Objects In Category Research Articles

The moduli space of matroids

In [3], Nathan Bowler and the first author introduced a category of algebraic objects called tracts and defined the notion of (weak and strong) matroids over a tract. In the first part of the paper, we summarize and clarify the connections to other algebraic objects which have previously been used in connection with matroid theory. For example, we show that both partial fields and hyperfields are fuzzy rings, that fuzzy rings are tracts, and that these relations are compatible with previously introduced matroid theories. We also show that fuzzy rings are ordered blueprints in the sense of the second author. Thus fuzzy rings lie in the intersection of tracts with ordered blueprints; we call the objects of this intersection idylls.We then turn our attention to constructing moduli spaces for (strong) matroids over idylls. We show that, for any non-empty finite set E, the functor taking an idyll F to the set of isomorphism classes of rank-r strong F-matroids on E is representable by an ordered blue scheme Mat(r,E). We call Mat(r,E) the moduli space of rank-r matroids on E. The construction of Mat(r,E) requires some foundational work in the theory of ordered blue schemes; in particular, we provide an analogue for ordered blue schemes of the “Proj” construction in algebraic geometry, and we show that line bundles and their global sections control maps to projective spaces, much as in the usual theory of schemes.Idylls themselves are field objects in a larger category which we call F1±-algebras; roughly speaking, idylls are to F1±-algebras as hyperfields are to hyperrings. We define matroid bundles over ordered blue F1±-schemes and show that Mat(r,E) represents the functor taking an ordered blue F1±-scheme X to the set of isomorphism classes of rank-r (strong) matroid bundles on E over X. This characterizes Mat(r,E) up to (unique) isomorphism.Finally, we investigate various connections between the space Mat(r,E) and known constructions and results in matroid theory. For example, a classical rank-r matroid M on E corresponds to a morphism Spec(K)→Mat(r,E), where K (the “Krasner hyperfield”) is the final object in the category of idylls. The image of this morphism is a point of Mat(r,E) to which we can canonically attach a residue idyll kM, which we call the universal idyll of M. We show that morphisms from the universal idyll of M to an idyll F are canonically in bijection with strong F-matroid structures on M. Although there is no corresponding moduli space in the weak setting, we also define an analogous idyll kMw which classifies weak F-matroid structures on M. We show that the unit group of kMw can be canonically identified with the Tutte group of M, originally introduced by Dress and Wenzel. We also show that the sub-idyll kMf of kMw generated by “cross-ratios”, which we call the foundation of M, parametrizes rescaling classes of weak F-matroid structures on M, and its unit group coincides with the inner Tutte group of M. As sample applications of these considerations, we show that a matroid M is regular if and only if its foundation is the regular partial field (the initial object in the category of idylls), and a non-regular matroid M is binary if and only if its foundation is the field with two elements. From this, we deduce for example a new proof of the fact that a matroid is regular if and only if it is both binary and orientable.

Many valued topologies on L-sets

Many valued topologies on L-sets, providing a common framework for fuzzy topologies on fuzzy sets and the fixed-basis lattice-valued topologies on ordinary sets, are the main subject of the present study. In this paper, we have introduced many valued topological L-set-spaces, referring to L-sets equipped with many valued topologies, in an axiomatic way and focused on the vindication of their axiomatization in a categorical framework. In order to attain this objective, we apply the theory of Höhle of topological space objects formulated in terms of a partially ordered monad on an abstract category, and show that the category of many valued topological L-set-spaces is isomorphic to the category of topological space objects with respect to a partially ordered monad on a category of L-sets.

Digital Objects of Civil Rights

The paper is devoted to the problem of digitalization of objects of civil rights. In the context of the development of the digital economy, objects are consolidated and reflected in the digital environment. Article 128 of the Civil Code of the Russian Federation sets forth the concept of digital rights. They are defined as property obligations and other rights, which does not allow them to be considered as independent new types of objects of civil rights. The category of digital rights introduced into the legislation does not cover all new objects that appear in the digital environment, which results in appearance of legal relations, in connection with which it is relevant to introduce the category of digital objects into the list of objects of civil rights as an independent type of objects of civil rights or as application of legal regimes of the named objects to new objects. For example, the categories of big data, big user data again make us think about the legal regime of information. Adhering to the understanding that information itself is not an independent type of objects of civil rights, we can conclude that information posted in the digital environment is capable of objectification as an intangible benefit (for example, personal data is an integral part of privacy, other rights enshrined in the legislation), while the owner of this information can transfer the right to use it to other persons. This right can be considered as a property (exclusive) right. The very provision of information can be objectified within the framework of services for its provision. Big data, if it does not contain personal information, can also be covered by a category of publicly available data that can be collected, analyzed, summarized by persons accessing this data legally (for example, from open sources on the Internet). In addition, the paper elucidates the problems of determining the legal regime of so-called virtual objects in the narrow sense (in-game objects, objects of virtual or augmented reality), artificial intelligence and robots created on the basis of artificial intelligence technology. In general, it is concluded that it is possible to extend to digital objects the legal regime of the named objects of civil rights with due regard to the peculiarities of their consolidation in the digital environment

Disassembling object representations without labels

In this paper, we study a new representation-learning task, which we termed as disassembling object representations. Given an image featuring multiple objects, the goal of disassembling is to acquire a latent representation, of which each part corresponds to one category of objects. Disassembling thus finds its application in a wide domain such as image editing and few- or zero-shot learning, as it enables category-specific modularity in the learned representations. To this end, we propose an unsupervised approach to achieving disassembling, named Unsupervised Disassembling Object Representation (UDOR). UDOR follows a double auto-encoder architecture, in which a fuzzy classification and an object-removing operation are imposed. The fuzzy classification constrains each part of the latent representation to encode features of up to one object category, while the object-removing, combined with a generative adversarial network, enforces the modularity of the representations and integrity of the reconstructed image. Furthermore, we devise two metrics to respectively measure the modularity of disassembled representations and the visual integrity of reconstructed images. Experimental results demonstrate that the proposed UDOR, despite unsupervised, achieves truly encouraging results on par with those of supervised methods.

Attack to Fool and Explain Deep Networks.

Deep visual models are susceptible to adversarial perturbations to inputs. Although these signals are carefully crafted, they still appear noise-like patterns to humans. This observation has led to the argument that deep visual representation is misaligned with human perception. We counter-argue by providing evidence of human-meaningful patterns in adversarial perturbations. We first propose an attack that fools a network to confuse a whole category of objects (source class) with a target label. Our attack also limits the unintended fooling by samples from non-sources classes, thereby circumscribing human-defined semantic notions for network fooling. We show that the proposed attack not only leads to the emergence of regular geometric patterns in the perturbations, but also reveals insightful information about the decision boundaries of deep models. Exploring this phenomenon further, we alter the 'adversarial' objective of our attack to use it as a tool to 'explain' deep visual representation. We show that by careful channeling and projection of the perturbations computed by our method, we can visualize a model's understanding of human-defined semantic notions. Finally, we exploit the explanability properties of our perturbations to perform image generation, inpainting and interactive image manipulation by attacking adversarialy robust 'classifiers'. In all, our major contribution is a novel pragmatic adversarial attack that is subsequently transformed into a tool to interpret the visual models. The article also makes secondary contributions in terms of establishing the utility of our attack beyond the adversarial objective with multiple interesting applications.

The dual actions, equivariant autoequivalences and stable tilting objects

Pour une catégorie linéaire munie d’une action d’un groupe abélien fini, on étudie l’action duale du groupe des caractères de ce groupe abélien sur la catégorie des objets équivariants. On montre que les groupes des auto-équivalences équivariantes de ces deux catégories sont isomorphes. Dans la situation où la catégorie linéaire est triangulée, les objets basculants stables dans ces deux catégories sont en bijection naturelle compatible avec l’isomorphisme ci-dessus. On applique ces résultats aux complexes basculants stables sur les droites projectives à poids de type tubulaire.

A Survey of Social Image Colocalization

Social image colocalization locates the objects belonging to the same category from a set of images. Its goal is to explore the consistent relationship among social entities in the social system, which is conducive to promoting the development of social scene understanding. In a social relationship, consistency is easy to be ignored but is useful for many fields, e.g., natural language processing and computer vision. The social image colocalization aims to utilize the consistent relationship to discover the objects belonging to the same category and locate them by rectangle bounding boxes. The consistency is principally reflected in the category of objects, which can be achieved by a similar appearance or a uniform structure. Currently, state-of-the-art colocalization methods mainly focus on three solving strategies: candidate region proposal selection, saliency maps-based methods, and deep descriptor transformation. In this article, we sort out several kinds of the present mainstream methods and provide a comprehensive review of their fundamentals and performance. We expect that the overview of colocalization would be helpful for the researchers who are new to this area and provide them enlightenments.

KPAM 2.0: Feedback Control for Category-Level Robotic Manipulation

In this letter, we explore generalizable, perception-to-action robotic manipulation for precise, contact-rich tasks. In particular, we contribute a framework for closed-loop robotic manipulation that automatically handles a category of objects, despite potentially unseen object instances and significant intra-category variations in shape, size and appearance. Previous approaches typically build a feedback loop on top of a realtime 6-DOF pose estimator. However, representing an object with a parameterized transformation from a fixed geometric template does not capture large intra-category shape variation. Hence we adopt the keypoint-based object representation proposed in [13] for category-level pick-and-place, and extend it to closed-loop manipulation policies with contact-rich tasks. We first augment keypoints with local orientation information. Using the oriented keypoints, we propose a novel object-centric action representation in terms of regulating the linear/angular velocity or force/torque of these oriented keypoints. This formulation is surprisingly versatile – we demonstrate that it can accomplish contact-rich manipulation tasks that require precision and dexterity for a category of objects with different shapes, sizes and appearances, such as peg-hole insertion for pegs and holes with significant shape variation and tight clearance. With the proposed object and action representation, our framework is also agnostic to the robot grasp pose and initial object configuration, making it flexible for integration and deployment. Video demonstration, source code and supplemental materials are available on https://sites.google.com/view/kpam2/home .

Software Security Requirement Engineering for Risk and Compliance Management

The objective of the research work is to propose a software based security requirement engineering model using categorical and morphisms theory. The earlier security requirement engineering models focus different viewpoints on parallel processing and develop rewrite based knowledge centred models but does not include different functional mappings between the security objects to select the best strategy. The security models have not considered the needed security functions that are to be implemented in different environments with different levels of executions. The proposed requirement engineering model is based on the formal theory of category of objects and the morphisms between them in addition to n categories and multiple morphisms that were used to organize the security requirement functional objects of different categories. The on demand security requirement objects, morphisms and the uncertain events in any one of the subsystems are considered to manage this security requirement category as an algebraic data types. The collection of security requirement objects using classification and clustering techniques are implicitly applied by the formation of category and morphism. The risk and compliances both in the form of direct and indirect categories are mapped so as to provide a security assurance functors with minimum risk on the requirements to the next design state. An ‘n’ category and ‘n’ morphic model for software security requirement model is proposed towards for minimum security risks through efficient compliance management techniques.

Software Security Requirement Engineering for Risk and Compliance Management

The objective of the research work is to propose a software based security requirement engineering model using categorical and morphisms theory. The earlier security requirement engineering models focus different viewpoints on parallel processing and develop rewrite based knowledge centred models but does not include different functional mappings between the security objects to select the best strategy. The security models have not considered the needed security functions that are to be implemented in different environments with different levels of executions. The proposed requirement engineering model is based on the formal theory of category of objects and the morphisms between them in addition to n categories and multiple morphisms that were used to organize the security requirement functional objects of different categories. The on demand security requirement objects, morphisms and the uncertain events in any one of the subsystems are considered to manage this security requirement category as an algebraic data types. The collection of security requirement objects using classification and clustering techniques are implicitly applied by the formation of category and morphism. The risk and compliances both in the form of direct and indirect categories are mapped so as to provide a security assurance functors with minimum risk on the requirements to the next design state. An ‘n’ category and ‘n’ morphic model for software security requirement model is proposed towards for minimum security risks through efficient compliance management techniques.

An efficient foreign objects detection network for power substation

A power substation is susceptible to intrusions of foreign objects. The intrusions can likely result in failures of power supplies. Therefore, recognizing foreign objects becomes important to ensure constant and stable power supplies. However, existing object recognition methods fail to achieve acceptable accuracy and performance. In this paper, we propose an efficient Foreign Objects Detection Network for Power Substation (FODN4PS) to improve the recognition accuracy with less time. FODN4PS consists of a Moving Object Region Extraction Network (MORE Net) and a classification network, where the MORE Net can get the position of foreign objects, and the classification network can recognize the category of foreign objects. Experimental results show that FODN4PS is faster and more accurate in object recognition than the Fast R-CNN and Mask R-CNN.

Analysis of fire hazard of livestock complexes for the maintenance of cattle

The article is devoted to the problems of ensuring fire safety of livestock complexes. The conducted research has established that the buildings of livestock complexes are characterized by a certain level of fire danger, and, taking into account the importance of this category of objects on the food security of the country, ensuring fire safety should be a priority.

Souvenirs from North America: Understanding and representing ‘Indianness’ in nineteenth-century Sweden

ABSTRACT Swedish museums curate numerous objects made by indigenous peoples of North America. Collected already in the seventeenth century, their numbers increased in the nineteenth and early twentieth century. While some of them were collected systematically by scientific expeditions, majority of these objects were obtained as personal mementoes. Scrutinizing examples of North American souvenirs collected in the early nineteenth century by Swedes visiting America and donated to the Lund University Historical Museum, this article explores souvenirs as a particular category of representational objects. It relates them to the early nineteenth-century popular notions of the American Indian stemming from the popular literature and investigates how these two tools of representation informed one another to create and perpetuate a stereotype of Indianness.

Cultic Inventory From the Bronze Age Settlement From Șoimuş – Teleghi (Hunedoara County)

The preventive archaeological research fulfilled on the Deva – Orăştie highway route, led us to discover a large settlement belonging to the Bronze Age, on the terrace of the Mureş River, at Şoimuş – Teleghi (Hunedoara County). Some of the investigated features from this site contain large quantity of pottery and bone artefacts. These artefacts are vessels with celestial symbolic representations, decorated hearths and portable stoves (pyraunoi) with anthropomorphic plastic applications. Among these, there are animal bones such as vertebras and phalanges, some of them processed and with intense using traces. Another category of special objects was the clay wheels models, which were found in several pits, whole or fragmentary. Despite being part of the assemblage of a clay wagon model, these items were found separately, indicating that the wheel itself had a special meaning in the imaginary of the community. We consider that all these artefacts had a special function in rituals activities and also that they were used, probably, in shamanic practices.

Typicality modulates attentional capture by object categories

What we pay attention to in the visual environment is often driven by what we know about the world. For example, a number of studies have found that observers can adopt attentional sets for a particular semantic category. However, some objects are more typical members of a category than others. While previous evidence suggests that an object's typicality can influence the guidance of attention in visual search, it is unclear whether typicality can also influence the capture of attention. To test whether this is the case, participants were given a category of objects at the beginning of each trial. Then, a rapid serial visual presentation (RSVP) stream was presented at fixation, and participants had to indicate whether an object of the given category was present or absent from the stream. Importantly, a single flanker image also appeared above or below the central stream just before the target. This flanker could belong either to the same category as the target or a different category, and could be a typical or atypical exemplar of that category. Participants were less accurate at detecting the target when the flanker belonged to the same category as the target. Moreover, participants were even less accurate when the flanker was a typical exemplar of this category. Similar findings were observed when targets consisted of typical and atypical exemplars. Together, these findings indicate that the extent of attentional capture toward a distractor depends on whether the distractor matches the category and typicality of one's attentional set.

Testing New Coatings for Outdoor Bronze Monuments: A Methodological Overview

Coatings to be used for cultural heritage protection face peculiar challenges. In the last few decades, several projects addressed the issue of new treatments in the field of copper alloy artworks. Nonetheless, no one has yet been recognised as a more acceptable solution with respect to traditional choices, with their known limits. The lack of standard methods to test new coatings that can be effectively applied to artworks make it more difficult to compare different studies and open the way to practical use in restoration. Over the years, several issues have gradually been better focused, even though they are not yet widely considered in new coatings efficacy evaluation for application on copper alloy artifacts. They are mainly linked to the quite complex surface of this category of heritage objects and the role it plays on coating effectiveness. An overview of the variety of relevant surface properties is provided (presence of corrosion products and old protective treatments, cleaning methods, surface unevenness, just to name a few) with a special focus on the role of coating performance. Some methodological choices are discussed for the selection of mock-ups, testing techniques and weathering procedures, with peculiar attention to comparison with real artworks.

Instant water body variation detection via analysis on remote sensing imagery

Water resource is one of the most valuable natural resources for human beings, which requires to be monitored for careful protection. Inspired by a significant power of machine learning methods, researchers have successfully developed many applications to automatically perform identification on the water body via analyzing remote sensing images. Since a similar category of ground objects could show a large difference in spectral representation, researchers try to propose distinctive and effective features to offer redundant information for category classification. Moreover, large amount of high-resolution remote sensing images require analyzing algorithms to be parallel processed for instant feedback. Based on these requirements, we propose a novel water body variation detection via analysis on remote sensing images. Specifically, the proposed method firstly perform pixel-level classification to locate abnormal changes with thoughts of visual word patterns. Afterwards, the proposed method proposes block division method to construct parallel running version with Mapreduce structure. With high representational and parallel running abilities, the proposed method is capable to accurately detect variation areas on remote sensing images with instant feedback. Experiments on several self-collected datasets show the proposed method has achieved better efficiencies than comparative studies.

Седельные канты из раскопанных курганов Алтая жужанского времени

Статья посвящена введению в научный оборот и разноплановой интерпретации серии костяных (роговых) седельных кантов, обнаруженных в ходе раскопок археологических комплексов Алтая жужанского времени (вторая половина IV — первая половина V в. н.э.). Данная категория предметов, как и в целом седла номадов Азиатского региона рубежа древности и Средневековья, исследована весьма слабо, что объясняется главным образом состоянием источниковой базы. Канты обнаружены в погребениях трех некрополей жужанского времени, относящихся к булан-кобинской культуре Алтая. Наиболее многочисленная коллекция таких предметов выявлена в ходе раскопок комплекса Чобурак-I. В статье приведено подробное описание этих изделий, представляющих собой собой верхние торцевые окантовки лук седел. Отмечено значительное сходство публикуемых элементов конского снаряжения с находками из памятников раннесредневековых тюрок второй половины V — начала VIII в. Вопрос о функциях седельных кантов, учитывая известную фрагментарность имеющихся материалов, пока остается открытым. Представляется возможным допустить как декоративное, так и утилитарное назначение рассматриваемых изделий.

Wooden anthropomorphic finials from mediaeval Novgorod (chronology and topography)

This paper is the first publication of the complete complex of anthropomorphic wooden finials from mediaeval Novgorod with a chronological and a topographical analysis of the finds. Also conditional variants of the representations themselves are considered. An interdisciplinary study demonstrates that this rare category of heathen cult objects was widespread in Novgorod from the 10th to 14th century without any chronological disruption. In terms of topography, the finds are mainly related with buildings that suggests their basic semantics as domestic talismans.

Blending of Learning-based Tracking and Object Detection for Monocular Camera-based Target Following

Deep learning has recently started being applied to visual tracking of generic objects in video streams. For the purposes of robotics applications, it is very important for a target tracker to recover its track if it is lost due to heavy or prolonged occlusions or motion blur of the target. We present a real-time approach which fuses a generic target tracker and object detection module with a target re-identification module. Our work focuses on improving the performance of Convolutional Recurrent Neural Network-based object trackers in cases where the object of interest belongs to the category of familiar objects. Our proposed approach is sufficiently lightweight to track objects at 85-90 FPS while attaining competitive results on challenging benchmarks.