autonomous operations are also described. A technology utilization breakdown is provided in terms of applications

Technology Directions for the 21st Century

The Office of Space Communications (OSC) is tasked by NASA to conduct a planning process to meet NASA's science mission and other communications and data processing requirements. A set of technology trend studies was undertaken by Science Applications International Corporation (SAIC) for OSC to identify quantitative data that can be used to predict performance of electronic equipment in the future to assist in the planning process. Only commercially available, off-the-shelf technology was included. For each technology area considered, the current state of the technology is discussed, future applications that could benefit from use of the technology are identified, and likely future developments of the technology are described. The impact of each technology area on NASA operations is presented together with a discussion of the feasibility and risk associated with its development. An approximate timeline is given for the next 15 to 25 years to indicate the anticipated evolution of capabilities within each of the technology areas considered. This volume contains four chapters: one each on technology trends for database systems, computer software, neural and fuzzy systems, and artificial intelligence. The principal study results are summarized at the beginning of each chapter