Frame Representation Research Articles

Frame vector multipliers for finite group representations

A frame vector (or generator) for a group representation π of a countable or finite group G on a Hilbert space H is a vector ξ∈H such that {π(g)ξ}g∈G is a Parseval frame for H. Frame vector multipliers are the unitary operators on H that map frame vectors to frame vectors. Based on a characterization of frame vectors with respect to the standard decomposition of a group representation as the direct sums of irreducible subrepresentations (with multiplicity), we obtain explicit characterizations of frame generator multipliers for two basic cases for finite group representations. With the help of these characterizations we obtain some necessary conditions of frame vector multipliers for general frame representations, and present several examples to demonstrate how these results can be used to get explicit characterizations for frame vector multipliers.

Two-bit transform using local binary pattern method for low-complexity block motion estimation

Low bit-depth representation-based motion estimation approaches have been drawing considerable attention recently, mainly because of their small hardware footprint. In this paper, a new two-bit transform using a local binary pattern (LBP) for low-complexity motion estimation is proposed. The proposed approach utilizes the LBP method to obtain two-bit representations of video frames in the binarization process. Video frames are transformed into their low bit-depth representations by the LBP and then a motion estimation process is carried out using these binary frames. A Boolean exclusive-OR operation is used to calculate the number of nonmatching points metric instead of the conventional sum of absolute differences metric in the motion estimation stage. The proposed method reduces the computational complexity, especially in the binarization stage, while improving the motion estimation accuracy compared to existing one-bit and two-bit transform-based low-complexity motion estimation approaches in the literature.

A deep semantic corpus-based approach to metaphor analysis

This paper demonstrates the fruitful application of the formalization of Conceptual Metaphor Theory, combined with metaphor constructions and computational tools to a large-scale, corpus-based approach to the study of metaphor expressions. As the case study of poverty metaphor expressions illustrates, the representation of individual metaphors and frames as parts of larger conceptual networks facilitates analyses that capture both local details and larger patterns of metaphor use. Significantly, the data suggest that the two most frequently used source domain networks in poverty metaphor expressions each support different types of inferences about poverty, its effects, and possible ways to reduce or end it.

The Interference of the Mass media in the Intercultural Dialogue during the Emergency Landings in the Mediterranean: Between Reality and Representation

The aim of the paper is to highlight the difficulties that characterise the intercultural dialogue in specific contexts and situations of emergency. The paper focuses on the interference of the mass media and their representations in the dynamics of the intercultural dialogue among emergency operators and migrants, at the borders .These aspects will be examined relating the results of the researches carried out on the mass media representations of the landings and those obtained by the participating observation in the island of Lampedusa island, during the landings and the migrants’protestes.The results show how the frames of the mass media representation in its alarmist/pietistic approach may be reiterated in the models of the intercultural dialogue between operators and migrants. Keywords: Intercultural communication; mass media, migration, frame, landingsÂ

Las posibilidades de la loa novohispana dieciochesca a través de la Relación peregrina del agua

Este artículo estudia un conjunto de seis loas representadas en carros triunfales como parte de la fiesta llevada a cabo en Querétaro en 1738, con motivo de la inauguración de su acueducto. Aunque la historiografía y la crítica de la literatura novohispana no suelen considerar este tipo de textos, se pretende demostrar que las loas escritas para carro triunfal constituyen una de las modalidades del género dramático breve loa, cercano por sus características formales y escénicas a la loa cortesana, pero con una marcada función ecfrástico-explicativa del aparato efímero que le sirve al mismo tiempo de referente alegórico y de marco físico de representación. Por otra parte, por la notable presencia de la música, el canto y el estilo recitativo, representan una muestra del proceso de musicalización al modo italiano de este género en la praxis novohispana.

Frame level sparse representation classification for speaker verification

In this paper, we analyze the application of the sparse representation of frames of the speech signal for the speaker verification. It is lately shown that Sparse Representation Classification (SRC), is promising for speaker recognition. We bring evidence that the frame level sparse representation classification resembles process of speech recognition in human sensory system. Since the recognition of different voices (noises) helps individuals to immediately distinguish between the noise and the original speech signal, a noise aware system was designed. As a principal in the sparse representation, we argued the mutual coherence of the dictionary columns, called dictionary atoms, which is not efficiently considered in the already published SRC base speaker verification researches. To suppress the mutual coherence, we use a dictionary learning method to construct a dictionary with effective atoms. Our proposed Frame Level Sparse Representation Classification (FSRC), provides new insights to the SRC based speaker verification. We demonstrate that, in the SRC based speaker verification, using a dictionary whose atoms are orthogonal can be more extensible than a dictionary whose atoms are highly correlated, and that the mutual coherence suppression is even more effective than imposing strong orthogonality on the dictionary atoms. We consider the performance of state-of-the-art speaker recognition systems and the proposed method on NIST SRE 2004 data. Experimental results show that in comparison to baseline methods, when we have enough amount of information in the registration of targets, the proposed method improves the performance of speaker verification system in noisy conditions.

Modules in process industry − A life cycle definition

The chemical and biochemical industry has to face the challenges of globalization, short product cycle times and volatile markets. Therefore, the lead time of development projects has to be shortened. Modules and module-based plant design are widely discussed to enable shorter time-to-market by reuse of engineering effort and standardization. In this paper general requirements on modules in process engineering and modules for particular applications in the chemical and biochemical industry are reviewed. This includes the impact of modules on the planning process and examples of realized modular equipment concepts. Based on this, a general terminology definition of ‘modules’ and of specific module types for the process industry is presented, whereas modules on various ‘aggregation levels’ are accounted. A ‘block representation frame’ stores information and tracks information fluxes along the whole process and plant life cycle and on different ‘realization levels’ from laboratory studies over miniplant validation to production plant design and operation.

Adaptive robust control of machining force and contour error with tool deflection using global task coordinate frame

Peripheral milling process productivity or quality can be improved by controlling either cutting force or contour error. While each means for improvement is often addressed individually, efforts to control both aspects simultaneously are less common in the literature. This article describes an approach to control both the contour error and force using an adaptive robust controller. The axes dynamic behavior and tool deflection are considered as the two major sources of error expressly considered in the control design and are embedded in a global task coordinate frame representation of contour error. The adaptive control component maintains high-performance control of both force and contour error in the presence of significant model error or external disturbances. The control approach is implemented on a three-axis machine tool for validation. Experimental results indicate that significant improvements to both contour error and force regulation have been achieved.

REPRESENTASI FRAME DALAM LATAR BELAKANG WACANA TAJUK TENTANG TERORISME

This study aims to describe the representations of frames in the backgrounds of editorials on terrorism. It uses the critical pragmatic approach combining pragmatics andcritical discourse analysis (CDA). There are three frames in the editorials on terrorism infour national dailies in Indonesia (Suara Pembaruan, Republika, Kompas, and Koran Tempo)in accordance with their ideologies (historical backgrounds and affiliations). The studyproves that the three frames are systematically represented in the backgrounds of editorialson terrorism. Suara Pembaruan, Republika, Kompas, and Koran Tempo represent their framesin their own ways. Each daily uses the background to present information or opinionsaccording to its frame.

Reading footnotes: Joe Sacco and the graphic human rights narrative

This article presents Joe Sacco’s Footnotes in Gaza (2009) as a graphic human rights narrative. It argues that the text draws on established conventions in historiography and investigative journalism to present Palestinians as human subjects in international media discourse. To do so, Sacco experiments with different strategies of documentary writing and recording and critiques the ways in which received frames of representation determine who is considered, in Judith Butler’s terms, a “grievable” life in a conflict zone. Thus while Sacco plays with fragments and footnotes, eyewitness accounts and human rights reports, he is ultimately concerned with constructing alternative “frames” for viewing, reading and recognizing lives. Footnotes in Gaza, as such, serves as an example of how the comics form can be used to enhance human rights narrative.

‘Legislative frame representation’: towards an empirical account of the deliberative systems approach

ABSTRACTThe systemic approach to deliberative democracy is an empirically underexplored topic. Since ‘classic’ micro indicators for deliberation are at loggerheads with the idea of distributed deliberation, appropriate assessment techniques for large-scale public deliberation are few and far between. This paper aims at exploring a novel pathway into the empirical translations of the deliberative systems approach, using discourse content and the representation of policy frames in the legislature. I argue that legislative frame representation (LFR) is a crucial indicator for the level of sub-systemic deliberative uptake and policy responsiveness. Next to the necessary theoretical and methodological work, the results of an explorative case study for the immigration discourse in the US and Canada are presented. The results indicate that there are considerable differences in the systems’ capacities to take up discourses from civil society and that LFR can be an important tool to explore deliberative systems empirically.

Gradient-layer feature transform for action detection and recognition

Exploring action feature representation in consecutive video frames is a basic but critical issue in the area of computer vision. This paper presents a principled technique transforming gradient-based features into coherent spatial-temporal descriptors for action detection and recognition. Specifically, Gaussian convolution based technique is first applied to extract spatial features of each image frame on gradient layer, based on which the spatial features are further processed according to the forward-backward frame difference and correspondence fusion between frames for frame sequence representation. Furthermore, region of actions is labeled via thresholding the projection of difference features in horizontal-vertical direction while action types are classified via learning the fused features. We evaluate our approach on samples from KTH, Weizmann, UCF Sports dataset and ChangeDetection.NET dataset 2014, which demonstrates its applicability and effectiveness.

Approximation property and nuclearity on mixed‐normLp, modulation and Wiener amalgam spaces

In this paper, we first prove the metric approximation property for weighted mixed-norm L (p1,...,pn) w spaces. Using Gabor frame representation, this implies that the same property holds in weighted modulation and Wiener amalgam spaces. As a consequence, Grothendieck’s theory becomes applicable, and we give criteria for nuclearity and r-nuclearity for operators acting on these spaces as well as derive the corresponding trace formulae. Finally, we apply the notion of nuclearity to functions of the harmonic oscillator on modulation spaces.

Distributed Noise-Shaping Quantization: I. Beta Duals of Finite Frames and Near-Optimal Quantization of Random Measurements

This paper introduces a new algorithm for the so-called "Analysis Problem" in quantization of finite frame representations which provides a near-optimal solution in the case of random measurements. The main contributions include the development of a general quantization framework called distributed noise-shaping, and in particular, beta duals of frames, as well as the performance analysis of beta duals in both deterministic and probabilistic settings. It is shown that for random frames, using beta duals results in near-optimally accurate reconstructions with respect to both the frame redundancy and the number of levels that the frame coefficients are quantized at. More specifically, for any frame $E$ of $m$ vectors in $\mathbb{R}^k$ except possibly from a subset of Gaussian measure exponentially small in $m$ and for any number $L \geq 2$ of quantization levels per measurement to be used to encode the unit ball in $\mathbb{R}^k$, there is an algorithmic quantization scheme and a dual frame together which guarantee a reconstruction error of at most $\sqrt{k}L^{-(1-\eta)m/k}$, where $\eta$ can be arbitrarily small for sufficiently large problems. Additional features of the proposed algorithm include low computational cost and parallel implementability.

Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging.

Compressed sensing (CS) has exhibited great potential for accelerating magnetic resonance imaging (MRI). In CS-MRI, we want to reconstruct a high-quality image from very few samples in a short time. In this paper, we propose a fast algorithm, called projected iterative soft-thresholding algorithm (pISTA), and its acceleration pFISTA for CS-MRI image reconstruction. The proposed algorithms exploit sparsity of the magnetic resonance (MR) images under the redundant representation of tight frames. We prove that pISTA and pFISTA converge to a minimizer of a convex function with a balanced tight frame sparsity formulation. The pFISTA introduces only one adjustable parameter, the step size, and we provide an explicit rule to set this parameter. Numerical experiment results demonstrate that pFISTA leads to faster convergence speeds than the state-of-art counterpart does, while achieving comparable reconstruction errors. Moreover, reconstruction errors incurred by pFISTA appear insensitive to the step size.

Sparse frame DOA estimations via a rank-one correlation model for low SNR and limited snapshots

As a typical problem of sparse frame representations or compressed sensing with frames, direction of arrival (DOA) estimations, via sparse recovery methodologies such as nonlinear optimizations or various greedy algorithms, suffer seriously under severe noisy measurement without proper treatment. In this article, a crucial and effective correlation operation is outlined to mitigate the severe noise effect from the sparse representation point of view. A fast and super resolution method for DOA estimations is therefore established under very low signal-to-noise ratio, and by a sparse recovery technique of null space tuning in the context of compressed sensing and sparse representations. Improvement to the technique using the thresholding difference and alternating grid refinements are also outlined to estimate the source/target numbers dynamically and to improve the precision. Another characteristic is that only a very small number of snapshots are needed in comparison with other techniques. Simulation results demonstrate apparent advantages of the proposed technique over known approaches. The proposed method has the effectiveness at simultaneous high resolution, robustness to noise, and source number estimations. The algorithm is also computationally efficient, which is critical for large array systems and/or mission critical real-time applications.

Why symbolic representation frames parliamentary public engagement

Research Highlights and Abstract The UK Parliament’s activity in public engagement has recently expanded considerably. Faced with declining levels of trust, it has invested considerable time and resources to new activities focusing specifically on engagement: educational resources and cultural events among many others. This embodies a new role for parliament of increasing importance particularly in the context of the 21st-century parliament. But it is an area that still requires further study, as we know little about the role performed by parliamentary public engagement. This article explores the institution’s aims in developing public engagement and reflects on the extent to which this embodies elements of symbolic representation. We utilise different theories on representation to develop a framework to understand the role played by public engagement in the 21st-century context. We then employ this perspective to analyse the aims and characteristics of public engagement activity in the UK Parliament. Besides a normative reflection on representation and engagement, our article is based on qualitative research which included elite in-depth interviews with parliamentary officials complemented by documentary analysis. Our research shows that public engagement planning in the UK Parliament aims to develop among the public a sense of connectivity that relies on more collective and symbolic forms of representation, which seek to present the institution detached from its actors and politics. The UK Parliament’s activity in public engagement has recently expanded considerably. Faced with declining levels of trust, it has invested considerable time and resources to new activities focusing specifically on engagement: educational resources and cultural events among many others. This embodies a new role for parliament of increasing importance particularly in the context of the 21st-century parliament. This article analyses the aims of public engagement and its consequences for representation. We explore the potential representative role of public engagement, identifying key changes that have affected the relationship between public and parliament. We utilise evidence from documentary analysis and elite in-depth interviews with parliamentary officials to show that public engagement planning aims to develop among the public a sense of connectivity that relies on more collective and symbolic forms of representation, which seek to present the institution detached from its actors and politics. We utilise constructivist representation theories to support our analysis.

Irrelevant frame removal for scene analysis using video hyperclique pattern and spectrum analysis

<p>Video often include frames that are irrelevant to the scenes for recording. These are mainly due to imperfect shooting, abrupt movements of camera, or unintended switching of scenes. The irrelevant frames should be removed before the semantic analysis of video scene is performed for video retrieval. An unsupervised approach for automatic removal of irrelevant frames is proposed in this paper. A novel log-spectral representation of color video frames based on Fibonacci lattice-quantization has been developed for better description of the global structures of video contents to measure similarity of video frames. Hyperclique pattern analysis, used to detect redundant data in textual analysis, is extended to extract relevant frame clusters in color videos. A new strategy using the k-nearest neighbor algorithm is developed for generating a video frame support measure and an h-confidence measure on this hyperclique pattern based analysis method. Evaluation of the proposed irrelevant video frame removal algorithm reveals promising results for datasets with irrelevant frames.</p>

How Proportional Representation Frames Pork Barrel Efforts: District Magnitude, Ballot Type and Position on the List Interactions

I focus on pork barrel efforts, i.e. legislators’ actions to seek local public goods for their constituencies. Efforts in closed-list and open-list proportional representation are better explained as the interaction of district magnitude (M) and list position. In closed-list systems efforts will be greater when M is very small and as M increases they will describe a concave distribution at the list level. In open list systems efforts increase the larger the M and for legislators elected in the closest positions to the top of the list. I test this argument using an original dataset of bills initiation in the Honduran Congress between 1990 and 2009. In 2004, Honduras shifted from closed-list to open-list while maintaining district magnitude constant.

Sparse regularization for force identification using dictionaries

The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.