The Characteristics of Wave Impacts on an Oscillating Wave Surge Converter

Wave impacts on an Oscillating Wave Surge Converter are examined using experimental and numerical methods. The mechanics of the impact event are identified experimentally with the use of images recorded with a high speed camera. It is shown that it is the device which impacts the wave rather than a breaking wave impacting the device. Numerical simulations using two different approaches are used to further understand the issue. Good agreement is shown between numerical simulations and experimental measurements at 25th scale.

Thomas Moore Music Project:The Genesis of Thomas Moore's Irish Melodies

This is a selection of images from the Gibson-Massie Moore Collection, supplement by a table created by curator Sarah McCleave. The purpose is to identify the numerous creators involved in the Irish Melodies series (music editor, illustrators, engravers, etc.), and to illustrate some characteristics kinds of variants

Detecting Ca2+ sparks on stationary and varying baselines.

Studies concerning the physiological significance of Ca2+ sparks often depend on the detection and measurement of large populations of events in noisy microscopy images. Automated detection methods have been developed to quickly and objectively distinguish potential sparks from noise artifacts. However, previously described algorithms are not suited to the reliable detection of sparks in images where the local baseline fluorescence and noise properties can vary significantly, and risk introducing additional bias when applied to such data sets. Here, we describe a new, conceptually straightforward approach to spark detection in linescans that addresses this issue by combining variance stabilization with local baseline subtraction. We also show that in addition to greatly increasing the range of images in which sparks can be automatically detected, the use of a more accurate noise model enables our algorithm to achieve similar detection sensitivities with fewer false positives than previous approaches when applied both to synthetic and experimental data sets. We propose, therefore, that it might be a useful tool for improving the reliability and objectivity of spark analysis in general, and describe how it might be further optimized for specific applications.

Moving Object Scanning Apparatus and Method

Apparatus for scanning a moving object includes a visible waveband sensor oriented to collect a series of images of the object as it passes through a field of view. An image processor uses the series of images to form a composite image. The image processor stores image pixel data for a current image and predecessor image in the series. It uses information in the current image and its predecessor to analyse images and derive likelihood measures indicating probabilities that current image pixels correspond to parts of the object. The image processor estimates motion between the current image and its predecessor from likelihood weighted pixels. It generates the composite image from frames positioned according to respective estimates of object image motion. Image motion may alternatively be detected be a speed sensor such as Doppler radar sensing object motion directly and providing image timing signals

Adaptive Bacteria Colony Picking in Unstructured Environments Using Intensity Histogram and Unascertained LS-SVM Classifier

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to avoid disturbing peaks, an entropy based mean shift filter is introduced to smooth images as a preprocessing step. The relevance and importance of these features can be determined in an improved support vector machine classifier using unascertained least square estimation. Experimental results show that the proposed unascertained least square support vector machine (ULSSVM) has better recognition accuracy than the other state-of-the-art techniques, and its training process takes less time than most of the traditional approaches presented in this paper.

Children’s essentialist reasoning about language and race

Across four studies, we directly compared children’s essentialist reasoning about the stability of race and language throughout an individual’s lifespan. Monolingual English-speaking children were presented with a series of images of children who were either White or Black; each face was paired with a voice clip in either English or French. Participants were asked which of two adults each target child would grow up to be – one who was a ‘match’ to the target child in race but not language, and the other a ‘match’ in language but not race. Nine- to 10-year-old European American children chose the race-match, rather than the language-match. In contrast, 5–6-year-old European American children in both urban, racially diverse, and rural, racially homogeneous environments chose the language-match, even though this necessarily meant that the target child would transform racial categories. Although surprising in light of adult reasoning, these young children demonstrated an intuition about the relative stability of an individual’s language compared to her racial group membership. Yet, 5–6-year-old African American children, similar to the older European American children, chose the race-match, suggesting that membership in a racial minority group may highlight children’s reasoning about race as a stable category. Theoretical implications for our understanding of children’s categorization of human kinds are discussed.

The P/2010 A2 Asteroid Collision Confirmed by Rosetta/OSIRIS Observation

The discovery of P/2010 A2 by the LINEAR survey in January 2010 revealed an object displaying a large trail of material similar in shape to a cometary tail although no central condensation or coma could be detected. The appearance of this object in an asteroidal orbit in the inner main belt attracted attention as a potential new member of the Main Belt Comets class (MBCs) but the discovery of a nucleus, with an estimated diameter of 120 m, around 1500 km away from the trail implied that the extended object we were seeing could be the debris trail from a recent collision rather than the tail of a comet. Due to the low inclination of its orbit, it is difficult to conclude about the nature of P/2010 A2 from Earth-based data only, as different scenarios lead to the same appearance in the orbital configuration at the times of observations. We present here another set of images, acquired from the unique viewing geometry provided by ESA's Rosetta spacecraft en route to comet 67P/Churyumov-Gerasimenko. Albeit faint (22 magnitude), the object could be observed by the high-resolution camera OSIRIS. We used a Finson-Probstein model to simulate the shape of the trail, and estimate the time of emission and β parameter (ratio between solar radiation pressure and gravity) for the dust grains. Simulations were compared to the OSIRIS images and ground based observations acquired at NTT and Palomar telescopes. Thanks to the different phase angle provided by Rosetta, we could reduce the number of solutions to a unique model, leading to the conclusive demonstration that the trail is due to a single event rather than a period of cometary activity.

Random Forest Based Approach for Concept-Drift Handling

Algorithms for concept drift handling are important for various applications including video analysis and smart grids. In this paper we present decision tree ensemble classication method based on the Random Forest algorithm for concept drift. The weighted majority voting ensemble aggregation rule is employed based on the ideas of Accuracy Weighted Ensemble (AWE) method. Base learner weight in our case is computed for each sample evaluation using base learners accuracy and intrinsic proximity measure of Random Forest. Our algorithm exploits both temporal weighting of samples and ensemble pruning as a forgetting strategy. We present results of empirical comparison of our method with îriginal random forest with incorporated replace-the-looser forgetting andother state-of-the-art concept-drift classiers like AWE2.