Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges in developing a high-quality surface wind-speed data-set for Australia

One of the main drivers for this project is the requirement to complement other high-quality surface data-sets with surface wind data for use in climate change detection and attribution studies. The high-quality data may also be used to analyse trends in storminess. Investigations highlighted the following three issues: Over the last two decades Automatic Weather Stations (AWS) have been installed at a large number of locations over the Australian region. The majority of newly installed wind instruments are rotating cup anemometers (Synchrotac), in many cases replacing older types, such as pressure tube anemometers (Dines). The corresponding changes in instrumentation alone can significantly change the characteristics of observed wind speed. Daylight Saving Time (DST) is in effect in the majority of Australian States, typically for a period from late October to late March. During this period, observations are taken according to DST rather than Local Standard Time (LST). Observations taken one hour earlier (compared with LST) can significantly affect the measured wind speed relative to climatology at a particular time. Estimates of daily mean wind speed depend on the frequency of synoptic observations. The frequency of these observations typically increases towards the latter part of the record, in some cases from two observations (at 0900 and 1500) to eight observations a day (at three-hourly intervals). Depending on the number of synoptic observations used to derive the daily mean wind speed, the true value may be significantly overor underestimated.
Cushionware: a practical sitting posture-based interaction system

Sitting posture-based interaction is to leverage user's sitting posture as an input for interaction. In order to realize it, user's sitting posture needs to be recognized accurately. However, existing works on sitting posture recognition either use intrusive wearable/visual sensors or rely on expensive high-resolution pressure sensor array, and thus hindering the widespread adoption. In this work, we introduce Cushionware, a practical sitting posture recognition system that is based on sparse pressure sensor array. Pressure sensor array is placed within the chair cushion to collect pressure data while user is sitting. After collecting the data, we first model sitting posture by extracting a set of user-invariant features and then identify the sitting posture using machine learning method. To demonstrate the utility of Cushionware, we develop two applications including video game playing and wheelchair motion control.
RTPS middleware for real-time distributed industrial vision systems

Designing and constructing real-time distributed industrial vision systems (RT-DIVS) from scratch is very complicated task. RT-DIVS has conflicting requirements such as reasonable development cost, ease of use, reusable code and high performance. The success key in building such systems is to recognize the need for middleware software. Middleware plays a major role in developing distributed systems efficiently. Real-time publish-subscribe (RTPS) model is one of the latest developments in real-time middleware technologies. Network data distribution service (NDDS) is RTPS middleware developed by real-time innovation (RTI). NDDS is widely used in real-time distributed and embedded systems for mission critical applications. The research work presented in this paper discusses the employment of NDDS for RT-DIVS and the advantages of NDDS's quality of service (QoS) policies in covering the requirements of RT-DIVS. An experimental test set-up is used to verify the NDDS's performance for RT-DIVS. Tests results show that RTPS middleware (and NDDS specifically) is suitable for soft and firm timelines requirements for distributed industrial vision systems.
Cicatricial Ectropion Secondary to Psoriatic Arthritis

Ectropion is characterized by the eversion of the eyelid margin and the consequent exposure of the conjunctiva and cornea. The shortening of the anterior lamella of the lid causes cicatricial ectropion. We described a case of skin pathology causing cicatricial ectropion. The case is about a 68-year-old woman with a 2-year history of psoriatic arthritis. She complained of eyelid tearing and redness for two years. Due to the psoriasis, she presented a very dry skin, also in the periocular region, resulting in cicatricial ectropion. A skin graft was indicated to correct the eyelid malposition. Careful investigation should be performed in patients who have a skin disease that can lead to cicatricial ectropion.
The natural history of non-alcoholic fatty liver disease in children: a follow-up study for up to 20 years

Objectives: The long-term prognosis of non-alcoholic fatty liver disease (NAFLD) in children remains uncertain. We aimed at determining the long-term outcomes and survival of children with NAFLD. Design: Retrospective longitudinal hospital-based cohort study. Patients: Sixty-six children with NAFLD (mean age 13.9 (SD 3.9) years) were followed up for up to 20 years with a total of 409.6 person-years of follow-up. Results: The metabolic syndrome was present in 19 (29%) children at the time of NAFLD diagnosis with 55 (83%) presenting with at least one feature of the metabolic syndrome including obesity, hypertension, dyslipidaemia and/or hyperglycaemia. Four children with baseline normal fasting glucose developed type 2 diabetes 4–11 years after NAFLD diagnosis. A total of 13 liver biopsies were obtained from five patients over a mean of 41.4 (SD 28.8) months showing progression of fibrosis stage in four children. During follow-up, two children died and two underwent liver transplantation for decompensated cirrhosis. The observed survival free of liver transplantation was significantly shorter in the NAFLD cohort as compared to the expected survival in the general United States population of the same age and sex (log-rank test, p<0.00001), with a standardised mortality ratio of 13.6 (95% confidence interval, 3.8 to 34.8). NAFLD recurred in the allograft in the two cases transplanted, with one patient progressing to cirrhosis and requiring re-transplantation. Conclusions: Children with NAFLD may develop end-stage liver disease with the consequent need for liver transplantation. NAFLD in children seen in a tertiary care centre may be associated with a significantly shorter survival as compared to the general population.
Studienarbeit Parallel Highway-Node Routing

Highway-Node Routing is a scheme for solving the shortest path problem showing excellent speedups over Dijkstra’s algorithm. There also is a dynamic variant that allows changes to the cost function. Based on an existing, sequential implementation, we present a parallel version of the precomputation required for Highway-Node Routing. We also present experimental results with the road network of Europe as the input. During parallelization, problems with imbalanced load and memory bandwidth limitations were encountered. We evaluated several load balancing variants and also a modification that makes the problem more regular. We also considered a scheme that tries to exploit the shared cache structure of the used machine to lessen the memory bandwidth limitation. The parallel version achieves a speedup of up to 3.1 with 4 threads and 4.5 with 8 threads over the original sequential implementation.
Human Hand Gesture Recognition System using Computer Vision

In this paper, the hand gesture of a person is being recognized and being identified that which hand is raised. This paper basically differentiates between the left and the second hand of the person. The human figure is first detected in the frame and then the skin color is taken into account to recognize the hands and the face of the person. The hands and the face are differentiated on the basis of the area and the centroid of the skin color map that represents basically the position and thus the hand, whether left or right hand. Camera is the only input device used in the process and then the captured digital image is being processed. The algorithm is being developed for both the captured and the real time images. The root algorithm that is being used in this paper is Mixture of Gaussian (MoG) for background subtraction that is an effective background mixture model for the background subtraction or foreground detection. Hence, a Human Machine Interface (HMI) has been developed by exploiting this method further.
Implementation and Evaluation of a Stator and Rotor Flux Linkage-Based Dead-Beat, Direct Torque Control of Induction Machines at the Operational Voltage Limits

Dead-beat, direct torque (and flux) control of an induction machine is experimentally achieved at a 10 kHz sampling frequency. The inverse solution utilized lends itself to a very insightful graphical representation. This allows for an objective experimental evaluation of voltage vector choices in the operational voltage limits. The parameter sensitivity of the control algorithm is also investigated.
Maximum likelihhood estimation and model selection for nonstationary processes

The Gaussian maximum likelihood estimate is investigated for time series models that have locally a stationary behaviour (e.g. for time varying autoregressive models). The asymptotic properties are studied in the case where the fitted model is either correct or misspecified. For example the behaviour of the maximum likelihood estimate is explained in the case where a stationary model is fitted to a nonstationary process. A general model selection criterion is suggested which can for example automatically select between stationary models, nonstationary models and deterministic trends.
Social-media monitoring for cold-start recommendations

Generating personalized movie recommendations to users is a problem that most commonly relies on user-movie ratings. These ratings are generally used either to understand the user preferences or to recommend movies that users with similar rating patterns have rated highly. However, movie recommenders are often subject to the ColdStart problem: new movies have not been rated by anyone, so, they will not be recommended to anyone; likewise, the preferences of new users who have not rated any movie cannot be learned. In parallel, Social-Media platforms, such as Twitter, collect great amounts of user feedback on movies, as these are very popular nowadays. This thesis proposes to explore feedback shared on Twitter to predict the popularity of new movies and show how it can be used to tackle the Cold-Start problem. It also proposes, at a finer grain, to explore the reputation of directors and actors on IMDb to tackle the Cold-Start problem. To assess these aspects, a Reputation-enhanced Recommendation Algorithm is implemented and evaluated on a crawled IMDb dataset with previous user ratings of old movies, together with Twitter data crawled from January 2014 to March 2014, to recommend 60 movies affected by the Cold-Start problem. Twitter revealed to be a strong reputation predictor, and the Reputation-enhanced Recommendation Algorithm improved over several baseline methods. Additionally, the algorithm also proved to be useful when recommending movies in an extreme Cold-Start scenario, where both new movies and users are affected by the Cold-Start problem.
Automatic Fine-Grained Issue Report Reclassification

Issue tracking systems are valuable resources during software maintenance activities. These systems contain different categories of issue reports such as bug, request for improvement (RFE), documentation, refactoring, task etc. While logging issue reports into a tracking system, reporters can indicate the category of the reports. Herzig et al. Recently reported that more than 40% of issue reports are given wrong categories in issue tracking systems. Among issue reports that are marked as bugs, more than 30% of them are not bug reports. The misclassification of issue reports can adversely affects developers as they then need to manually identify the categories of various issue reports. To address this problem, in this paper we propose an automated technique that reclassifies an issue report into an appropriate category. Our approach extracts various feature values from a bug report and predicts if a bug report needs to be reclassified and its reclassified category. We have evaluated our approach to reclassify more than 7,000 bug reports from HTTP Client, Jackrabbit, Lucene-Java, Rhino, and Tomcat 5 into 1 out of 13 categories. Our experiments show that we can achieve a weighted precision, recall, and F1 (F-measure) score in the ranges of 0.58-0.71, 0.61-0.72, and 0.57-0.71 respectively. In terms of F1, which is the harmonic mean of precision and recall, our approach can substantially outperform several baselines by 28.88%-416.66%.
Spectral-spatial classification of hyperspectral images using different spatial features and composite kernels

The high spectral and spatial resolution of hyperspectral images increases the capability to distinguish physical materials and objects, presenting new challenges to image analysis and classification. In fact, many studies have been conducted to extract and integrate spectral and contextual information in the classification process. However, the availability of various spatial features (e.g. morphological features, wavelet-based texture) and the inability to find the optimal one for all cases present a difficulty. In order to solve this problem, we proposed, in this paper, a novel spectral-spatial classification approach based on the integration of different spatial features. The proposed method exploited the performance of support vector machine (SVM) in the processing of data with high dimensionality and the properties of Mercer's kernels to construct composite kernels combining spectral and diverse spatial features. In this work, we employed all spectral information and two different spatial features which are Extended Multi-Attribute Profile (EMAP) and the mean of neighborhood pixels. The proposed kernels are compared to other multifeature SVM methods including stacked vector and traditional composite kernels. Experiments are conducted on the familiar AVIRIS “Indian Pines” data set. It was found that the proposed multifeature kernels provided more accurate classification results.
Research on Texture Images Retrieval Based on the Gabor Wavelet Transform

A technique of texture images retrieval based on Gabor wavelet transform is presented in this paper.A group of filters of different directions and different scales, generated from the basic wavelet of Gabor function are used for the wavelet transforamtion of texture images,then the means and Variances of the wavelet transformation coefficients are calculated as texture features of the image for the use of image retrieval. The parameters used in experiments are circumspectly selected according to the retrieval results.Experiments show that this method has an excellent performance on texture images retrieval.
Disability Weight of Clonorchis sinensis Infection: Captured from Community Study and Model Simulation

Background Clonorchiasis is among the most neglected tropical diseases. It is caused by ingesting raw or undercooked fish or shrimp containing the larval of Clonorchis sinensis and mainly endemic in Southeast Asia including China, Korea and Vietnam. The global estimations for population at risk and infected are 601 million and 35 million, respectively. However, it is still not listed among the Global Burden of Disease (GBD) and no disability weight is available for it. Disability weight reflects the average degree of loss of life value due to certain chronic disease condition and ranges between 0 (complete health) and 1 (death). It is crucial parameter for calculating the morbidity part of any disease burden in terms of disability-adjusted life years (DALYs). Methodology/Principal Findings According to the probability and disability weight of single sequelae caused by C. sinensis infection, the overall disability weight could be captured through Monte Carlo simulation. The probability of single sequelae was gained from one community investigation, while the corresponding disability weight was searched from the literatures in evidence-based approach. The overall disability weights of the male and female were 0.101 and 0.050, respectively. The overall disability weights of the age group of 5–14, 15–29, 30–44, 45–59 and 60+ were 0.022, 0.052, 0.072, 0.094 and 0.118, respectively. There was some evidence showing that the disability weight and geometric mean of eggs per gram of feces (GMEPG) fitted a logarithmic equation. Conclusion/Significance The overall disability weights of C. sinensis infection are differential in different sex and age groups. The disability weight captured here may be referred for estimating the disease burden of C. sinensis infection.
Gaussian Multi-factor Interest Rate Models: Theory, Estimation, and Implications for Option Pricing

Gaussian interest rate models are attractive because of their analytical tractabil-ity. Examples are the one-factor models of Ho/Lee and Vasicek, and two-factor models resulting from combinations of both. We show by factor analysis that the variation in spot rates of the German Government bond market in the period 1980-93 can essentially be explained by two factors. Consequently, we restrict ourselves to one-factor and two-factor models which are estimated by nonlinear regression. We compare these models with respect to their ability to explain observed changes in the term structure of interest rates. On the basis of theoretical insights and our empirical ndings we conclude that the two one-factor models considered should be discarded, because of the models' inability to explain a twist of the term structure where short term and long term rates move in opposite directions. Although the combination of the Ho/Lee and Vasicek one-factor model as proposed by Heath/Jarrow/Morton is able to explain the term structure twist, we recommend a two-factor Vasicek model (which contains the other models as special cases) for pricing interest rate options. The latter model is the only one which captures a u-shaped volatility function induced by the term structure twist. This situation occured in two of the seven 2-year subperiods analyzed. A comparison of model prices for calls on zero bonds which indicates that neglecting the volatility smile might cause a substantial valuation error completes the paper.
Optimization of a Fuzzy-Logic-Control-Based Five-Stage Battery Charger Using a Fuzzy-Based Taguchi Method

Lithium ion (Li-ion) batteries have been widely used in various kinds of applications, including consumer electronics, green energy systems and electrical vehicles. Since the charging method has a significant influence on the performance and lifetime of Li-ion batteries, an intelligent charging algorithm which can properly determine the charging current is essential. In this study, a fuzzy-logic-control-based (FLC-based) five-stage Li-ion battery charger is proposed. The proposed charger takes the temperature rise and the gradient of temperature rise of battery into account, and adjusts the charging current accordingly. To further improve the performance of the proposed FLC, the fuzzy-based Taguchi method is utilized to determine the optimal output membership functions (MFs). Comparing with the conventional constant current-constant voltage (CC-CV) method, the charging time, charging efficiency, average temperature rise and the obtained cycle life of the Li-ion battery are improved by about 58.3%, 1.65%, 26.7% and 59.3%, respectively.
Factors affecting speakers² choice of fillers in Japanese presentations

Disfluencies are intrinsic in spontaneous speech. Although it is known that there is a wide range of frequencies and types of disfluencies among speech, little is known about factors affecting speakers∂ choice of disfluency types. We first conducted a correspondence analysis using ratios of seven types of fillers, and other disfluencies, in 174 presentations and quantified the data. We conducted a cluster analysis using 4 dimension scores from the correspondence analysis, and extracted five filler-type groups. We then examined frequent types of presentations (formal or casual) and speaker attributes (gender and age) in each group. The results indicate that speakers∂choice of filler types is affected by speech levels, speakers∂gender and age, and that relevant factors differ depending on the type of fillers. Index Terms: disfluency type, fillers, sociolinguistic factors, speaker variation, Japanese
SPECTRAL EVOLUTION OF SUPERLUMINAL COMPONENTS IN PARSEC-SCALE JETS

We present numerical simulations of the spectral evolution and emission of radio components in relativistic jets. We compute jet models by means of a relativistic hydrodynamics code. We have developed an algorithm (SPEV) for the transport of a population of nonthermal electrons including radiative losses. For large values of the ratio of gas pressure to magnetic field energy density, αB ∼ 6 × 104, quiescent jet models show substantial spectral evolution, with observational consequences only above radio frequencies. Larger values of the magnetic field (αB ∼ 6 × 102), such that synchrotron losses are moderately important at radio frequencies, present a larger ratio of shocked-to-unshocked regions brightness than the models without radiative losses, despite the fact that they correspond to the same underlying hydrodynamic structure. We also show that jets with a positive photon spectral index result if the lower limit γmin of the nonthermal particle energy distribution is large enough. A temporary increase of the Lorentz factor at the jet inlet produces a traveling perturbation that appears in the synthetic maps as a superluminal component. We show that trailing components can be originated not only in pressure matched jets, but also in overpressured ones, where the existence of recollimation shocks does not allow for a direct identification of such features as Kelvin–Helmholtz modes, and its observational imprint depends on the observing frequency. If the magnetic field is large (αB ∼ 6 × 102), the spectral index in the rarefaction trailing the traveling perturbation does not change much with respect to the same model without any hydrodynamic perturbation. If the synchrotron losses are considered the spectral index displays a smaller value than in the corresponding region of the quiescent jet model.
Modeling dual role preferences for trust-aware recommendation

Unlike in general recommendation scenarios where a user has only a single role, users in trust rating network, e.g. Epinions, are associated with two different roles simultaneously: as a truster and as a trustee. With different roles, users can show distinct preferences for rating items, which the previous approaches do not involve. Moreover, based on explicit single links between two users, existing methods can not capture the implicit correlation between two users who are similar but not socially connected. In this paper, we propose to learn dual role preferences (truster/trustee-specific preferences) for trust-aware recommendation by modeling explicit interactions (e.g., rating and trust) and implicit interactions. In particular, local links structure of trust network are exploited as two regularization terms to capture the implicit user correlation, in terms of truster/trustee-specific preferences. Using a real-world and open dataset, we conduct a comprehensive experimental study to investigate the performance of the proposed model, RoRec. The results show that RoRec outperforms other trust-aware recommendation approaches, in terms of prediction accuracy.