GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

About the determination of key of a musical excerpt

Knowledge of the key of a musical passage is a pre-requisite for all the analyses that require functional labelling. In the past, people from either a musical or AI background have tended to solve the problem by means of implementing a computerized version of musical analysis. Previous attempts are discussed and then attention is focused on a non-analytical solution first reported by J.A.Gabura. A practical way to carry it out is discussed as well as its limitations in relation to examples. References are made to the MusicXML format as needed. © Springer-Verlag Berlin Heidelberg 2006.

Indexing and integrating multiple features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image's multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition's center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images have similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the dimensionality curse existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude. And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.

Indexing text and visual features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index imagersquos multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partitionrsquos center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images haves similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the ldquodimensionality curserdquo existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms imagersquos text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partitionrsquos center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude.

Mach edges: local features predicted by 3rd derivative spatial filtering

Edges are key points of information in visual scenes. One important class of models supposes that edges correspond to the steepest parts of the luminance profile, implying that they can be found as peaks and troughs in the response of a gradient (1st derivative) filter, or as zero-crossings in the 2nd derivative (ZCs). We tested those ideas using a stimulus that has no local peaks of gradient and no ZCs, at any scale. The stimulus profile is analogous to the Mach ramp, but it is the luminance gradient (not the absolute luminance) that increases as a linear ramp between two plateaux; the luminance profile is a blurred triangle-wave. For all image-blurs tested, observers marked edges at or close to the corner points in the gradient profile, even though these were not gradient maxima. These Mach edges correspond to peaks and troughs in the 3rd derivative. Thus Mach edges are inconsistent with many standard edge-detection schemes, but are nicely predicted by a recent model that finds edge points with a 2-stage sequence of 1st then 2nd derivative operators, each followed by a half-wave rectifier.

Special issue:key debates in the translation of advertising material

Much has been written about the marketing aspects of promotional material in general, and several scholars (particularly in linguistics) have addressed questions relating to the structure and function of advertisements, focusing on images, rhetorical structure, semiotic functions, discourse features and audio-visual media, amongst other aspects of the genre. Not much, on the other hand, has been written within translation studies about the complexities involved in the transfer of an advertising message. Contributors to this volume explore various interdependent aspects of the interlingual and intercultural transfer of an advertising message. They emphasize features of culture specificity, of multi-medial semiotic interaction, of values and stereotypes, and most importantly, they recommend strategies and approaches to assist translators. Topics covered include a critique of the Western-based approach to advertising in the context of the Far East; different perceptions of the concept of cleanliness in advertising texts in Italy, Russia and the UK; the Walls Cornetto strategy of internationalization of product appeal, followed by localization; the role of the translator in recreating appeal in different lingua-cultural contexts; what constitutes 'Italianness' in advertisements for British consumers; and strategies for repackaging France as a tourist destination.

Three key regimes of single pulse generation per round trip of all-normal-dispersion fiber lasers mode-locked with nonlinear polarization rotation

We show experimentally and numerically new transient lasing regime between stable single-pulse generation and noise-like generation. We characterize qualitatively all three regimes of single pulse generation per round-trip of all-normal-dispersion fiber lasers mode-locked due to effect of nonlinear polarization evolution. We study spectral and temporal features of pulses produced in all three regimes as well as compressibility of such pulses. Simple criteria are proposed to identify lasing regime in experiment. © 2012 Optical Society of America.

Maintaining tree islands in the Florida Everglades: nutrient redistribution is the key

The Florida Everglades is an oligotrophic wetland system with tree islands as one of its most prominent landscape features. Total soil phosphorus concentrations on tree islands can be 6 to 100 times greater than phosphorus levels in the surrounding marshes and sloughs, making tree islands nutrient hotspots. Several mechanisms are believed to redistribute phosphorus to tree islands: subsurface water flows generated by evapotranspiration of trees, higher deposition rates of dry fallout, deposition of guano by birds and other animals, groundwater upwelling, and bedrock mineralization by tree exudates. A conceptual model is proposed, in which the focused redistribution of limiting nutrients, especially phosphorus, onto tree islands controls their maintenance and expansion. Because of increased primary production and peat accretion rates, the redistribution of phosphorus can result in an increase in both tree island elevation and size. Human changes to hydrology have greatly decreased the number and size of tree islands in parts of the Everglades. The proposed model suggests that the preservation of existing tree islands, and ultimately of the Everglades landscape, requires the maintenance of these phosphorus redistribution mechanisms.

Assessing Organizational Image: Triangulation Across Different Applicant Perceptions, Website, and Facebook Features

This study examined the role of corporate websites and company Facebook profiles in shaping perceptions of organizational image in the recruitment context. A primary purpose of this research was to determine whether or not perceptions of organizational image vary across different web-based recruitment methods, specifically examining corporate websites and social networking (SNW) sites, such as company Facebook profiles. A secondary goal was to determine how these perceptions of image are shaped by the objective components of websites and Facebook profiles. Finally, this study sought to determine the most influential components of websites and Facebook profiles, in terms of impacting image, to better understand how organizations can maximize their web-based recruitment efforts. A total of 102 companies selected from Fortune Magazine’s 2011 top 500 were chosen for the study. Perceptions of organizational personality as well as objective assessments of personality were gathered for each organization in a two phase approach. Results indicate that exposure to corporate websites and company Facebook profiles do influence perceptions of image in different ways. Furthermore, individual components of the websites were identified as key drivers for influencing specific image dimensions, particularly for company Facebook pages. Findings are beneficial for advising practitioners on how to best manage their web-based recruitment sources in order to maximize efficiency. The present study serves to further our understanding of the process through which perceptions of organizational image are influenced by new recruitment sources.

Complexity as key to designing cognitive-friendly environments for older people

The lived environment is the arena where our cognitive skills, preferences, and attitudes come together to determine our ability to interact with the world. The mechanisms through which lived environments can benefit cognitive health in older age are yet to be fully understood. The existing literature suggests that environments which are perceived as stimulating, usable and aesthetically appealing can improve or facilitate cognitive performance both in young and older age. Importantly, optimal stimulation for cognition seems to depend on experiencing sufficiently stimulating environments while not too challenging. Environmental complexity is an important contributor to determining whether an environment provides such an optimal stimulation. The present paper reviews a selection of studies which have explored complexity in relation to perceptual load, environmental preference and perceived usability to propose a framework which explores direct and indirect environmental influences on cognition, and to understand these influences in relation to aging processes. We identify ways to define complexity at different environmental scales, going from micro low-level perceptual features of scenes, to design qualities of proximal environments (e.g., streets, neighborhoods), to broad geographical areas (i.e., natural vs. urban environments). We propose that studying complexity at these different scales will provide new insight into the design of cognitive-friendly environments.

Datasets, features, learning, and models in visual recognition

Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.

KEY COMPONENTS OF TEAMWORK AND THE SERVICE (TO) YOU (A) (A) DOMESTIC (A) AND EXTERNAL (A)

The article examines a range of components for the customer service from the point of view of marketing.It start with the explanation of several features that are required for a company to crystallize teamwork that finally, after all, will be provided by the success or failure of that company.These features are named: engagement, cooperation, companionship, communication, motivation and leadership.Subsequently, this article presents a section which explores human relationships and conflict management within organizations, with emphasis on attitudes, skills and personality types that present human beings as part of its essence.Finally, this text includes a section that highlights concepts related to customer service and sales techniques that exist today.

Investigating the use of LiDAR scanning as a method for the measurement of timber distortion features

Measuring the extent to which a piece of structural timber has distorted at a macroscopic scale is fundamental to assessing its viability as a structural component. From the sawmill to the construction site, as structural timber dries, distortion can render it unsuitable for its intended purposes. This rejection of unusable timber is a considerable source of waste to the timber industry and the wider construction sector. As such, ensuring accurate measurement of distortion is a key step in addressing ineffciencies within timber processing. Currently, the FRITS frame method is the established approach used to gain an understanding of timber surface profile. The method, while reliable, is dependent upon relatively few measurements taken across a limited area of the overall surface, with a great deal of interpolation required. Further, the process is unavoidably slow and cumbersome, the immobile scanning equipment limiting where and when measurements can be taken and constricting the process as a whole. This thesis seeks to introduce LiDAR scanning as a new, alternative approach to distortion feature measurement. In its infancy as a measurement technique within timber research, the practicalities of using LiDAR scanning as a measurement method are herein demonstrated, exploiting many of the advantages the technology has over current approaches. LiDAR scanning creates a much more comprehensive image of a timber surface, generating input data multiple magnitudes larger than that of the FRITS frame. Set-up and scanning time for LiDAR is also much quicker and more flexible than existing methods. With LiDAR scanning the measurement process is freed from many of the constraints of the FRITS frame and can be done in almost any environment. For this thesis, surface scans were carried out on seven Sitka spruce samples of dimensions 48.5x102x3000mm using both the FRITS frame and LiDAR scanner. The samples used presented marked levels of distortion and were relatively free from knots. A computational measurement model was created to extract feature measurements from the raw LiDAR data, enabling an assessment of each piece of timber to be carried out in accordance with existing standards. Assessment of distortion features focused primarily on the measurement of twist due to its strong prevalence in spruce and the considerable concern it generates within the construction industry. Additional measurements of surface inclination and bow were also made with each method to further establish LiDAR's credentials as a viable alternative. Overall, feature measurements as generated by the new LiDAR method compared well with those of the established FRITS method. From these investigations recommendations were made to address inadequacies within existing measurement standards, namely their reliance on generalised and interpretative descriptions of distortion. The potential for further uses of LiDAR scanning within timber researches was also discussed.

Quantification of key biological processes determining the dynamics and the assessment of the anchovy population in the Bay of Biscay: growth, reproduction, demography and natural mortality.

333 p.

PCOS remains a diagnosis of exclusion:a concise review of key endocrinopathies to exclude

Polycystic ovarian syndrome (PCOS) is a heterogenous disorder associated with clinical, endocrine and ultrasonographic features that can also be encountered in a number of other diseases. It has traditionally been suggested that prolactin excess, enzymatic steroidogenic abnormalities and thyroid disorders need to be excluded before a diagnosis of PCOS is made. However, there is paucity of data regarding the prevalence of PCOS phenotype in some of these disorders, whereas other endocrine diseases that exhibit PCOS-like features may elude diagnosis and proper management if not considered. This article reviews the data of currently included entities that exhibit a PCOS phenotype and those that potentially need to be looked for, and attempts to identify specific features that distinguish them from idiopathic PCOS.