Miracle-dz/UniFAR-FTUs huggingface dataset:
Resource sharing in RTSJ and SCJ systems

This paper reviews the currently available multiprocessor resource allocation policies and analyzes their applicability to the Real-Time Specification for Java and Safety-Critical Java. It also proposes some new RTSJ mechanisms that would facilitate the programming of a variety of synchronized object access protocols. The approach taken to managing potential deadlocks in current multiprocessor resource allocation protocols is rather simplistic. Nested resource accesses are either prohibited or the protocols resort to a "group lock". The paper considers an alternative mechanism based on deadlock prevention rather than deadlock avoidance.
Compact and robust video fingerprinting using sparse represented features

In this paper, we propose a compact and robust video fingerprinting scheme by using sparse represented features (SRF). The SRF are extracted by a two dimensional matching pursuit decomposition (2D-MPD) method. The motivation of using sparse features is that the sparse coding method can significantly reduce the data dimensionality and effectively retain the structure of the images. To further reduce the length of the fingerprint, a two-stage cascade SVD method is applied. The SVD-based feature extraction method can improve the robustness to certain attacks, such as geometric attack. Then, a locally adaptive quantization (AQ) method which considers the local probability distribution of the sample is applied. This method can quantize the real-valued fingerprints into binary bits without degrading the detection performance too much. At last, a secret key based interleaving method is applied to the binary fingerprints. The interleaving can enlarge the Hamming distance of the fingerprints, so the detection performance is improved. According to the experimental results, the proposed method offers a favourable robustness versus discriminability tradeoff over the state-of-the-art video fingerprint methods.
An automatic image based modeling system by patch growing

In this paper, we present an automatic and efficient image based modeling system which can create objects' 3D models directly from images captured from different viewpoints. The system firstly uses structure from motion to generate camera parameters and sparse 3D patches. Then, a conservative plane based sweep stereo method on GPU is used to compute quasi-dense depth maps which usually have many holes and create many new patches. Finally, a simplified patch based surface growing method is used to compute dense depth maps together with a dense 3D geometry shape model. Different from others, our system constructs patches from reconstructed points by structure from motion. These patches grow denser gradually from sparse, quasi dense to dense through the following expansion steps. During expansion, conservative strategies are used and object normal is not optimized but gradually computed from reconstructed quasi dense neighbors. This makes the system work better and faster on more difficult scenarios, e.g. wide baseline, varying illumination. Experiments show that our method can generate high fidelity 3D object shape models quite efficiently.
Physically and Chemically Evaluation for the Water Quality Criteria in a Farm on Akcay

Akcay is a high flow stream supported with strong bracket and is emerging from border of Beyagac County in Denizli province. In this study, it was performed for determining some limnological traits of Akcay River in Bozdogan County in Aydin province. This study was conducted with a 12-month period between January 2010 and December 2010. The chosen pilot farm is raising fish (Oncorhynchus mykiss). The water of Akcay River is used on farm. Some limnological parameters (dissolved oxygen, temperature, pH, EC, nitrite, nitrate, orthophosphate, minerals) were investigated for determining the water quality of zone.
Supplementary material for Shapecollage : occlusion-aware , example-based shape interpretation

As the paper explains, the basic idea is to define the local appearance score as the average difference in pixel value between the test image and the candidate patch, for pixels where ownership is nonzero. In general the average difference of pixel values is very vulnerable to slight misalignments in the matching patches. In our patch-based framework, misalignment is the rule rather than the exception. To make our metric robust to (slight) misalignment, we first blur both the test and candidate patches by a Gaussian G with σ = r/9. The score is then
DEM Registration and Error Analysis using ASCII values

Digital Elevation Model (DEM), while providing a bare earth look, is heavily used in many applications including construction modeling, visualization, and GIS. Their registration techniques have not been explored much. Methods like Coarse-to-fine or pyramid making are common in DEM-to-image or DEM-to-map registration. Self-consistency measure is used to detect any change in terrain elevation and hence was used for DEM-to-DEM registration. But these methods apart from being time and complexity intensive, lack in error matrix evaluation. This paper gives a method of registration of DEMs using specified height values as control points by initially converting these DEMs to ASCII files. These control points may be found by two mannerisms - either by direct detection of appropriate height data in ASCII files or by edge matching along congruous quadrangle of the control point, followed by sub-graph matching. Error analysis for the same has also been done.
Registration of Range Images Using Texture of High-Resolution Color Images

We propose a novel method of modeling high quality 3D model in shape and appearance by aligning multiple view range images obtained by a range scanner and multiple view color images taken by a high-resolution color camera around the object. In the proposed method, we achieve accurate registration of range images by using texture consistency of the high-resolution color images. Our registration method consists of the following two stages. First stage of registration is done by the ICP algorithm with searching corresponding points using information of the high-resolution color images. ICP algorithm is one of the registration method searching correspondence points of different range images, which greatly depends on initial position, so we improve it by using the high-resolution color images. Second stage of registration is accomplished by using difference value of the high-resolution image and the warping image. Warping image is created by viewing one data set of range image and high-resolution image from the view-point of another data set. Coordinate transformation is optimized to reduce differential error of high-resolution image and warping image from another viewpoint. This process drastically reduces misalignment of textures from another viewpoints on the surface of the ﬁnally reconstructed model. We present results that demonstrate our approach’s ability to create realistic 3D model of the actual object.
M2C2: A mobility management system for mobile cloud computing

Mobile devices have become an integral part of our daily lives. Applications running on these devices may avail storage and compute resources from the cloud(s). Further, a mobile device may also connect to heterogeneous access networks (HANs) such as WiFi and LTE to provide ubiquitous network connectivity to mobile applications. These devices have limited resources (compute, storage and battery) that may lead to service disruptions. In this context, mobile cloud computing enables offloading of computing and storage to the cloud. However, applications running on mobile devices using clouds and HANs are prone to unpredictable cloud workloads, network congestion and handoffs. To run these applications efficiently the mobile device requires the best possible cloud and network resources while roaming in HANs. This paper proposes, develops and validates a novel system called M2C2 which supports mechanisms for: i. ) multihoming, ii. ) cloud and network probing, and iii. ) cloud and network selection. We built a prototype system and performed extensive experimentation to validate our proposed M2C2. Our results analysis shows that the proposed system supports mobility efficiently in mobile cloud computing.
Position dependencies in transcription factor binding sites

MOTIVATION Most of the available tools for transcription factor binding site prediction are based on methods which assume no sequence dependence between the binding site base positions. Our primary objective was to investigate the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and to use the resulting data to develop improved scoring functions for binding-site prediction. RESULTS Using three statistical tests, we analyzed the number of binding sites showing dependent positions. We analyzed transcription factor-DNA crystal structures for evidence of position dependence. Our final conclusions were that some factors show evidence of dependencies whereas others do not. We observed that the conformational energy (Z-score) of the transcription factor-DNA complexes was lower (better) for sequences that showed dependency than for those that did not (P < 0.02). We suggest that where evidence exists for dependencies, these should be modeled to improve binding-site predictions. However, when no significant dependency is found, this correction should be omitted. This may be done by converting any existing scoring function which assumes independence into a form which includes a dependency correction. We present an example of such an algorithm and its implementation as a web tool. AVAILABILITY http://promoterplot.fmi. ch/cgi-bin/dep.html
Development and validation of a condom self-efficacy scale for college students.

This study proposed to develop and validate a scale for the college population that measures self-efficacy in using condoms. The Condom Use Self-Efficacy Scale (CUSES) was derived from several sources and consisted of 28 items describing an individual's feelings of confidence about being able to purchase condoms, put them on and take them off, and negotiate their use with a new sexual partner. This scale was administered to a sample of 768 college students. It was found to possess adequate reliability (Cronbach's alpha = .91; test-retest correlation = .81) and correlated well with the Attitude Toward the Condom Scale (r = .51) and the Contraceptive Self-Efficacy Scale for women (r = .55). Our scale also correlated with a measure of intention to use condoms (r = .40) but was unrelated to a measure of social desirability. Students who differed on measures of previous condom use as well as on sexual intercourse experience also showed significant differences on this scale in the expected direction, indicating evidence of this scale's discriminant validity. The potential uses of this scale in a college population are discussed, along with the issues underlying condom usage self-efficacy.
Experiments in Adaptive Power Control for Truly Wearable Biomedical Sensor Devices

Emerging body-wearable devices for continuous health monitoring are severely energy constrained and yet required to offer high communication reliability under fluctuating channel conditions. Such devices require very careful management of their energy resources in order to prolong their lifetime. In our earlier work we had proposed dynamic power control as a means of saving precious energy in off the-shelf sensor devices. In this work we experiment with a real body-wearable device to assess the power savings possible in a realistic setting. We quantify the power consumption against the packet loss and establish the feasibility of dynamic power control for saving energy in a truly-body-wearable setting.
Sentence Extraction for Legal Text Summarisation

We describe a system for generating extractive summaries of texts in the legal domain, focusing on the relevance classifier, which determines which sentences are abstract-worthy. We experiment with naive Bayes and maximum entropy estimation toolkits and explore methods for selecting abstract-worthy sentences in rank order. Evaluation using standard accuracy measures and using correlation confirm the utility of our approach, but suggest different optimal configurations.
Mixtures of Multinomials

We consider two different types of multinomial mixtures, (1) a wordlevel mixture, and (2) a document-level mixture. We show that the wordlevel mixture is, in fact, no different than a regular multinomial. However, the document-level mixture can produce distributions that a regular multinomial cannot. We point out that Latent Dirichlet Allocation contains a word-level mixture that can be collapsed into a single multinomial. Finally, we discuss a natural parameter variant of the word-level mixture. 1 Mixtures of Multinomials The multinomial model over term frequencies is defined as P (~x|~ μ) = l!
Refinement of LC-MS Methodology for the Analysis of Saponins

Systematic evaluation of the factors affecting LC-MS detection of some saponins and sapogenins associated with hepatogenous photo-sensitisation diseases in livestock, as determined using a Thermo Finnigan LCQ Advantage mass spectrometer, showed that ion responses could be substantially improved by careful selection of analysis parameters. Eluent composition, capillary temperatures and flow rate were found to significantly affect the ionisation of the target analytes. Optimisation of ionisation conditions resulted in a more than 100 fold (2 orders of magnitude) improvement in the detection of the model sapogenins and sapogenin glycosides relative to conditions utilised in previous studies at the University of Waikato. Optimal ESI and APCI responses were achieved using formic acid buffered acetonitrile-water eluent mixtures which possessed 30-40% acetonitrile for sapogenin glycosides or 50-60% acetonitrile for sapogenins and capillary interface temperatures in the range 275-325 C. Lower eluent flow rates also results in increased detector responses. Optimised ESI responses were greater by ca 2-10 times when compared to optimised APCI responses. Analyses of full scan and MSn ESI and APCI mass spectral fragmentation data showed that the molecular weight of conjugated sapogenin glycosides could be readily determined from [M+H]+ ions observed in full scan spectra. Under MS2 conditions sapogenin glycosides [M+H]+ ions fragmented to afford ions attributable to the protonated parent sapogenin and a series of other ions that were found to present in the ESI and APCI mass spectra of parent sapogenins, including m/z 399, m/z 273 and m/z 255 ions. Detailed analysis of full scan, MS2 and MS3 ESI and APCI fragmentation and chromatographic data determined for sarsasapogenin, episarsasapogenin, smilagenin, 20,20,23-2H3-sarsasapogenin and 2,2,4,4-2H4-episarsasapogenin, tigogenin and diosgenin showed that, unlike previously reported EI-GC-MS data, neither LC-MS ion ratio data, or retention time data could not be used to distinguish isomeric 3α/β, 5 α/β, 25(R/S)-spirostanol sapogenins of the type known to be present in the rumen and other GI tracts samples recovered from livestock suffering hepatogenous photo-sensitisation diseases. Based on the results reported in this thesis it is apparent that a combination of EI-GC-MS and LC-ESI-MSn data will be required to identify conjugated sapogenins present in rumen and other GI tract samples recovered from livestock suffering from hepatogenous photo-sensitisation diseases since LC-MSn data alone is not capable of distinguishing isomeric forms of free and conjugated sapogenins. It has been hypothesised that genetic factors may influence the nature of conjugates in the rumen and their metabolism to alternate conjugated analogues. The availability of combination of EI-GC-MS and optimised LC-MS methods to probe the nature and distribution of free and conjugated sapogenins in rumen and GI tact samples may assist in the identification of susceptible and resistant animals.
Detecting Emotions in Speech

Human language carries various kinds of information. In human computer interaction the detection of the emotional state of a speaker as re ected in his or her utterances is crucial. In this investigation we will explore how acoustic and prosodic information can be used to detect the emotional state of a speaker. We will show how prosodic information can be combined and integrated with acoustic information within a hidden Markov model architecture, which allows one to make observations at a rate appropriate for the phenomena to be modeled. Using this architecture, we will demonstrate that prosodic information adds discriminative power to the overall system.
Improved region-of-interest based rate control for error resilient HEVC framework

In this paper, we propose the improvement of Region-of-Interest (ROI) rate control on our previously proposed error resilient framework for High Efficiency Video Coding (HEVC). Reference picture selection (RPS) method and ROI-based intra refresh method are jointly considered in our previous work [6]. In addition, we also proposed ROI-based CTU depth level decision algorithm for reducing the complexity of the algorithm. To enable coding unit (CU) level intra refresh, we also integrate ROI information into the existing rate control. The ROI information is used not only for intra refresh frame but also for every frame in this paper. Experimental results show that the improved rate control contributes to the better quality than the work in [6] and HEVC with reference picture selection (RPS). For 10% packet error rate, the average PSNR improvement for 720p sequences and WVGA sequences are about 0.5 dB and 0.2 dB respectively. The maximum PSNR improvement is 0.88 dB and the minimum value is 0.13 dB. In addition, we also evaluate the impact of ROI-based CTU depth level decision module over complexity reduction by comparing proposed algorithm with and without CTU depth level decision module. Results show that ROI-based CTU depth level decision module can reduce the computational cost from 1.2% to 11.37%.
Sliding-mode control of an induction motor without flux measurement

A new approach to controlling the speed and rotor flux of an induction motor using sliding-mode theory is presented. Sabanovic's equations for an induction motor are first modified to a state-space form suitable for the present design of the algorithm. A simple control algorithm that is based on the existence of a certain positive definite matrix is proposed. The Lyapunov direct method is used to ensure reaching and sustaining of the sliding-mode. To avoid direct measurement of the rotor flux, a technique based on manipulation of Stanley's equations is introduced. Simulation studies were conducted. The control algorithm exhibited excellent drive performance in the presence of load disturbances and stator and rotor resistances changes of up to 100% of the nominal values. <<ETX>>
Green strain based FE modeling of rheological objects for handling large deformation and rotation

Rheological object, such as clay, various food products, biological organs and tissues, has both elastic and plastic properties. Modeling of such objects has not been studied intensively comparing with elastic objects. Previous rheological models were mostly based on linear constitutive law of stress and strain, which is limited to small deformation. In this paper, finite element (FE) model of rheological objects based on linear Cauchy strain tensor was summarized at first. Nonlinear FE model formulated with Green strain tensor was then presented for simulating large deformation and deformation with rotation motion. Instead of constant and symmetrical connection matrices in the linear model, nonlinear model yields non-constant and unsymmetrical connection matrices, which vary with displacements of nodal points. Simulation results with both linear and nonlinear FE models were presented to show the differences. We found that the nonlinear model formulated with Green strain tensor demonstrates more natural simulation behaviors.
An elasto-plastic model for underwater tunnels considering seepage body forces and strain-softening behaviour

This paper proposes an analytical–numerical model for elasto-plastic analysis of underwater tunnels that considers seepage body forces and strain-softening behaviour. Using the finite difference method, a theoretical solution is presented for calculation of the pore-water pressure, stress and strain distributions around the circular tunnels in axisymmetric and plain strain conditions. In this method, strain-softening behaviour and non-linear Hoek–Brown failure criterion are used. The proposed model also takes into account the effects of elastic strain increments and dilatancy angle () of the rock mass in the plastic zone. Through developing previous seepage models, a more accurate model is proposed for calculation of pore-water pressure distribution in all directions around underwater tunnels. Taking into account strain-softening behaviour of the rock mass, the stepwise method is applied to the plastic zone where parameters of strength and dilatancy, stresses, strains and deformation vary from their elasto-plastic boundary values to the tunnel boundary values. On the other hand, the analytical equations are derived for the elastic zone. Accuracy and the practical performance of the proposed model are evaluated by a number of examples. The results present the effects of seepage body forces, elastic strain increment and variations of the dilatancy angle in the plastic zone appropriately.
The fast subsampled-updating fast newton transversal filter (FSU FNTF) algorithm for adaptive filtering based on a schur procedure and the FFT

The fast Newton transversal filter (FNTF) algorithm starts from the recursive least-squares algorithm for adapting a finite impulse response filter. The FNTF algorithm approximates the Kalman gain by replacing the sample covariance matrix inverse by a banded matrix of total bandwidth 2M+1 (AR(M) assumption for the input signal). In this algorithm, the approximate Kalman gain can still be computed using an exact recursion that involves the prediction parts of two fast transversal filter (FTF) algorithms of order M. We introduce the subsampled updating (SU) approach in which the FNTF filter weights and the Kalman gain are provided at a subsampled rate, say every L samples. Because of its low computational complexity, the prediction part of the FNTF algorithm is kept as such. A Schur type procedure is used to compute various filter outputs at the intermediate time instants, while some products of vectors with Toeplitz matrices are carried out with the FFT. This leads to the fast subsampled-updating FNTF (FSU FNTF) algorithm, an algorithm that is mathematically equivalent to the FNTF algorithm in the sense that exactly the same filter output is produced. However it shows a significantly smaller computational complexity for large filter lengths at the expense of some relatively small delay. The FSU FNTF algorithm (like the FNTF algorithm) has good convergence and tracking properties. This renders the FSU FNTF algorithm very interesting for applications such as acoustic echo cancellation.