Miracle-dz/UniFAR-FTUs huggingface dataset:
A Game-Theoretic Approach to Prioritized Transmission in Wireless CSMA/CA Networks

Support of traffic with QoS requirements in wireless scenarios is a challenging topic and methodologies for supporting different traffic priorities have recently emerged. Unfortunately in wireless scenarios, it is well known that contention problems are met. The latter can be modeled as a game. Accordingly, in this paper we present a game-theoretic model of priori- tized data transmission in CSMA/CA networks where nodes are considered as potential cheaters which should be punished through a jamming mechanism when misbehaving and trying to monopolize wireless resources. Then, we also describe the distributed algorithm to be performed by network nodes to implement the model and assess the validity of both the model and the algorithm through simulations. Index Terms: Wireless networks, QoS, game-theory, algorithms, simulation. I. I NTRODUCTION
Integrating Structured Metadata with Relational Affinity Propagation

Structured and semi-structured data describing entities, taxonomies and ontologies appears in many domains. There is a huge interest in integrating structured information from multiple sources; however integrating structured data to infer complex common structures is a difficult task because the integration must aggregate similar structures while avoiding structural inconsistencies that may appear when the data is combined. In this work, we study the integration of structured social metadata: shallow personal hierarchies specified by many individual users on the SocialWeb, and focus on inferring a collection of integrated, consistent taxonomies. We frame this task as an optimization problem with structural constraints. We propose a new inference algorithm, which we refer to as Relational Affinity Propagation (RAP) that extends affinity propagation (Frey and Dueck 2007) by introducing structural constraints. We validate the approach on a real-world social media dataset, collected from the photosharing website Flickr. Our empirical results show that our proposed approach is able to construct deeper and denser structures compared to an approach using only the standard affinity propagation algorithm.
Scaling and rotating texture classification based on JSEG algorithm

In this paper a novel algorithm is proposed for classifying variant textures resulting from scale magnification, narrowing caused by cutting into the original size, or spatial rotation. These variations usually occur in images captured by a camera using different focal distances. This study proposes a representative region-matched algorithm for improving texture classification after magnification, narrowing, and spatial rotation. The principle of a representative region-matched algorithm is to use a minimum ellipse to enclose a specific region extracted by the JSEG algorithm. After translating the coordinates, the ellipse in the rotated texture would be formulated as the ellipse in the original texture. Besides, by adopting scale invariant parameters, the scale variant representative region can be classified. Also in this paper a hybrid texture filter is proposed. In the hybrid texture filter the scheme of texture feature extraction include Gabor wavelet and the representative region matched algorithm. Support vector machines (SVMs) are introduced as the classifier. Experimental results reveal that this proposed algorithm outperforms existing design algorithms.
Saliency detection using centroid weight map

This paper presents a novel approach to compute an image saliency map using Centroid Weight map (CWM). Detection of salient image regions is useful for applications like object segmentation and tracking. We developed and tested a method to detect saliency area using 4 features which are color, intensity, Different of Gaussian (DOG), CWM. A key idea is the CWM technique which is followed with N-classes using mean-shift and pixel location variation. The scheme successfully detects saliency region compare with five state-of-the-art saliency region detection method on the 1000 MSRA benchmark database. The proposed method has achieved superior detection accuracy with both higher precision and better recall than traditional method.
Parkes H I observations of galaxies behind the southern Milky Way - II. The Crux and Great Attractor regions (l ${\approx}$ 289°to 338°)

As part of our programme to map the large-scale distribution of galaxies behind the southern Milky Way, we observed 314 optically-selected, partially-obscured galaxies in the Zone of Avoidance (ZOA) in the Crux and Great Attractor (GA) regions. An additional 29 galaxies were observed in the Vela ZOA survey region (because of the small numbers they are not discussed any further). The observations were conducted with the Parkes 64 m (210 ft) radio telescope, in a single-pixel pointed mode, reaching an rms noise level of typically 2-6 mJy over the velocity search range of 400 < u < 10 500 km s ―1 . A total of 162 galaxies were detected (plus 14 galaxies in the Vela region). The detection rate is slightly higher than for the Hydra/Antlia region (52% versus 45%) observed in the same way. This can be explained by the prominence of the GA overdensity in the survey regions, which leads to a relatively higher fraction of nearby galaxies. It is also evident from the quite narrow velocity distribution (largely confined to 3000-6000 km s ―1 ) and deviates significantly from the expectation of a uniform galaxy distribution for the given sensitivity and velocity range. No systematic differences were found between detections and non-detections, in terms of latitude, foreground extinction, or environment, except for the very central part of the rich Norma cluster, where hardly any galaxies were detected. A detailed investigation of the H I content of the galaxies reveals strong H I deficiency at the core of the Norma cluster (within about a 0.4 Abell radius), similar to what has been found in the Coma cluster. The redshifts obtained by this observing technique result in a substantial reduction of the so-called redshift ZOA. This is obvious when analysing the large-scale structure of the new HI data in combination with data from other (optical) ZOA redshift surveys. The lower latitude detections provide further evidence of the extension of the Norma Wall, across the ZOA, in particular its bending towards the Cen-Crux clusters above the Galactic plane at slightly higher redshift, rather than a straight continuation towards the Centaurus clusters.
Combining dense features with interest regions for efficient part-based image matching

One of the most popular approaches for object recognition is bag-of-words which represents an image as a histogram of the frequency of occurrence of visual words. But it has some disadvantages. Besides requiring computationally expensive geometric verification to compensate for the lack of spatial information in the representation, it is particularly unsuitable for sub-image retrieval problems because any noise, background clutter or other objects in vicinity influence the histogram representation. In our previous work, we addressed this issue by developing a novel part-based image matching framework that utilizes spatial layout of dense features within interest regions to vastly improve recognition rates for landmarks. In this paper, we improve upon the previously published recognition results by more than 12% and achieve significant reductions in computation time. A region of interest (ROI) selection strategy is proposed along with a new voting mechanism for ROIs. Also, inverse document frequency weighting is introduced in our image matching framework for both ROIs and dense features inside the ROIs. We provide experimental results for various vocabulary sizes on the benchmark Oxford 5K and INRIA Holidays datasets.
Application of Transductive Inference SVM Based Relevant Documents Acquiring in Query-Biased Summarization

There is an important issue that text summarization has to embody the personal information need and provide the indicative message for user. In this paper, a method of acquiring relevant documents based on user-feedback information and transductive inference SVM machine learning technology is presented. This method can well avoid subjectivity of deciding relevant documents empirically. To validate the effect, we extract important sentences as the final summary using a feature-fusion sentence selection strategy. The result shows that the method can improve the performance of the query-biased summarization effectively.
Abbreviating words systematically

A great step forward in lhe definition of a common lani guage for computers can be realized by the general accepta~me of a standard method for forming abbreviations of words and phr:~scs. This could be a turning point in the solution of this stMemated many-headed common language problem, thereby releasing a reservoir of creative talent for work on the next higher levels of activity. Examine a nuinber of computer applications and note how many s ~ machine descriptions of a problem contain abbreviated iI } forms of words and phrases. These names are shortened to ~ comply with certmn fixed machine characteristics and also I 1 to indulge human idiosyncrasies. They are shortened for the same reason that abbreviations are used in ore" everye day writing, i.e., to save space, conserve effort and still retain the full meaning of words. '{, When a name is written only once, it is usually written in full. When a name is constantly repeated, it is usually
Advanced imaging techniques in brain tumors

Abstract Perfusion, permeability and magnetic resonance spectroscopy (MRS) are now widely used in the research and clinical settings. In the clinical setting, qualitative, semi-quantitative and quantitative approaches such as review of color-coded maps to region of interest analysis and analysis of signal intensity curves are being applied in practice. There are several pitfalls with all of these approaches. Some of these shortcomings are reviewed, such as the relative low sensitivity of metabolite ratios from MRS and the effect of leakage on the appearance of color-coded maps from dynamic susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging and what correction and normalization methods can be applied. Combining and applying these different imaging techniques in a multi-parametric algorithmic fashion in the clinical setting can be shown to increase diagnostic specificity and confidence.
Wideband linear distributed GaN HEMT MMIC power amplifier with a record OIP3/Pdc

We report on multi-octave (100 MHz - 8 GHz) GaN HEMT nonuniform distributed amplifier (NDPA) with and without linearization in a MMIC architecture for the first time. The NDPAs were fabricated with 0.14-μm field-plate AlGaN/GaN HEMT technology with fT of 58 GHz and breakdown voltage of 90 - 100 V. The NDPAs were built with six sections in a nonuniform distributed amplifier approach. The small signal gain was ~10 dB over the band with saturated CW output power of 33 - 37 dBm at Vdd = 20 V. The PAE was >35% - 30% up to 6 GHz. The linear NDPAs consist of main and gm3 cells, and show a small signal gain of 6 - 9 dB due to input RF signal routing. The Psat was ~35 dBm at Vdd = 20 V. Based on two-tone testing, the linear NDPA shows improved OIP3 of >50 dBm, compared to OIP3 of 42 dBm of the NDPA without linearization. The resulting OIP3/Pdc is 16:1, which is the highest reported amongst GaN-based distributed amplifiers.
An improved 2D optical flow sensor for motion segmentation

A functional focal-plane implementation of a 2D optical flow system is presented that detects and preserves motion discontinuities. The system is composed of two different network layers of analog computational units arranged in a retinotopical order. The units in the first layer (the optical flow network) estimate the local optical flow field in two visual dimensions, where the strength of their nearest-neighbor connections determines the amount of motion integration. Whereas in an earlier implementation (A.A. Stocker and R.J. Douglas, 1999) the connection strength was set constant in the complete image space, it is now dynamically and locally controlled by the second network layer (the motion discontinuities network) that is recurrently connected to the optical flow network. The connection strengths in the optical flow network are modulated such that visual motion integration is ideally only facilitated within image areas that are likely to represent common motion sources. Results of an experimental aVLSI chip illustrate the potential of the approach and its functionality under real-world conditions.
Continuous Fourier Volume Rendering of Irregularly Sampled Data Using Anisotropic RBFs

We describe a Fourier Volume Rendering (FVR) algorithm for datasets that are irregularly sampled and require anisotropic (e.g., elliptical) kernels for reconstruction. We sample the continuous frequency spectrum of such datasets by computing the continuous Fourier transform of the spatial interpolation kernel which is a radially symmetric basis function (RBF) that may be anisotropically scaled. While in the frequency domain, we can apply low, band, and high-pass filters and arbitrary magnification and minification of the dataset before performing an inverse 2D Fourier transform to obtain the X-ray projection. Our algorithm is particularly amenable to implementation on commodity programmable graphics boards, and can interactively render X-rays for datasets on the order of tens of thousands of points. We describe the theoretical considerations to properly sample the frequency spectrum of anisotropic RBFs to avoid aliasing in the resulting X-ray and present a practical method for datasets with high sampling requirements. A significant benefit of our algorithm is that it can be applied to anisotropic RBFs that have been fitted to data through optimization techniques, allowing the incorporation of advanced data-sensitive constraints, such as smoothness, sharpness, and feature preservation.
Common Errors in Large Software Development Projects

www.stsc. hill.af. mil 21 D software is a relatively new area of enterprise that bears little resemblance to other engineering disciplines. Although the term software engineering is widely used throughout the business, the act of creating a new piece of software can hardly be compared to the design and construction of a new building or bridge. Computer scientists are still struggling after 30 years [1] to define software engineering and to find the right combination of techniques, procedures, and tools that assure success in development of large complex systems. The closest comparison I can make of software engineering to another creative process is writing a book. Give two authors the exact same subject matter; they will almost certainly generate different works. Although the subject matter may be the same and perhaps the outcome of the book similar, other aspects such as number of pages, references, organization, writing styles, and even the number of chapters would be all different. As a creative process, writing a book shares many things in common with writing software. [2] A great deal of research as well as planning is required. Knowing the outcome of the book or the desired effect is essential for success. The book, like software, will evolve over time going through many stages of development and modification. Software, like a book, once created need not be created again, just replicated for whoever wishes to use it. Although development of software is a complex and mysterious process to most, there are some basic management techniques that you can apply that may greatly reduce the risk of failure. In this article, I provide some general guidelines that I have gathered over the years in dealing with large and complex software development projects that have remained constant over several decades. While many books and articles focus on techniques that you should use, they often ignore the fact that mistakes can still be made during a project that will cause it to fail if certain aspects are ignored. This article will focus on some of the more common errors I have observed over years of participation in large software development projects.
Outlier detection in video sequences under affine projection

A novel robust method for outlier detection in structure and motion recovery for affine cameras is presented. It is an extension of the well-known Tomasi-Kanade factorization technique (C. Tomasi T. Kanade, 1992) designed to handle outliers. It can also be seen as an importation of the LMedS technique or RANSAC into the factorization framework. Based on the computation of distances between subspaces, it relates closely with the subspace-based factorization methods for the perspective case presented by G. Sparr (1996) and others and the subspace-based-factorization for affine cameras with missing data by D. Jacobs (1997). Key features of the method presented are its ability to compare different subspaces and the complete automation of the detection and elimination of outliers. Its performance and effectiveness are demonstrated by experiments involving simulated and real video sequences.
Image deconvolution using ℓ1 sparse regularization

This paper studies sparse regularization image deconvolution scheme over the space of measures. This regularization method is the natural extension of the ℓ1 norm of vectors to the setting of measures. The proposed model is composed of data fitting term and regularization term. The regularization parameter controls the degree of sparsity of the solution, ℓ1 fitting term promotes sparsity, and the ℓ2 data fitting term promotes smoothness while preserving edges. We use convex analysis tools and get a simple iterative algorithm. Extensive experiments on image deblurring and image inpainting verify the effectiveness of the proposed algorithm.
Piketty's Calibration Economics: Inequality and the Dissolution of Solutions?

Abstract By popularising interest in inequality, Thomas Piketty's Capital in the Twenty-First Century has made a significant contribution. It has helped to change the basic terms of debate regarding wealth and income. However, Capital exhibits several weaknesses. The overall statement of Piketty's 3 laws tends to confuse the reader by conflating capital with all forms of wealth, and capital with the current market valuation of wealth assets. The whole creates a form of empiricism by metrics or calibration. The aggregation also lends itself to data as history rather than as historically grounded explanation of evidence. Concomitantly, it lacks a theorisation of capitalism, of power, of the state, of social movements, and of social transformations. This affects the way in which possible solutions to inequality are conceived. However, it does provoke further grounds for ethical counterargument productive of more progressive solutions to the problems it highlights.
Infinitesimal rigidity for hyperbolic actions

Let Γ be a finitely-generated group, M a compact manifold and φ: Γ x M -» M a enaction of Γ on M. Let TZ(Γ^Diff(M)) denote the variety of representations of Γ into Diff(M). It is a natural problem to study the local structure of 1Z(Γ,Diff(M)) in a neighborhood of a given action. For example, there is a natural "formal tangent space" at the point [φ] determined by the action φ, which is given by the 1-cocycles over φ with coefficients in the continuous vector fields on M (cf. Chapter 2, [15]). The 1-coboundaries form a closed subspace of the formal tangent space, and when these two spaces are equal the action is said to be infinitesimally rigid. Every action φ can be perturbed by conjugating it with a diffeomorphism of M, and the set of these conjugates yields a subvariety of U(Γ,Diff(M)). The action φ is C-locally rigid if the set of conjugates forms an open neighborhood around [φ] that is, every action ψ\ which is C-close to φ on a set of generators of Γ must be (^-conjugate to ψ. Weil proved that for a representation p: Γ -» G into a connected Lie group G, infinitesimal rigidity implies rigidity, for the tangent space to the variety of representations is contained in the space of 1-cocycles over the Adjoint representation [20]. The converse is not true: there are rigid representations which are not infinitesimally rigid (cf. proof of Theorem B, [17]; section 2, [15]). For non-isometric group actions on manifolds, only partial results are known connecting infinitesimal rigidity and local rigidity (cf. [1]).
Adaptive Heuristic Search for Soft-Input Soft-Output Decoding of Arithmetic Codes

Arithmetic coding for data compression has gained widespread acceptance for optimum compression when used in a suitable model. The "traditional" hard bit based decoding suffers from severe loss of data when errors are present in the received bitstream. In this paper, heuristic-search based algorithms are introduced for the decoding of arithmetic coded bitstreams. They utilize both channel "soft" bit reliability information and synchronization and number of symbols information to identify the most likely sequence of source symbols received.
Toward agent programs with circuit semantics

New ideas are presented for computing and organizing actions for autonomous agents in dynamic environments - environments in which the agent''s current situation cannot always be accurately discerned and in which the effects of actions cannot always be reliably predicted. The notion of "circuit semantics" for programs based on "teleo-reactive trees" is introduced. Program execution builds a combinational circuit which receives sensory inputs and controls actions. These formalisms embody a high degree of inherent conditionality and thus yield programs that are suitably reactive to their environments. At the same time, the actions computed by the programs are guided by the overall goals of the agent. The paper also speculates about how programs using these ideas could be automatically generated by artificial intelligence planning systems and adapted by learning methods.
An undergraduate teaching exercise that explores contemporary issues in the manufacture of titanium dioxide on the industrial scale

A teaching exercise is described that aims to expose undergraduate chemistry students to the type and range of complex and interacting issues that a chemist active in an industrial organisation might typically encounter. The business area selected is the titanium dioxide pigment manufacturing sector, that is meant to be representative of large-scale chemical manufacturing. Although the students are exposed to a range of chemical topics, they are also expected to understand some of the associated economic, environmental and legislative drivers that, inevitably, impinge on the business operations. Indirectly, the exercise aims to make the students aware of the concepts of sustainable development, as applied to the chemicals industry. The students are asked to engage in a mature discussion as to whether a new titanium dioxide manufacturing facility should be constructed within their area. The background information supplied to the students is based around a real situation that existed in 2001. Evaluation of the exercise by the students indicates a definite positive response and suggests that such teaching packages can play a positive role in demonstrating the real issues related to enhanced environmental awareness within the chemicals industry.