Miracle-dz/UniFAR-FTUs huggingface dataset:
Web Service Matching by Ontology Instance Categorization

Identifying similar Web services is becoming increasingly important to ensure the success of dynamically integrated Web-service-based applications. We propose a categorization-based scheme to match equivalent Web services that can operate on heterogeneous domain ontologies. Given the upper ontology for services and domain ontologies, our service matching scheme determines whether a given Web service is a possible replacement using a categorization utility called OnExCat. OnExCat categorizes ontology instances extracted from the service descriptions by a probabilistic categorization measurement that incorporates the concept relationships in the upper ontology for services. In addition to tackling the issue of heterogeneity of domain ontology in service descriptions using categorization, our matching scheme also adapts itself by enhancing the known ontologies with newly discovered ontology instances. Experiments on service matching using our matching scheme based on the OnExCat utility have been performed with promising results, a correct matching rate of over 85%.
Macs'06 6th Joint Conference on Mathematics and Computer Science

Preface The University of Pécs welcomes the participants of the 6th Joint Conference on Mathematics and Computer Science! We are proud to have the right to organize this Conference. The University of Pécs was founded by the Anjou King Louis the Great, as the first university in Hun-gary. Now it has 10 faculties and more than 17 000 full-time students. These Joint Conferences were initiated by the Eötvös Loránd University in Budapest and the Babes¸-Bolyai University in Cluj-Napoca. However, with an increasing number of participants, several other universities entered this cooperation: It is important to note that there were always participants from countries different from Hungary and Romania as well. The first five Joint Conferences took For this Conference there are registered more than 110 participants with more than 90 talks. We hope that this Conference will contribute to deepen the old and to initiate new friendships and will lead to an intensive exchange of scientific ideas. This year's program includes also a Workshop on Quantum Information Processing, but its abstracts are not presented here. On behalf of the local organizers, we wish to all participants an inspirating scientific atmosphere and an enjoyable stay in Pécs.
Enhancement Throughput of Unplanned Wireless Mesh Networks Deployment Using Partitioning Hierarchical Cluster (PHC)

Wireless mesh networks based on IEEE 802.11 technology are a scalable and efficient solution for next generation wireless networking to provide wide-area wideband internet access to a significant number of users. The deployment of these wireless mesh networks may be within different authorities and without any planning, they are potentially overlapped partially or completely in the same service area. The aim of the proposed model is design a new model to Enhancement Throughput of Unplanned Wireless Mesh Networks Deployment Using Partitioning Hierarchical Cluster (PHC), the unplanned deployment of WMNs are determinates there performance. We use throughput optimization approach to model the unplanned WMNs deployment problem based on partitioning hierarchical cluster (PHC) based architecture, in this paper the researcher used bridge node by allowing interworking traffic between these WMNs as solution for performance degradation. Keywords—Wireless Mesh Networks, 802.11s Internetworking, partitioning Hierarchical Cluste.
The Comparison between Robotic and Manual Ablations in the Treatment of Atrial Fibrillation: A Systematic Review and Meta-Analysis

Objective To examine in what aspects and to what extent robotic ablation is superior over manual ablation, we sought to design a meta-analysis to compare clinical outcomes between the two ablations in the treatment of atrial fibrillation. Methods and Results A literature search was conducted of PubMed and EMBASE databases before December 1, 2013. Data were extracted independently and in duplicate from 8 clinical articles and 792 patients. Effect estimates were expressed as weighted mean difference (WMD) or odds ratio (OR) and the accompanied 95% confidence interval (95% CI). Pooling the results of all qualified trials found significant reductions in fluoroscopic time (minutes) (WMD; 95% CI; P: -8.9; -12.54 to -5.26; <0.0005) and dose-area product (Gy×cm2) (WMD; 95% CI; P: -1065.66; -1714.36 to -416.96; 0.001) for robotic ablation relative to manual ablation, with evident heterogeneity (P<0.0005) and a low probability of publication bias. In subgroup analysis, great improvement of fluoroscopic time in patients with robotic ablation was consistently presented in both randomized and nonrandomized clinical trials, particularly in the former (WMD; 95% CI; P: -12.61; -15.13 to -10.09; <0.0005). Success rate of catheter ablation was relatively higher in patients with robotic ablation than with manual ablation (OR; 95% CI; P: 3.45; 0.24 to 49.0; 0.36), the difference yet exhibiting no statistical significance. Conclusions This study confirmed and extended previous observations by quantifying great reductions of fluoroscopic time and dose-area product in patients referred for robotic ablation than for manual ablation in the treatment of atrial fibrillation, especially in randomized clinical trials.
Do Equity Preferences Matter in Climate Negotiations? An Experimental Investigation

This paper investigates in how far equity preferences may matter for climate negotiations. For this purposes we conducted a simple experiment with people who have been involved in international climate policy. The experiment, which was run via the Internet, consisted of two simple non-strategic games suited to measure the parameters of inequity aversion in a Fehr and Schmidt (1999) utility function. We find that our participants show aversion against advantageous as well as disadvantageous inequity to a considerable amount. Moreover, the degree of inequity aversion is higher compared to that of students in the similar study of Dannenberg et al. (2007). Regarding the geographical variety in our sample, we cannot confirm significant differences in the degree of inequity aversion between different regions in the world, which is in line with previous findings from the experimental literature. This finding lends support to the hypothesis that equity preferences are "hard-wired" and not much influenced by socio-economic or cultural circumstances.
Inhomogeneous Measurement High-speed Reconstruction Method of Image Block Compressed Sensing

The complexity of block compressed sensing of images algorithm is very high. And it is too difficult to apply the algorithm on hardware platform. A low complexity compressed sensing method based on non-uniform measurement is presented in this paper which use different measurement to the transform domain coefficient with different significance of every image blocks. And as the experimental results on PC platform suggest, the proposed method is better than original method on reconstructed image's subjective and objective quality. And this method is optimized and implemented on a high performance digital signal processor TMS320C6455 platform including algorithm structure design and C code opti- mization according to the hardware feature. It is also faster than original method and it get about 4 times speedup on the DSP platform after optimization. The proposed method can be combined with the existing image and video compression scheme very easily.
Chronic lymphocytic leukemia cell segmentation from microscopic blood images using watershed algorithm and optimal thresholding

Chronic lymphocytic leukemia (CLL) is the most common type of blood cancer in Canadian adults. CLL cells are abnormal lymphocytes, which tend to be slightly larger than normal resting lymphocytes and have a condensed appearance to their chromatin. There is a low number of related works on this disease. This paper presents a method to segment normal and CLL lymphocytes into two parts: nucleus, and cytoplasm using a watershed algorithm and optimal thresholding. The goal of this work is reducing the over and under segmentation error of the watershed algorithm by suppressing 1% of the local minima. We tested 140 microscopic lymphocyte images (normal and CLL), and the algorithm obtained 99.92% maximum accuracy for nucleus segmentation, and 99.85% maximum accuracy for cell segmentation. The cytoplasm can be extracted with a 99.63% maximum accuracy with simple mask subtraction. The code for the presented algorithm is shared on the MATLAB® file exchange website.
Unsupervised segmentation of random discrete data using triplet Markov chains

The hidden Markov chain (HMC) model is a couple of random sequences ) , ( Y X , in which X is an unobservable Markov chain, and Y is its observable noisy version. Classically, HMC enables one to use different Bayesian restoration techniques. HMC model, which is powerful in hidden data restoration and widely used, has recently been extended to "triplet Markov chain" (TMC) model, which is obtained by adding a third chain U and considering the Markovianity of the triplet ) ,
Adaptive Nonlinear Approximations

The problem of optimally approximating a function with a linear expansion over a redundant dictionary of waveforms is NP-hard. The greedy matching pursuit algorithm and its orthogonalized variant produce sub-optimal function expansions by iteratively choosing the dictionary waveforms which best match the function's structures. Matching pursuits provide a means of quickly computing compact, adaptive function approximations. Numerical experiments show that the approximation errors from matching pursuits initially decrease rapidly, but the asymptotic decay rate of the errors is slow. We explain this behavior by showing that matching pursuits are chaotic, ergodic maps. The statistical properties of the approximation errors of a pursuit can be obtained from the invariant measure of the pursuit. We characterize these measures using group symmetries of dictionaries and using a stochastic di erential equation model. These invariant measures de ne a noise with respect to a given dictionary. The dictionary elements selected during the initial iterations of a pursuit correspond to a function's coherent structures. The expansion of a function into its coherent structures provides a compact approximation with a suitable dictionary. We demonstrate a denoising algorithm based on coherent function expansions. We also introduce an algorithm for adapting a dictionary for e ciently decomposing a given class of functions.
Inhibition of Protein Synthesis by Y Box-Binding Protein 1 Blocks Oncogenic Cell Transformation

ABSTRACT The multifunctional Y box-binding protein 1 (YB-1) is transcriptionally repressed by the oncogenic phosphoinositide 3-kinase (PI3K) pathway (with P3K as an oncogenic homolog of the catalytic subunit) and, when reexpressed with the retroviral vector RCAS, interferes with P3K- and Akt-induced transformation of chicken embryo fibroblasts. Retrovirally expressed YB-1 binds to the cap of mRNAs and inhibits cap-dependent and cap-independent translation. To determine the requirements for the inhibitory role of YB-1 in P3K-induced transformation, we conducted a mutational analysis, measuring YB-1-induced interference with transformation, subcellular localization, cap binding, mRNA binding, homodimerization, and inhibition of translation. The results show that (i) interference with transformation requires RNA binding and a C-terminal domain that is distinct from the cytoplasmic retention domain, (ii) interference with transformation is tightly correlated with inhibition of translation, and (iii) masking of mRNAs by YB-1 is not sufficient to block transformation or to inhibit translation. We identified a noncanonical nuclear localization signal (NLS) in the C-terminal half of YB-1. A mutant lacking the NLS retains its ability to interfere with transformation, indicating that a nuclear function is not required. These results suggest that YB-1 interferes with P3K-induced transformation by a specific inhibition of translation through its RNA-binding domain and a region in the C-terminal domain. Potential functions of the C-terminal region are discussed.
Non-recursive paired tracking for vessel extraction from retinal images

This paper reports on a novel vessel tracking algorithm being developped as part of a set of tools for the automated diagnosis of diabetic retinopathy. The algorithm tracks vessels in low-resolution optical images of the retina using their edge map as computed by the Canny edge operator. Tracking proceeds by following an edge line (which coincides with a vein border) while monitoring the connectivity of its twin border. Breaks in the connectivity trigger the creation of seeds that serve as extra starting points for future tracking. Seed creation allows the algorithm to handle bifurcations (a key issue in vessel tracking) and jump over broken or missing edges. Results are presented for ve typical fundus images.
An Algorithm for Leakage Power Reduction through IVC in CMOS VLSI Digital Circuits

current in CMOS circuits can be controlled at the circuit level and at the device level as well. One of the circuit level control techniques is the Input Vector Control (IVC). By using IVC, leakage power consumption of a circuit can be reduced in the sleep state. In this paper, an algorithm has been given to determine the optimum input vector that can be applied to the circuit in the sleep state for getting low leakage power. This algorithm uses the concept of controllability of the nodes in the circuit and the dependency of a gate on the remaining gates in the circuit to determine the optimum input vector. The proposed algorithm has been applied on an ISCAS benchmark circuit C17, the results showed that the algorithm gives a vector having a leakage nearer to the vector obtained using exhaustive search in CADENCE that gives low leakage value with less execution time as well. Keywordscurrent control, Low leakage vector, VLSI digital circuits, Low leakage power, CMOS combinational circuits.
Prevalence and Control of Hypertension and Albuminuria in South Korea: Focus on Obesity and Abdominal Obesity in the Korean National Health and Nutrition Examination Survey, 2011–2012

Background Albuminuria is associated with cardiovascular disease, and the relationship between albuminuria and hypertension is well established in many studies. So the control of hypertension is critical for decreasing cardiovascular events and albuminuria. Obesity and abdominal obesity are also associated with hypertension and albuminuria. Therefore, we analyzed the relationship between albuminuria and the prevalence and control of hypertension in the general Korean population according to obesity status. Methods We analyzed data from the 2011–2012 Korea National Health and Nutrition Examination Survey, and 9,519 subjects were included. Subjects were divided into four groups: non-obese/normal waist circumference, non-obese/high waist circumference, obese/normal waist circumference, and obese/high waist circumference. Results Systolic blood pressure and diastolic blood pressure were positively associated with albumin–creatinine ratio in all groups (all p values <0.005). Non-obese/normal waist circumference group were more likely to have hypertension (odds ratios [95% confidential intervals (CIs)] were 3.20 [2.21–4.63] in microalbuminuria level and 3.09 [1.05–9.14] in macroalbuminuria level), and less likely to have controlled hypertension (odds ratios <1 for both albuminuria levels) after adjusting for all covariates. Obese/normal waist circumference group were also more likely to have hypertension (odds ratio [95% CI] were 3.10 [1.56–6.15] in microalbuminuria level and 21.75 [3.66–129.04] in macroalbuminuria level), and less likely to have controlled hypertension in macroalbuminuria level (odds ratio [95% CI], 0.04 [0.01–0.15]). Conclusions Non-obese and normal waist circumference subjects have an increased prevalence and decreased control of hypertension in microalbuminuria and macroalbuminuria levels. Screening for albuminuria may provide helpful information about hypertension and blood pressure control, particularly in the non-obese and normal waist circumference subjects.
ITERATIVE ALGORITHMS FOR MULTICHANNEL EQUALIZATION

A fast iterative algorithm, with computation based on the fa st Fourier transform (FFT), is presented. It can be used to control a soundfield at several control points with a loudspeaker arra y f om multiple reference signals. It designs an equalizer able to invert long FIR filters and which achieves better performance than t raditionnal FFT-based deconvolution methods with a limited num ber of coefficients in the inverse filters.
BDD-based logic partitioning for sequential circuits

Presents a binary decision diagram (BDD) based approach to perform logic partitioning for sequential circuits. We use a sequential machine to model a circuit and represent the machine by its transition relation. A heuristic algorithm based on the BDD representation of the transition relation is proposed to partition the sequential machine with minimum number of input/output pins. Using BDDs and their operations, we have developed an efficient method to iteratively improve a partition. Experimental results show that our sequential logic partitioning algorithm significantly outperforms partitioning algorithms at the netlist level.
Path Planning of Autonomous Underwater Vehicles in Current Fields with Complex Spatial Variability: an A* Approach

Autonomous Underwater Vehicles (AUVs) operate in ocean environments characterized by complex spatial variability which can jeopardize their missions. To avoid this, planning safety routes with minimum energy cost is of primary importance. This work explores the benefits, in terms of energy cost, of path planning in marine environments showing certain spatial variability. Extensive computations have been carried out to calculate, by means of an A* search procedure, optimal paths on ocean environments with different length scale of eddies and different current intensities. To get statistical confidence, different realizations of the eddy field and starting-ending points of the path have been considered for each environment. Unlike previous works, the more realistic and applied case of constant thrust power navigation is considered. Results indicate that substantial energy savings of planned paths compared to straight line trajectories are obtained when the current intensity of the eddy structures and the vehicle speed are comparable. Conversely, the straight line path between starting and ending points can be considered an optimum path when the current speed does not exceed half of the vehicle velocity. In both situations, benefits of path planning seem dependent of the spatial structure of the eddy field.
Active continuous quality control

We present Active Continuous Quality Control (ACQC), a novel approach that employs incremental active automata learning technology periodically in order to infer evolving behavioral automata of complex applications accompanying the development process. This way we are able to closely monitor and steer the evolution of applications throughout their whole life-cycle with minimum manual effort. Key to this approach is to establish a stable level for comparison via an incrementally growing behavioral abstraction in terms of a user-centric communication alphabet: The letters of this alphabet, which may correspond to whole use cases, are intended to directly express the functionality from the user perspective. At the same time their choice allows one to focus on specific aspects, which establishes tailored abstraction levels on demand, which may be refined by adding new letters in the course of the systems evolution. This way ACQC does not only allow us to reveal serious bugs simply by inspecting difference views of the (tailored) models, but also to visually follow and control the effects of (intended) changes, which complements our model-checking-based quality control. All this will be illustrated along real-life scenarios that arose during the component-based development of a commercial editorial system.
False data injection attacks identification for smart grids

False Data Injection Attacks (FDIA) in Smart Grid is considered to be the most threatening cyber-physics attack. According to the variety of measurement categories in power system, a new method for false data detection and identification is presented. The main emphasis of our research is that we have equivalent measurement transformation instead of traditional weighted least squares state estimation in the process of SE and identify false data by the residual researching method. In this paper, one FDIA attack case in IEEE 14 bus system is designed by exploiting the MATLAB to test the effectiveness of the algorithm. Using this method the false data can be effectively dealt with.
Periapsis and gravitomagnetic precessions of stellar orbits in Kerr and Kerr–de Sitter black hole spacetimes

The exact solution for the motion of a test particle in a non-spherical polar orbit around a Kerr black hole is derived. Exact novel expressions for frame dragging (Lense–Thirring effect), periapsis advance and the orbital period are produced. The resulting formulae are expressed in terms of Appell's first hypergeometric function F1, Jacobi's amplitude function and Appell's F1 and Gauss hypergeometric function, respectively. The exact expression for frame dragging is applied for the calculation of the Lense–Thirring effect for the orbits of S-stars in the central arcsecond of our Galaxy assuming that the galactic centre is a Kerr black hole, for various values of the Kerr parameter including those supported by recent observations. In addition, we apply our solutions for the calculation of frame dragging and periapsis advance for stellar non-spherical polar orbits in regions of strong gravitational field close to the event horizon of the galactic black hole, e.g. for orbits in the central milliarcsecond of our galaxy. Such orbits are the target of the GRAVITY experiment. We provide examples with orbital periods in the range of 100 min–54 days. Detection of such stellar orbits will allow the possibility of measuring the relativistic effect of periapsis advance with high precision at the strong field realm of general relativity. Further, an exact closed form formula for the orbital period of a test particle in a non-circular equatorial motion around a Kerr black hole is produced. We also derive exact expressions for the periapsis advance and the orbital period for a test particle in a non-circular equatorial motion in the Kerr field in the presence of the cosmological constant in terms of Lauricella's fourth hypergeometric function FD.
A space classification-based hybrid exploration strategy for narrow and wide-open spaces

This paper addresses a problem of mobile robot exploration and map building for narrow space and wide-open space with 2D metric sensor. We estimate the type of environment with three steps of criteria, and apply different target pose extraction methods for each space. For the wide-open space, we use a concept of inverse skeleton based strategy which is proposed in this paper, while the narrow space, we use the generalized Voronoi diagram (GVD) for target point extraction. For the overlapped region of narrow space and wide-open space, we suggest a node extraction method using the uncertain region detection strategy and the GVD. With the experiments in the real environment, we show that the proposed method can be a solution for exploration with hybrid map, in indoor environments with narrow space and wide-open space.