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There are several studies dealing with the phenotypic variance of the vertebral number in the spinal column of rabbits. According to the literature the number of thoracic and lumbar vertebrae varies between 11-13 and 6-8, respectively. The length of the m. longissimus dorsi (MLD) - a valuable meat part of rabbits - is determined by the length of the vertebral column therefore the number of vertebrae may have economic importance in breeding. The aim of this study was to create an automatic counter using computed tomography (CT) images. In the first step, a skeleton binary mask was created using the radiodensity range between 120 and 3071 HU, then the lumbar and thoracic regions were processed by two different methods. The lumbar part was evaluated based on the frequency of the bone voxels along the axial plane. The number of thoracic vertebrae was determined from the number of ribs. The left and right ribs were processed separately. The developed method was tested on CT examination of 40 Hycole rabbits compared to manual evaluation. The results of the automatic algorithm had few errors: in one case in the lumbar region (2.5%) and in 3 cases in the thoracic region (5%). The automated evaluation process takes a few seconds per individual and then the program visualizes the results on a graph. The incorrectly evaluated rabbits are recognizable on graphs and they can be easily corrected with a minimal time investment.

Electrospun nonwovens are widely applied in biomedicine and various other fields. For control of the manufacturing process and quality assurance Scanning electron microscopy (SEM) imaging is one standard practice. In this study, statistical datasets of 60 SEM images of three nonwoven samples were evaluated using Gaussian fit to obtain numerical results of their fiber diameter distributions. The question of how much effort is required for acceptable imaging and processing is being discussed. As determined here, for reliable statistics, a minimum surface area of the nonwoven has to be evaluated. The fiber diameter should be in a range of approximately 2 - 3% of the edge length of the square equivalent of the evaluated image area, using sufficiently magnified SEM images, in which the fiber diameter is imaged over at least 30 pixels.

International audience; In information visualization, it has become mandatory to assess visualization techniques efficiency either to write a survey, optimize a technique or even design a new one. To do so, the common way is to conduct user evaluations through which human subjects are asked to solve a task on different visualization techniques while their performances are measured to assess which technique is the most efficient. These evaluations can be complex to design and setup in order not to be biased and, in the end, their results can become contestable when the evaluation methods standards evolve. To overcome these flaws, new evaluation methods are emerging, mostly making use of modern and efficient computer vision techniques such as deep learning. These new methods rely on a strong assumption that has not been studied deeply enough yet: humans and deep learning models performances can be correlated. This paper explores the performances of both a state-of-the-art deep neural network and human subjects on an outlier detection task taken from a previous experiment of the literature. The objective is to study whether the machine and humans behaviors were different or if some correlations can be observed. Our study shows that their results are significantly correlated and a machine learning model efficiently learned to predict human performances using deep neural network metrics as input. Hence, this work presents a use case where using a deep neural network to assess human subjects performances is efficient.

Purpose: Size and density measurements of the ablation zones on contrast-enhanced computed tomography (CT) after radiofrequency ablation (RFA) of hepatic metastases of primary breast or colorectal cancer were acquired over time. Materials and Methods: Twenty-five liver metastases [colorectal cancer (CRC): n = 16; mean size: 19.6 ± 8.5 mm; breast cancer (BC): n = 9; 27.9 ± 13.6 mm] in 15 patients (CRC: n = 11; age: 65.4 ± 6.5 years; BC: n = 4; 62.0 ± 13.8 years) treated by RFA were included in this retrospective study. All patients had undergone postinterventional serial follow-up using multidetector CT (MDCT) (1 day/1/4/7/10/14/18/23/>24 months) without evidence of local tumor recurrence during the follow-up. The ablation zones were evaluated using a commercial software tool (Syngo CT Oncology) in order to determine volumetric, RECIST-, WHO- and density changes over the course of time. Results were compared by applying repeated measures analysis of variance and displayed graphically. Results: The RF ablation zones demonstrated significant shrinkage (P ≤ 0.05) over the first 7 months (volume, RECIST, WHO) of the follow-up. Follow-up after 7 months did not show any significant changes in size (P > 0.05) (mean volume (ml): 55.2/34.7/26.3/16.5/12.7/10.0/8.9/8.1/7.5; RECIST (mm): 58.7/49.3/43.7/37.8/34.2/31.3/29.1/27.3/24.8; WHO (mm2): 2458.3/1769.3/1341.8/1027.1/870.1/720.2/649.0/570.4/511.3). Mean density values decreased significantly between 1 day (58.9 HU) and 1 month (47.5 HU) after the procedure. Conclusion: Typical changes in size and density values of RF-induced, recurrence-free ablation zones after RFA of hepatic metastases of colorectal and breast cancer were acquired, showing a significant decrease in density of the ablation zone within the first month and significant shrinkage within the first 7 months after RFA.

Automated documents processing allows production of large amount of documents. Formal quality of the documents is very important as it contributes to better understanding and information transmission. The paper deals with the automated documents quality evaluation. This requires a design of a document model. The model contains the objects of which the pages are compiled, the types of objects and, the most important, the objects’ parameters. The parameters of the object are very important as they are inputs for the document evaluation according to the typographical rules. The parameters are an important part of the model which should reliably describe the document. A set of criteria is designed, which are used to describe the requirements on appropriate methods for model formation. From large amount of methods, methods that meet the criteria can be applied to the document. The result is a model of a real document which can be used for the automatic evaluation based on the typographical rules.

Web Content Accessibility Guidelines (WCAG) from W3C consist of a set of 65 checkpoints or specifications that Web pages should accomplish in order to be accessible to people with disabilities or using alternative browsers. Many of these 65 checkpoints can only be checked by a human operator, thus implying a very high cost for full evaluation. However, some checkpoints can be automatically evaluated, thus spotting accessibility barriers in a very effective manner. Well known tools like Bobby, Tawdis or WebXACT evaluate Web accessibility by using a mixture of automated, manual and semiautomated evaluations. However, the automation degree of these Web evaluations is not the same for each of these tools. Since WCAG are not written in a formalized manner, these evaluators may have different “interpretations” of what these rules mean. As a result, different evaluation results might be obtained for a single page depending on which evaluation tool is being used.Taking into account that a fully automated Web accessibility evaluation is not feasible because of the nature of WCAG, this paper evaluates the WCAG automation coverage of some well known Web accessibility evaluation tools spotting their weaknesses and differences. We also provide a formalized specification for those checkpoints where these differences have been detected, thus challenging nowaday's tools for more automated coverage.

Describing test results in a standardized format facilitates the exchange of information between different types of tools that are used to evaluate Web sites for accessibility. The Evaluation and Report Language (EARL) is a machine-readable, platform-independent, and vendor-neutral format that builds on Semantic Web technologies to provide a powerful data model for expressing test results. While the primary motivation for developing this language is to facilitate the automation of Web accessibility evaluations, it is has been designed so that it can serve generic Web quality assurance purposes as well as other use cases outside the scope of Web site evaluation.

El programa EssA fue creado en 2004 como un instrumento para ayudar a valorar narraciones en el área de lengua extranjera. El análisis de regresión múltiple, según variables léxico-gramaticales, determinó una ecuación de regresión que predice la calificación de los textos con un coeficiente de regresión del 0.79. EssA ha demostrado realizar la valoración gramatical de las narraciones con mayor objetividad y fiabilidad que los docentes. Por otra parte, proporciona feedback inmediato al estudiante sobre el uso que hace de los distintos recursos lingüísticos en el contexto de la narración, al mismo tiempo que le muestra la valoración del mismo. EssA software was created in 2004 as an instrument to help EFL teachers to assess narrative stories. Multiple regression analysis, using lexical-grammar variables, determined a regression equation to predict the score of each text with a regression coefficient of 0.79. The final result we found was that the EssA's analysis of the stories has proven to be more reliable and more objective compare to the scores given by the teachers. It also provides immediate feedback on those linguistics resources of the academic curriculum the student uses in their story, as well as the score.

The purpose of this article – is to create theoretical model in order to enable in automated manner to compare different solutions of building, its part or structure design and to select the best alternative under specific circumstances. Summarizing variant design theory and practice applications in Lithuania and abroad, evaluation model of alternative design solutions is created. By assistance of this model it will be possible to evaluate design solutions which can be characterized by quantitative and qualitative indicators which possibly have different weight, dimention and direction of optimization (maksimization or minimization). Automated alternatives’ evaluation working principle is demonstrated by selecting the best facade system to cover the building. For this purpose four building facades alternatives is under consideration. It is soundly described how all stages of alternatives comparison is performed and which multiple criteria evaluation methods can be applied by selecting the best alternative.

This paper presents a comparison of some methodologies for the automatic construction of video summaries. The work is based on the simulated user principle to evaluate the quality of a video summary in a way that is automatic, yet related to the user′s perception. The method is studied for the case of multiepisode video, where we do not describe only what is important in a video but rather what distinguishes this video from the others. Experimental results are presented to support the proposed ideas.

Automated evaluation of generalization output relies to a large extent on that requirements (e.g. specifications, constraints) being formalized in machine-readable formats. Previous studies suggest that the formalization and automated evaluation are relatively easier for legibility constraints (improve the readability of maps) than for preservation constraints (preserving important real-world phenomena). Three major difficulties, i.e., pattern classification and characterization, pattern matching, and constraint formalization, in the automated evaluation of building pattern preservation constraint are analyzed in this paper. A classification of available building patterns is reviewed based on a previous work. In addition, the transition events describing allowed changes for building patterns to preserve during generalization are obtained through the study of existing maps series (from 1:10k to 1:100k). Based on the obtained knowledge on pattern types and acceptable transition events, an approach to automatically match corresponding building patterns at different scales is presented. The methodology proposed is validated by applying it to the interactively generalized data. The result shows promising results and also further improvement in order to apply the method in an overall evaluation to indicate acceptable generalization solutions.