Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Block based Feature Level Image Fusion Technique using Wavelet Transform and Neural Network

fusion is a process of combining relevant information from two or more images into a single informative image. In this paper, wavelet transform is integrated with neural network, which is one of the feature extraction or detection machine learning applications. This paper has derived an efficient block based feature level wavelet transform with neural network (BFWN) model for image fusion. In the proposed BFWN model, the two fusion techniques, discrete wavelet transform (DWT) and neural network (NN) are discussed for fusing IRS-1D images using LISS III scanner about the location Hyderabad, Vishakhapatnam, Mahaboobnagar and Patancheru in India. Also QuickBird image data and Landsat 7 image data are used to perform experiments on the proposed BFWN method. The features under study are contrast visibility, spatial frequency, energy of gradient, variance and edge information. Feed forward back propagation neural network is trained and tested for classification since the learning capability of neural network makes it feasible to customize the image fusion process. The trained neural network is then used to fuse the pair of source images. The proposed BFWN model is compared with DWT alone to assess the quality of the fused image. Experimental results clearly prove that the proposed BFWN model is an efficient and feasible algorithm for image fusion.
Abstraction-Based Static Analysis of Buffer Overruns in C Programs

SRINIVASA, GOPAL RANGANATHA. Abstraction-Based Static Analysis of Buffer Overruns in C Programs. (Under the direction of Associate Professor Dr. S. Purushothaman Iyer). Bounds violations or buffer overruns have historically been a major source of defects in software systems, making bounds checking a key component in practical automatic verification methods. With the advent of the Internet, buffer overruns have been exploited by attackers to break into secure systems as well. Many security violations ranging from the 1988 Internet worm incident to the AnalogX Proxy server vulnerability have been attributed to buffer overruns. Programs written in the C language, which comprise most of the systems software available today, are particularly vulnerable because of the lack of array bounds checking in the C compiler, presence of pointers that can be used to write anywhere in memory, and the weak type system of the C language. Many methods have been proposed to detect these errors. Runtime methods that detect buffer overruns suffer from significant overhead and incomplete coverage, while compile time methods could suffer from low accuracy and poor scalability. In this thesis, we propose a new technique for bounds checking based on data abstraction that is more accurate, more scalable, and suffers from no runtime overhead. Enhancements have been made to C Wolf, a suite of model generation tools, to handle buffer overflow analysis. Case studies on web2c, a publicly available software package, pico server, an open source web server, and on the wu-ftpd server are presented to demonstrate the practicality of the technique. Abstraction-Based Static Analysis of Buffer Overruns in C Programsion-Based Static Analysis of Buffer Overruns in C Programs
Design of a body area network for medical applications: the WiserBAN project

This paper deals with some preliminary results achieved in the framework of the FP7 project WiserBAN (Smart miniature low-power wireless microsystem for Body Area Networks), aiming at the creation of a low-power and miniature microsystem targeting wearable and implanted devices for medical applications. The results achieved in the first year of the project, related to the radio channel characterization and protocol design, are reported. Different Medium Access Control protocols, based on existing and emerging standards, are proposed and their performance are compared. Results show that the proposed protocols allow to satisfy the end users requirements.
Robust , Light-weight Approaches to compute Lexical Similarity

Most text processing systems need to compare lexical units – words, entities, semantic concepts – with each other as a basic processing step within large and complex systems. A significant amount of research has taken place in formulating and evaluating multiple similarity metrics, primarily between words. Often, such techniques are resourceintensive or are applicable only to specific use cases. In this technical report, we summarize some of our research work in finding robust, lightweight approaches to compute similarity between two spans of text. We describe two new measures to compute similarity, WNSim for word similarity, and NESim for named entity similarity, which in our experience have been more useful than more standard similarity metrics. We also present a technique, Lexical Level Matching (LLM), to combine such token-level similarity measures to compute phraseand sentence-level similarity scores. We have found LLM to be useful in a number of NLP applications; it is easy to compute, and surprisingly robust to
Adaptive gene regulatory networks

Regulatory interactions between genes show a large amount of cross-species variability, even when the underlying functions are conserved: there are many ways to achieve the same function. Here we investigate the ability of regulatory networks to reproduce given expression levels within a simple model of gene regulation. We find an exponentially large space of regulatory networks compatible with a given set of expression levels, giving rise to an extensive entropy of networks. Typical realisations of regulatory networks are found to share a bias towards symmetric interactions, in line with empirical evidence.
Prosody-based Topic Segmentation for Mandarin Broadcast News

Automatic topic segmentation, separation of a discourse stream into its constituent stories or topics, is a necessary preprocessing step for applications such as information retrieval, anaphora resolution, and summarization. While significant progress has been made in this area for text sources and for English audio sources, little work has been done in automatic, acoustic feature-based segmentation of other languages. In this paper, we focus on prosody-based topic segmentation of Mandarin Chinese. As a tone language, Mandarin presents special challenges for applicability of intonation-based techniques, since the pitch contour is also used to establish lexical identity. We demonstrate that intonational cues such as reduction in pitch and intensity at topic boundaries and increase in duration and pause still provide significant contrasts in Mandarin Chinese. We also build a decision tree classifier that, based only on word and local context prosodic information without reference to term similarity, cue phrase, or sentence-level information, achieves boundary classification accuracy of 89--95.8% on a large standard test set.
A combined component-based approach for the design of distributed software systems

Component-based software development enables the construction of software artefacts by assembling binary units of production, distribution and deployment, the so-called components. Several approaches to component-based development have been proposed recently. Most of these approaches are based on the Unified Modeling Language (UML). UML has been increasingly used in component-based development, despite some shortcomings of this language. This paper presents a methodology for the design of component-based applications that combines a model-based approach with a UML-based approach. This combined approach tackles some of the limitations of UML, allowing a better control of the design process.
On Speaker-Independent Personality Perception and Prediction from Speech

In this paper, we present ongoing experiments and insights regarding automatic and human assessment of perceived personality. While within the INTERSPEECH Speaker Trait Challenge participants will train systems in order to recognize binary targets along the Big 5 personality trait, we will analyze and discuss properties of the data, the labeling scheme and the predictive quality. Conducting factor analyses, estimating reliability, and building regression models capturing dimensions of personality we compare all results to our own work and introduce a new extension of our personality database. In conclusion, this paper contributes in methodology and understanding on how to asses the perceived personality from an unknown speaker by humans and machines. Index Terms: extra-linguistic speech properties, personality modeling from speech, speaker characteristics
Visual Representation of Vector Fields Recent Developments and Research Directions

The state of the art in the visual representation of vector and tensor fields is described. Fundamentals and basic techniques are covered, and recent advances in the field are reviewed, such as extensions of volume rendering, vector field topology, streamline and stream surface generation, particle-based techniques, tensor field visualization, and the selection and visualization of salient features of the data. Research issues in vector field and CFD visualization are identified, including interaction, validation, and quality assessment. For a fruitful development of the field, it is argued that integration of knowledge and results from several related domains is desirable.
AdS/CFT correspondence and geometry

In the first part of this paper we provide a short introduction to the AdS/CFT correspondence and to holographic renormalization. We discuss how QFT correlation functions, Ward identities and anomalies are encoded in the bulk geometry. In the second part we develop a Hamiltonian approach to the method of holographic renormalization, with the radial coordinate playing the role of time. In this approach regularized correlation functions are related to canonical momenta and the near-boundary expansions of the standard approach are replaced by covariant expansions where the various terms are organized according to their dilatation weight. This leads to universal expressions for counterterms and one-point functions (in the presence of sources) that are valid in all dimensions. The new approach combines optimally elements from all previous methods and supersedes them in efficiency.
Duality in supersymmetric Yang-Mills theory

These lectures provide an introduction to the behavior of strongly-coupled supersymmetric gauge theories. After a discussion of the effective Lagrangian in nonsupersymmetric and supersymmetric field theories, the author analyzes the qualitative behavior of the simplest illustrative models. These include supersymmetric QCD for N{sub f} < N{sub c}, in which the superpotential is generated nonperturbatively, N = 2 SU(2) Yang-Mills theory (the Seiberg-Witten model), in which the nonperturbative behavior of the effect coupling is described geometrically, and supersymmetric QCD for N{sub f} large, in which the theory illustrates a non-Abelian generalization of electric-magnetic duality. 75 refs., 12 figs.
Pseudorandom Walks in Biregular Graphs and the RL vs. L Problem

A crystalline vanadium (IV) phosphate composition having an intrinsic surface area in excess of 10 square meters per gram is prepared by the reaction of orthophosphoric acid with a vanadium (IV) oxycompound. The vanadium compound is suspended in a suitable hydroxylic organic medium, for example isobutanol, and contacted with the acid at a temperature in the range 20 DEG C. to 210 DEG C. until the conversion is completed.
Principles of Pseudo-Random Number Generation in Cryptography

The ability to sample discrete random variables is essential to many areas of cryptography. The most obvious example is key-generation for encryption algorithms or keyed hash functions – if one uses deterministic algorithms to generate keys, then the security of the key is dependent on the secrecy of the algorithm, which is both impractical and unnecessary. Modern cryptography posits that messages and keys are the secrets, not algorithms. Only (well-constructed) algorithms incorporating random keys offer legitimate users abilities that an adversary cannot replicate. Since security should not reside in uncertainty about a party’s algorithm, it must instead originate from the entropy of the key-space. However, it is often impractical to generate and transfer very long strings of random bits. A good way to minimize these problems is to use cryptographically secure pseudo-random number generators (CSPRNG). This paper hopes to be an accessible resource to introduce the principles of pseudo-random number generation in cryptography. Key topics are what it means to be a CSPRNG, the conditions for the existence of a CSPRNG, as well as more general cryptographic concepts such as ‘security’ and ‘adversary. ’
Getting to grips with "interactivity": helping teachers assess the educational value of CD-ROMs

Many commercial CD-ROMs are now being marketed as suitable for home and school use, increasingly promoted as covering the National Curriculum. However, such promises are failing to be realised because many CD-ROMS are poorly constructed, consisting simply of a mishmash of images, sounds and video that offer little more than light entertainment. The aim of this paper is to provide guidance on assessing the added value of educational CD-ROMs compared with traditional materials by explicating more the notion of interactivity as it pertains to learning.
Solution of Time Domain Pmchw Formulation for Transient Electromagnetic Scattering from Arbitrarily Shaped 3-D Dielectric Objects

In this paper, we analyze the transient electromagnetic response from three-dimensional (3-D) dielectric bodies using a time domain PMCHW (Poggio, Miller, Chang, Harrington, Wu) integral equation. The solution method in this paper is based on the Galerkin's method that involves separate spatial and temporal testing procedures. Triangular patch basis functions are used for spatial expansion and testing functions for arbitrarily shaped 3-D dielectric structures. The time domain unknown coefficients of the equivalent electric and magnetic currents are approximated by a set of orthonormal basis functions that are derived from the Laguerre functions. These basis functions are also used as the temporal testing. Use of the Laguerre polynomials as expansion functions characterizing the time variable enables one to handle the time derivative terms in the integral equation and decouples the space-time continuum in an analytic fashion. We also propose an alternative formulation using a differential form of time domain PMCHW equation with a different expansion for the equivalent currents. Numerical results computed by the two proposed methods are presented and compared.
SnO2 Highly Sensitive CO Gas Sensor Based on Quasi-Molecular-Imprinting Mechanism Design

Response of highly sensitive SnO2 semiconductor carbon monoxide (CO) gas sensors based on target gas CO quasi-molecular-imprinting mechanism design is investigated with gas concentrations varied from 50 to 3000 ppm. SnO2 nanoparticles prepared via hydrothermal method and gas sensor film devices SC (exposed to the target gas CO for 12 h after the suspension coating of SnO2 film to be fully dried, design of quasi-molecular-imprinting mechanism, the experiment group) and SA (exposed to air after the suspension coating of SnO2 film to be fully dried, the comparison group) made from SnO2 nanoparticles are all characterized by XRD, SEM and BET surface area techniques, respectively. The gas response experimental results reveal that the sensor SC demonstrates quicker response and higher sensitivity than the sensor SA does. The results suggest that in addition to the transformation of gas sensor materials, surface area, and porous membrane devices, the Molecular Imprinting Theory is proved to be another way to promote the performance of gas sensors.
Testing the equality of central tendency measures using various trimming strategies

Ft statistic test is a non classical method of comparing two or more groups. This statistical procedure is able to handle problems of sample locations when non-normality occurs but the homogeneity of variances assumption still applies. This method is not robust under the existence of variance heterogeneity. To make this test less sensitive when either one or both of the common assumptions are violated, in this study the test is modified and improved by replacing the test’s original central tendency measure that is, the fixed symmetric trimmed mean with a predetermined asymmetric trimmed mean and a modified one-step M-estimator (MOM) trimmed mean. The finding shows that when the data is suspected to be extremely skewed, then, it will be advantageous to adopt MOM procedures for homogeneous variance cases. On the other hand, for heterogeneous variances, a trimmed mean which uses predetermined asymmetric trimmed mean should be considered as an alternative, particularly for testing the equality of four groups.
A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Potential games form a class of non-cooperative games where unilateral improvement dynamics are guaranteed to converge in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed.
Making spaces: how design workbooks work

In this paper, I discuss design workbooks, collections of design proposals and related materials, both as a method for design and as a design methodology. In considering them as a method, I describe a number of examples of design workbooks we have developed in our studio and describe some of the practical techniques we have used in developing them. More fundamentally, I discuss design workbooks as embodiments of a methodological approach which recognises that ideas may emerge slowly over time, that important issues and perspectives may emerge from multiple concrete ideas, potentially generated by multiple members of a team, rather than being theory-driven, and that maintaining the provisionality and vagueness of early proposals can be useful in supporting a quasi-participatory design approach that allows participants to interpret, react to and elaborate upon the ideas they present.
Cortical Columns as the Base Unit for Hierarchical and Scalable Machine Learning

Studying the cortex via columnar organization of neurons is a perspective. One which is more holistic than single cell models but still far less ambitious than studying diverse networks [1]. Though there are confusions in terminology, studying columnar organization instead of neurons have allowed many researchers to attain a functional understanding of and ability to model processes such as map cell placement [9] and pattern recognition. We report an extension to a model proposed by A.G. Hashmi, M.H. Lipasti. We discuss the biological plausability of cortical column modeling and show a two level implementation. 1 Biological Background Lorente de No first described what are now known as cortical columns in 1938 [7]. Then, he suggested that these originations of cells could be called an “elementary unit” which builds to brain function. In 1957, Mountcastle gave the name cortical columns. Since the initial descriptions and definitions, the term “cortical column” is widely used and is the source of some confusion. In addition, the term hyper column is used as well. Here, we will refrain from using “general” terms as possible. A “cortical column” in the broad sense, refers to the vertical organization of neurons found in the cortex. We use the terms minicolumn and macrocolumn to be more precise. A minicolumn is a vertically organized group of neurons, between 80-100, which are responsible for independent receptive fields. These minicolumns communicate with other minicolumns in a organization termed the macrocolumn. Each macrocolumn has found to contain between 60-80 minicolumns [1]. Much of the interest in cortical columns arise from how they appear to code for information. The minicolumns of each macrocolumn appear to traverse laminas II VI with feed-forward, feed-back, and horizontal connections. Calvin (1998) has suggested that laminas II and III code for associations, laminas V and VI code out, and lamina IV receives the inputs [6]. These mechanisms also seem to represent one orthogonal type of input, where minicolumns use lateral inhibition to sharpen their borders and increase their own field’s definition [5]. The mechanism for this process has been suggested to be derived from axon bundles of double bouquet cells [5]. These attributes are even more attractive because no research has yet to find minicolumn activity outside its own macrocolumn. This suggests that they act as independent feature detection and processing agents. In-vivo mouse studies show that in the barrel cortex the minicolumn excitation and inhibition connections work to enhance important information while suppressing distracting information [4]. Furthermore, these general methodologies for processing are nearly identical throughout the central nervous system. Columns integrate a diverse set of information; including auditory, visual, sensory, motor, and memory [1]. So far, the studies of these species support the concept of using cortical
Exponentially Sliding Mode Control for Uncertain Input-Delay Systems Based on Invariant Conditions

This paper provides a sliding mode control method for a class of input-delay systems with unmatched uncertainties based on new invariant conditions. The controller is constructed to guarantee that the motions of sliding surfaces are exponentially convergent to the desired manifolds with an arbitrary prespecified decay rate. The reduced-order sliding mode dynamics are also exponentially convergent to a ball such that the effects of delay and unmatched uncertainties in the sliding mode are overcome. A numerical example is included to illustrate the proposed method
Grouping from motion using the medoid shift and topological relations

We consider the problem of extracting various moving objects on an image by analyzing the topological relations induced by the positions of a sparse set of putative matching points on two images of one scene. Topological relations among triples of matched point pairs are found, and we formulate the task as a hypergraph clustering problem which is then performed by the medoid shift, a non-parametric mode-seeking algorithm similar to mean shift. The method finds the number of clusters automatically and filters out outliers. We report the performance of our method on a synthetic dataset.
The Dirac equation in Cartesian gauge

It is shown that in the case of the spherically symmetric static backgrounds there is a gauge in which the Dirac equation is manifestly covariant under rotations. This allows us to separate the spherical variables like in the flat space-time, obtaining a pair of radial equations and a specific form of the radial scalar product.
Discrete-time quantum mechanics.

The finite-element (collocation) method enables us to construct discrete time-lattice quantum systems that accurately approximate continuum quantum systems. The discrete quantum systems so generated are fully consistent quantum-mechanical systems in their own right. This paper gives a comprehensive treatment of such quantum systems. We examine various finite-element schemes, construct the effective lattice Hamiltonian, and calculate eigenvalues. Numerical results are extremely easy to obtain and are very accurate.