Determining the most representative image on a Web page

We investigate how to determine the most representative image on a Web page. This problem has not been thoroughly investigated and, up to today, only expert-based algorithms have been proposed in the literature. We attempt to improve the performance of known algorithms with the use of Support Vector Machines (SVM). Besides, our algorithm distinguishes itself from existing literature with the introduction of novel image features, including previously unused meta-data protocols. Also, we design and attempt a less-restrictive ranking methodology in the image preprocessing stage of our algorithm. We find that the application of the SVM framework with our improved classification methodology increases the F1 score from 27.2% to 38.5%, as compared to a state-of-the-art method. Introducing novel image features and applying backward feature selection, we find that the F1 score rises to 40.0%. Lastly, we use a class-weighted SVM in order to resolve the imbalance in number of representative images. This final modification improves the classification performance of our algorithm even further to 43.9%, outperforming our benchmark algorithms, including those of Facebook and Google. Suggested beneficiaries are the search engine community, image retrieval community, including the commercial sector due to superior performance

The colour of life: novel visualisations of population Lifestyles

Colour permeates our daily lives, yet we rarely take notice of it. In this work we utilise the SenseCam (a visual lifelogging tool), to investigte the predominant colours in one million minutes of human life that a group of 20 individuals encounter throughout their normal daily activities. We also compare the colours that different groups of people are exposed to in their typical days. This information is presented in using a novel colour-wheel visualisation which is a new means of illustrating that people are exposed to bright colours over longer durations of time during summer months, and more dark colours during winter months

Creating a Religious Properties Database for the City of New Bedford: an Analysis of Best Practices and Available Systems

This policy analysis was written to provide the city of New Bedford, the Waterfront Historic Area League, Inter-church Council of Greater New Bedford, and the congregations with possible database systems to consider in creating their historic religious properties database. It also provides the best methodology to use when choosing a database. Deciding on who will be involved in the choosing process, determining a budget, and listing the mandatory requirements the database should provide are all important to consider in the decision making process

Authenticity and Admissibility of Social Media Website Printouts

Social media posts and photographs are increasingly denied admission as evidence in criminal trials. Courts often cite issues with authentication when refusing to admit social media evidence. Cases and academic writings separate recent case law into two approaches: The Maryland Approach and the Texas Approach. The first method is often seen as overly skeptical of social media evidence, setting the bar too high for admissibility. The second approach is viewed as more lenient, declaring that any reasonable evidence should be admitted in order for a jury to weigh its sufficiency. This Brief addresses the supposed differences between the two sets of cases and suggests that courts are not actually employing two distinct approaches. The Maryland Approach courts are not holding social media content to a higher standard than the Texas Approach courts, but are merely responding to a lack of evidence connecting the proffered content to the purported author

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Teaching Health Impact and Behavior with Infographics

The use of Infographics can be a tool that not only allows for the communication of empirical health data in an understandable format, but encourages the health administration student to present evidence-based research in a creative manner. The purpose of this paper is to describe a learning exercise that implements Infographics to demonstrate an impact of a health issue and/or encourage a health behavior change. This learning exercise is developed to increase student knowledge and visual literacy skills with respect to presenting, in a concise format, a well-researched and referenced health issue and/or a health behavior change. Specifically, the exercise was designed to: (a) curate health statistics and reference information for the selected health issue; (b) identify media resources and apply copyright and fair use in a proper manner; (c) evaluate internet resources for credibility and accuracy; and (d) utilize Infographic tools to communicate one\u27s visual viewpoint. At the conclusion of the course, students reflected on the effective visual aspects of their Infographics and the points that were challenging to communicate using this medium. The benefits of this applied learning approach for students and the faculty instructor are discussed

WISeREP - An Interactive Supernova Data Repository

We have entered an era of massive data sets in astronomy. In particular, the number of supernova (SN) discoveries and classifications has substantially increased over the years from few tens to thousands per year. It is no longer the case that observations of a few prototypical events encapsulate most spectroscopic information about SNe, motivating the development of modern tools to collect, archive, organize and distribute spectra in general, and SN spectra in particular. For this reason we have developed the Weizmann Interactive Supernova data REPository - WISeREP - an SQL-based database (DB) with an interactive web-based graphical interface. The system serves as an archive of high quality SN spectra, including both historical (legacy) data as well as data that is accumulated by ongoing modern programs. The archive provides information about objects, their spectra, and related meta-data. Utilizing interactive plots, we provide a graphical interface to visualize data, perform line identification of the major relevant species, determine object redshifts, classify SNe and measure expansion velocities. Guest users may view and download spectra or other data that have been placed in the public domain. Registered users may also view and download data that are proprietary to specific programs with which they are associated. The DB currently holds >8000 spectra, of which >5000 are public; the latter include published spectra from the Palomar Transient Factory, all of the SUSPECT archive, the Caltech-Core-Collapse Program, the CfA SN spectra archive and published spectra from the UC Berkeley SNDB repository. It offers an efficient and convenient way to archive data and share it with colleagues, and we expect that data stored in this way will be easy to access, increasing its visibility, usefulness and scientific impact.Comment: To be published in PASP. WISeREP: http://www.weizmann.ac.il/astrophysics/wiserep

Colour Text Segmentation in Web Images Based on Human Perception

There is a significant need to extract and analyse the text in images on Web documents, for effective indexing, semantic analysis and even presentation by non-visual means (e.g., audio). This paper argues that the challenging segmentation stage for such images benefits from a human perspective of colour perception in preference to RGB colour space analysis. The proposed approach enables the segmentation of text in complex situations such as in the presence of varying colour and texture (characters and background). More precisely, characters are segmented as distinct regions with separate chromaticity and/or lightness by performing a layer decomposition of the image. The method described here is a result of the authors’ systematic approach to approximate the human colour perception characteristics for the identification of character regions. In this instance, the image is decomposed by performing histogram analysis of Hue and Lightness in the HLS colour space and merging using information on human discrimination of wavelength and luminance

Normal background concentrations (NBCs) of contaminants in English soils : final project report

The British Geological Survey (BGS) has been commissioned by the Department for Environment, Food and Rural Affairs (Defra) to give guidance on what are normal levels of contaminants in English soils in support of the Part 2A Contaminated Land Statutory Guidance. This has initially been done by studying the distribution of four contaminants – arsenic, lead, benzo[a]pyrene (BaP) and asbestos – in topsoils from England. This work was extended to a further four contaminants (cadmium, copper, nickel and mercury) which enabled methodologies developed to be tested on a larger range of contaminants. The first phase of the Project gathered data sets that were: nationally extensive; systematically collected so a broad range of land uses were represented; and collected and analysed to demonstrably and acceptable levels of quality. Information on the soil contaminant concentrations in urban areas was of particular importance as the normal background is considered to be a combination of both natural and diffuse anthropogenic contributions to the soil. Issues of soil quality are most important in areas where these affect most people, namely, the urban environment. The two principal data sets used in this work are the BGS Geochemical Baseline Survey of the Environment (G-BASE) rural and urban topsoils (37,269 samples) and the English NSI (National Soil Inventory) topsoils (4,864 samples) reanalysed at the BGS laboratories by X-ray fluorescence spectrometry (XRFS) so both data sets were highly compatible. These two data sets provide results for most inorganic element contaminants, though results explored for mercury and BaP are drawn from a variety of different and much less extensive data sets