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We present an approach for propagation of user interests in ontology- based user models taking into account the properties declared for the concepts in the ontology. Starting from initial user feedback on an object, we calculate user interest in this particular object and its properties and further propagate user interest to other objects in the ontology, similar or related to the initial object. The similarity and relatedness of objects depends on the number of properties they have in common and their corresponding values. The approach we propose can support finer recommendation modalities, considering the user interest in the objects, as well as in singular properties of objects in the recommendation process. We tested our approach for interest propagation with a real adaptive application and obtained an improvement with respect to IS-A-propagation of interest values.

presented at WoLLIC 2012, 15 pages; International audience; We give an algebraic characterization of the syntax and semantics of a class of simply-typed languages, such as the language PCF: we characterize simply-typed binding syntax equipped with reduction rules via a universal property, namely as the initial object of some category. For this purpose, we employ techniques developed in two previous works: in [2], we model syntactic translations between languages over different sets of types as initial morphisms in a category of models. In [1], we characterize untyped syntax with reduction rules as initial object in a category of models. In the present work, we show that those techniques are modular enough to be combined: we thus characterize simply-typed syntax with reduction rules as initial object in a category. The universal property yields an operator which allows to specify translations - that are semantically faithful by construction - between languages over possibly different sets of types. We specify a language by a 2-signature, that is, a signature on two levels: the syntactic level specifies the types and terms of the language, and associates a type to each term. The semantic level specifies, through inequations, reduction rules on the terms of the language. To any given 2-signature we associate a category of models. We prove that this category has an initial object, which integrates the types and terms freely generated by the 2-signature, and the reduction relation on those terms generated by the given inequations. We call this object the (programming) language generated by the 2-signature. [1] Ahrens, B.: Modules over relative monads for syntax and semantics (2011), arXiv:1107.5252, to be published in Math. Struct. in Comp. Science [2] Ahrens, B.: Extended Initiality for Typed Abstract Syntax. Logical Methods in Computer Science 8(2), 1-35 (2012)

Mathematical simulation of the process of self-compaction in mixtures replaces the initial object by its mathematical “copy,” and a dialog with the copy gives a general picture of the effect of multiple parameters on the processes of filtration moisture transfer and self-compaction in the mixtures and a description of the relations between the parameters, which allows the investigator to solve practical problems and recommend manufacturing parameters.

The aim of this note is to study the L-fuzzy subgroups through categorial methods. For this we construct the category G (L) whose objects are L-fuzzy subgroups and whose morphisms are L-admissible homomorphisms. By applying certain conditions we obtain the sub-categories G 1 (L) , G 2 (L) , G N (L) and G com (L) of the category G (L) . We observe that these categories are complete.

Let $A$ and $B$ be commutative rings with identity. An {\it $A$-$B$-biring} is an $A$-algebra $S$ together with a lift of the functor $Hom_A(S,-)$ from $A$-algebras to sets to a functor from $A$-algebras to $B$-algebras. An {\it $A$-plethory} is a monoid object in the monoidal category, equipped with the composition product, of $A$-$A$-birings. The polynomial ring $A[X]$ is an initial object in the category of such structures. The $D$-algebra $Int(D)$ has such a structure if $D = A$ is a domain such that the natural $D$-algebra homomorphism $\theta_n: {\bigotimes_D}_{i = 1}^n Int(D) \longrightarrow Int(D^n)$ is an isomorphism for $n = 2$ and injective for $n \leq 4$. This holds in particular if $\theta_n$ is an isomorphism for all $n$, which in turn holds, for example, if $D$ is a Krull domain or more generally a TV PVMD. In these cases we also examine properties of the functor $Hom_D(Int(D),-)$ from $D$-algebras to $D$-algebras, which we hope to show is a new object worthy of investigation in the theory of integer-valued polynomials., Comment: 8 pages

We give an algebraic characterization of the syntax and semantics of a class of languages with variable binding. We introduce a notion of 2-signature: such a signature specifies not only the terms of a language, but also reduction rules on those terms. To any 2-signature $S$ we associate a category of "models" of $S$. This category has an initial object, which integrates the terms freely generated by $S$, and which is equipped with reductions according to the inequations given in $S$. We call this initial object the language generated by $S$. Models of a 2--signature are built from relative monads and modules over such monads. Through the use of monads, the models---and in particular, the initial model---come equipped with a substitution operation that is compatible with reduction in a suitable sense. The initiality theorem is formalized in the proof assistant Coq, yielding a machinery which, when fed with a 2-signature, provides the associated programming language with reduction relation and certified substitution., v2: - Abstract and Introduction completely rewritten - Addition of examples and remarks in Secs. 1 and 2 - Sec 3 now describes the implementation in proof assistant Coq of the main theorem v3: - final version for publication in MSCS

Initial Semantics aims at interpreting the syntax associated to a signature as the initial object of some category of 'models', yielding induction and recursion principles for abstract syntax. Zsid\'o proves an initiality result for simply-typed syntax: given a signature S, the abstract syntax associated to S constitutes the initial object in a category of models of S in monads. However, the iteration principle her theorem provides only accounts for translations between two languages over a fixed set of object types. We generalize Zsid\'o's notion of model such that object types may vary, yielding a larger category, while preserving initiality of the syntax therein. Thus we obtain an extended initiality theorem for typed abstract syntax, in which translations between terms over different types can be specified via the associated category-theoretic iteration operator as an initial morphism. Our definitions ensure that translations specified via initiality are type-safe, i.e. compatible with the typing in the source and target language in the obvious sense. Our main example is given via the propositions-as-types paradigm: we specify propositions and inference rules of classical and intuitionistic propositional logics through their respective typed signatures. Afterwards we use the category--theoretic iteration operator to specify a double negation translation from the former to the latter. A second example is given by the signature of PCF. For this particular case, we formalize the theorem in the proof assistant Coq. Afterwards we specify, via the category-theoretic iteration operator, translations from PCF to the untyped lambda calculus.

One might assume that familiarity with a scene or previous encounters with objects embedded in a scene would benefit subsequent search for those items. However, in a series of experiments we show that this is not the case: When participants were asked to subsequently search for multiple objects in the same scene, search performance remained essentially unchanged over the course of searches despite increasing scene familiarity. Similarly, looking at target objects during previews, which included letter search, 30 seconds of free viewing, or even 30 seconds of memorizing a scene, also did not benefit search for the same objects later on. However, when the same object was searched for again memory for the previous search was capable of producing very substantial speeding of search despite many different intervening searches. This was especially the case when the previous search engagement had been active rather than supported by a cue. While these search benefits speak to the strength of memory-guided search when the same search target is repeated, the lack of memory guidance during initial object searches – despite previous encounters with the target objects - demonstrates the dominance of guidance by generic scene knowledge in real-world search.

Man-made environments are abundant with planar surfaces which have attractive properties for robotics manipulation tasks and are a prerequisite for a variety of vision tasks. This work presents automatic on-line 3D object model acquisition assuming a robot to manipulate the object. Objects are represented with piecewise planar surfaces in a spatio-temporal graph. Planes once detected as homographies are tracked and serve as priors in subsequent images. After reconstruction of the planes the 3D motion is analyzed and initial object hypotheses are created. In case planes start moving independently a split event is triggered, the spatio-temporal object graph is traced back and visible planes as well as occluded planes are assigned to the most probable split object. The novelty of this framework is to formalize Multi-body Structure-and-Motion (MSaM), that is, to segment interest point tracks into different rigid objects and compute the multiple-view geometry of each object, with Minimal Description Length (MDL) based on model selection of planes in an incremental manner. Thus, object models are built from planes, which directly can be used for robotic manipulation.

FOOM is an integrated methodology for analysis and design of information systems, which combines the two essential software-engineering paradigms: the functional- (or process-) oriented approach and the object-oriented (OO) approach. In FOOM, system analysis includes both functional and data modeling activities, thereby producing both a functional model and a data model. These activities can be performed either by starting with functional analysis and continuing with data modeling, or vice versa. FOOM products of the analysis phase include: a) a hierarchy of OO-DFDs (object-oriented data flow diagrams), and b) an initial object schema, which can be created directly from the user requirements specification or from an entity-relationship diagram (ERD) that is mapped to that object schema. System design is performed according to the OO approach. The products of the design phase include: a) a complete object schema, consisting of the classes and their relationships, attributes, and method interfaces; b) object classes for the menus, forms and reports; and c) a behavior schema, which consists of detailed descriptions of the methods and the application transactions, expressed in pseudo-code and message diagrams. The seamless transition from analysis to design is attributed to ADISSA methodology, which facilitates the design of the menus, forms and reports classes, and the system behavior schema, from DFDs and the application transactions.

An integrated system for measuring shape, color and reflection properties of 3D objects has been developed along with the methodology for creating a surface model with intrinsic visual properties assigned locally to that surface. We present a processing path for 3D reconstruction by means of the available 3D printing technology, together with an application optimized for viewing virtual models in realistic conditions. To show examples of data processing at successive stages we provide images and screenshots of digitally processed real cultural heritage objects (CHO). To show the process of model retrieval as a whole, we provide the final comparison of input and output data, i.e. the initial object and the final reconstruction - both printed and virtual model. We provide the overall evaluation of methodology used.

Object shape representation is an important issue in pattern recognition and computer vision applications. A set of new polygonal approximation schemes, namely, the internal maximum area polygonal approximation (IMAPA), the external minimum area polygonal approximation (EMAPA), and the minimum area deviation polygonal approximation (MADPA), are proposed for object shape representation. The area deviation between the initial object shape and its approximation polygon is defined as the cost function. Instead of outputting a unique approximation polygon, each proposed scheme outputs a sequence of approximation polygons with different numbers of line segments and different area deviations for various application situations. For a given area deviation bound and an initial object shape, each proposed scheme can give a corresponding “optimal” approximation polygon with a minimum number of line segments. A performance comparison among the proposed schemes is included. The proposed schemes are compared with two other existing schemes. Some experimental results show the feasibility of the proposed approaches.

Local variables in imperative languages have been given denotational semantics in at least two fundamentally different ways. One is by use of functor categories, focusing on the idea of possible worlds. The other might be termed event-based, exemplified by Reddy's object spaces and models based on game semantics. O'Hearn and Reddy have related the two approaches by giving functor category models whose worlds are object spaces, then showing that their model is fully abstract for Idealised Algol programs up to order two. But the category of object spaces is not small, and so in order to construct a functor category that is locally small, and hence Cartesian closed, they need to work with a restricted collection of object spaces. This weakens the connection between the object spaces model and the functor-category model: the Yoneda embedding no longer provides a full embedding of the original category of object spaces into the functor-category. Moreoever the choice of the restricted collection of object spaces is ad hoc. In this paper, we refine the approach by proving that the finite objects form a small dense subcategory of a simplified object-spaces model. The functor category over these finite objects is therefore locally small and Cartesian closed, and contains the object-spaces category as a full subcategory. All this work is necessarily enriched in Cpo. We further refine their full abstraction result by showing that full abstraction fails at order three.

Runtime architecture is important because it helps reason about quality attributes such as performance and security. We conducted an on-site field study to help us understand how developers understand object relationships, and what tool features a developer might need to convey their mental model of object relationships.The subject of our study was an experienced, professional programmer. We asked the developer questions to check if he understood which tiers objects belonged to, and whether certain objects were conceptually part of other objects. We also took an initial runtime architecture and refined it to convey his intent. The developer's mental model seemed to agree with the one supported by the current, batch-oriented approach for extracting architectures.This indicates that an interactive tool that allows making an object conceptually part of another, and abstracting away a low-level object would be useful to iteratively refine an initial object model.

This paper introduces an initial object architecture and prototype for the flexible, hybrid genetic-neural processing environment called ELYSE, the Evolving, Life-like Yielding, Symbiotic Environment. This architecture will allow the system to dynamically adapt its structure as it evolves and learns more about the types of environments it must deal with. The architecture accommodates a variety of memory classes and algorithm methods. The basic building blocks of ELYSE, the fuzzy, genetic perceptron, may be added or deleted from the system, depending on the complexity of the classes of information the system must process. Presented will be a theoretical description of dynamic adaptation along with the object architecture and high-level requirements for the system.

Both explicit analysis and FEM numerical simulation are used to analyze the field distribution of a line current in the so-called Maxwell's fish eye lens [bounded with a perfectly electrical conductor (PEC) boundary]. We show that such a 2D Maxwell's fish eye lens cannot give perfect imaging due to the fact that high order modes of the object field can hardly reach the image point in Maxwell's fish eye lens. If only zeroth order mode is excited, a good image of a sharp object may be achieved in some cases, however, its spot-size is larger than the spot size of the initial object field. The image resolution is determined by the field spot size of the image corresponding to the zeroth order component of the object field. Our explicit analysis consists very well with the FEM results for a fish eye lens. Time-domain simulation is also given to verify our conclusion. Multi-point images for a single object point are also demonstrated., Comment: This article has been published on Progress In Electromagnetics Research(PIER): F. Sun and S. He, "Can maxwell's fish eye lens really give perfect imaging?," Progress In Electromagnetics Research, Vol. 108, 307-322, 2010. Web-link: http://www.jpier.org/PIER/pier.php?paper=10091003 The former version of this article is 1009.2814

In the case of cluttered backgrounds or low quality video input, automatic video object segmentation based on spatial-temporal information is still a problem without a general solution. A new approach is introduced in this work to deal with this problem by using depth information. The proposed approach obtains the initial object masks based on depth density image and motion segmentation. The objects boundaries are obtained by updating object masks using a simultaneous combination of multiple cues, including spatial location, colour, depth and motion, within a maximum likelihood method. The experimental result shows that this method is effective and has good output in cluttered backgrounds.

For every closed model category with zero object, Quillen gave the construction of Eckman-Hilton and Puppe sequences. In this paper, we remove the hypothesis of the existence of zero object and construct (using the category over the initial object or the category under the final object) these sequences for unpointed model categories. We illustrate the power of this result in abstract homotopy theory given some interesting applications to group cohomology and exterior homotopy groups.

In a previous paper, we investigated the relation between the initial algebra and terminal coalgebra for an endofunctor on the category of sets. In this one we study conditions on a functor to be algebraically compact, which means that the canonical comparison morphism between those objects is an isomorphism.

In this paper, a new algorithm to segment object from a pair of stereo images is presented. First, we matched every pixel in corresponding scan line pairs using a one-dimensional window, obtained the disparity map and initial object segmentation mask. Second, constructed complete and reliable background region from the accumulated frames by using background statistical technology. As compared with current frame to segmented the accurate target object mask. Then a post-processing was applied to remove noise and smooth the object boundary of segmentation mask, thus we obtained the object. The algorithm does not need to know the shape and number of motion objects beforehand, and it can separate objects from stationary and complex background. The experiment shows that this algorithm has certain practicality.

Participants lifted a canister by its handle while balancing a ball on the lid. Experiment 1 allowed object rotation prior to lifting. A lifting comfort zone was measured by the variability in object orientation at lift; its size depended on the object mass and required task precision. The amount of pre-lift rotation correlated with the resulting change in lifting capability, as measured for different object orientations. Experiment 2 required direct grasping, without preparatory rotation. Task completion time and success rate decreased, and initial object orientation affected pre-lift time. Results suggest that lifting from the comfort zone produces more robust performance at a cost of slower completion; moreover, physical rotation could be replaced by mental planning when direct grasping is enforced.

Object segmentation and tracking are important techniques in video applications. In this paper, we present a novel system for active contour tracking of moving objects in video sequences. Our method includes preprocessing to identify an initial object contour, and object contour segmentation to refine the contour of the moving object. The edge flows and ant colony optimization are incorporated to improve the efficiency during system convergence. Experimental results demonstrated that our system has achieved the automatic segmentation accuracy of < 1 pixel on average as compared with manual segmentation results. In summary, our system is particularly useful in segmenting and tracking a moving object without constructing a background model for a video scene. Ultimately, our system could be used in object-based video coding or other analysis such as behavior analysis in video surveillance systems.

Conditions on a categoryC are studied which imply that every structure of rectangular band on an objectS ofC arises from a unique product decompositionS=S1×S2, especially in the case whereC is the opposite of a category of algebras.

In this paper, a novel and simple approach for tracking the object pose, position and orientation, using two object points when the object is rotated about one of the axes of the reference coordinate system is presented. The object rotation angle can be tracked up to a range of 180? for object rotations around each axis of the reference coordinate system from an initial object situation. The considered two object points are arbitrary points of the object which can be uniquely identified in stereo images. Since the approach requires only two object points, it is advantageous for the robotic applications where very few feature points can be obtained because of lack of pattern information on the objects. The paper also presents the results for the pose estimation of a meal tray in a rehabilitation robotics environment.

In this paper we want to investigate two notions of the cardinality of relations in the context of allegories. The different axiom systems are motivated on the existence of injective and surjective functions, respectively. In both cases we provide a canonical cardinality function and show that it is initial in the category of all cardinality functions over the given allegory.

International audience; In this paper, we present an algorithm for computing efficiently homology generators of 3D subdivided orientable objects which can contain tunnels and cavities. Starting with an initial subdivision, represented with a generalized map where every cell is a topological ball, the number of cells is reduced using simplification operations (removal of cells), while preserving homology. We obtain a minimal representation which is homologous to the initial object. A set of homology generators is then directly deduced on the simplified 3D object.

Our objective was to study changes in EEG time-domain power spectral density (PSDt) and localization of language areas during covert object naming tasks in human subjects with epilepsy. EEG data for subjects with epilepsy were acquired during the covert object naming tasks using a net of 256 electrodes. The trials required each subject to provide the names of common objects presented every 4 seconds on slides. Each trial comprised the 1.0 second before and 3.0 seconds after initial object presentation. PSDt values at baseline and during tasks were calculated in the theta, alpha, beta, low gamma, and high gamma bands. The spatial contour plots reveal that PSDt values during object naming were 10-20% higher than the baseline values for different bands. Language was lateralized to left frontal or temporal areas. In all cases, the Wada test disclosed language lateralization to the left hemisphere as well.

In this paper we present an approach for probabilistic contour prediction in an object tracking system. We combine level-set methods for image segmentation with optical flow estimations based on probability distribution functions (pdf's) calculated at each image position. Unlike most recent level-set methods that consider exclusively the sign of the level-set function to determine an object and its background, we introduce a novel interpretation of the value of the level-set function that reflects the confidence in the contour. To this end, in a sequence of consecutive images, the contour of an object is transformed according to the optical flow estimation and used as the initial object hypothesis in the following image. The values of the initial level-set function are set according to the optical flow pdf's and thus provide an opportunity to incorporate the uncertainties of the optical flow estimation in the object contour prediction.

Starting from an nDgeometrical object, a cellular subdivision of such an object provides an algebraic counterpart from which homology information can be computed. In this paper, we develop a process to drastically reduce the amount of data that represent the original object, with the purpose of a subsequent homology computation. The technique applied is based on the construction of a sequence of elementary chain homotopies (integral operators) which algebraically connect the initial object with a simplified one with the same homological information than the former.

Humans exhibit a rich set of manipulation strategies that may be desirable to mimic in humanoid robots. This study investigates preparatory object rotation as a manipulation strategy for grasping objects from different presented orientations. First, we examine how humans use preparatory rotation as a grasping strategy for lifting heavy objects with handles. We used motion capture to record human manipulation examples of 10 participants grasping objects under different task constraints. When sliding contact of the object on the surface was permitted, participants used preparatory rotation to first adjust the object handle to a desired orientation before grasping to lift the object from the surface. Analysis of the human examples suggests that humans may use preparatory object rotation in order to reuse a particular type of grasp in a specific capture region or to decrease the joint torques required to maintain the lifting pose. Second, we designed a preparatory rotation strategy for an anthropomorphic robot manipulator as a method of extending the capture region of a specific grasp prototype. The strategy was implemented as a sequence of two open-loop actions mimicking the human motion: a preparatory rotation action followed by a grasping action. The grasping action alone can only successfully lift the object from a 45-degree region of initial orientations (4 of 24 tested conditions). Our empirical evaluation of the robot preparatory rotation shows that even using a simple open-loop rotation action enables the reuse of the grasping action for a 360-degree capture region of initial object orientations (24 of 24 tested conditions).

Suggested in this paper is the new model of structure and dynamics of pure water. It is supported by complex dielectric permittivity and absorption data within the whole range of polarization orientation. This model is generalized to the aqueous electrolyte and nonelectrolyte solutions.The structural specification of mm frequency band is established. The primary target of mm emission is proposed.

This paper presents a learning-based algorithm for object tracking. During on-line learning we employ most informative and hard to classify examples, features maximizing individually the mutual information, stable object features within all past observations and features from the initial object template. The object undergoing tracking is discriminated criminated by a boosted classifier built on regression stumps. We seek mode in the confidence map calculated by the strong classifier to sample new features. In a supplementing tracker based upon a particle filter we use a recursively updated mixture appearance model, which depicts stable structures in images seen so far, initial object appearance as well as two-frame variations. The update of slowly varying component is done using only pixels that are classified by the strong classifier as belonging to foreground. The estimates calculated by particle filter allow us to sample supplementary features for learning of the classifier. The performance of the algorithm is demonstrated on freely available test sequences. The resulting algorithm runs in real-time.

We present two ERP studies on the processing of word order variations in Japanese, a language that is suited to shedding further light on the implications of word order freedom for neurocognitive approaches to sentence comprehension. Experiment 1 used auditory presentation and revealed that initial accusative objects elicit increased processing costs in comparison to initial subjects (in the form of a transient negativity) only when followed by a prosodic boundary. A similar effect was observed using visual presentation in Experiment 2, however only for accusative but not for dative objects. These results support a relational account of word order processing, in which the costs of comprehending an object-initial word order are determined by the linearization properties of the initial object in relation to the linearization properties of possible upcoming arguments. In the absence of a prosodic boundary, the possibility for subject omission in Japanese renders it likely that the initial accusative is the only argument in the clause. Hence, no upcoming arguments are expected and no linearization problem can arise. A prosodic boundary or visual segmentation, by contrast, indicate an object-before-subject word order, thereby leading to a mismatch between argument "prominence" (e.g. in terms of thematic roles) and linear order. This mismatch is alleviated when the initial object is highly prominent itself (e.g. in the case of a dative, which can bear the higher-ranking thematic role in a two argument relation). We argue that the processing mechanism at work here can be distinguished from more general aspects of "dependency processing" in object-initial sentences Refereed/Peer-reviewed

Triangular norms or t-norms, in short, and automorphisms are very useful to fuzzy logics in the narrow sense. However, these notions are usually limited to the set [0,1]. In this paper we will consider a generalization of the t-norm notion for arbitrary bounded lattices as a category, where these generalized t-norms are the objects, and a generalization of automorphism notion as the morphism of the category. We will prove that, this category is Cartesian and a subcategory of it is Cartesian closed. We show that the usual interval t-norms can be seen as a covariant functor for that category.

This paper proposes an approach that combines selective visual attention with the Markov random field (MRF) framework for segmenting moving objects of interest in video sequences. The gray level and motion features are first extracted from the input image. Then moving regions are obtained by combining motion features with connected component labeling. The shape features of the moving regions are extracted and compared with the predefined shape features of interesting objects, and initial object mask is generated by a set of selected moving regions. Finally, MRF classification is exploited to further classify every pixel in the initial object mask into either an object or background. Experimental results demonstrate the good segmentation performance of the proposed approach.

Let Σ be a ranked set. A categorical Σ-algebra, cΣa for short, is a small category C equipped with a functor σC: C n →C, for each σ ∈ Σn, n ≥ 0. A continuous categorical Σ-algebra is a cΣa which has an initial object and all colimits of ω-chains, i.e., functors ℕ≥C; each functor σc preserves colimits of ω-chains. (ℕ is the linearly ordered set of the nonnegative integers considered as a category as usual.)

In this paper product and coproduct of CF symmetric group categories are defined based on the definition of CF symmetric group categories proposed in [1], and the definition of isomorphism between morphisms is also proposed. Based on these works, we put forward some properties of isomorphism and prove the uniqueness of product and coproduct.

We introduce the concept of strict ample sequence in a fibered triangulated category and define the stability of the objects in a triangulated category. Then we construct the moduli space of (semi) stable objects by GIT construction.

We investigate the class of unital C*-algebras that admit a unital embedding into every unital C*-algebra of real rank zero, that has no finite-dimensional quotients. We refer to a C*-algebra in this class as an initial object. We show that there are many initial objects, including for example some unital, simple, infinite-dimensional AF-algebras, the Jiang-Su algebra, and the GICAR-algebra. That the GICAR-algebra is an initial object follows from an analysis of Hausdorff moment sequences. It is shown that a dense set of Hausdorff moment sequences belong to a given dense subgroup of the real numbers, and hence that the Hausdorff moment problem can be solved (in a non-trivial way) when the moments are required to belong to an arbitrary simple dimension group (i.e., unperforated simple ordered group with the Riesz decomposition property).

We define the concept of a regular object with respect to another object in an arbitrary category. We present basic properties of regular objects and we study this concept in the special cases of abelian categories and locally finitely generated Grothendieck categories. Applications are given for categories of comodules over a coalgebra and for categories of graded modules, and a link to the theory of generalized inverses of matrices is presented. Some of the techniques we use are new, since dealing with arbitrary categories allows us to pass to the dual category.

In this paper we use a priori information in the object domain to reconstruct the object from the partly available spectrum. Basically, when a priori information consists of the support constraints only, this is a well known problem [1] where an iterative IFFT/FFT is more or less efficient depending on the amount of the a prior information and relative share of the available part of the spectrum. Conceptually we use the same approach, however, we use a prior information in a more complete way by using the object distribution function and not only the constrains in the object domain. This, soft approach, compared with a classical (hard) approach, contributes both in the increased speed of the convergence as well as in the total gain obtained at the end of iterations. Total gain and convergence speed in the soft approach depend on the preliminary object and generally increase with amount of the a priori information included in the initial step that defines an initial object.

We prove that every stable, combinatorial model category has a natural enrichment by symmetric spectra (or more precisely, a natural equivalence class of enrichments). This in some sense generalizes the simplicial enrichments of model categories provided by the Dwyer-Kan hammock localization. As one particular application, we are able to associate to every object of a stable, combinatorial model category a "homotopy endomorphism ring spectrum". The homotopy types of these ring spectra are preserved by Quillen equivalences, and so are an invariant for stable model categories.

This paper describes some experiments in using algebraic and categorical ideas to write programs. In particular a program to compute colimits in a category given coproducts and coequalisers has been written, also one to ‘lift’ such colimits to comma categories. The discussion is informal and aims to show how categorical concepts can be painlessly realised in computational practice.

The effect of the periodic object image self-restoration in Talbot's planes was experimentally studied. Comparative investigation of the image parameters in paraxial area and in side lobes of diffraction is made. The images in side lobes have more high resistance against damages of an initial object it is proved. On the basis of these investigations, mechanisms which influence to deterioration of images in paraxial area and in side lobes are offered.

International audience; While the neural bases of prehension have been extensively studied in monkeys, a few kinematic studies have examined their prehension behavior. Recently (Roy et al. 2000, 2002), we have described the kinematics of reaching and grasping in freely behaving monkeys under normal conditions by applying the high-resolution recording techniques (Optotrak system) and behavioral paradigms used in humans. Here we determined whether online movement reorganization observed in monkeys following sudden changes of either object size or location at movement onset is similar to that observed in humans. We found that changing object size led to rapid on-flight re-calibration of the different movement parameters, eventually preserving the unitary aspect of the movement with a minor time cost. By contrast, a shift in object location triggered a massive time-consuming reorganization. Re-directed movements appeared as a concatenation of two sub-movements: a first one directed to the initial object and a second one directed to the new object location. These findings first complement our earlier studies in providing further evidence of the similarities between monkey and human prehension. Second, they suggest that the two components of prehension, reaching and grasping, interact through coordination mechanisms that are more efficient to correct for size than for location perturbation. This difference may reflect a hierarchical organization in which reaching would be the subordinate of grasping in both primate species.