Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision-aided carrier phase estimation with selective averaging for low-cost optical coherent communication

Digital carrier phase estimation (CPE) is used in coherent optical receiver to estimate and track carrier phase. The carrier phase estimated from a single symbol is corrupted by noise; hence, it is necessary for CPE to average a block of symbols to mitigate the noise effect. Symbols with significant noise in the averaging block can severely distort the overall phase estimation, especially when the averaging block is small. We propose a selective averaging (SA) method to identify those symbols with significantly large noise and exclude them in the phase averaging process of CPE. We apply our proposed SA technique to the decision-aided maximum likelihood (DAML) CPE and demonstrate via Monte Carlo simulation and experimental results that the modified DA-ML has better optical signal-to-noise ratio (OSNR) performance compared to the conventional DAML in large laser linewidth and medium to high OSNR region.
Álgebra de mapas de atributos de solos para estimativa da aptidão agrícola das terras.

The land suitability evaluation is used to establish land zonings for agriculture activities. Geographic information systems (GIS) are useful for integrating different attributes necessaries to define apt and not apt lands. The present study had as main objective to describe procedures to define land suitability using GIS tools, soils maps and data soils profiles data, emphasizing procedures to define soil atributes. The area studied was the watershed of Corrego Espraiado, Ribeirao Preto-SP, located on the recharging area of the Guarani Aquifer, with approximately 4,130 ha and predominance of sugar cane culture. The database project was developed using the GIS Idrisi 32. The land suitability evaluation was done considering the intensive agricultural production system predominant in the watershed, adjusted for the vulnerability of the areas of recharge and for the methodology of GIS tools. Numerical terrain models (NTM) had been constructed for cation exchange capacity, basis saturation, clay content and silt+clay content using kriging (geostatistical interpolator), and for aluminum saturation using the inverse-square-distance. Boolean operations for handling geographic fields (thematic maps and NTM) to produce information plans are described and a land suitability map obtained by GIS tools is presented, indicating that 85% of watershed lands are apt to annual cultures.
Dual band compact CRLH antenna for mobile application

In this paper, we presented a compact CRLH antenna which consists of an LH line and an RH line which have different frequencies. Thus dual band operation is possible, and the frequencies can be easily changed by altering LH or RH line parameters. Impedance matching can be adjusted using the stub length. Because of its small size, printed form, dual band operation, this antenna can be utilized in mobile applications that require various frequency ranges.
Active sensing in a mormyrid fish: electric images and peripheral modifications of the signal carrier give evidence of dual foveation

SUMMARY Weakly electric fish generate electric fields with an electric organ and perceive them with cutaneous electroreceptors. During active electrolocation, nearby objects are detected by the distortions they cause in the electric field. The electrical properties of objects, their form and their distance, can be analysed and distinguished. Here we focus on Gnathonemus petersii (Günther 1862), an African fish of the family Mormyridae with a characteristic chin appendix, the Schnauzenorgan. Behavioural and anatomical results suggest that the mobile Schnauzenorgan and the nasal region serve special functions in electroreception, and can therefore be considered as electric foveae. We investigated passive pre-receptor mechanisms that shape and enhance the signal carrier. These mechanisms allow the fish to focus the electric field at the tip of its Schnauzenorgan where the density of electroreceptors is highest (tip-effect). Currents are funnelled by the open mouth (funnelling-effect), which leads to a homogenous voltage distribution in the nasal region. Field vectors at the trunk, the nasal region and the Schnauzenorgan are collimated but differ in the angle at which they are directed onto the sensory surface. To investigate the role of those pre-receptor effects on electrolocation, we recorded electric images of objects at the foveal regions. Furthermore, we used a behavioural response (novelty response) to assess the sensitivity of different skin areas to electrolocation stimuli and determined the receptor densities of these regions. Our results imply that both regions – the Schnauzenorgan and the nasal region – can be termed electric fovea but they serve separate functions during active electrolocation.
Report on the Evaluation-as-a-Service (EaaS) Expert Workshop

In this report, we summarize the outcome of the "Evaluation-as-a-Service" workshop that was held on the 5th and 6th March 2015 in Sierre, Switzerland. The objective of the meeting was to bring together initiatives that use cloud infrastructures, virtual machines, APIs (Application Programming Interface) and related projects that provide evaluation of information retrieval or machine learning tools as a service.
Optimal Sizing for a Solar Water Heating System based on Life Cycle Cost Using Genetic Algorithm

An optimization method for the optimal sizing of a solar water heating system is presented. The aim of the proposed method is to determine, among a list of commercially available devices in the actual market, the optimal sizing of components ensuring that life cycle cost is minimized subject to the constraint. The genetic algorithm is utilized for optimization design. As an example, we have designed the optimal sizing for a solar water heating system in an office building in Incheon, South Korea. The simulation results show that the developed method can obtain the optimal sizing of the components for a SWHS in a reasonable time.
Group Norm for Learning Structured SVMs with Unstructured Latent Variables

Latent variables models have been applied to a number of computer vision problems. However, the complexity of the latent space is typically left as a free design choice. A larger latent space results in a more expressive model, but such models are prone to over fitting and are slower to perform inference with. The goal of this paper is to regularize the complexity of the latent space and learn which hidden states are really relevant for prediction. Specifically, we propose using group-sparsity-inducing regularizers such as ℓ1-ℓ2 to estimate the parameters of Structured SVMs with unstructured latent variables. Our experiments on digit recognition and object detection show that our approach is indeed able to control the complexity of latent space without any significant loss in accuracy of the learnt model.
Configuring resource managers using model fuzzing: A case study of the .NET thread pool

Resource managers (RMs) often expose configuration parameters that have a significant impact on the performance of the systems they manage. Configuring RMs is challenging because it requires accurate estimates of performance for a large number of configuration settings and many workloads, which scales poorly if configuration assessment requires running performance benchmarks. We propose an approach to evaluating RM configurations called model fuzzing that combines measurement and simple models to provide accurate and scalable configuration evaluation. Based on model fuzzing, we develop a methodology for configuring RMs that considers multiple evaluation criteria (e.g., high throughput, low number of threads). Applying this methodology to the . NET thread pool, we find a configuration that increases throughput by 240% compared with the throughput of a poorly chosen configuration. Using model fuzzing reduces the computational requirements to configure the . NET thread pool from machine-years to machine-hours.
Psychology Research and Behavior Management Dovepress Calligraphy and Meditation for Stress Reduction: an Experimental Comparison

Background: Chinese calligraphic handwriting (CCH) has demonstrated a new role in health and therapy. Meanwhile, meditation is an traditional and effective method for coping with stress and staying healthy. This study compared the effectiveness of CCH and meditation as distinctive and parallel stress reduction interventions. Methods: Thirty graduate students and academic staff members in Taiwan who suffered from stress were selected by the General Health Questionnaire and randomly assigned to one of three treatment groups, ie, a CCH group, a meditation group, or a control group, for 8 consecutive weeks. Changes in physiological parameters were measured before, during, and after treatment. Results: CCH and meditation showed their strength in the respective indices of stress. There was a significant difference in respiratory rate, heart rate, and electromyographic scores between the groups. Comparing pre-and post-effects, a decrease in heart rate and an increase in skin temperature was seen in subjects who practiced CCH. Increased skin temperature and decreased respiratory rate were also seen in subjects who practiced meditation, along with reduced muscle tension and heart rate. Conclusion: CCH and meditation have good effects in stress reduction. CCH is a particularly promising new approach to reducing stress.
Working Paper Series Ict Externalities: Evidence from Cross Country Data Ict Externalities: Evidence from Cross Country Data Ict and Externalities

This paper reports the findings of an empirical study on the external effects of Information and Communication Technologies (ICT) on economic growth and productivity at an aggregate level. It focuses on possible network effects and spillovers emerging as externalities from investments in ICT. The existence of externalities is well described in theoretical work however empirical evidence is scarce. By using time series at the macro level for a panel of 15 countries I find positive externalities for investments in IT software and in telecommunication equipment, but not for IT hardware. The analysis, which accounts for cyclical effects and also takes external effects from non‐ICT factors into account, points at considerable lags between the time of investing in these technologies and the time at which the externalities arise. Taking these externality effects into account, the paper shows that the impact of ICT on productivity is almost twice as high as compared to a model that does not include such effects. Introduction Most studies that investigate the effects of Information and Communication Technologies (ICT) on productivity at the macro or the sectoral level are carried out in the tradition of growth accounting starting from the neoclassical model using a linear homogeneous production function with capital and labour as input factors and value added as a measure for output. 1,2 By assuming competitive markets for both inputs and outputs and by assuming neutral technical change, one can determine the contribution from each input factor to output or output growth. Since capital can be disaggregated into various sub categories like ICT capital, equipment, non‐residential buildings, etcetera, the contribution of each of these sub categories to economic growth can be accounted for. This allows for the determination of the contribution of ICT to economic growth, or even of sub categories within the cluster of ICT technologies to economic growth, such as hardware, software, and telecommunication equipment. Such growth accounting analysis rules out the presence of market imperfections and externalities from the outset. There is an important and growing body of literature that argues that ICT induces externalities and that externalities are an important factor of economic growth and productivity growth. If this argument indeed holds true and if externalities are positive, then the impact of ICT on economic growth is underestimated in growth accounting studies. This paper focuses on the empirical relevance of externalities arising from ICT. By using time series at the macro level …
Fatness, fitness, and cardiovascular disease risk factors in children and adolescents.

OBJECTIVE The purpose of this study was to examine differences in cardiovascular disease (CVD) risk factors across four cross-tabulated groups of cardiorespiratory fitness and body fatness in youth. METHODS Subjects included 860 males and 755 females aged 9-15 yr from the Australian Schools Health and Fitness Survey. Participants were cross-tabulated into four groups using percent body fat and estimated maximal oxygen consumption (VO2max) to split the groups. CVD risk factors included blood pressure, triglycerides (TG), fasting total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and TC:HDL-C. RESULTS In males, significant differences across groups were observed for blood pressure, TG, HDL-C, LDL-C, and TC:HDL-C (P < 0.05). In females, significant group differences were observed for blood pressure and HDL-C (P < 0.05). In females, a significant difference was also evident between those in the high-fat/high-fitness group compared with the high-fat/low-fitness group for all blood pressure measures. A general trend of lower blood pressure values for both males and females in the low-fat group compared with the high-fat group was also observed. This same trend was found for males in the blood lipids. There was a linear relationship across groups for the CVD risk score for both genders. There were also significant differences between the low- and high-fat subgroups within a fitness group for both genders. CONCLUSION The results provide evidence for the consideration of both fatness and fitness when interpreting CVD risk factors in youth, particularly among high-fat youth.
Advances in the epidemiology, diagnosis and treatment of cryptosporidiosis

Cryptosporidiosis, the disease caused by protozoa of the genus Cryptosporidium, represents a major public health problem in both developing and developed countries. The infection can be severe and life threatening among immunocompromised individuals, particularly in AIDS patients and in those with primary immunodeficiency diseases. This review examines the essential aspects of the epidemiology of the infection, highlighting the role of animals, water and food. A critical evaluation of the diagnostic tools used in clinical settings is also provided. Lastly, the review examines the chemotherapeutic options available to treat the infection, and underlines the need to design and test new drugs. The review concludes with a five-year outlook on some aspects of interest for future research on this pathogen.
Detectability of low energy X-ray spectral components in type 1 AGN

In this paper we examine the percentage of type 1 AGN which require the inclusion of a soft excess component and/or significant cold absorption in the modelling of their X-ray spectra obtained by XMM-Newton. We do this by simulating spectra which mimic typical spectral shapes in order to find the maximum detectability expected at different count levels. We then apply a correction to the observed percentages found for the Scott et al. (2011) sample of 761 sources. We estimate the true percentage of AGN with a soft excess component to be 75+/-23%, suggesting that soft excesses are ubiquitous in the X-ray spectra of type 1 AGN. By carrying out joint fits on groups of low count spectra in narrow z bins in which additional spectral components were not originally detected, we show that the soft excess feature is recovered with a mean temperature kT and blackbody to power-law normalisation ratio consistent with those of components detected in individual high count spectra. Cold absorption with nH values broadly consistent with those reported in individual spectra are also recovered. We suggest such intrinsic cold absorption is found in a minimum of ~5% of type 1 AGN and may be present in up to ~10%.
Chemotherapy options for previously untreated acute myeloid leukemia

Introduction: Intensive chemotherapy with cytarabine and an anthracycline for untreated acute myeloid leukemia (AML) has remained largely unchanged over the past 40 years, despite many large trials examining the choice and dosing of these agents. Areas covered: We will review the major published clinical trials for untreated AML that have established the dosing choice and schedule for intensive therapy, as well as trials for patients not eligible for more intensive therapy. We will also discuss treatment considerations for subgroups of patients. Expert opinion: While one or two cycles of anthracycline and cytarabine-based combination regimens remain the standard of care for younger and older patients with AML deemed fit to receive induction chemotherapy, controversy remains regarding the optimal selection and dosing schedule for anthracyclines. Low-intensity regimens, such as low-dose cytarabine and hypomethylating agents, can achieve a complete response even with adverse risk features, and can be used in a fit subset of older patients not eligible for clinical trial or transplant. Incorporation of new targeted agents, such as tyrosine kinase and small-molecule inhibitors, combined with better selection of drugs for unique patient cohorts, will likely be necessary to substantially improve outcomes in AML.
Performance study of high frequency link AC-AC converter

In this paper operation performance of an high-frequency (HF) link ac/ac converter is demonstrated using computer aided simulation package PSCAD/EMTDC. The converter consists of input filter, input matrix converter, HF transformer, and output matrix converter. The proposed configuration permits flexibility in the choice of voltage levels and frequency in the system without the penalty of bulky magnetic components. The proposed approach achieve high voltage transfer ratio, HF galvanic isolation of the input source from the output utility, higher power density by introducing a HF transformer in between the two stages of the converter. It is capable of having bidirectional power flow, achieve lower harmonic distortion on both input and output sides with proper filter design and controllable input displacement power factor. It also provides fast response, high efficiency, and free from acoustic noise. Comprehensive results are presented to assess the performance of the converter. Several features like voltage sag compensation, instantaneous voltage regulation, and power factor correction can be combined to this converter. This kind of converter laid the base for regulated ac power supplies and electronic transformers.
Linkable Ring Signature with Unconditional Anonymity

In this paper, we construct a linkable ring signature scheme with unconditional anonymity. It has been regarded as an open problem in [22] since 2004 for the construction of an unconditional anonymous linkable ring signature scheme. We are the first to solve this open problem by giving a concrete instantiation, which is proven secure in the random oracle model. Our construction is even more efficient than other schemes that can only provide computational anonymity. Simultaneously, our scheme can act as an counterexample to show that [19, Theorem 1] is not always true, which stated that linkable ring signature scheme cannot provide strong anonymity. Yet we prove that our scheme can achieve strong anonymity (under one of the interpretations).
Super Resolution Image Reconstruction Through Bregman Iteration Using Morphologic Regularization

Multiscale morphological operators are studied extensively in the literature for image processing and feature extraction purposes. In this paper, we model a nonlinear regularization method based on multiscale morphology for edge-preserving super resolution (SR) image reconstruction. We formulate SR image reconstruction as a deblurring problem and then solve the inverse problem using Bregman iterations. The proposed algorithm can suppress inherent noise generated during low-resolution image formation as well as during SR image estimation efficiently. Experimental results show the effectiveness of the proposed regularization and reconstruction method for SR image.
Symbolic crosschecking of floating-point and SIMD code

We present an effective technique for crosschecking an IEEE 754 floating-point program and its SIMD-vectorized version, implemented in KLEE-FP, an extension to the KLEE symbolic execution tool that supports symbolic reasoning on the equivalence between floating-point values. The key insight behind our approach is that floatingpoint values are only reliably equal if they are essentially built by the same operations. As a result, our technique works by lowering the Intel Streaming SIMD Extension (SSE) instruction set to primitive integer and floating-point operations, and then using an algorithm based on symbolic expression matching augmented with canonicalization rules. Under symbolic execution, we have to verify equivalence along every feasible control-flow path. We reduce the branching factor of this process by aggressively merging conditionals, if-converting branches into select operations via an aggressive phi-node folding transformation. We applied KLEE-FP to OpenCV, a popular open source computer vision library. KLEE-FP was able to successfully crosscheck 51 SIMD/SSE implementations against their corresponding scalar versions, proving the bounded equivalence of 41 of them (i.e., on images up to a certain size), and finding inconsistencies in the other 10.
Manifold‐valued Thin‐Plate Splines with Applications in Computer Graphics

We present a generalization of thin‐plate splines for interpolation and approximation of manifold‐valued data, and demonstrate its usefulness in computer graphics with several applications from different fields. The cornerstone of our theoretical framework is an energy functional for mappings between two Riemannian manifolds which is independent of parametrization and respects the geometry of both manifolds. If the manifolds are Euclidean, the energy functional reduces to the classical thin‐plate spline energy. We show how the resulting optimization problems can be solved efficiently in many cases. Our example applications range from orientation interpolation and motion planning in animation over geometric modelling tasks to color interpolation.
Efficient Hiding of Collaborative Recommendation Association Rules with Updates

We propose here an efficient data mining algorithm to hide collaborative recommendation association rules when the database is updated, i.e., when a new data set is added to the original database. For a given predicted item, a collaborative recommendation association rule set [10] is the smallest association rule set that makes the same recommendation as the entire association rule set by confidence priority. Several approaches to hide collaborative recommendation association rules from static databases have been proposed [10, 11]. However, frequent updates to the database may require repeated sanitizations of original database and added data sets. The efforts of previous sanitization are not utilized in these approaches. In this work, we propose using pattern inversion tree to store the added data set in one database scan. It is then sanitized and merged to the original sanitized database. Numerical experiments show that the proposed approach out performs the direct sanitization approach on original and added data sets, with similar side effects.