Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Content with Double Hashing Techniques

Image mining deals with knowledge discovery in image data bases. In Existing system they represent a data mining techniques to discover significant patterns and they introduce association mining algorithm for discovery of frequent item sets and the generation of association rules. But in the new association rule mining algorithm the completion time of the process is increased. so the proposed work in this paper is the double hashing method for generation of the frequent item sets. Double hashing is another alternative to predict the frequent item sets from tremendous amount of data sets. Double hashing is another method of generating a probing sequence.
Functional differences between statistical learning with and without explicit training

Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and prepare for incoming input. In this study, we ask whether the function of statistical learning may be enhanced through supplementary explicit training, in which underlying regularities are explicitly taught rather than simply abstracted through exposure. Learners were randomly assigned either to an explicit group or an implicit group. All learners were exposed to a continuous stream of repeating nonsense words. Prior to this implicit training, learners in the explicit group received supplementary explicit training on the nonsense words. Statistical learning was assessed through a speeded reaction-time (RT) task, which measured the extent to which learners used acquired statistical knowledge to optimize online processing. Both RTs and brain potentials revealed significant differences in online processing as a function of training condition. RTs showed a crossover interaction; responses in the explicit group were faster to predictable targets and marginally slower to less predictable targets relative to responses in the implicit group. P300 potentials to predictable targets were larger in the explicit group than in the implicit group, suggesting greater recruitment of controlled, effortful processes. Taken together, these results suggest that information abstracted through passive exposure during statistical learning may be processed more automatically and with less effort than information that is acquired explicitly.
Acoustical and topological experiments for an HMM-based speech segmentation system

Several speciﬁc tasks in the ﬁeld of text-to-speech synthesis requires a huge amount of labeled speech corpora. Mostly, these labels correspond to phone marks aligned on the speech wave-form. Different kind of solutions have been applied to this problem from rule-based systems to stochastic-based ones. We validate here a solution based on Hidden Makov Models. Various test conﬁgurations are proposed. At the acoustic level, we compare LSP to MFCC coefﬁcients and the ﬁtness of multigaussians for this segmentation task. At the topological level, we compare standard left-to-right models to phonological dependent topologies. The best conﬁguration we found is related to an MFCC analysis with standard left-to-right models and with diagonal multi-gaussians per state. For this conﬁguration the overall root mean squared error on the test database is 18 (cid:6) 0 : 3 ms within a 99% conﬁdence interval.
Hydroxylated aAl 2 O 3 ( 0001 ) surfaces and metal / aAl 2 O 3 ( 0001 ) interfaces

X-ray photoelectron spectroscopy was applied to study the hydroxylation of a-Al2O3 (0001) surfaces and the stability of surface OH groups. The evolution of interfacial chemistry of the a-Al2O3 (0001) surfaces and metal/a-Al2O3 (00 01) interfaces are well illustrated via modifications of the surface O1s spectra. Clean hydroxylated surfaces are obtained through waterand oxygen plasma treatment at room temperature. The surface OH groups of the hydroxylated surface are very sensitive to electron beam illumination, Ar sputtering, UHV heating, and adsorption of reactive metals. The transformation of a hydroxylated surface to an Al-terminated surface occurs by high temperature annealing or Al deposition. 2006 Elsevier B.V. All rights reserved.
Density of Wild Prey Modulates Lynx Kill Rates on Free-Ranging Domestic Sheep

Understanding the factors shaping the dynamics of carnivore–livestock conflicts is vital to facilitate large carnivore conservation in multi-use landscapes. We investigated how the density of their main wild prey, roe deer Capreolus capreolus, modulates individual Eurasian lynx Lynx lynx kill rates on free-ranging domestic sheep Ovis aries across a range of sheep and roe deer densities. Lynx kill rates on free-ranging domestic sheep were collected in south-eastern Norway from 1995 to 2011 along a gradient of different livestock and wild prey densities using VHF and GPS telemetry. We used zero-inflated negative binomial (ZINB) models including lynx sex, sheep density and an index of roe deer density as explanatory variables to model observed kill rates on sheep, and ranked the models based on their AICc values. The model including the effects of lynx sex and sheep density in the zero-inflation model and the effect of lynx sex and roe deer density in the negative binomial part received most support. Irrespective of sheep density and sex, we found the lowest sheep kill rates in areas with high densities of roe deer. As roe deer density decreased, males killed sheep at higher rates, and this pattern held for both high and low sheep densities. Similarly, females killed sheep at higher rates in areas with high densities of sheep and low densities of roe deer. However, when sheep densities were low females rarely killed sheep irrespective of roe deer density. Our quantification of depredation rates can be the first step towards establishing fairer compensation systems based on more accurate and area specific estimation of losses. This study demonstrates how we can use ecological theory to predict where losses of sheep will be greatest, and can be used to identify areas where mitigation measures are most likely to be needed.
Grid Security and Integration with Minimal Performance Degradation

Computational grids are believed to be the ultimate framework to meet the growing computational needs of the scientific community. Here, the processing power of geographically distributed resources working under different ownerships, having their own access policy, cost structure and the likes, is logically coupled to make them perform as a unified resource. The continuous increase of availability of high-bandwidth communication as well as powerful computers built of low-cost components further enhance chances of computational grids becoming a reality. However, the question of grid security remains one of the important open research issues. Here, we present some novel ideas about how to implement grid security, without appreciable performance degradation in grids. A suitable alternative to the computationally expensive encryption is suggested, which uses a key for message authentication. Methods of secure transfer and exchange of the required key(s) are also discussed.
Low-Level Laser Therapy and the Recovery of Muscle Function After a Single Session of Neuromuscular Electrical Stimulation: A Crossover Trial

Abstract Introduction. Neuromuscular electrical stimulation is applied in muscle atrophy and in muscle strength and endurance training in athletes. Muscle soreness and temporary reduction in muscle strength may occur as adverse effects. Laser therapy has been used as a method of counteracting delayed onset muscle soreness following volitional exercise, but not following electrical stimulation. The aim of the study was to determine whether low-level laser therapy applied prior to electrical stimulation accelerates the recovery of muscle strength and decreases the duration and intensity of muscle soreness at rest after intensive isometric neuromuscular electrical stimulation of the quadriceps femoris muscle. Material and methods. A randomised crossover trial was carried out on 24 healthy, recreationally active men aged 22-24 years. Low-level laser therapy or sham laser therapy was applied prior to a single session of neuromuscular electrical stimulation of the quadriceps femoris muscle with typical technical and training-related parameters. Irradiations were performed immediately prior to and shortly after electrical stimulation as well as 24, 48, 72, and 96 hours after this procedure. Muscle soreness was examined using the VAS scale in the same time periods. Quadriceps moments of force were recorded with the use of a Biodex 4 Pro device during maximum voluntary static contraction and during electrical stimulation that triggered a tetanic contraction of the quadriceps femoris muscle reaching the level of maximum tolerance. Results. No significant differences were noted in the severity of quadriceps soreness and in the magnitude of the decrease in the moments of force of maximum voluntary contractions after stimulation preceded by laser therapy and that preceded by sham irradiations. Conclusions. In the group studied, laser therapy applied before single electrical stimulation with typical parameters did not bring about a faster recovery of muscle strength or a more rapid decrease in soreness than sham laser therapy used prior to electrical stimulation. Further research on larger groups of subjects with the application of various procedures as well as research on training programmes is needed.
Application of Support Vector Machines to Accelerate the Solution Speed of Metaheuristic Algorithms

The support vector machine (SVM) is proposed as a response surface model to accelerate the solution speed of metaheuristic algorithms in solving inverse problems. The detail formulations of the SVM regression model using epsiv-insensitive loss function are derived. Primary numerical results are reported to demonstrate the feasibility, performance, and robustness of the proposed SVM based response surface model for solving both mathematical functions and engineering design problems.
Exploiting known unknowns: Scene induced cross-calibration of lidar-stereo systems

We propose an automatic, targetless, data-driven, extrinsic calibration method to calibrate push-broom 2D lidars with a multi-camera system. The calibration problem is decoupled into alternating optimisers over two hierarchical levels, where both levels are linked with a penalty term. The lower-level optimises the six degrees-of-freedom (DoF) rigid-body transforms between the lidar and each camera of the multi-camera unit by minimising the Normalised Information Distance between intensity measurements obtained from both sensor modalities. The upper-level minimises a nonlinear least squares error between the lower-level solutions. We describe the theory, implement the method, and provide a detailed performance analysis with experiments on real-world data.
Multi-ISP Cooperative Cache Sharing for Saving Inter-ISP Transit Cost in Content Centric Networking

Content-Centric Networking (CCN) has an in-network caching mechanism, which can reduce the traffic volume along the route to the destination host. This traffic volume reduction on the transit link can decrease inter-ISP transit cost. However, the memory space for caching in CCN routers is small relative to content volume. In addition, any initial access to the content requested by a user must use the transit link, even when a nearby CCN router outside the route has the cached content. In this paper, we propose a method of cooperative cache sharing among CCN routers in multiple ISPs. It aims to attain a further reduction in the inter-ISP transit cost by improving the cache hit ratio. In the proposed method, the CCN routers share the memory space for caching of non-overlapping cache content. We evaluate the proposed method by simulation experiments using the IP-level network topology of actual ISP, and show that the inter-ISP transit traffic can be reduced by up to 28% compared with normal caching behavior of CCN. key words: Content-Centric Networking, in-network caching, cache sharing, inter-ISP transit cost
Multidisciplinary co-operation in building design according to urbanistic zoning and seismic microzonation

Abstract. Research and practice in seismology and urban planning interfere concerning the impact of earthquakes on urban areas. The roles of sub-area wide or typological divisions of the town were investigated with the methodology of regression, regarding their contribution to urban earthquake risk management. The inductive data set comprised recovery, preparedness, mitigation and resilience planning. All timely constituted planning types are refound today as layers, as the zoning results are used by differently backgrounded actors: local authorities, civil protection, urban planners, civil engineers. In resilience planning, the urban system is complexly theoretised, then integratedly approached. The steady restructuring process of the urban organism is evident in a dynamic analysis. Although expressed materially, the "urban-frame" is realised spiritually, space adaptation being also social. A retrospective investigation of the role of resilient individual buildings within the urban system of Bucharest, Romania, was undertaken, in order to learn systemic lessons considering the street, an educational environment. (In)formation in the study and decision making process stay in a reciprocal relationship, both being obliged in the (in)formation of the public opinion. For a complete view on resilience, both zoning types, seismic and urbanistic, must be considered and through their superposition new sub-area wide divisions of the town appear, making recommendations according to the vulnerability of the building type.
A Practical Approach for Routing and Wavelength Assignment in Large Wavelength-Routed Optical Networks

We consider large optical networks in which nodes employ wavelength-routing switches which enable the establishment of wavelength-division-multiplexed (WDM) channels, called lightpaths, between node pairs. We propose a practical approach to solve routing and wavelength assignment (RWA) of lightpaths in such networks. A large RWA problem is partitioned into several smaller subproblems, each of which may be solved independently and efficiently using well-known approximation techniques. A multicommodity flow formulation combined with randomized rounding is employed to calculate the routes for lightpaths. Wavelength assignments for lightpaths are performed based on graph-coloring techniques. Representative numerical examples indicate the accuracy of our algorithms.
Practical Network Coding for Two Way Relay Channels in LTE Networks

In this paper, the implementation aspects and constraints of the simplest network coding (NC) schemes for a two-way relay channel (TWRC) composed of a user equipment (mobile terminal), an LTE relay station (RS) and an LTE base station (eNB) are considered in order to assess the usefulness of the NC in more realistic scenarios. The information exchange rate gain (IERG), the energy reduction gain (ERG) and the resource utilization gain (RUG) of the NC schemes with and without subcarrier division duplexing (SDD) are obtained by computer simulations. The usefulness of the NC schemes are evaluated for varying traffic load levels, the geographical distances between the nodes, the RS transmit powers, and the maximum numbers of retransmissions. Simulation results show that the NC schemes with and without SDD, have the throughput gains $0.5\%$ and $25\%$, the ERGs $7-12\%$ and $16-25\%$, and the RUGs $0.5-3.2\%$, respectively. It is found that the NC can provide performance gains also for the users at the cell edge. Furthermore, the ERGs of the NC increase with the transmit power of the relay while the ERGs of the NC remain the same even when the maximum number of retransmissions is reduced.
Utilizing Object Compression for Better J2ME Remote Method Invocation in 2.5G Networks

This paper introduces two new Java 2 Platform Micro Edition (J2ME) Remote Method Invocation (RMI) packages. These packages make use of serialized object compression and encryption in order to respectively minimize the transmission time and to establish secure channels. The currently used J2ME RMI package does not provide either of these features. Our packages substantially outperform the existing Java package in the total time needed to compress, transmit, and decompress the object for General Packet Radio Service (GPRS) networks, often called 2.5G networks, even under adverse conditions. The results show that the extra time incurred to compress and decompress serialized objects is small compared to the time required to transmit the object without compression in GPRS networks. Existing RMI code for J2ME can be obliviously used with our new packages.
Inhibition of Hms Oncogene Transformation of NIH 3 T 3 Cells by Protease Inhibitors 1

The protease inhibitors antipain, leupeptin, Â«,-antitrvpsin, and . -aminocaproic acid were found to inhibit transformation of NIH3T3 cells after transfection with an activated H-nu oncogene. Inhibition of focus formation by protease inhibitors was concentration dependent and maximal at 50% of control values. Transfection of a gene for neomycin resistance was not affected by protease inhibitors. Antipain was inactive if present only during the first 2 days of the gene transfer protocol or only during the final 10 days of the experiment. However, the full effect was observed when antipain was added at the subculture step on day 3 and during the subsequent cell proliferation. If cells were not subcultured, the yield of the foci per Â«Â¿g of DNA was sharply reduced and addition of antipain did not further suppress the transformation rate. Subculture of NIH3T3 cells 3 days after transfection at lower cell densities resulted in higher transformation efficiency. The results suggest that transformation of NIH3T3 cells by a single mutated oncogene may involve multiple stages including cell proliferation and that part of this process is susceptible to inhibition by protease inhibitors.
Application of Computational Intelligence to Predict Churn and Non-Churn of Customers in Indian Telecommunication

In the modern society, mobile communication became the leading medium of communication. Now the public policies and standardization of mobile communication allows customers to switch from one service provider to another service provider easily. One of the most critical challenges in data and voice telecommunication service industry is retaining customers. The cost of retaining an existing customer is lesser than the cost of getting a new customer. So service providers now shifted their focus from customer acquisition to customer retention. As a result, churn prediction has emerged as the most essential Business Intelligence (BI) application that aims to identify the customers who are about to transfer their service to a competitor i.e. To churn. In this paper, we proposed Counter Propagation Neural Networks (CPNN), Classification and Regression Trees (CART), J48 and fuzzy ARTMAP to predict customer churn and non-churn in telecommunication sector. The dataset analyzed is taken from Indian Telecommunication Service Industry.
Investigating the Relationship between Foreign Language Anxiety and Oral Performance of Non-English Major University Students in Indonesia

This quantitative study was conducted to find out the relationship between Foreign Language Anxiety (FLA) and the achievements of non-English major university students in Indonesia. Through descriptive analysis, the study found that learners experienced various degrees of FLA with the mean score 93.07 (SD = 17.69, N = 119). This study also found a statistically significant, negative correlation between the learners’ FLA and their achievements as measured with their grades, r (117) = -. 37, p < . 01. Consistent with that, significant, negative relationships were also found between the learners' achievements and all the three related situation-specific anxieties, namely, communication apprehension, test anxiety, and fear of negative evaluation. Considering the results, it is suggested that both teachers and students should minimise the debilitating effects of students’ FLA. Based on the limitations of this study, some recommendations for future researches are also stated. Suggested directions of future researches on FLA in Indonesia are investigations on the relationship between FLA and achievements across different levels of education as well as thorough qualitative investigations of FLA. Keywords: Foreign Language Anxiety, learners’ achievements, correlations.
Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation

We describe predictions of the structures of CASP5 targets using Rosetta. The Rosetta fragment insertion protocol was used to generate models for entire target domains without detectable sequence similarity to a protein of known structure and to build long loop insertions (and N‐and C‐terminal extensions) in cases where a structural template was available. Encouraging results were obtained both for the de novo predictions and for the long loop insertions; we describe here the successes as well as the failures in the context of current efforts to improve the Rosetta method. In particular, de novo predictions failed for large proteins that were incorrectly parsed into domains and for topologically complex (high contact order) proteins with swapping of segments between domains. However, for the remaining targets, at least one of the five submitted models had a long fragment with significant similarity to the native structure. A fully automated version of the CASP5 protocol produced results that were comparable to the human‐assisted predictions for most of the targets, suggesting that automated genomic‐scale, de novo protein structure prediction may soon be worthwhile. For the three targets where the human‐assisted predictions were significantly closer to the native structure, we identify the steps that remain to be automated. Proteins 2003;53:457–468. © 2003 Wiley‐Liss, Inc.
SPARSE COLLABORATIVE APPEARANCE MODEL USING ROBUST OBJECT TRACKING 1

Sparse model has been applied to visual tracking to find the target with the minimum reconstruction error from the target templates subspace. An active video surveillance system using a robust object tracking algorithm which is based on a sparse collaborative model that performs both holistic templates and local representations to account for drastic appearance changes. Within the collaborative appearance model, we use a sparse generative model (SGM) and sparse discriminative classifier (SDC) for object tracking. In the SDC module, for separating the foreground object from the background based on holistic we present a classifier. In the SGM module, a histogram-based method proposed by us that takes the spatial information of each local patch into consideration. The update scheme considers both the original templates and most recent observations, thereby enabling the algorithm to deal with appearance changes alleviate and effectively the tracking drift problem. number of experiments on various challenging videos illustrate that the tracker performs fairly against several state-of-the-art algorithms.