Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPARATIVE EVALUATION OF PATTERN RECOGNITION TECHNIQUES FOR DETECTION OF MICROCALCIFICATIONS IN MAMMOGRAPHY

Computer-assisted detection of microcalcifications in mammographic images will likely require a multistage algorithm that includes segmentation of possible microcalcifications, pattern recognition techniques to classify the segmented objects, a method to determine if a cluster of calcifications exists, and possibly a method to determine the probability of malignancy. This paper focuses on the first three of these stages, and especially on the classification of segmented local bright spots as either calcification or noncalcification. Seven classifiers (linear and quadratic classifiers, binary decision trees, a standard backpropagation network, 2 dynamic neural networks, and a K-nearest neighbor) are compared. In addition, a postprocessing step is performed on objects identified as calcifications by the classifiers to determine if any clusters of microcalcifications exist. A database of digitized film mammograms is used for training and testing. Detection accuracy of individual and clustered microcalcificat.
A comparison of adaptive algorithms based on the methods of steepest descent and random search

This paper compares the performance characteristics of three algorithms useful in adjusting the parameters of adaptive systems: the differential (DSD) and least-mean-square (LMS) algorithms, both based on the method of steepest descent, and the linear random search (LRS) algorithm, based on a random search procedure derived from the Darwinian concept of "natural selection. " The LRS algorithm is presented here for the first time. Analytical expressions are developed that define the relationship between rate of adaptation and "misadjustment," a dimensionless measure of the difference between actual and optimal performance due to noise in the adaptive process. For a fixed rate of adaptation it is shown that the LMS algorithm, which is the most efficient, has a misadjustment proportional to the number of adaptive parameters, while the DSD and LRS algorithms have misadjustments proportional to the square of the number of adaptive parameters. The expressions developed are verified by computer simulations that demonstrate the application of the three algorithms to system modeling problems, of the LMS algorithm to the cancelling of broadband interference in the sidelobes of a receiving antenna array, and of the DSD and LRS algorithms to the phase control of a transmitting antenna array. The second application introduces a new method of constrained adaptive beamforming whose performance is not significantly affected by element nonuniformity. The third application represents a class of problems to which the LMS algorithm in the basic form described in this paper is not applicable.
Novel interfaces for modeling and painting

The last decade witnessed the rapid development of interaction techniques. There has been a growing number of interactive devices, such as multi-touch displays, motion sensing input devices and voice input devices. Among them, touch based hardware are becoming more and more powerful in terms of screen size, resolution, accuracy, as well as the number of touch points, while the prices are dropping quickly. More and more electronic devices have emerged with touch screens, including smart phones, tablet PCs, GPS devices, ATM machines, various information and ticketing systems, etc. Compared to traditional WIMP interfaces that require the user to input information indirectly with IO devices, such as mice, touch-based interfaces, including multi-touch and sketch-based interfaces, allow the user to interact with the content directly using fingers and pens; a technique which has proved to be extremely intuitive and easy to learn. Additionally, multi-touch based interfaces can be more efficient than mouse-based interfaces and have great potential to facilitate collaboration among multiple people. Also, sketch-based interfaces can be very intuitive due to the simple sketch-based input and physical direct manipulation with the input screen. Because of the application-driven nature of computer graphics and the difficulty of visualizing and manipulating various aspects of computer graphics, including geometry creation, editing and so on, the interface and interaction method of applications play an important role in computer graphics applications. However, there are relatively few successful applications have been presented which have exploited novel interfaces in computer graphics applications due to the complexity of such applications. In this thesis, we demonstrate three graphics applications that use novel interfaces to improve the user interaction in terms of efficiency and intuitiveness. By conducting user studies for the specified applications and tasks, we also explore some touch interaction principles that
MRF model based image segmentation using hierarchical distributed genetic algorithm

An unsupervised method for segmenting noisy and blurred images is proposed. A Markov random field (MRF) model is used which is robust to degradation. Since this is computationally intensive, a hierarchical distributed genetic algorithm (HDGA) is used which is unsupervised and parallel. Experimental results show that the proposed method is effective at segmenting real images.
Topic Research with Semantics

This study is a broadly review on the literatures from science citation index expanded (SCI-EXPANED) database, concerning topic research with semantic. The result indicates that the number of literature productions on this topic reaches climax of 4 in publication year 2012 and then followed by 2011 and 2007 of three papers respectively. The main research development country is China, and from the analysis of document type, articles accounts for 80%. Computer science acts as the main source title of this research. In general, the related research can be classified into application research and theory research. Multimedia, electronic document and general application are explored in application field, meanwhile text analysis, passage segmentation and semantic clustering are the main topics in theory research.
Coarse‐grained models of protein folding as detailed tools to connect with experiments

Protein folding, a process that spans a wide range of timescales and that involves complex conformational dynamics, is an extremely challenging problem to decode at the atomic level. Over the past decade, coarse‐grained (CG) models that rely on a reduced representation of the polymer chain as dictated by the native structure have been quite successful in characterizing and predicting a variety of aspects of the folding mechanism of single‐domain proteins. The ever‐increasing ability of this minimalist treatment is a primarily due to the rapid and efficient sampling afforded by coarse‐graining that smoothens the folding landscape and the simple nature of the constituent physical energy functions that can be easily cast in various forms or parameterized using experimental or knowledge‐based approaches. With the advances in computational power we have now reached a stage where CG simulations can be routinely performed to test various mechanistic hypothesis, to interpret intricate experimental observables and even suggest new experimental avenues. Here, we provide an overview of recent CG developments that have predicted experiments quantitatively and others that have sought to use experimental information as constraints to tune the energetics and answer fundamental questions in folding and conformational behavior of proteins. We further discuss open issues and point to new directions that can drive the CG models toward better agreement with experiments and to a better understanding of folding mechanisms in general. © 2012 John Wiley & Sons, Ltd.
The Acquisition Of Morphophonology

MACWHINNEY, BRIAN. The Acquisition of Morphophonology. Monographs of the Societyfor Research in Child Development, 1978, 43(1-2, Serial No. 174). A model is presented which details the ways in which children in different language communities acquire the morphophonological structure of their languages. In this model, the processes of rote, combination, and analogy are integrated into a single processing goal stack. The model views learning as a cyclical process in which acquisition leads to application, application leads to correction, and correction leads to renewed acquisition. The processes of acquisition, application, and correction are formulated in relatively precise terms. The empirical aspects of the model are then summarized as a series of 16 claims. The validity of these 16 claims is evaluated in the light of experimental and diary data on the acquisition of Arabic, Chinese, English, Finnish, French, German, Hungarian, Latvian, Russian, and Spanish. Experiment 1 examines the acquisition of nine patterns in Hungarian morphophonology by children between 2 and 6 years of age. It indicates that the sequence of acquisition of morphophonological productions is determined chiefly by applicability as defined by the model. Experiment 2 indicates that preschoolers tend to avoid acquisition of synonymous inflections. Experiment 3 gives some evidence that Hungarian 5-year-olds can use information on allomorphic variations to determine the use of allomorph selection productions. Experiment 4 examines the learning of the German plural formation by children between the ages of 3 and 11. The order of acquisition of strategies in plural formation was determined by the interaction of applicability and correctness, as suggested by the model. Experiment 5 gives evidence for the ordering of rote, combination, and analogy as a goal stack in the formation of German gender. The concluding chapters review the success of the model in accounting for the available data on the acquisition of morphophonology. In general, the model constitutes an advance in our ability to account for the acquisition of complex linguistic structures in terms of specific cognitive processing. Every normal newborn is, in a sense, a subject in a vast experiment of nature. Each of these newborns brings to this experiment some set of abilities
New image super-resolution scheme based on residual error restoration by neural networks

The scheme proposed combines an existing image interpola- tion algorithm with an artificial neural network (ANN) used to model the residual errors between the interpolated image and the respective origi- nal image. Mathematical analysis shows that the performance of the proposed method is superior to that of known single-frame interpolation algorithms. The image restoration results using the presented scheme indicate that the restored images are very similar to the real high- resolution images. We also illustrate that the performance of any single- frame interpolation algorithm can be enhanced by combining the inter- polation algorithm into our scheme. Experimental results show the proposed method on generalization and computation complexity is su- perior to other neural network schemes. © 2003 Society of Photo-Optical Instru- mentation Engineers. (DOI: 10.1117/1.1604397)
Do non-native listeners benefit from speech modifications designed to promote intelligibility for native listeners?

Given the increasing use of sound output technologies in cluttered acoustic environments such as transport interchanges, it is of interest to discover ways to modify generated speech which maximise the likelihood of correct message reception, without resorting to excessive sound output level or repetitive announcements. Additionally, speech modifications deployed in public spaces should ideally be beneficial to all listeners, regardless of their first language.
Reflecting on Literacy Practices

Abstract Within the context of an undergraduate literacy methods course, preservice teachers received opportunities to read engaging and meaningful text that challenged their thinking (McVee, Baldassarre, & Bailey, 2004) and respond to specific prompts through an online dialogue discussion and written reflective summaries. This article describes the process these preservice teachers engaged in as they discussed and reflected on their experiences in a language arts class. In the online dialogue, the preservice teachers engaged in reflective strategies that included clarifying, enhancing, providing evidence, challenging, and different thinking. As they dialogued and wrote reflective summaries, these students deepened their comprehension of literacy instruction and enhanced their meta-cognitive awareness of instructional practice as teachers of literacy.
Feedback control of a Lotus Notes server: modeling and control design

This paper considers the modeling and feedback control of a mail server running Lotus Notes/sup TM/. Computing systems such as this typically have two competing control goals: maximize throughput and minimize response time. To achieve these goals, a control input (tuning control) is used to limit the number of users allowed to connect to the mail server at any one time. The measured output is the server queue length-the number of requests that are waiting to be processed. Because response time is a client metric and thus difficult to measure at the server, we formulate the control problem as tracking a reference server queue length. A linear input-output model of the system is identified experimentally and used to design an integral controller. Losses in the queue length measurement due to the fact that requests are only logged after they are served are accounted for by another linear model. Experimental results are presented showing the effectiveness of a low-gain controller and the saturation problems experienced by a high-gain controller. The paper concludes with a discussion of future work.
Stochastic Generation of Dots for Computer Aided Stippling

AbstractCurrent computer stippling methods experience problems with the placement and the appearance of dots. In this paper we present a solution to both problems with a new method to generate synthetic yet realistic dots, and a new algorithm for dot placement, solving problems of overlapping and the formation of patterns, and allowing a full tonal range. Both solutions are based on probabilistic algorithms. The method runs in real time allowing the illustration to be modified while it is being created. This is possible by means of a simple set of tools, which are mapped to high level operators allowing the application of artistic techniques to improve the final result.
Kernel structures for a distributed operating system

In recent years there has been considerable interest in developing distributed computing systems. Distribution of computing resources suggests many possible benefits including greater flexibility, enhanced computing power through greater parallelism, and increased reliability. In practice, achieving any of these benefits has been difficult, since a distributed system also presents potential problems in naming, synchronization, and the effective use of resources. Consistency problems arise when dealing with operations and data structures that may span machine and device boundaries; that is, should a communications or machine failure occur at an inopportune time, the data may be left in an unknown, incorrect, or inaccessible condition. This type of problem is certainly undesirable in user programs, but special problems arise when operating system data structures become inconsistent. Due to the larger number of components involved in a distributed system, these problems are more likely to occur and more damaging in their effects. Since 1982, the Clouds project has been researching an approach to the construction of a distributed computing environment intended to address these concerns. The Clouds operating system is intended to reliably support effective use of distributed resources. Some of that design is derived from the action/object model of computation developed in Jim Allchin's dissertation. That work suggested an architecture for a distributed, reliable computing system built from abstract data objects and atomic transactions. The architecture, properly implemented, can be used to address many of the problems presented by distributed systems. However, Allchin's work does not address the structure or implementation of the kernel and operating system services necessary for a functional distributed system. This dissertation explores the requirements for services and structures needed to support a distributed computing environment as suggested by Allchin's work. It contains the design of a distributed operating system kernel which meets these requirements and which could flexibly support various implementations of the Clouds reliable system as well as other forms of object-oriented distributed systems. This dissertation also describes a prototype implementation, which was done to help refine and validate the design and provide a testbed for further research.
Yield Model for Productivity Optimization of VLSI Memory Chips with Redundancy and Partially Good Product

A model with mixed Poisson statistics has been developed for calculating the yield for memory chips with redundant lines and for partially good product. The mixing process requires two parameters which are readily obtained from product data. The product is described in the model by critical areas which depend on the circuit's sensitivity to defects, and they can be determined in a systematic way. The process is represented in the model by defect densities and gross yield losses. These are measured with defect monitors independently of product type. This paper shows how the yield for any product can be calculated given the critical areas, defect density, and mixing parameter. Future yields are forecast by using expected improvements in defect densities. Examples show good agreement between actual and calculated yields.
1. Applications of genetic algorithms to the prediction of blood-brain partitioning of a large set of drugs

In this study, the relationships between the brain-blood concentration ratio of 96 structurally diverse compounds with a large number of structurally derived descriptors were investigated. The linear models were based on molecular descriptors that can be calculated for any compound simply from a knowledge of its molecular structure. The linear correlation coefficients of the mod- els were optimized by genetic algorithms (GAs), and the descriptors used in the linear models were automatically selected from 27 structurally derived descriptors. The GA optimizations resulted in a group of linear models with three or four molecular descriptors with good statis- tical significance. The change of descriptor use as the evolution proceeds demonstrates that the octane/water partition coefficient and the partial negative solvent- accessible surface area multiplied by the negative charge are crucial to brain-blood barrier permeability. More- over, we found that the predictions using multiple QSPR models from GA optimization gave quite good results in spite of the diversity of structures, which was better than the predictions using the best single model. The predic- tions for the two external sets with 37 diverse com- pounds using multiple QSPR models indicate that the best linear models with four descriptors are sufficiently effective for predictive use. Considering the ease of computation of the descriptors, the linear models may be used as general utilities to screen the blood-brain barrier partitioning of drugs in a high-throughput fashion.
GeneTerrain: visual exploration of differential gene expression profiles organized in native biomolecular interaction networks

We propose a new network visualization technique using scattered data interpolation and surface rendering, based upon a foundation layout of a scalar field. Contours of the interpolated surfaces are generated to support multi-scale visual interaction for data exploration. Our framework visualizes quantitative attributes of nodes in a network as a continuous surface by interpolating the scalar field, therefore avoiding scalability issues typical in conventional network visualizations while also maintaining the topological properties of the original network. We applied this technique to the study of a bio-molecular interaction network integrated with gene expression data for Alzheimer's Disease (AD). In this application, differential gene expression profiles obtained from the human brain are rendered for AD patients with differing degrees of severity and compared to healthy individuals. We show that this alternative visualization technique is effective in revealing several types of molecular biomarkers, which are traditionally difficult to detect due to "noises" in data derived from DNA microarray experiments.
Auto-And Hetero-Associative Memory Using A 2-D Optical Logic Gate

An optical associative memory system suitable for both auto- and hetero-associative recall is demonstrated. This system utilizes Hamming distance as the similarity measure between a binary input and a memory image with the aid of a 2-D optical EXCLUSIVE OR (XOR) gate and a parallel electronics comparator module. Based on the Hamming distance measurement, this optical associative memory performs a nearest neighbor search and the result is displayed in the output plane in real-time. This optical associative memory is fast and noniterative and produces no output spurious states as compared with that of the Hopfield neural network model.
Improvements of on-membrane method for thin-film thermal conductivity and emissivity measurements

In this paper we present a numerical simulation and various test-structure configurations, which enable the measurement of the thermal conductivity and emissivity of thin films by the Volklein method to be more versatile and accurate. The capabilities of the Volklein method to measure a broader range of materials are extended by using smaller membranes and by taking into account the two-dimensional heat transfer in the membrane. The measurement method is extended to the measurement of the heat transfer coefficient of convection. The test-structures are adapted to be integrated in the process flow of a thin-film-based thermoelectric micro-generator by putting the thermoelectric material to be measured on the top of the membrane and side by side with the heater. The measurement method is tested on various materials ranging from ceramics and metal to polycrystalline silicon.
Instructional Methodology for Video Editing in Image Content Production

This thesis suggests a methodology of video editing education that is a part of post-production process. The methodology is educating students on contents, theories, technology in phases according to the characteristics of each process. It is based on the training results from the class 'Understanding of Video Contents Production Technology' conducted for high school students between December, 2013 and August, 2014. The result of the satisfaction survey by enrolled students indicated that high educational satisfaction can be obtained by the education methodology