Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Hiding in Halftone Images using Error Diffusion Halftoning with Adaptive Thresholding

Halftoning is the process of representing a gray-level image with a binary image. Data hiding is the technique of embedding data in an image without affecting its perceptual quality. DHSED is a watermarking algorithm to embed hidden binary visual patterns in two error diffused halftone images such that the hidden patterns can be visually inspected when the images are overlaid. A drawback of the DHSED method is that if the image has large areas of the same grey-level, hiding data causes some edge effects which may reveal the hidden data. In this paper we propose an improvement to the DHSED which fairly reduces the edge effects
Iterative Off-resonance and Signal Decay Correction for Improved Multi-echo Imaging in MRI

Local deviations of the main field and signal decay due to transverse relaxation lead to perturbations of the Fourier encoding commonly applied in magnetic resonance imaging. Hence, images acquired with trajectories having long readout times suffer from artefacts such as blurring, geometric distortion, and intensity inhomogeneity. These effects can be corrected by means of iterative reconstruction algorithms, provided a field map and a relaxation map are available. Recently, a fast griddingbased approach to field inhomogeneity correction was proposed. In this work, this algorithm is extended to also handle the signal decay due to relaxation. It is then embedded in a novel fixedpoint iteration algorithm that allows for the joint estimation of the field map, relaxation map, and echo images from a single multi-echo acquisition. This joint estimation approach enables the application of fast acquisition trajectories in multi-echo imaging experiments, such as spiral and echo planar, while avoiding artefacts in the reconstruction of the echo images, the field map, and the relaxation map. Since the method dispenses with the acquisition of a separate calibration scan, an appreciable overall reduction in scan time can be achieved. The evaluation of the proposed algorithm in simulations and in-vivo experiments shows a significant improvement in the reconstruction of the echo images and the estimation of the relaxation map, as compared to the standard case, where no correction is applied. The demonstrated rapid convergence of the fixed-point iteration algorithm together with the computational efficiency of the gridding-based reconstruction keeps the overall computation time reasonable.
Explaining divorce rate determinants: new evidence from Spain

ABSTRACT This article examines the main determinants of divorce rates in Spain for the period 1995 to 2010. According to the results, the so-called Express Divorce Law (passed in 2005) seems to be positively associated with divorce rates in the short term. Income level and growth, female employment rate, and the proportion of foreign population are also positively related to divorce rates. However, as expected, the percentage of conservative vote seems to have a negative impact.
A Uniform and Automatic Approach to Copy Elimination in System Extensions via Program Specialization

Most operating systems heavily rely on intermediate data structures for modularity or portability reasons. This paper extends program specialization to eliminate these intermediate data structures in a uniform manner. Our transformation process is fully automatic and is based on a specializer for C programs, named Tempo. The key advantage of our approach is that the degree of safety of the source program is preserved by the optimization. As a result, mature system code can be reused without requiring additional verification. Our preliminary results on the automatically optimized RPC code are very promising in that they are identical to the results we obtained by manual specialization of the same code. In this last experiment, performance measurement of the specialized RPC fragments shows a minimal speedup of 30% compared to the non-specialized code. Elimination of intermediate data structures is part of our research effort towards optimizing operating system components via program specialization. It improves on our previous work in that optimizations are now carried out automatically using our specialization tool. Furthermore, it shows how generic subsystems can be automatically specialized into specific system extensions by exploiting application constraints.
Netquest : An Abstract Model for Pervasive Applications Version of January 18 , 2009

One of the barriers to the implementation and deployment of pervasive applications is the lack of a programming abstraction for ubiquitous computing. We propose a system (i) that supports a declarative programming language, Netlog, well suited to rapid prototyping of distributed applications, (ii) which relies on an embedded DBMS, which facilitates its implementation and its portability over heterogeneous devices, and (iii) supports important functionalities such as implicit routing or adaptive behavior.
Innovation Effort as 'Productive Consumption:' The Power of Participation Benefits to Amplify Innovation

When economists and innovation practitioners think about whether developing an innovation will be worthwhile, they tend to think exclusively about the economic value of the outcome of the innovation process. In this article, we develop and explore the idea that innovators can also gain significant benefits from participation in a development process as well as or even instead of benefits from using or selling the innovation created. When this is the case, the net cost of innovation projects can be much lower for developers – in effect, a portion of project development costs becomes “productive consumption. ”We draw on the findings of empirical studies to document that a significant fraction of the benefits that individuals obtain from engaging in innovation projects can consist of benefits derived from participation. We offer an “innovation amplification” metric to quantify the associated cost reductions for project sponsors, and discuss implications for innovation research and practice.
An Evolutionary Approach to Speech Quality Estimation

In this paper we have employed a genetic programming (GP) based symbolic regression approach to estimate the speech quality as a function of impairments due to IP network and low bitrate coding. A main advantage of GP is that it can produce human-readable results in the form of analytical expressions. Moreover, GP is capable of weeding out irrelevant parameters and concentrating on the most salient ones. These features of GP make our results superior to the past research based on Artificial Neural Networks (ANNs) by Sun and Ifeachor, Mohamed et. al. and on lookup tables by Hoene et. al. We have used PESQ as a reference for evolutionary modeling. The results of proposed models show a high correlation with PESQ. Moreover, our models are suitable for real-time and non-intrusive estimation of VoIP quality.
Fast Wavelet-Based Image Characterization for Highly Adaptive Image Retrieval

Adaptive wavelet-based image characterizations have been proposed in previous works for content-based image retrieval (CBIR) applications. In these applications, the same wavelet basis was used to characterize each query image: This wavelet basis was tuned to maximize the retrieval performance in a training data set. We take it one step further in this paper: A different wavelet basis is used to characterize each query image. A regression function, which is tuned to maximize the retrieval performance in the training data set, is used to estimate the best wavelet filter, i.e., in terms of expected retrieval performance, for each query image. A simple image characterization, which is based on the standardized moments of the wavelet coefficient distributions, is presented. An algorithm is proposed to compute this image characterization almost instantly for every possible separable or nonseparable wavelet filter. Therefore, using a different wavelet basis for each query image does not considerably increase computation times. On the other hand, significant retrieval performance increases were obtained in a medical image data set, a texture data set, a face recognition data set, and an object picture data set. This additional flexibility in wavelet adaptation paves the way to relevance feedback on image characterization itself and not simply on the way image characterizations are combined.
How to Avoid the Formal Verification of a Theorem Prover

The purpose of this papers to show a technique to automatically certify answers coming from a nontrustable theorem prover. As an extreme consequence, the development of non-sound theorem provers has been considered and investigated, in order to evaluate their relative efficiency on particular classes of difficult theorems. The presentation will consider as a case study, a tableau-based theorem prover for first-order intuitionistic logic without equality [1].
Accessing A Learning Object Repository Through A Semantic Layer

This paper describes ongoing work on the issue of exploiting a Learning Object Repository, i.e., a large library of learning resources, which incorporates different and often heterogeneous types of objects, to feed activities to a Virtual Learning Community. These objects include re-usable contents that are described by means of metadata. Our proposal leans on an ontology for interpreting the annotations and suggesting the LO best fitting the community’s necessities for a given activity. The ontology, as a representation mechanism, interprets all the available knowledge and provides adequate ways of exploiting it, which include social navigation and recommendation through enhanced searching capabilities.
Graph method for generating affine moment invariants

A general method of systematic derivation of affine moment invariants of any weights and orders is introduced. Each invariant is expressed by its generating graph. Techniques for elimination of reducible invariants and dependent invariants are discussed. This approach is illustrated on the set of all affine moment invariants up to the weight ten.
Experiences from the Development and Use of Simulation Software for Complex Systems Education

In this paper, we present our lessons from the design and use of two educational software tools for teaching behavioral modeling to graduate students of digital art. The tools, PainterAnts and VLab, allow the experimentation and control of simulated ants that paint, or Braitenberg vehicle-like agents (Braitenberg 1984). To better address the target audience of digital art students, we have transcribed both systems in ways that would excite art students, that is, by finding graphical equivalents of behavior. This arrangement allows us to exploit the users’ visual experience and motivation to manipulate and experiment with complex visual forms. Experience with using the systems reveals that the artists show a high motivation for experimenting with them, which is partly due to the fact that they tend to regard them as simple abstract art tools that may produce interesting complex forms. Our experience has also identified several methodological and theoretical issues on educational system design that have been partly tackled and that merit extended study and research.
A Fast and General Implementation of Mach IPC in a Network

This paper describes an implementation of the Mach IPC abstraction on a network. Our implementation, called Mach NetIPC, is done in the context of the x-kernel, which provides a networking subsystem for Mach. The paper motivates the design choices we made, describes the x-kernel protocol graph that implements the design, and reports on the performance of the resulting system.
Local Changes in the Excitability of the Cerebellar Cortex Produce Spatially Restricted Changes in Complex Spike Synchrony

Complex spike (CS) synchrony patterns are modulated by the release of GABA within the inferior olive (IO). The GABAergic projection to most of the IO arises from the cerebellar nuclei, which are themselves subject to strong inhibitory control by Purkinje cells in the overlying cortex. Moreover, the connections between the IO and cerebellum are precisely aligned, raising the possibility that each cortical region controls its own CS synchrony distribution. This possibility was tested using multielectrode recordings of CSs and simple spikes (SSs) in crus 2a of anesthetized rats. Picrotoxin or muscimol was applied to the cerebellar cortex at the borders of the recording array. These drugs induced significant changes in CS synchrony and in CS and SS firing rates and changes in post-CS pauses and modulation of SS activity. The level of CS synchrony was correlated with SS firing rate in control, and application of picrotoxin increased both. In contrast, muscimol decreased CS synchrony. Furthermore, when picrotoxin was applied only at the lateral edge of the array, changes in CS synchrony occurred sequentially across the recording array, with cells located in the lateral half of the array having earlier and larger changes in CS synchrony than cells in the medial half. The results indicate that a double-inhibitory feedback circuit from Purkinje cells to the IO provides a mechanism by which SS activity may regulate CS synchrony. Thus, CS synchrony may be a physiologically controlled parameter of cerebellar activity, with the cerebellum and IO comprising a series of self-updating circuits.
The Number of Independent Sets in a Grid Graph

If f(m,n) is the (vertex) independence number of the $m\times n$ grid graph, then we show that the double limit $\eta\eqdef\lim_{m,n\to\infty}f(m,n)^{1\over {mn}}$ exists, thereby refining earlier results of Weber [Rostock. Math. Kolloq. , 34 (1988), pp. 28--36] and Engel [Fibonacci Quart.,, 28 (1990), pp. 72--78]. We establish upper and lower bounds for $\eta$ and {\it prove} that $1.503047782. \le \eta \le 1.5035148\ldots $. Numerical computations suggest that the true value of $\eta$ (the "hard square constant") is around 1.5030480824753323.
A Sample of Low-Redshift BL Lacertae Objects. II. EVN and MERLIN Data and Multiwavelength Analysis

We present new radio observations of 9 members of a sample of 29 nearby (z < 0.2) BL Lac objects. The new data have been obtained with the European VLBI Network and/or MERLIN at 1.6 and 5 GHz and complement previous observations. For one object, the TeV source Mrk 421, we also present deep multiepoch VLBA and global VLBI data, which reveal a resolved diffuse jet with clear signatures of limb brightening. We use the new and old data to estimate physical parameters of the jets of the sample from which the subset with new radio data is drawn. We derive Doppler factors in the parsec-scale radio jet in the range 2 ≲ δ ≲ 9. Using HST data, we separate the contribution of the host galaxy from that of the active core. From the measured and debeamed observables, we find a weak correlation between radio power and black hole mass, and a tight correlation between radio and optical core luminosities. We interpret this result in terms of a common synchrotron origin, with little contribution from a radiatively efficient accretion disk. The BL Lac objects in our sample have debeamed properties similar to low-power radio galaxies, including the fundamental plane of black hole activity.
Implementing High Grade Security in Cloud Application using Multifactor Authentication and Cryptography

As a high-speed internet foundation is being developed and people are informationized, most of the tasks are engaged in internet field so there is a risk that any private data like personal information or applications for managing money can be wiretapped or eavesdropped. The consolidation of One Time Passwords (OTPs) and Hash encryption algorithms are used to evolve a more secured password-protected web sites and data storage systems. The new outlined scheme had higher security, small system overhead and is easy to implement.
Non-Local Means Image Denoising with Local Geometric Structures Matching Strategy

Efficient and valid image denoising method is still a challenge, and Non-local means is a rising and effective image denoising method. We propose a NL-Means image denoising algorithm based on self-similarity of local geometric structures in the image. As local contrast is an important geometric property of digital image, our algorithm can find patches which are similar not only in grey value but also in local contrast. We demonstrate the application of this approach to enhance the edge and corner structures by simulation experiments, and the result shows that our algorithm increases the PSNR effectively.
3 MANOVA TEST CRITERIA AND F APPROXIMATIONS AND UNIVARIATE F TESTS FOR THE HYPOTHESIS OF OVERALL DESIGN , SEASON , DESIGN * SEASON , AND THE COVARAITE EFFECTS

1 Department of Civil and Environmental Engineering, University of Nevada-Reno, Nevada, U.S.A College of Agriculture, Biotechnology and Natural Resources, University of Nevada Reno, Nevada, U.S.A ABSTRACT Steamboat Creek (Reno, Nevada) is contaminated by agricultural and stormwater runoff. Exploratory, descriptive, and statistical modeling was performed using SAS software version 9.13 in order to predict the performance of small-scale constructed wetlands. The performance of 6 constructed wetland designs with different combinations of sediment and water were considered. Water sampling was conducted twice a month. The removals of total nitrogen (TN), total phosphorus (TP), total suspended solids (TSS), and total organic carbon (TOC) within the wetlands were monitored. Data exploration using box plots were examined to check for trends, outliers, and distribution patterns. Efficiency of nutrient removal associated with each wetland design, seasonal changes, and interactions between design and season were analyzed using Mulitvariate Analysis of Variance (MANOVA) using the SAS/STAT procedure GLM. Canonical correlations between operational conditions such as flow, pH, and temperature and the removal of TN, TP, TSS, and TOC were analyzed using the SAS/STAT CANCORR procedure. Scatter plots were used to explore the linear trends, significance and the range of the majority values in a correlation. Multivariate test statistic was used to check for the overall significance in canonical correlations. Following canonical correlation, multiple regression models were developed for TN, TP, TSS, and TOC with respect to each of the predictor variables. The results from the statistical analyses performed on the data from the small-scale constructed wetlands demonstrated that the construction of a large-scale wetlands system would be an effective method to improve water quality in Steamboat Creek by reducing the loadings of TN, TP, TSS, and TOC into the lower Truckee River.
Non-Data-Aided Timing Recovery for Filter-Bank Multicarrier Wireless Communications

In this paper, we design and evaluate the performance of non-data-aided timing recovery methods for a filter bank multicarrier modulation technique called filtered multitone (FMT). Starting from a maximum likelihood approach as optimality criterion, we illustrate the derivation of a closed-loop tracker and demonstrate how to derive a relatively low-complexity scheme with reasonable performance loss. The features of the proposed timing estimators (S-curve, acquisition time, estimation accuracy) are derived through a combination of analysis and simulation both on the additive white Gaussian noise channel and a typical static frequency-selective wireless channel. Unlike previously published works, a remarkable acquisition range equal to plus and minus one-half the FMT signaling interval is achieved. We also show by simulation a significant robustness with respect to the multipath channel and nonideal carrier frequency estimation
Parallel Algorithm for Learning Optimal Bayesian Network Structure

We present a parallel algorithm for the score-based optimal structure search of Bayesian networks. This algorithm is based on a dynamic programming (DP) algorithm having O(n ⋅ 2n) time and space complexity, which is known to be the fastest algorithm for the optimal structure search of networks with n nodes. The bottleneck of the problem is the memory requirement, and therefore, the algorithm is currently applicable for up to a few tens of nodes. While the recently proposed algorithm overcomes this limitation by a space-time trade-off, our proposed algorithm realizes direct parallelization of the original DP algorithm with O(nσ) time and space overhead calculations, where σ>0 controls the communication-space trade-off. The overall time and space complexity is O(nσ+1 2n). This algorithm splits the search space so that the required communication between independent calculations is minimal. Because of this advantage, our algorithm can run on distributed memory supercomputers. Through computational experiments, we confirmed that our algorithm can run in parallel using up to 256 processors with a parallelization efficiency of 0.74, compared to the original DP algorithm with a single processor. We also demonstrate optimal structure search for a 32-node network without any constraints, which is the largest network search presented in literature.
Evaluating Item-Item Similarity Algorithms for Movies

Recommender systems such as those used in e-commerce or Video-On-Demand systems generally show users a list of "similar items. " Many algorithms exist to calculate item-item similarity and we wished to evaluate how users perceive these numerically expressed similarity. In our experiment, we performed a user study with four similarity algorithms to evaluate perceived correctness in item-item similarity as it relates to movies. We implemented three algorithms: collaborative filtering with Pearson, collaborative filtering with cosine, and content-filtering with TF-IDF. A pre-generated similarity list from TheMovieDB.org (TMDb) was used as the baseline. Our experiment showed that TMDb has the highest perceived similarity, followed by cosine and TF-IDF, while Pearson was practically unusable for users. A by-product of our experiment was a set of similar movie pairs, which we intend to use for offline evaluation.
Trading resiliency for security: model and algorithms

An attack-resistant network is a purpose-built network to survive attacks; by construction, it should be both resilient and secure. Resiliency is the ability to provide alternative communication paths should one path become disrupted due to failures or attacks; while security is the ability to contain and limit the impact of compromises. Interestingly, these two can present conflicting demands. We provide a first formulation of a new class of problems focusing on the engineering of attack-resistant networks. Our model considers both resiliency and security, and uses a notion of blocking probability as a rigorous measure for evaluating different network constructions. We propose several efficient approximation algorithms for computing blocking probability and provide bounds for their errors. Based on these algorithms, we introduce a family of heuristics to guide the construction of optimal attack-resistant networks with minimum blocking probabilities. We also present extensive results to evaluate and demonstrate the near-optimal performance of our heuristics and approximation algorithms.
Charging and Rate Control for Elastic Traac

This paper addresses the issues of charging, rate control and routing for a communication network carrying elastic traac, such as an ATM network ooering an available bit rate service. A model is described from which max{min fairness of rates emerges as a limiting special case; more generally, the charges users are prepared to pay in-uence their allocated rates. In the preferred version of the model, a user chooses the charge per unit time that the user will pay; thereafter the user's rate is determined by the network according to a proportional fairness criterion applied to the rate per unit charge. A system optimum is achieved when users' choices of charges and the network's choice of allocated rates are in equilibrium.