Miracle-dz/UniFAR-FTUs huggingface dataset:
Fingerprint Verification Using the Center of Mass and Learning Vector Quantization

This paper describes a new implementation of a mixture of techniques not used before for fingerprint recognition. The implementation consists of three stages: the location of the core, which is done through Radon transformation, the extraction of features (out of which a square fingerprint is produced with the core, and the center of the mass is obtained from it), in stage three, the resulting image is used to train the neural network in order to obtain better LVQ classification. The improvement of effectiveness is tested using two databases of fingerprints. Correct recognition rates have exceeded 90 percent, which demonstrate its great stability with fingerprints that display a well-defined core.
Tetrahedralization of Multi-material Images with Quality and Hausdor ff Distance Guarantees

We present a method for generating three-dimensional unstructured tetrahedral meshes of multi-material images. The method uses an octree as the background grid from which to build the final graded conforming meshes. The algorithm is fast and robust. It produces a small number of mesh elements and provides guaranteed bounds on the smallest dihedral angle and the two-sided Hausdorff distance between the boundaries of the mesh and the boundaries of the materials. The technique is illustrated with examples. c © 2016 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of IMR 25.
A novel multiple attributes query processing mechanism in WSN

With the rapid development of the Internet of Things, billions of smart devices should be available for sensing environment variables and reporting events that may be happened in certain regions. These devices are composed as wireless sensor networks (WSN) for supporting real-world applications. Typically, multiple attributes are usually being used together for enabling the event detection and reaction. In this setting, query processing is a challenge where multiple attributes are necessary to be sensed in a certain region interested. To remedy this issue, we propose to construct an indexing tree for facilitating query processing. Specifically, the network region is represented in terms of grid cells. An indexing tree is constructed considering the energy consumption of exchanging the same size of message between neighboring grid cells or sub-regions. Generally, queries in WSN can be classified into four types, and query mechanisms have been proposed for processing these four types of queries. The evaluation result shows that our technique is more energy efficient when the more number of attributes to be queried are considered.
MEASURING HEDGE EFFECTIVENESS FOR FAS 133 COMPLIANCE

Financial Accounting Standard (FAS) 133 requires business entities to document their anticipation of hedge effectiveness in order to qualify for hedge accounting treatment of gains and losses from financial derivatives. In the absence of specific guidelines, the accounting industry has espoused the "80-125" rule for determining hedge effectiveness. But the authors observe that meaningful assessment of anticipated hedge effectiveness must consider two distinct aspects of a firm's hedging strategy: (1) the strength of the hedging relationship, which is determined by the choice of the hedging instrument; and (2) the position taken in the hedging instrument relative to the holdings of the hedged item. They take both aspects of hedging into consideration in developing alternative measures of hedge effectiveness and distinguishing between the "potential" and "attained" effectiveness of a particular hedge. This approach enables the user to evaluate the relative merits of alternative hedging strategies to support risk management decisions, and also to document a selected hedging strategy's anticipated effectiveness for purposes of compliance with FAS 133. While the authors endorse a fairly broad interpretation of hedge effectiveness, their approach can also be used in the narrower context of an "80-125" rule. 2003 Morgan Stanley.
Chapter 1 HIGH-DIMENSIONAL OUTLIER DETECTION : THE SUBSPACE METHOD

" In view of all that we have said in the foregoing sections, the many obstacles we appear to have surmounted, what casts the pall over our victory celebration? It is the curse of dimensionality, a malediction that has plagued the scientist from the earliest days. " – Richard Bellman 1. Introduction Many real data sets are very high dimensional. In some scenarios, real data sets may contain hundreds or thousands of dimensions. With increasing dimensionality, many of the conventional outlier detection methods do not work very effectively. This is an artifact of the well known curse of dimensionality. In high-dimensional space, the data becomes sparse, and the true outliers become masked by the noise effects of multiple dimensions, when analyzed in full dimensionality. A main cause of the dimensionality curse is the difficulty in defining locality for the high dimensional case. For example, proximity-based methods define locality with the use of distance functions. On the other hand, it has been shown in [65, 215], that all pairs of points are almost equidistant in high-dimensional space. This is referred to as data spar­ sity. Since outliers are defined as data points in sparse regions, this results in a poorly discriminative situation where all data points are sit­ uated in an almost equally sparse regions in full dimensionality. The challenges arising from the dimensionality curse are not specific to out­ lier detection. It is well known that many problems such as clustering and similarity search experience qualitative challenges with increasing
Learning Electropalatograms from Acoustics

Electropalatography is a well established technique for recording information on the patterns of contact between the tongue and the hard palate during speech, leading to a stream of binary vectors called electropalatograms, consisting of elecropalatographic events - contacts or non-contacts between the tongue and the palate. A data-driven approach to mapping the speech signal onto electropalatographic information is presented. A combination of principal component analysis and support vector regression is used, yielding classification scores of more than 93% on individual electropalatographic events, for a single speaker. This may be viewed as a special case of the, well-known in the speech community, speech inversion problem which refers to inferring production parameters from the speech signal
A German Corpus for Similarity Detection Tasks

Text similarity detection aims at measuring the degree of similarity between a pair of texts. Corpora available for similarity detection are designed to evaluate the algorithms to assess the paraphrase level among documents. In this paper we present a textual German corpus for similarity detection. The purpose of our corpus is to automatically assess the similarity between a pair of texts and to evaluate different similarity measures, both for whole documents or for individual sentences. Therefore we have calculated several simple measures on our corpus based on a library of similarity functions.
Chapter 9 Multiscale Modeling of RNA Structure and Dynamics

We have developed a multiscale approach for RNA folding using discrete molecular dynamics (DMD), a rapid conformational sampling algorithm. We use a coarse-grained representation to effectively model RNA structures. Benchmark studies suggest that the DMD-based RNA model is able to accurately fold small RNA molecules (<50 nucleotides). However, the large conformational space and force field inaccuracies make it difficult to computationally identify the native states of large RNA molecules. We devised an automated modeling approach for prediction of large and complex RNA structures using experimentally derived structural constraints and tested it on several RNA molecules with known experimental structures. In all cases, we were able to bias the DMD simulations to the native states of these RNA molecules. Therefore, a combination of experimental and computational approaches has the potential to yield native-like models for the diverse universe of functionally important RNAs, whose structures cannot be characterized by conventional structural methods.
Impact of Anonymity (Unlinkability, Pseudonymity, Unobservability) on Information Sharing

Since many web users have posted their opinions and information without revealing their personal identities (i.e. demographics, social standing, or expertise), anonymity has become a common form of exchanging information in online communities, such as social media, Internet forums, social networks, etc. In the meantime, negative social consequences due to malicious comments or identity deception, have been resulted from anonymous activities in online social community. The current literature has found largely mixed results about the impact of anonymity on group outcomes. In order to clarify mixed results about anonymity in the current literature, this study proposes a new operational definition of anonymity which consists of three dimensions: unlinkability, unobservability, and pseudonymity. The data used in this study was collected from 238 online communities’ users through a web-based survey conducted in South Korea. The results show that unlinkability, unobservability and pseudonymity positively influence self-discrepancy, which in turn positively influences the quality and quantity of information sharing.
Secured histories for presence systems

As sensors become ever more prevalent, more and more information will be collected about each of us. A long-term research question is how best to support beneficial uses while preserving individual privacy. Presence systems are an emerging class of applications that support collaboration. These systems leverage pervasive sensors to estimate end-user location, activities, and available communication channels. Because such presence data are sensitive, to achieve wide-spread adoption, sharing models must reflect the privacy and sharing preferences of the users. To reflect users' collaborative relationships and sharing desires, we introduce CollaPSE security, in which an individual has full access to her own data, a third party processes the data without learning anything about the data values, and users higher up in the hierarchy learn only statistical information about the employees under them. We describe simple schemes that efficiently realize CollaPSE security for time series data. We implemented these protocols using readily available cryptographic functions, and integrated the protocols with FXPAL's myUnity presence system.
A Further Note on Alternatives to Bpref

This paper compares the robustness of information retrieval (IR) metrics to incomplete relevance assessments, using four different sets of graded-relevance test collections with submitted runs – two from TREC and two from NTCIR. We investigate the effect of reducing the original relevance data on discriminative power (i.e., how often statistical significance can be detected given the probability of Type I Error) and on Kendall’s rank correlation between two system rankings. According to these experiments, Q ′, nDCG′ and AP′ proposed by Sakai are superior to bpref proposed by Buckley and Voorhees and to Rank-Biased Precision proposed by Moffat and Zobel. We also clarify some properties of these metrics that immediately follow from their definitions.
Gappy Pattern Matching on GPUs for On-Demand Extraction of Hierarchical Translation Grammars

Grammars for machine translation can be materialized on demand by finding source phrases in an indexed parallel corpus and extracting their translations. This approach is limited in practical applications by the computational expense of online lookup and extraction. For phrase-based models, recent work has shown that on-demand grammar extraction can be greatly accelerated by parallelization on general purpose graphics processing units (GPUs), but these algorithms do not work for hierarchical models, which require matching patterns that contain gaps. We address this limitation by presenting a novel GPU algorithm for on-demand hierarchical grammar extraction that is at least an order of magnitude faster than a comparable CPU algorithm when processing large batches of sentences. In terms of end-to-end translation, with decoding on the CPU, we increase throughput by roughly two thirds on a standard MT evaluation dataset. The GPU necessary to achieve these improvements increases the cost of a server by about a third. We believe that GPU-based extraction of hierarchical grammars is an attractive proposition, particularly for MT applications that demand high throughput.
Development of a disease specific health related quality of life measure for adults and adolescents with cystic fibrosis

BACKGROUND Health related quality of life (HRQoL) measurement is important in determining the impact of disease on daily functioning and subsequently informing interventions. In cystic fibrosis (CF) generic HRQoL measures have been employed but these may not be sufficiently specific. The aim of the current work was to develop and validate a disease specific HRQoL measure for adults and adolescents with cystic fibrosis. METHODS Areas of concern to adults and adolescents with CF were identified by unstructured interviews, self-administered questionnaires, consultation with multidisciplinary specialist staff, a review of the relevant literature, and examination of other HRQoL measures. Items for the questionnaire were generated on the basis of this process. Continued evaluation and development of the Cystic Fibrosis Quality of Life (CFQoL) questionnaire was undertaken by a process of statistical analysis and continued feedback from patients. The full testing and validation of the CFQoL questionnaire took place over four phases: (1) initial item generation and testing of a preliminary questionnaire, (2) testing and validation of the second version of the questionnaire, (3) test-retest reliability of a third and final version of the questionnaire, and (4) sensitivity testing of the final version of the questionnaire. RESULTS Nine domains of functioning were identified using principal components analysis with varimax rotation. Internal reliability of the identified domains was demonstrated using Cronbach alpha coefficients (range 0.72–0.92) and item to total domain score correlations. Concurrent validity (ranger = 0.64–0.74), discriminatory ability between different levels of disease severity, sensitivity across transient changes in health (effect size range, moderate d = 0.56 to large d = 1.95), and test-retest reliability (r = 0.74–0.96) were also found to be robust. CONCLUSIONS The CFQoL questionnaire is a fully validated disease specific measure consisting of 52 items across nine domains of functioning which have been identified by, and are of importance to, adolescents and adults with cystic fibrosis. This measure will be useful in clinical trials and longitudinal studies.
Analysis on the thermal stability of the amorphous region in insulation paper

The molecular simulation at atomic level is helpful for exploring and analyzing the microscopic mechanism of various complex phenomenon of thermal stability in the transformer insulation paper. Therefore, by using the molecular dynamics (MD) method and density functional theory (DFT), this paper established the amorphous region model of cellulose in insulation paper, and analyzed its thermal stability. The force field used in the model optimization and the molecular dynamics simulation is the PCFF (Polymer Consistent Forcefield), which is suitable for the carbohydrate. After the analysis of the simulation results, it is concluded that the mechanical parameter of amorphous region hardly changed under different temperature, which indicated that operating temperature of transformer has little influence on the mechanical parameter. As the temperature increased, the molecular activities in cellulose became more active, the hydrogen bond was partly damaged and the stability in the amorphous region weakened gradually.
The contribution of early education to vulnerable and resilient developmental pathways

This study investigates the relationship between early education and cognitive and social development in young British children between the ages of 3-7 years. It is hypothesised that pre-school education might facilitate resilience in children's developmental pathways that have proved vulnerable due to the significant impact of risks. This study aimed to provide a systematic examination of the relationship between cognitive and social development, child or family specific developmental risks, and the structures and processes of early education. Adopting the methodology of secondary analysis, this study re-examined the data of the Effective Provision of Pre-school Education (EPPE) project that followed the developmental progress of nearly 3,000 British young children as they experienced different kinds of early education from 1997 to 2001 and later primary school. Three sets of longitudinal statistical analyses were carried out. First, a new method was developed for measuring the relative weight of different kinds of risks as they predict development. Second, the impact of different kinds of risks upon development during the pre-school period (ages 3-5) was examined to see whether it was lessened by high quality early education. Third, the developmental skills and abilities of children at exit from early education were studied in terms of their prediction of developmental pathways during the first two years of school (ages 5-7). Results from these three sets of analyses suggested the following: (1) validity of the new method of measuring developmental risks, (2) strong evidence of partial protection of young children's general cognitive ability when examining child level developmental risks and the quality of the processes that take place in programmes of early education, (3) that high quality early education can contribute to resilient developmental pathways during the first two years of school by boosting the vital cognitive and social skills of children at entrance to primary school. In policy terms, high quality early education programmes have the potential to serve as interventions within normal populations. Further, high quality early education programmes also have the potential to act as a type of primary prevention in a manner similar to targeted Early Interventions for children already at risk.
Review on image enhancement methods of old manuscript with the damaged background

Quite often that old documents are suffering from background damage. Examples of background damages are varying contrast, ancient document age and the documents have degraded over time due to storage conditions and the quality of the written parchment. These have damaged background for example such as: have varying contrast, smudges, dirty, presence of seeping ink from the other side of the document, uneven background. In order to make them readable, image processing offers a selection of approaches. The aim of this paper is to provide comprehensive review methods to enhance old document images with damaging background. Three kinds of enhancement methods are: (a) Image enhancement methods using binarization method or thresholding method, (b) Image enhancement methods using binarization method or thresholding method and other methods, (c) Image enhancement methods using other methods only. As conclusion, the second method has becoming more popular and has a great potential to improve in future.
Heap Dependence Analysis for Sequential Programs

Identifying dependences present in the body of sequential program is used by parallelizing compilers to automatically extract parallelism from the program. Dependence detection mechanisms for programs with scalar and static variables is well explored and have become a standard part of parallelizing and vectorizing compilers. However, detecting dependences in the presence of dynamic (heap) recursive data structures is highly complex because of the unbound and dynamic nature of the structure. The problem becomes more critical due to the presence of pointer-induced aliasing . This thesis addresses the aforementioned problem and gives a novel approach for dependence analysis of sequential programs in presence of heap data structure. The novelty of our technique lies in the two-phase mechanism, where the first phase identifies dependences for whole procedure. It computes abstract heap access paths for each heap accessing statement in the procedure. The access paths approximate the locations accessed by the statement. For each pair of statements these access paths are checked for interference. The second phase refines the dependence analysis in the context of loops. The main aspect of the second phase is the way we convert the precise access paths, for each statement, into equations that can be solved using traditional tests, e.g. GCD test, and Lamport test. The technique discovers loop dependences, i.e. the dependence among two different iterations of the same loop. Further, we extend the intra-procedural analysis to inter-procedural one. This thesis is dedicated to my parents and my beloved friend.
Gaussianity of Degree-Scale Cosmic Microwave Background Anisotropy Observations

We present results from a first test of the Gaussianity of degree-scale cosmic microwave background (CMB) anisotropy. We investigate Gaussianity of the CMB anisotropy by studying the topology of CMB anisotropy maps from the QMAP and Saskatoon experiments. We also study the QMASK map, a combination map of the QMAP and Saskatoon data. We measure the genus from noise-suppressed Wiener-filtered maps at an angular scale of about 1. °5. To test the Gaussianity of the observed anisotropy, we compare these results to those derived from a collection of simulated maps for each experiment in a Gaussian spatially flat, cosmological constant dominated, cold dark matter model. The genus-threshold level relations of the QMAP and Saskatoon maps are consistent with Gaussianity. While the combination QMASK map has a mildly non-Gaussian genus curve that is not a consequence of known foreground contamination, this result is not statistically significant at the 2 σ level. These results extend previous upper limits on the non-Gaussianity of the large angular scale (>10°) CMB anisotropy (measured by the COBE Differential Microwave Radiometer experiment) down to degree angular scales.