Big Objects Research Articles

Fast computation of 2D and 3D Legendre moments using multi-core CPUs and GPU parallel architectures

Legendre moments and their invariants for 2D and 3D image/objects are widely used in image processing, computer vision, and pattern recognition applications. Reconstruction of digital images by nature required higher-order moments to get high-quality reconstructed images. Different applications such as classification of bacterial contamination images utilize high-order moments for feature extraction phase. For big size images and 3D objects, Legendre moments computation is very time-consuming and compute-intensive. This problem limits the use of Legendre moments and makes them impractical for real-time applications. Multi-core CPUs and GPUs are powerful processing parallel architectures. In this paper, new parallel algorithms are proposed to speed up the process of exact Legendre moments computation for 2D and 3D image/objects. These algorithms utilize multi-core CPUs and GPUs parallel architectures where each pixel/voxel of the input digital image/object can be handled independently. A detailed profile analysis is presented where the weight of each part of the entire computational process is evaluated. In addition, we contributed to the parallel 2D/3D Legendre moments by: (1) a modification of the traditional exact Legendre moment algorithm to better fit the parallel architectures, (2) we present the first parallel CPU implementation of Legendre moment, and (3) we present the first parallel CPU and GPU acceleration of the reconstruction phase of the Legendre moments. A set of numerical experiments with different gray-level images are performed. The obtained results clearly show a very close to optimal parallel gain. The extreme reduction in execution times, especially for 8-core CPUs and GPUs, makes the parallel exact 2D/3D Legendre moments suitable for real-time applications.

A familiar-size Stroop effect in the absence of basic-level recognition

When we view a picture of an object, we automatically recognize what the object is and know how big it typically is in the world (Konkle & Oliva, 2012). Is information about an object’s size activated only after we’ve identified the object, or can this size information be activated before object recognition even occurs? We previously found that big and small objects differ in mid-level perceptual features (Long, Konkle, Cohen, & Alvarez, 2016). Here we asked whether these perceptual features can automatically trigger real-world size processing, bypassing the need for basic-level object recognition. To test this hypothesis, we used an image synthesis algorithm to generate “texform” images, which are unrecognizable versions of big and small objects that still preserve some textural and form information from the original images. Across two experiments, we find that even though these synthesized stimuli cannot be identified, they automatically trigger familiar size processing and give rise to a Size-Stroop effect. Furthermore, we isolate perceived curvature as one feature the visual system uses to infer real-world size. These results suggest that mid-level perceptual features can automatically feed forward to facilitate object processing, and challenge the idea that we must first identify an object before we can access its higher-level properties.

Model based object localization and shape estimation using electric sense on underwater robots

Recently, biologists have shown that the weakly electric fish are able to estimate the electric nature, the localization and the 3D geometric properties of an object using active electric sense. Incredibly, the Gnathonemus petersii performs this task in the dark only by moving towards and around the object, its vision is not required. In this paper, we proposed to address the challenging issue of object localization and shape estimation using a real underwater robot equipped with artificial electric sense. To that end, we used a corrected version of the dipolar tensor dedicated to small objects [Ammari et al., 2014] able to capture the electric response of big objects (typically objects whose size is about the one half of the robot length < 10cm). The principal contribution consists in the development of a multi-scale exhaustive search algorithm based on this tensor that allows to estimate in a same step the localization, orientation and shape of an object from electric currents measured along a given trajectory close to the object. Over 108 experiments, our method shows good results as on average we obtained 18% of shape error, 25° of orientation error and 1cm of localization error within a range of [5, 11]cm distance with the robot. These results are promising since the problem solved is known to be complex localization and shape being intricately linked in the electrical measurements [Rasnow, 1996].

Reading Difference in Identity: Lacanian Reasoning in Paul Auster’s Invisible

The prevailing motifs of Auster’s literary oeuvre such as chance, contingent events, writing and the binary opposition of reader and author are also noticeable in Paul Auster’s Invisible; however, in this article, we examine the novel in terms of the characters’ psychological attempts to form their different identifications within Lacanian theoretical framework. Born acts as both reified big Other and object petit a for Walker, while Walker, in his different encounters with Born, experiences disparate Zizekian parallax views. Holding such views, Walker stands in the middle of the various courses of subjectivities, thereby undergoing a complicated interwoven subjectivity. Furthermore, Born’s encounters with the Real, epitomized in Born, place him in the two concurrent positions of subjectivities both in the Imaginary and the Symbolic order. As a result, his constant Symbolic identifications with signifying traits of Born’s bring him nothing but an aporia of logical perplexities. Last but not the least, we emphasize that the fluctuation between lost object and the loss itself, as an object, plums the depth of the anxieties embedded in such interwoven subjectivity.

Enhancement of the Detection for Intelligent Vehicle Systems - Case Rain/Snow

Intelligent vehicle systems based on vision clearly have remarkably progressed. However, they still suffer from the degradation of results quality in case of unfavorable acquisition conditions as fog, rain, and snow. Few works, where the aim is to enhance the visibility and reduce the effect of weather conditions like rain and snow, can be quoted in the context of intelligent vehicle systems. In this work, the authors established a method to enhance vehicles detection, in case of rain/snow. This method gathers a succession of phases: the extraction of the characteristics of Gaussian susceptible fields -type Gaussian -, the separation of these characteristics in two objects classes according to the criteria of the area, the modeling of the small area in a form of ellipses where one of those parameters ‘orientation’ was exploited, the distinction between the small objects that represent rain / snow and those that represent the rest of details of big objects based on probability laws, the elimination of small objects representing rain/snow and the exploitation of the big objects for the detection of vehicles. This detection enhancement method allowed a considerable increase in the detection rate.

Robotic AM System for Plastic Materials: Tuning and On-line Adjustment of Process Parameters

Additive Manufacturing (AM) techniques based on thermoplastic polymer extrusion allow the manufacture of complex parts, but their slow printing speed limits their use for mass production. To overcome this drawback, an industrial screw-based extruder has been mounted on an anthropomorphic robot, realizing a flexible AM platform for big objects. The most important process parameters have been set by a suitable experimental campaign, ensuring a regular deposited layer geometry. A closed-loop control has been implemented to further improve the process parameter setting based on data measured during the deposition, in this way compensating the material withdrawal or other unexpected defects.

The HURRA filter: An easy method to eliminate collimator artifacts in high-energy gamma camera images

PurposeThe correct determination and delineation of tumor/organ size is crucial in 2-D imaging in 131I therapy. These images are usually obtained using a system composed of a Gamma camera and high-energy collimator, although the system can produce artifacts in the image. This article analyses these artifacts and describes a correction filter that can eliminate those collimator artifacts. MethodsUsing free software, ImageJ, a central profile in the image is obtained and analyzed. Two components can be seen in the fluctuation of the profile: one associated with the stochastic nature of the radiation, plus electronic noise and the other periodically across the position in space due to the collimator. These frequencies are analytically obtained and compared with the frequencies in the Fourier transform of the profile. A specially developed filter removes the artifacts in the 2D Fourier transform of the DICOM image. This filter is tested using a 15-cm-diameter Petri dish with 131I radioactive water (big object size) image, a 131I clinical pill (small object size) image, and an image of the remainder of the lesion of two patients treated with 3.7GBq (100mCi), and 4.44GBq (120mCi) of 131I, respectively, after thyroidectomy. ResultsThe artifact is due to the hexagonal periodic structure of the collimator. The use of the filter on large-sized images reduces the fluctuation by 5.8–3.5%. In small-sized images, the FWHM can be determined in the filtered image, while this is impossible in the unfiltered image. The definition of tumor boundary and the visualization of the activity distribution inside patient lesions improve drastically when the filter is applied to the corresponding images obtained with HE gamma camera. ConclusionThe HURRA filter removes the artifact of high-energy collimator artifacts in planar images obtained with a Gamma camera without reducing the image resolution. It can be applied in any study of patient quantification because the number of counts remains invariant. The filter makes possible the definition and delimitation of small uptakes, such as those presented in treatments with 131I.

Ring formation around giant planets by tidal disruption of a single passing large Kuiper belt object

The origin of rings around giant planets remains elusive. Saturn’s rings are massive and made of 90–95% of water ice with a mass of ∼1019 kg. In contrast, the much less massive rings of Uranus and Neptune are dark and likely to have higher rock fraction. According to the so-called “Nice model”, at the time of the Late Heavy Bombardment, giant planets could have experienced a significant number of close encounters with bodies scattered from the primordial Kuiper Belt. This belt could have been massive in the past and may have contained a larger number of big objects (Mbody=1022 kg) than what is currently observed in the Kuiper Belt. Here we investigate, for the first time, the tidal disruption of a passing object, including the subsequent formation of planetary rings. First, we perform SPH simulations of the tidal destruction of big differentiated objects (Mbody=1021 and 1023 kg) that experience close encounters with Saturn or Uranus. We find that about 0.1–10% of the mass of the passing body is gravitationally captured around the planet. However, these fragments are initially big chunks and have highly eccentric orbits around the planet. In order to see their long-term evolution, we perform N-body simulations including the planet’s oblateness up to J4 starting with data obtained from the SPH simulations. Our N-body simulations show that the chunks are tidally destroyed during their next several orbits and become collections of smaller particles. Their individual orbits then start to precess incoherently around the planet’s equator, which enhances their encounter velocities on longer-term evolution, resulting in more destructive impacts. These collisions would damp their eccentricities resulting in a progressive collapse of the debris cloud into a thin equatorial and low-eccentricity ring. These high energy impacts are expected to be catastrophic enough to produce small particles. Our numerical results also show that the mass of formed rings is large enough to explain current rings including inner regular satellites around Saturn and Uranus. In the case of Uranus, a body can go deeper inside the planet’s Roche limit resulting in a more efficient capture of rocky material compared to Saturn’s case in which mostly ice is captured. Thus, our results can naturally explain the compositional difference between the rings of Saturn, Uranus and Neptune.

The HURRA filter: An easy method to eliminate collimator artifacts in high-energy gamma camera images.

The correct determination and delineation of tumor/organ size is crucial in 2-D imaging in 131I therapy. These images are usually obtained using a system composed of a Gamma camera and high-energy collimator, although the system can produce artifacts in the image. This article analyses these artifacts and describes a correction filter that can eliminate those collimator artifacts. Using free software, ImageJ, a central profile in the image is obtained and analyzed. Two components can be seen in the fluctuation of the profile: one associated with the stochastic nature of the radiation, plus electronic noise and the other periodically across the position in space due to the collimator. These frequencies are analytically obtained and compared with the frequencies in the Fourier transform of the profile. A specially developed filter removes the artifacts in the 2D Fourier transform of the DICOM image. This filter is tested using a 15-cm-diameter Petri dish with 131I radioactive water (big object size) image, a 131I clinical pill (small object size) image, and an image of the remainder of the lesion of two patients treated with 3.7GBq (100mCi), and 4.44GBq (120mCi) of 131I, respectively, after thyroidectomy. The artifact is due to the hexagonal periodic structure of the collimator. The use of the filter on large-sized images reduces the fluctuation by 5.8-3.5%. In small-sized images, the FWHM can be determined in the filtered image, while this is impossible in the unfiltered image. The definition of tumor boundary and the visualization of the activity distribution inside patient lesions improve drastically when the filter is applied to the corresponding images obtained with HE gamma camera. The HURRA filter removes the artifact of high-energy collimator artifacts in planar images obtained with a Gamma camera without reducing the image resolution. It can be applied in any study of patient quantification because the number of counts remains invariant. The filter makes possible the definition and delimitation of small uptakes, such as those presented in treatments with 131I.

Imagine a mouse and an elephant: Hemispheric asymmetries of imagination

ABSTRACTThe present study aimed to explore the existence of an asymmetrical bias in the imagination of pairs of objects of unequal size. We assumed that such pairs are conceptualized with the smaller object being placed on the left, creating an ascending size order from left to right. Such a bias could derive from a cognitive strategy known from the mental number line. Sixty-four participants were instructed to imagine stimulus-pairs that were staggered from those showing very prominent intra-pair size differences (e.g., elephant vs. mouse) to very low size differences (e.g., orange vs. apple). The results showed that the tendency to imagine the bigger object on the right side increases with the size difference of the two stimuli. Such a visual field bias was also present in stimulus-pairs including numbers so that the participants imagined smaller and larger numbers on the left and the right side of the visual fields, respectively. Taken together, our findings could imply that the left-to-right orientation observed in our object imagining task may share the same cognitive mechanism as the mental number line.

"All these places have their moments": Exploring the Micro-Geography of Music Scenes: The Indica Gallery and the Chelsea Hotel

In this article, we focus on the micro-geography of the relationship between music and place by homing in at two iconic cultural hotspots where innovative artists, notably (pop) musicians, came together in the 1960s. Because of their many famous visitors and residents, both spaces are well documented in (auto)biographies, monographs on art scenes, as well as in newspapers. We contend that the Chelsea Hotel and the Indica Gallery spaces were able to become cultural hotspots because of their location and due to the fact that these were tolerant spaces managed by people close to the artists.

Mid-level perceptual features distinguish objects of different real-world sizes.

Understanding how perceptual and conceptual representations are connected is a fundamental goal of cognitive science. Here, we focus on a broad conceptual distinction that constrains how we interact with objects--real-world size. Although there appear to be clear perceptual correlates for basic-level categories (apples look like other apples, oranges look like other oranges), the perceptual correlates of broader categorical distinctions are largely unexplored, i.e., do small objects look like other small objects? Because there are many kinds of small objects (e.g., cups, keys), there may be no reliable perceptual features that distinguish them from big objects (e.g., cars, tables). Contrary to this intuition, we demonstrated that big and small objects have reliable perceptual differences that can be extracted by early stages of visual processing. In a series of visual search studies, participants found target objects faster when the distractor objects differed in real-world size. These results held when we broadly sampled big and small objects, when we controlled for low-level features and image statistics, and when we reduced objects to texforms--unrecognizable textures that loosely preserve an object's form. However, this effect was absent when we used more basic textures. These results demonstrate that big and small objects have reliably different mid-level perceptual features, and suggest that early perceptual information about broad-category membership may influence downstream object perception, recognition, and categorization processes.

The End and Ruin of Wonderful Universe, Contemporary Science and Islamic Point of View

All the objects of the present universe-from the stars, galaxies and mountains to the atoms and the electrons are different phenomena of deep reality. The followers of materialism and those who believed in the absolute analysis of life used to call them separate and independent bodies Whereas most of the philosophers and intellectuals since the ancient times to this day, have been calling them an unbroken reality. What is the truth? Let us go towards the scientific observation first. It is easy to say in this relation, in the light of results of modern scientific researches and specially the quantum theory, that the natural phenomena are various parts of some unknown reality. Quantum mechanics reveals a wonderful fact, according to which the micro physical system of substance possesses an unseen or hidden potency that is related to the real world. Werner Heisenberg believes in nature as a supernatural and transcendent reality and calls the multidimensional objects of the universe a continuity of the same reality.(1) Thus the scientists believe in an organic whole that will lead to decline and ruin in the long run. Similarly the quantum mechanics expresses a likely outcome reality cause and effect instead of a certain one. Discontinuity and ignorance of electronic location in the biggest challenges in the wavy world of particles. .It is a fact that the destiny and the future of the material world will unveil provided that the ignorance should be replaced by learning. Casting an intellectual glance at the philosophy of creation, we find that the visible macro world came into being by the unity of invisible tiny particles. Peeping through the macro world into the micro world of atoms and by atoms, using the scientific glasses, it looks rather strange. It is so because the big universal objects work almost under the accepted scientific norms, but when we look into the inner world of those very objects, we find a haphazard and irregular world apparently on which the same universal rules and regulations of science and logic do not apply i.e. at times an electron is a wave and sometime it possess the both properties simultaneously. Moreover it jumps from place to place irregularly off and on. All such behavior of electron is called “quantum strange”. (2)

Conceptual size representation in ventral visual cortex

Recent findings suggest that visual objects may be mapped along the ventral occipitotemporal cortex according to their real-world size (Konkle and Oliva, 2012). It has been argued that such mapping does not reflect an abstract, conceptual size representation, but rather the visual or functional properties associated with small versus big real-world objects. To determine whether a more abstract conceptual size representation may affect visual cortical activation we used meaningless geometrical shapes, devoid of semantic or functional associations, which were associated with specific size representations by virtue of extensive training. Following training, participants underwent functional magnetic resonance imaging (fMRI) scanning while performing a conceptual size comparison task on the geometrical shapes. In addition, a size comparison task was conducted for numeral digits denoting small and big numbers. A region-of-interest analysis revealed larger blood oxygenation level dependent (BOLD) responses for conceptually ‘big’ than for conceptually ‘small’ shapes, as well as for big versus small numbers, within medial (parahippocampal place area, PPA) and lateral (occipital place area, OPA) place-selective regions. Processing of the ‘big’ visual shapes further elicited enhanced activation in early visual cortex, possibly reflecting top-down projections from PPA. By using arbitrary shapes and numbers we minimized visual, categorical, or functional influences on fMRI measurement, providing evidence for a possible neural mechanism underlying the representation of abstract conceptual size within the ventral visual stream.

High-speed Digital Image Correlation as a Tool for 3D Motion Analysis of Mechanical Systems

The contribution deals with the use of high-speed digital image correlation in a measurement and motion analysis of relatively big objects such as robots or manipulators. Digital image correlation method is an optic non-contact technique, which can be used in a wide range of applications in experimental mechanics. This method uses two precise CCD cameras for measuring. Cameras are usually placed stereoscopically, what allows to determine displacements and deformations in 3D space. In this contribution the theoretical basis of this method as well as the practical aspects concerning high-speed measurements are contained. As an example the experimental measurement of the motion of manipulator arm is mentioned. The output of the measurement is in the form of trajectories of its investigated points and the displacements of oscillation as well.

NoSQL technologies for the CMS Conditions Database

With the restart of the LHC in 2015, the growth of the CMS Conditions dataset will continue, therefore the need of consistent and highly available access to the Conditions makes a great cause to revisit different aspects of the current data storage solutions.We present a study of alternative data storage backends for the Conditions Databases, by evaluating some of the most popular NoSQL databases to support a key-value representation of the CMS Conditions. The definition of the database infrastructure is based on the need of storing the conditions as BLOBs. Because of this, each condition can reach the size that may require special treatment (splitting) in these NoSQL databases. As big binary objects may be problematic in several database systems, and also to give an accurate baseline, a testing framework extension was implemented to measure the characteristics of the handling of arbitrary binary data in these databases. Based on the evaluation, prototypes of a document store, using a column-oriented and plain key-value store, are deployed. An adaption layer to access the backends in the CMS Offline software was developed to provide transparent support for these NoSQL databases in the CMS context. Additional data modelling approaches and considerations in the software layer, deployment and automatization of the databases are also covered in the research. In this paper we present the results of the evaluation as well as a performance comparison of the prototypes studied.

Quantum Revolution and Rethinking the “Eternal Truths” of the Economic Science

Abstract Quantum physics requires a rethinking of basic postulates of economic science. The article presents the fundamental ideas of the hypothesis theory “The economy of creative imagination”. Also, it identifies the reevaluation methods of mechanistic economic paradigms that were formulated through analogy with classical mechanics. The paper shows that the economic process is performed at two levels - first in individual imagination, and then in traditional workshops and factories. In individual’s imagination, real goods are “truly created” at the subatomic level. As determinism principle dominates big material objects and the uncertainty principle operates at the quantum level, the author believes that rethinking the economic science refers primarily to the discovery of laws that enable us to predict the evolution of economic phenomena within the limitations imposed by the uncertainty principle.

A data-oriented profiler to assist in data partitioning and distribution for heterogeneous memory in HPC

We describe the key details of our data-oriented extensions to the Callgrind profiler.We introduce a novel technique for data partitioning targeting performance.We demonstrate the applicability of our methodology based on cache miss histograms.We showcase the potential benefits of our proposal. Profiling is of great assistance in understanding and optimizing an application's behavior. Today's profiling techniques help developers focus on the pieces of code leading to the highest penalties according to a given performance metric. In this paper we describe a profiling tool we have developed by extending the Valgrind framework and one of its tools: Callgrind. Our extended profiling tool provides new object-differentiated profiling capabilities that help software developers and hardware designers (1) understand access patterns, (2) identify unexpected access patterns, and (3) determine whether a particular memory object is consistently featuring a troublesome access pattern. We use this tool to assist in the partition of big data objects so that smaller portions of them can be placed in small, fast memory subsystems of heterogeneous memory systems such as scratchpad memories. We showcase the potential benefits of this technique by means of the XSBench miniapplication from the CESAR codesign project. The benefits include being able to identify the optimal portion of data to be placed in a small scratchpad memory, leading to more than 19% performance improvement, compared with nonassisted partitioning approaches, in our proposed scratchpad-equipped compute node.

Personal Spaces in Public Repositories as a Facilitator for Open Educational Resource Usage

Learning object repositories are a shared, open and public space; however, the possibility and ability of personal expression in an open, global, public space is crucial. The aim of this study is to explore personal spaces in a big learning object repository as a facilitator for adoption of Open Educational Resources (OERs) into teaching practices and to gain more insight into different types of OER user behaviors by analyzing the users' behaviors in the Bookmark Collection of MERLOT (a personal space, formerly known as Personal Collection), along with other community activities in that repository: writing comments and peer reviews, as well as sharing learning materials, learning exercises, and contents that were built with the content builder. In addition, using a data mining methodology, most active Bookmark Collection contributors (N=507) were classified into clusters of users with the same patterns of activity. Three clusters resulted, which gave insights into different types of contributor behavior. Furthermore, it was found that personal spaces are applicable for a variety of uses with diverse goals. Members create personal spaces for their own use, while allowing others to view and copy; or for other users. Personal space encourages the reuse of learning materials and enables the construction of unique learning processes that suit the learner's needs. They may offer the possibility of personalizing public repositories and promoting the reuse of OERs.

Fast, multicore-scalable, low-fragmentation memory allocation through large virtual memory and global data structures

We demonstrate that general-purpose memory allocation involving many threads on many cores can be done with high performance, multicore scalability, and low memory consumption. For this purpose, we have designed and implemented scalloc, a concurrent allocator that generally performs and scales in our experiments better than other allocators while using less memory, and is still competitive otherwise. The main ideas behind the design of scalloc are: uniform treatment of small and big objects through so-called virtual spans, efficiently and effectively reclaiming free memory through fast and scalable global data structures, and constant-time (modulo synchronization) allocation and deallocation operations that trade off memory reuse and spatial locality without being subject to false sharing.