Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying visual knowledge representations: a foundation for visualization research

An exploratory effort to classify visual representations into homogeneous clusters is discussed. The authors collected hierarchical sorting data from twelve subjects. Five principal groups of visual representations emerged from a cluster analysis of sorting data: graphs and tables, maps, diagrams, networks, and icons. Two dimensions appear to distinguish these clusters: the amount of spatial information and cognitive processing effort. The authors discuss visual information processing issues relevant to the research, methodology and data analyses used to develop the classification system, results of the empirical study, and possible directions for future research. <<ETX>>
Dynamo models and differential rotation in late-type rapidly rotating stars

Received ; accepted Abstract. Increasing evidence is becoming available about not only the surface di erential rotation of rapidly rotating cool stars but, in a small number of cases, also about temporal variations, which possibly are analogous to the solar torsional oscillations. Given the present di culties in resolving the precise nature of such variations, due to both the short length and poor resolution of the available data, theoretical input is vital to help assess the modes of behaviour that might be expected, and will facilitate interpretation of the observations. Here we take a rst step in this direction by studying the variations in the convection zones of such stars, using a two dimensional axisymmetric mean eld dynamo model operating in a spherical shell in which the only nonlinearity is the action of the azimuthal component of the Lorentz force of the dynamo generated magnetic eld on the stellar angular velocity. We consider three families of models with di erent depths of dynamo-active regions. For moderately supercritical dynamo numbers we nd torsional oscillations that penetrate all the way down to the bottom of the convection zones, similar to the case of the Sun. For larger dynamo numbers we nd fragmentation in some cases and sometimes there are other dynamical modes of behaviour, including quasi-periodicity and chaos. We nd that the largest deviations in the angular velocity distribution caused by the Lorentz force are of the order of few percent, implying that the original assumed 'background' rotation eld is not strongly distorted.
Power Distribution System ( PDS ) Design : Using Bypass / Decoupling Capacitors

NOTICE OF DISCLAIMER: Xilinx is providing this design, code, or information "as is. " By providing the design, code, or information as one possible implementation of this feature, application, or standard, Xilinx makes no representation that this implementation is free from any claims of infringement. You are responsible for obtaining any rights you may require for your implementation. Xilinx expressly disclaims any warranty whatsoever with respect to the adequacy of the implementation, including but not limited to any warranties or representations that this implementation is free from claims of infringement and any implied warranties of merchantability or fitness for a particular purpose. Summary This application note specifies how to build power distribution systems for VirtexTM devices. It also covers the basic principles of power distribution systems and bypass or decoupling capacitors. A step-by-step process is described where a power distribution system can be designed and verified. The final section discusses additional sources of power supply noise and provides resolutions.
Predictive minimum Bayes risk classification for robust speech recognition

This paper presents a new Bayes classification rule towards minimizing the predictive Bayes risk for robust speech recognition. Conventionally, the plug-in maximum a posteriori (MAP) classification is constructed by adopting nonparametric loss function and deterministic model parameters. Speech recognition performance is limited due to the environmental mismatch and the ill-posed model. Concerning these issues, we develop the predictive minimum Bayes risk (PMBR) classification where the predictive distributions are inherent in Bayes risk. More specifically, we exploit the Bayes loss function and the predictive word posterior probability for Bayes classification. Model mismatch and randomness are compensated to improve generalization capability in speech recognition. In the experiments on car speech recognition, we estimate the prior densities of hidden Markov model parameters from adaptation data. With the prior knowledge of new environment and model uncertainty, PMBR classification is realized and evaluated to be better than MAP, MBR and Bayesian predictive classification.
UNITOR-CORE_TYPED: Combining Text Similarity and Semantic Filters through SV Regression

This paper presents the UNITOR system that participated in the *SEM 2013 shared task on Semantic Textual Similarity (STS). The task is modeled as a Support Vector (SV) regression problem, where a similarity scoring function between text pairs is acquired from examples. The proposed approach has been implemented in a system that aims at providing high applicability and robustness, in order to reduce the risk of over-fitting over a specific datasets. Moreover, the approach does not require any manually coded resource (e.g. WordNet), but mainly exploits distributional analysis of unlabeled corpora. A good level of accuracy is achieved over the shared task: in the Typed STS task the proposed system ranks in 1st and 2nd position.
A C ] 2 6 Fe b 20 04 SUBDIVISIONS OF TORIC COMPLEXES

We introduce toric complexes as polyhedral complexes consisting of rational cones together with a set of integral generators for each cone, and we define their associated face rings. Abstract simplicial complexes and rational fans can be considered as toric complexes, and the face ring for toric complexes extend Stanley and Reisner's face ring for abstract simplicial complexes [18] and Stanley's face ring for rational fans [19]. Given a toric complex with defining ideal I for the face ring we give a geometrical interpretation of the initial ideals of I with respect to weight orders in terms of subdivisions of the toric complex generalizing a theorem of Sturmfels in [21]. We apply our results to study edgewise subdivisions of abstract simplicial complexes.
CRITERIA FOR SYSTEM IDENTIFICATION WITH QUANTIZED DATA AND THE OPTIMAL QUANTIZATION SCHEMES

Abstract In this paper, we first examine several criteria for system identification with quantized output data and show that the ordinary parameter estimator for quantization-free case is still reasonable according to those criteria. Then, we give the optimal quantization schemes for minimizing the estimation errors under a constraint on the number of the quantized subsections of the output signals or the expectation of the optimal code length when the quantized data is encoded.
Evaluation of some English-Hindi MT systems

MT evaluation is a very important activity in MT system development. Evaluation of MT systems can help MT developers in understanding the short-comings of their systems and clear focus on the problem areas, so that systems performance can increase. In this paper we have discussed evaluation of some English-Hindi MT engines. For this, we have applied human as well as automatic evaluations of these systems. Automatic evaluation metrics across linguistic levels have been used to perform this study.
Market BuVaR: A Countercyclical Risk Metric

The malfunction of the Value-at-risk (VaR) model is a risk management failure during the 2008 credit crisis. This metric is now criticized for being too little, too late. We propose an improvement - making VaR countercyclical and more robust to fat-tails. The new metric is called, bubble-VaR (BuVaR), the expected shortfall of a trading book portfolio removed of the effects of procyclicality. It involves inflating one side of the return distribution of an asset by a scaling factor called bubble that depends on the location of the present state in the boom-bust cycle. In a boom cycle, the negative side of the distribution is inflated, in a bust cycle, the positive side is inflated. Compared to VaR, buVaR is countercyclical (it leads crashes), distinguishes between long and short positions (is asymmetrical) and provides an additional buffer for fat-tails by recognizing that crashes can happen only in the counter-trend direction. Thus, this method is useful for the purpose of a countercyclical capital buffer for market risk. The approach relaxes the VaR assumptions of i.i. d. and stationarity of variables. It postulates that empirical phenomena of fat-tails, skewness, volatility clustering and the leverage effect, can be better understood by modeling the noise and cycle components together, instead of just the noise of the time series as modeled in VaR.
Comparison of the Diagnostic Accuracy of Three Rapid Tests for the Serodiagnosis of Hepatic Cystic Echinococcosis in Humans

Background The diagnosis of cystic echinococcosis (CE) is based primarily on imaging, in particular with ultrasound for abdominal CE, complemented by serology when imaging results are unclear. In rural endemic areas, where expertise in ultrasound may be scant and conventional serology techniques are unavailable due to lack of laboratory equipment, Rapid Diagnostic Tests (RDTs) are appealing. Methodology/Principal Findings We evaluated the diagnostic accuracy of 3 commercial RDTs for the diagnosis of hepatic CE. Sera from 59 patients with single hepatic CE cysts in well-defined ultrasound stages (gold standard) and 25 patients with non-parasitic cysts were analyzed by RDTs VIRapid HYDATIDOSIS (Vircell, Spain), Echinococcus DIGFA (Unibiotest, China), ADAMU-CE (ICST, Japan), and by RIDASCREEN Echinococcus IgG ELISA (R-Biopharm, Germany). Sensitivity, specificity and ROC curves were compared with McNemar and t-test. For VIRapid and DIGFA, correlation between semiquantitative results and ELISA OD values were evaluated by Spearman’s coefficient. Reproducibility was assessed on 16 randomly selected sera with Cohen’s Kappa coefficient. Sensitivity and Specificity of VIRapid (74%, 96%) and ADAMU-CE (57%, 100%) did not differ from ELISA (69%, 96%) while DIGFA (72%, 72%) did (p = 0.045). ADAMU-CE was significantly less sensitive in the diagnosis of active cysts (p = 0.019) while DIGFA was significantly less specific (p = 0.014) compared to ELISA. All tests were poorly sensitive in diagnosing inactive cysts (33.3% ELISA and ADAMU-CE, 42.8% DIGFA, 47.6% VIRapid). The reproducibility of all RDTs was good-very good. Band intensity of VIRapid and DIGFA correlated with ELISA OD values (r = 0.76 and r = 0.79 respectively, p<0.001). Conclusions/Significance RDTs may be useful in resource-poor settings to complement ultrasound diagnosis of CE in uncertain cases. VIRapid test appears to perform best among the examined kits, but all tests are poorly sensitive in the presence of inactive cysts, which may pose problems with accurate diagnosis.
Inhibition of apoptosis in human tumour cells by the tumour-associated serpin, SCC antigen-1

The squamous cell carcinoma antigen (SCC Ag) is a tumour-associated protein and a member of theserineproteaseinhibitor (serpin) family. The SCC Ag has been used as a serologic tumour marker for SCC progression, and its elevated serum levels are a risk factor for disease relapse. However, the biologic significance of this intracytoplasmic protein in cancer cells remains unknown. In this report, we demonstrated that apoptosis induced by 7-ethyl-10-hydroxycamptothecin, tumour necrosis factor-α (TNF-α) or interleukin (IL)-2-activated natural killer (NK) cells was significantly inhibited in tumour cells transduced with the SCC Ag-1 cDNA, as compared to control cells in vitro. Also, inhibition of the SCC Ag-1 expression in tumour cells by transfection of antisense SCC Ag-1 cDNA was accompanied by significantly increased sensitivity of these cells to apoptosis induced by etoposide or TNF-α. The mechanism of protection of tumour cells from apoptosis involved inhibition of caspase-3 activity and/or upstream proteases. In vivo, tumour cells overexpressing the SCC Ag-1 formed significantly larger tumours in nude mice than the SCC Ag-1-negative controls. Thus, overexpression of the SCC Ag-1, a member of the serpin family, in human cancer cells contributed to their survival by mediating protection from drug-, cytokine- or effector cell-induced apoptosis. © 2000 Cancer Research Campaign
Secure Computation on Mobile Devices

Secure two-party computation has been an interesting theoretical concept for decades, but until recently has been considered too expensive for practical applications. With significant advances in the design and implementation of secure protocols, secure computation is becoming feasible in practice. However, with the notable exceptions of biometric identification and secure auctions, the research community has historically struggled to find realistic and useful applications for secure computation. In this work, we explore new opportunities implementing secure computing applications on rapidly evolving mobile computing platforms. Through a series of Android applications, we demonstrate the feasibility and power of secure computation protocols in this new domain. Keywords-secure computation; mobile devices; Yao’s circuits.
Radio-Frequency Tomography for Passive Indoor Multitarget Tracking

Radio-frequency (RF) tomography is the method of tracking targets using received signal-strength (RSS) measurements for RF transmissions between multiple sensor nodes. When the targets are near the line-of-sight path between two nodes, they are more likely to cause substantial attenuation or amplification of the RF signal. In this paper, we develop a measurement model for multitarget tracking using RF tomography in indoor environments and apply it successfully for tracking up to three targets. We compare several multitarget tracking algorithms and examine performance in the two scenarios when the number of targets is 1) known and constant, and 2) unknown and time varying. We demonstrate successful tracking for experimental data collected from sensor networks deployed in three different indoor environments posing different tracking challenges. For the fixed number of targets, the best algorithm achieves a root-mean-squared error tracking accuracy of approximately 0.3 m for a single target, 0.7 m for two targets and 0.8 m for three targets. Tracking using our proposed model is more accurate than tracking using previously proposed observation models; more importantly, the model does not require the same degree of training.
Intelligent file scoring system for malware detection from the gray list

Currently, the most significant line of defense against malware is anti-virus products which focus on authenticating valid software from a white list, blocking invalid software from a black list, and running any unknown software (i.e., the gray list) in a controlled manner. The gray list, containing unknown software programs which could be either normal or malicious, is usually authenticated or rejected manually by virus analysts. Unfortunately, along with the development of the malware writing techniques, the number of file samples in the gray list that need to be analyzed by virus analysts on a daily basis is constantly increasing. In this paper, we develop an intelligent file scoring system (IFSS for short) for malware detection from the gray list by an ensemble of heterogeneous base-level classifiers derived by different learning methods, using different feature representations on dynamic training sets. To the best of our knowledge, this is the first work of applying such ensemble methods for malware detection. IFSS makes it practical for virus analysts to identify malware samples from the huge gray list and improves the detection ability of anti-virus software. It has already been incorporated into the scanning tool of Kingsoft's Anti-Virus software. The case studies on large and real daily collection of the gray list illustrate that the detection ability and efficiency of our IFSS system outperforms other popular scanning tools such as NOD32 and Kaspersky.
Traceability management for impact analysis

Software change impact analysis is the activity of the software maintenance process that determines possible effects of proposed software changes. This activity is necessary to be aware of ripple-effects caused by the change and record them so that nothing is overlooked. A change has not only impact on the source code, but also on the other related software artefacts, such as requirements, design, and test. For this reason, impact analysis can be efficiently supported through traceability information. In this paper we review traceability management in the context of impact analysis and discuss the main challenges and research directions.
Alumina and LTCC Technology for RF MEMS Switches and True Time Delay Lines

The technology for the realization of RF MEMS ohmic series switches on LTCC substrates has been set up for their implementation in true time delay line configurations. Alumina and LTCC structures for validating the technological process on the individual switches have been obtained and characterized. Static delay lines on LTCC have been manufactured and tested to get the expected electrical performances for the final configuration.
HSF : Image Compression From Segmentation using Duality and Mesh Compression

We propose and implement a new image compression algorithm. Beginning with a planar straight-line graph created via image segmentation software, we create a modified dual graph consisting of triangles, with a triangle face corresponding to every polygon vertex. Using the Edgebreaker algorithm, we compress the connectivity of the triangle mesh (at a rate of about two bits per polygonal vertex) and encode the vertex and color data in the order of the connectivity of the triangle mesh. From this connectivity data, we can reconstruct the triangle mesh from which the polygonal dual graph (the original segmentation) is rebuilt. For high compression rates, we expect that our algorithm's compression ratios will be competitive with those of the JPEG and TIFF file formats, while still retaining the essential features of the image.
Object recognition for SLAM in floor environments using a depth sensor

Depth sensors have been increasingly used for object recognition in recent years. However, it is very challenging for simultaneous localization and mapping (SLAM) to make use of the forward scenes from a depth sensor. To this end, we introduce the object recognition framework for SLAM in indoor environments based on the extraction of an object-level descriptor. The proposed object-level descriptor can be obtained based on the surface appearances acquired from a depth sensor without any training. To express the surface normal distribution, a well-known descriptor, fast point feature histogram (FPFH), with a small sampling radius is used to define basic shape elements of a plane, a cylinder and a sphere. The object-level descriptor to recognize the objects can be obtained using these shape elements. Several experiments on arbitrary objects on the floor show the proposed scheme is useful in object recognition and generation of the feature map.
Shibvomgsite: a Framework for Providing Username and Password Support to Gridsite with Attribute Based Authorization Using Shibboleth and Voms

The GridSite relies on the Grid credentials for user authentication and authorization. It does not support username/password pair and attribute­based authorization. Since Public Key Infrastructure (PKI) certificate cannot be installed on all the devices a user will use, access to GridSite protected resources by users while attending conferences, at airport kiosk, working in Internet Café, on holidays etc. is not possible without exposing the certificate's private key on multiple locations. Exposing the private key on multiple locations poses a security risk. This paper describes our work in progress, called ShibVomGSite: a framework that integrates Shibboleth, VOMS and GridSite to solve this problem. ShibVomGSite issues to users a username and Time Limited Password bind to their Distinguished Name (DN) and Certificate Authority's DN in a database, which the users can later use to gain access to their attributes that are used for authorization.
Third Parties and Contract Design: The Case of Contracts for Technology Transfer

Given the challenges associated with drafting technology‐transfer contracts, we examine decisions to involve third parties offering technical or legal support in the contract‐drafting process. We first argue that the attributes of the transaction are key drivers of third‐party involvement. We then draw on the behavioral theory of the firm to develop arguments regarding the influence of third parties on contract complexity. Our results reveal that the involvement of legal third parties tends to magnify the contract's overall complexity. In contrast, the involvement of technical third parties reduces the inclusion of monitoring provisions and increases the inclusion of coordination provisions. Copyright © 2015 John Wiley & Sons, Ltd.
Benefits of Cooperation between Buyers and Providers: a study in the field of information and communications technology

This study examined the relationships between manufacturers and their distributors and retailers in the Information Technology sector. The characteristics of these relationships were identified, particularly cooperation between buyers and suppliers, and its impact on the relationship performance. Four cooperative behaviors represented the idea of cooperation. Efficiency and effectiveness were used as a performance evaluation of the relationship. Interviews with company managers were the main source of data. This research identified a significant level of cooperation within relationships, and exchange of information, joint problem-solving and flexibility were the most visible behaviors. The positive effect of cooperation in partner satisfaction concerning the relationship was observed, leading managers to the decision to buy and to a positive experience as to the relationship. The study also showed that effectiveness feeds back the process.
0 v 1 3 0 Ju n 20 05 Spin-1 / 2 particles moving on a 2 D lattice with nearest-neighbor interactions can realize an autonomous quantum computer

What is the simplest Hamiltonian which can implement quantum computation without requiring any control operations during the computation process? In a previous paper we have constructed a 10-local finite-range interaction among qubits on a 2D lattice having this property. Here we show that pair-interactions among qutrits on a 2D lattice are sufficient, too, and can also implement an ergodic computer where the result can be read out from the time average state after some postselection with high success probability. Two of the 3 qutrit states are given by the two levels of a spin-1/2 particle located at a specific lattice site, the third state is its absence. Usual hopping terms together with an attractive force among adjacent particles induce a coupled quantum walk where the particle spins are subjected to spatially inhomogeneous interactions implementing holonomic quantum computing. The holonomic method ensures that the implemented circuit does not depend on the time needed for the walk. Even though the implementation of the required type of spin-spin interactions is currently unclear, the model shows that quite simple Hamiltonians are powerful enough to allow for universal quantum computing in a closed physical system.