Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic classification of sleep apnea epochs using the electrocardiogram

This study investigated the automatic prediction of epochs of sleep apnea from the electrocardiogram. A large independently validated database of 70 single lead ECGs, each of approximately 8 hours in duration, was used throughout the study. Thirty five of these records were used for training and 35 retained for independent testing. After considering a wide variety of features the authors found that features based on the power spectral density estimates of the R-wave maxima and R-R intervals to be the most discriminating. Results show that a classification rate of approximately 89% is achievable.
The BINGO! focused crawler: from bookmarks to archetypes

The BINGO! system implements an approach to focused crawling that aims to overcome the limitations of the initial training data. To this end, BINGO! identifies, among the crawled and positively classified documents of a topic, characteristic "archetypes" and uses them for periodically re-training the classifier; this way the crawler is dynamically adapted based on the most significant documents seen so far. Two kinds of archetypes are considered: good authorities as determined by employing Kleinberg's link analysis algorithm, and documents that have been automatically classified with high confidence using a linear SVM classifier.
Accelerating design space exploration

The size of search spaces in embedded system design is one of the most critical problems during design space exploration. Pareto-Front Arithmetics (PFA) has shown to be useful to overcome this problem by decomposing a hierarchical search space and just exploring each part of the system separately. Later, the exploration results are combined at higher levels of the hierarchy. In order to decrease the exploration time, this combination is performed in the objective space only. In general, this will lead to suboptimal and infeasible results. In this paper, we present new results regarding the trade-off between the quality of the results and the exploration time.
A Direct Adaptive Predictive Functional Control Based on T-S Fuzzy Model

An adaptive predictive functional control algorithm based on T-S fuzzy model for discrete-time nonlinear systems is proposed. In this algorithm the consequent parameters of T-S fuzzy model are identified by the weighting recursive least square method. Parameters of the fuzzy model are used to directly recursively compute the model prediction output, and needn't solve Diophantine equations. Analysis solution of the predictive control input is derived. Simulation result shows that the proposed algorithm is an effective control strategy with excellent tracing ability and strong robustness
Simulation analysis of EKF and UKF implementations in PHD filter

The probability hypothesis density (PHD) filter is a practical alternative to the optimal Bayesian multi-target filter based on finite set statistics. This paper presents two extensions implementation to nonlinear models in PHD filters, namely the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), and discusses their advantage and disadvantage. The simulation scenarios with different target numbers are presented while OSPA distance, clutter parameters and execute time comparisons are also analyzed as a guide for further application research.
Control of humanoid robot motions with impacts: Numerical experiments with reference spreading control

This work explores the stabilization of desired dynamic motion tasks involving hard impacts at non-negligible speed for humanoid robots. To this end, a so-called reference spreading hybrid control law is designed showing promising results in simulation. The simulations are performed employing a dynamical model of an existing humanoid robot and impacts are assumed to be inelastic. The desired motion task consists of having the robot balancing on one foot while repeatedly making and breaking contact with a wall by means of one hand. The simulation results illustrate that the considered controller is suited to control humanoid robot motions with impacts.
Global F0 features of Mandarin L2 English — Reflection of higher level planning difficulties from discourse association and information structure

It has been reported that one major feature of global prosody in continuous speech is to express cross-phrase association and cohesion through adjustment of individual phrase intonations. Another major feature of global prosody that also requires phrase intonation to adjust is to express information structure. Both features involve multi-level large scale speech planning; their interactions multifaceted. These higher level prosodic expressions are systematic and predictable in LI speech, but these expressions are realized in L2 speech that can be attributed to foreign accent remains unknown. The current acoustic study thus attempts to address these two issues through corpus analysis with focus on normalization procedures that remove respective interactions in order to derive pattern that better reflect each feature involved. The global FO constitution of LI vs. Mandarin L2 English is compared to see the difference. As expected, respective positive correlations and patterns can be derived from LI speech whereas divergent patterns found in L2 speech provide explanations of L2 accent. Overall cumulative effects of interaction further account for how both features collectively contribute to accent specific to Mandarin L2 English. These findings are readily applicable to CALL that targets global prosody training.
Geometry Independent Surface Light Fields for Real Time Rendering of Precomputed Global Illumination

We present a framework for generating, compressing and rendering of Surface Light Field (SLF) data. Our method is based on radiance data generated using physically based rendering methods. Thus the SLF data is generated directly instead of re-sampling digital photographs. Our SLF representation decouples spatial resolution from geometric complexity. We achieve this by uniform sampling of spatial dimension of the SLF function. For compression, we use Clustered Principal Component Analysis (CPCA). The SLF matrix is first clustered to low frequency groups of points across all directions. Then we apply PCA to each cluster. The clustering ensures that the withincluster frequency of data is low, allowing for projection using a few principal components. Finally we reconstruct the CPCA encoded data using an efficient rendering algorithm. Our reconstruction technique ensures seamless reconstruction of discrete SLF data. We applied our rendering method for fast, high quality off-line rendering and real-time illumination of static scenes. The proposed framework is not limited to complexity of materials or light sources, enabling us to render high quality images describing the full global illumination in a scene.
Cm-pmi: improved web-based association measure with contextual label matching

WebPMI is a popular web-based association measure to evaluate the semantic similarity between two queries (i.e. words or entities) by leveraging search results returned by search engines. This paper proposes a novel measure named CM-PMI to evaluate query similarity at a finer granularity than WebPMI, under the assumption that a query is usually associated with more than one aspect and two queries are deemed semantically related if their associated aspect sets are highly consistent with each other. CM-PMI first extracts contextual labels from search results to represent the aspects of a query, and then uses the optimal matching method to assess the consistency between the aspects of two queries. Experimental results on the benchmark Miller Charles' dataset demonstrate the good effectiveness of the proposed CM-PMI measure. Moreover, we further fuse WebPMI and CM-PMI to obtain improved results.
A Mitochondrial Target Sequence Polymorphism in Manganese Superoxide Dismutase Predicts Inferior Survival in Breast Cancer Patients Treated with Cyclophosphamide

Purpose: Manganese superoxide dismutase protects against oxidative damage and modulates the efficacy of chemotherapeutic drugs. A functional single-nucleotide polymorphism in codon 16 of SOD2 (rs4880), which encodes manganese superoxide dismutase, results in a substitution of valine by alanine (Val16Ala). We hypothesized that this single-nucleotide polymorphism affects breast cancer survival of patients receiving chemotherapy. Experimental Design: Two patient populations from the United States (n = 248) and Norway (n = 340) were genotyped for Val16Ala. Kaplan-Meier survival and Cox proportional hazards regression analyses were used to examine the relationship between Val16Ala and disease-specific survival. Results: Val16Ala was significantly associated with breast cancer outcome in both patient populations. Carriers of the Ala allele had inferior survival rates in the multivariate analysis [hazard ratio (HR), 2.44 and 95% confidence interval (95% CI), 1.11-5.37 in U.S. cohort; HR, 1.91 and 95% CI, 1.06-3.45 in Norway cohort for Ala/Ala versus Val/Val]. In an analysis of the combined cohorts, this association was significant for patients receiving adjuvant therapy (HR, 2.47; 95% CI, 1.46-4.19), but not for patients without it (HR, 1.47; 95% CI, 0.57-3.74). After further stratification by type of chemotherapy, the effect of the Ala allele was mostly restricted to cyclophosphamide-containing chemotherapy regimens (HR, 22.0; 95% CI, 5.22-92.9; Ala/Ala versus Val/Val). Conclusion: The Val16Ala polymorphism affects survival of patients receiving cyclophosphamide-containing chemotherapy. The findings provide the first evidence pointing toward a mechanism for cyclophosphamide resistance in breast cancer patients.
Maize response to in-field rainwater harvesting on the Fort Hare/Oakleaf ecotope

The majority of rural households in the Eastern Cape Province struggle to meet basic needs especially in terms of household food security. Recent studies done in the Province indicate that agriculture contributes little to solve this problem especially in the villages around Alice. Despite poverty, most households rely on purchasing food from urban markets instead of producing food themselves. Crops are usually produced under dryland conditions by using mouldboard plough (conventional tillage) as the primary cultivation method. Research on clayey soils in semi-arid ecotopes showed that in-field rainwater harvesting technique (IR'WH) has potential to increase maize grain yield by up to 50% compared to conventional tillage (CON). The question was whether IRWH will also perform better than CON in the Alice district using Fort Hare/Oakleaf as a benchmark ecotope. The main aims of this study were to characterize important climate, soil properties and soil processes related to maize production on the selected ecotope and to compare the influence of IR WH treatments and CON on; (i) maize grain yield (ii) soil water balance components and (iii) crop-water related efficiencies. The ecotope was characterized in detail with respect to slope, long-term climate and soil characteristics. Long-term (27 years) climate data was used to analyze climate parameters which are related to maize production. A profile pit was dug next to the experimental plot and the soil was described in detail and classified using the South African Classification System. To compare the influence of IRWH treatments and CON on maize grain yield, a fully randomized complete block design experiment was used in 2004/05 and 2005/06 growing seasons. The three treatments viz. IRWH (with mulch), IRWH (without mulch) and CON were
Locus of Control, Sources of Motivation, and Mental Boundaries as Antecedents of Leader–Member Exchange Quality

In this study were examined leaders' and members' scores on locus of control, sources of motivation, and mental boundaries to predict the quality of leader–member exchanges. 80 elected officials and their 388 direct reports were sampled in a field study. Analysis indicated followers' scores on locus of control, leaders' scores of self-concept internal motivation, leaders' scores on locus of control, and followers' rated goal-internalization motivation were positively related to leader–member exchanges. Implications and directions for research are discussed.
Defining personas in games using metrics

Game metrical data are increasingly being used to enhance game testing and to inform game design. There are different approaches and techniques to gather the metrics data; however there seems to be a lack of frameworks to read and make sense of it. In this paper, the concept of play-persona is applied to game metrics, in the specific case of character-based computer games, where the player controls a single protagonist, around whom the gameplay and -- story evolves. A case is presented for Hitman: Blood Money (IO Interactive, 2007). Player-controlled game characters can be deconstructed into a range of components and these expressed as monitored game metrics. These metrics can subsequently be utilized to discover patterns of play by building play-personas: Modeled representations of how players interact with the game. This process can also be useful to assist game design, by informing whether the game facilitates the specific play patterns implied by theoretical play-personas.
Improving Native Language Identification by Using Spelling Errors

In this paper, we explore spelling errors as a source of information for detecting the native language of a writer, a previously under-explored area. We note that character n-grams from misspelled words are very indicative of the native language of the author. In combination with other lexical features, spelling error features lead to 1.2% improvement in accuracy on classifying texts in the TOEFL11 corpus by the author’s native language, compared to systems participating in the NLI shared task.
Analysis of T cell function in autoimmune murine strains. Defects in production and responsiveness to interleukin 2

In the studies reported here, we have analyzed the production and consumption of T cell growth factor, more recently termed interleukin 2 (IL-2), as well as some cell-mediated immune functions, in murine strains [MRL, BXSB, NZB, and (NZB x NZWF1] manifesting systemic lupus erythematosus (SLE)-like syndromes. Young (4-6 wk) or old (4-8 mo) autoimmune or normal mice were studied and compared with regard to the following T cell functions in vitro after stimulation with concanavalin A (Con A): (a) mitogenic response; (b) IL-2 levels in culture supernates; and (c) the ability to respond to and adsorb IL-2. In addition, proliferative activity in the allogeneic mixed leukocyte culture and frequency of alloreactive cytotoxic T lymphocyte precursors (CTLp) were analyzed in some of these strains. Reduced Con A-induced mitogenic responses and IL-2 production appeared at 3-6 wk of age in the early, severe SLE developing strains MRL-Mp-lpr/lpr (MRL/l) and male BXSB and progressed thereafter. Similar defects appeared at a later stage in MRL/Mp-+/+ and (NZB x NZW)F1 hybrid mice, which develop late disease. Detailed analysis of cells from the enlarged lymph nodes and spleens of older MRL/l mice demonstrated that such cells: (a) responded poorly to Con A or allogeneic stimulator cells, even in the presence of exogenous IL-2; (b) did not suppress IL-2 production by normal spleen cells; (c) were relatively incapable of adsorbing or inactivating IL-2; and (d) had a markedly reduced anti-H-2b CTLp frequency in the mesenteric lymph nodes but a normal one in spleen. These results indicate that the proliferating Thy-1.2+, Lyt-1+ T cells in MRL/l mice are defective in their responses to mitogenic stimuli, in IL-2 production, and in expression of acceptor sites for IL-2. The relevance of these defects to the MRL/l disease as well as to the role of IL-2 in autoimmunity in general remains to be determined.
PDE battery model simplification for charging strategy evaluation

A safe, fast charging strategy is desired in the utilisation of rechargeable Lithium-ion batteries. Traditionally, experimental methods are used in exploring and evaluating new strategies, but these require extensive time and cost. This paper aims to establish a model-based system for quick and accurate evaluation of charging strategies. Starting from a nonlinear coupled partial differential equation (PDE) battery model that accurately captures system dynamics, simplification techniques are conducted based on the identification of separable time scales within the states. By pertinent use of a singular perturbation approach, a PDE model simplification framework containing families of simplified battery models is established. All assumptions are explicitly stated and shown to enable families of simplified models to be rigorously justified. An evaluation procedure synthesised from the simplified models and averaging theory is proposed. This procedure is implemented on several typical battery charging strategies. The benefits relative to simulation on other higher order models are assessed in terms of computational efficiency and accuracy and demonstrate significant computational savings are possible with the proposed approach.
Time aggregation problems in Financial Time Series

The aim of this communication is to analyse the process of estimation of the adequate time unit in financial series. The problem in time aggregation is the loss of information, that will be acceptable if it is possible to fit a financial model. We present an example of time aggregation problems in Financial Time series over the daily Deutsche Aktienindex (DAX) using three comparative methods: descriptive statistics, Fourier analysis and Artificial Neural Networks.
Active thermal control for reliability improvement of MOS-gated power devices

This paper proposes an Active Thermal Control (ATC) method for MOS-gated power switches aimed at reducing temperature swing amplitude during operation. It leverages on the fact that thermal cycle amplitude of many actuation system components (such as power devices) has a large impact on the system reliability and lifetime. These figures can then be improved, which eases the adoption of electrification in markets, such as transportation, where they are still below target values. The proposed ATC method leaves electric load parameters untouched, while acting dynamically on gate parameters, namely voltage and resistance. A model-predictive control (MPC) strategy is used to determine the most suitable parameters to use. Simulations of the control scheme are presented first, to predict the potential benefits on temperature swing amplitude, and the consequent improvements in terms of device lifetime are inferred, using literature models. Then, experimental proof of concept is presented and discussed, together with its limitations and drawbacks.
Towards optimal post-fault self-healing in future smart distribution grids

This paper deals with a key functionality of the future distribution smart grids namely the automatic post-fault network self-healing. To this end we propose an optimization approach that aims finding the post-fault grid topology that minimizes the amount of unsupplied energy to consumers. The approach extends existing optimization models, developed in the context of losses minimization, for our particular application and proposes ways to overcome their limitations. We prove the interest of the approach on a 33-bus benchmark distribution system as well as on a 61-bus real-life distribution grid.
Slice-processors: an implementation of operation-based prediction

We describe the Slice Processor micro-architecture that implements a generalized operation-based prefetching mechanism. Operation-based prefetchers predict the series of operations, or the computation slice that can be used to calculate forthcoming memory references. This is in contrast to outcome-based predictors that exploit regularities in the (address) outcome stream. Slice processors are a generalization of existing operation-based prefetching mechanisms such as stream buffers where the operation itself is fixed in the design (e.g., address + stride). A slice processor dynamically identifies frequently missing loads and extracts on-the-fly the relevant address computation slices. Such slices are then executed in-parallel with the main sequential thread prefetching memory data. We describe the various support structures and emphasize the design of the slice detection mechanism. We demonstrate that a relatively simple organization can significantly improve performance over an aggressive, dynamically-scheduled processor and for a set of pointer-intensive programs and for some integer applications from the SPEC'95 suite. In particular, a slice processor that can detect slices of up to 8 instructions extracted over of a region of up to 32 instructions improves performance by 11% on the average (even if slice detection requires up to 32 cycles). Allowing slices of up to 16 instructions results in an average performance improvement of 15%. Finally, we study how our operation-based predictor interacts with an outcome-based one and find them mutually beneficial.
Routing over Bursty Wireless Links

Accurate estimation of link quality is the key to enable efficient routing in wireless sensor networks. Current link estimators focus mainly on identifying long-term stable links for routing, leaving out a potentiality large set of intermediate links offering significant routing progress. Fine-grained analysis of link qualities reveals that such intermediate links are bursty, i.e., stable in the short term. In this paper, we use short-term estimation of wireless links to accurately identify short-term stable periods of transmission on bursty links. Our approach allows a routing protocol to forward packets over bursty links if they offer better routing progress than long-term stable links. We integrate a Short Term Link Estimator and its associated routing strategy with a standard routing protocol for sensor networks. Our evaluation reveals an average of 22% reduction in the overall transmissions when routing over long-range bursty links. Our approach is not tied to any special routing protocol and integrates seamlessly with existing routing protocols and link estimators.
Harnessing Recommendations from Weakly Linked Neighbors in Reputation-Based Trust Formation

Interactions between individuals are inherently dependent upon trust, no matter if they occur in the real world or in cyber communities. Over the past years, proposals have been made to model trust relations computationally, either to assist users or for modeling purposes in multi-agent systems. These models rely implicitly on the social networks established by participating entities (be they autonomous agents or internet users). However, state-of-the-art trust frameworks often neglect the structure of those complex networks. In this paper, we present a new approach allowing agent-based trust frameworks to leverage information from so-called weak ties that would otherwise be neglected. An effective and robust voting scheme based on an agreement metric is presented and its benefit is shown through simulations.
Sicherheitsanforderungen und Sicherheitsmechanismen bei IT-Systemen

SCHLÜSSELWÖRTER Sicherheitsanforderung, Sicherheitsmechanismus, Vertraulichkeit, Integrität, Authentizität, Nichtabstreitbarkeit, Kryptosystem, Session-Key-Verfahren, One-WayHashfunktion, Trapdoor-One-Way-Funktion, Message Authentication Code, Digitale Signatur, Authentifizierungsprotokoll, Challenge&Response-Protokoll, Sicherheitsinfrastruktur, Trust Center, Public-KeyInfrastruktur, Originalität.