Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse Texture Representation Using Affine-Invariant Neighborhoods CVPR Paper

This paper proposes a novel texture representation suitabl e for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and non-rigid deformations. Unlike many existing feature extraction methods, which treat the neighborhood of every pixel as a candidate texture element, the proposed algorithm works by selecting a sparse set of affine-invariant local patches. This spatial selection process, besides provi ding greater computational efficiency and reducing redundancy in texton dictionaries, permits the computation of characteristic scale and neighborhood shape for every texture element. Shape information is used to determine the right support region for computing intensity-based descri ptors. When affine invariance is not required, shape can itsel f become a discriminative feature. The proposed texture representation is evaluated in retrieval and classification tasks using the entire Brodatz database and a collection of photographs of textured surfaces featuring viewpoint changes and non-rigid deformations, as well as variations in illumination and appearance .
Extending the wyliodrin platform for windows 10 IoT core

The Internet of Things is a thriving field in which multiple open source tools are used. On the other hand, Windows 10 Iot Core, a closed source operating system designed with Internet of Things in mind, shows great potential. This paper presents the main platforms required for expanding open source development tools for this operating system, as well as the process of expanding an open source IDE to a Qualcomm board running Windows 10 IoT Core.
Stochastic Resonance in Ensembles of Nondynamical Elements: The Role of Internal Noise

While many examples of noise-induced signal enhancement have been reported, the role of internal noise has received little attention. Here we study aperiodic stochastic resonance in parallel arrays of nondynamical elements with internal noise. Ensembles of both threshold and threshold-free elements are studied, and the model is applied to two-state ion channels. In finite systems where the input signal controls the probability of discrete events, we demonstrate that the internal noise is modulated by both the applied signal and the external noise. We also show that the internal noise plays a constructive role in information transfer through such systems via an increase in external noise.
Smart adaptation of beacons transmission rate and power for enhanced vehicular awareness in VANETs

In this work, we are interested in periodic beacons transmission, the main cause of the Control Channel (CCH) congestion and the major obstacle delaying the progress of safety messages dissemination in VANETs. In order to offload the network, solutions that range from transmit rate to transmit power adaptations including hybrid solutions have been proposed. Although some of these solutions have managed to successfully reduce the load on the wireless channel, none, to the best of our knowledge, have considered the impact of the applied adaptation scheme on the overall level of awareness among vehicles and its quality. ETSI TS released a technical specification stating a limit for the minimum beacons transmit rate in order to maintain a good level of awareness among vehicles and ensure a certain accuracy in VANET applications. In this paper, we propose to jointly adapt both transmit rate and power in a new smart way that guarantees a strict beaconing frequency as well as a good level of awareness in closer ranges, while maintaining a marginal beacons collision rate and a good level of channel utilisation. First, the transmit rate is adapted to meet the channel requirements in terms of collision rate and channel load; then, once the minimum beacon transmit rate, set by ETSI, has been reached, transmit power is adapted in a way that guarantees a good level of awareness for closer neighbours. The simulation results show a significant enhancement in terms of the quality as well as the level of awareness.
Gender Differences in the Management of Diabetic Patients with Hypertension and Chronic Ischemic Heart Disease

Objective: To determine gender differences in cardiovascular risk factors control and clinical management in hypertensive diabetics with chronic ischemic heart disease. Research design and methods: CINHTIA was a cross-sectional and multicenter survey aimed to evaluate the clinical profile and management of hypertensive outpatients with chronic ischemic heart disease attended by cardiologists in Spanish clinical practice setting. The aim of the present work was to examine the gender differences in the control and treatment of cardiovascular risk factors in the subgroup of patients with diabetes. Adequate blood pressure (BP), LDL-cholesterol and diabetes control rates were defined according to ESH-ESC 2003, NCEP-ATP III and ADA-2005 guidelines, respectively. Results: A total of 654 patients (42.4% women) were included for the present analysis. Women were older. Smoking, sed- entary lifestyle and peripheral arterial disease were more frequent in men; left ventricular hypertrophy and heart failure in women. The total number of lipid lowering and antihypertensive agents were similar between genders, but with a trend to use more antidiabetic drugs in women. There was a tendency to a better BP control in men (21.5% vs 17.0%, p=0.09). LDL-cholesterol and diabetes were better controlled in men (34.6% vs 26.6%, p=0.04 and 29.7% vs 22.3%, p=0.025, re- spectively). Conclusions: Diabetic women with hypertension and chronic ischemic heart disease exhibit lower control rates of cardio- vascular risk factors.
Acquisition of traffic flow density using multi-source data fusion

Traffic flow density is one of the most important parameters in traffic flow theory. It provides basic data for urban traffic management and control. However, it is highly difficult to directly collect real-time traffic flow density. The existing methods are simple in form, which are not suitable for complex traffic situations. The main purpose of this paper is to studying acquisition method of real-time traffic flow density by fusing Floating Car Data (FCD) and geomagnetic detection data. Least Squares Support Vector Regression (LS-SVR), which has properties such as global convergence and strong generalization capacity, is introduced to accomplish multi-source data fusion. The experimental result indicated that our approach has higher estimation accuracy than the traditional models.
Portable, automatic water level estimation using mobile phone cameras

Frequent and more accurate water level measurement will allow for a more efficient distribution of water, resulting in less water loss. Therefore in this paper we propose a novel method for accurate water level detection and measurement applied on images of staff gauges, retrieved from mobile device camera. In the first step, we propose fast segmentation of the staff gauge using a 2-class random forest classifier based on a feature vector of textons. To obtain bars and numbers we apply Gaussian Mixture Model segmentation followed by optical character recognition based on random forest classifier and bar detection using shape moments. Based on the recognized lines and numbers a quadratic function for the water level measurement to obtain metric values is introduced. Finally, we propose a novel step for the water level line detection. The water level function and the detected water line provide the value of the water level based on the units on the staff-gauge. The water level can then be uploaded to a central server to determine if water flow needs to increase or decrease. Testing with a real world images from Dutch canals show very accurate detection with many different staff-gauge locations despite complex challenges of viewpoints variations, low quality images as well as changing illumination conditions.
Testing the statistical isotropy of large scale structure with multipole vectors

A fundamental assumption in cosmology is that of statistical isotropy - that the universe, on average, looks the same in every direction in the sky. Statistical isotropy has recently been tested stringently using Cosmic Microwave Background (CMB) data, leading to intriguing results on large angular scales. Here we apply some of the same techniques used in the CMB to the distribution of galaxies on the sky. Using the multipole vector approach, where each multipole in the harmonic decomposition of galaxy density field is described by unit vectors and an amplitude, we lay out the basic formalism of how to reconstruct the multipole vectors and their statistics out of galaxy survey catalogs. We apply the algorithm to synthetic galaxy maps, and study the sensitivity of the multipole vector reconstruction accuracy to the density, depth, sky coverage, and pixelization of galaxy catalog maps.
An Efficient Method for Improving Data Collection Precision in Lifetime-adaptive Wireless Sensor Networks

Two important factors that affect the performance of wireless sensor networks (WSNs) are data quality and network lifetime. This paper exploits the tradeoff between data quality and network lifetime to improve data collection precision while the network lifetime is adapted. The problem is to minimize the total error bound for approximate data aggregation in both single-hop and multi-hop WSNs to achieve the adaptive network lifetime. This problem is formulated as an optimization problem by combining the changing pattern of sensor readings, the residual energy of sensor nodes, and the communication cost from the sensor node to the base station. Our method is theoretically analyzed and further evaluated by conducting simulation experiments. To the best of our knowledge, this is the first study on minimizing the total error bound while achieving the adaptive network lifetime.
VSIPL++ Acceleration Using Commodity Graphics Processors

The High Performance Embedded Computing Software Initiative (HPEC-SI) is developing a unified software framework for computation and communication for high performance signal processing tasks on parallel computers. The goal of the program is to address the high cost of software in Department of Defense (DoD) systems by improving the portability and productivity of signal processing application development, while simultaneously improving performance compared to current practices. The Vector, Signal, and Image Processing Library (VSIPL) is a portable application programming interface (API) that is widely used for embedded DoD signal processing systems. One portion of the HPEC-SI effort includes the development of C++ extensions for the existing VSIPL standard, called VSIPL++. Commodity graphics processing units (GPUs) are application-specific processors that implement a standardized three-dimensional graphics-rendering pipeline, and provide significant floating-point processing capacity at much lower cost, power consumption, and physical space compared to general-purpose processors. Recent changes in GPUs have increased programmability and flexibility in portions of the rendering pipeline, allowing non-graphics applications to exploit their computational capacity. Restrictions on the programming model, lack of appropriate tools, unusual performance behavior, and other factors make exploiting GPUs a costly, difficult, and time-consuming process for application developers. The embedded systems that VSIPL and VSIPL++ are commonly used on share several important characteristics with GPUs, making VSIPL++ well suited to abstract and exploit GPUs. This paper describes GPUVSIPL++, an implementation of portions of the VSIPL++ standard that exploits a GPU to accelerate computation beyond what is possible on a development workstation
The Current State of Ant Colony Optimisation Applied to Dynamic Problems

In recent years Ant Colony Optimisation (ACO) algorithms have been applied to more challengingand complex problem domains. One such domain, which is suggested in [1], is dynamic problems.The majority of dynamic problems addressed using biologically inspired computation techniquesare from the general ﬁeld of Operations Research and are usually modiﬁcations of popular staticproblem domains such as the travelling salesman problem and the vehicle routing problem. Thisdocument aims to summarise the current state of the ﬁeld with regard to ACO algorithms and theirapplication to dynamic problems. The document will attempt to answer questions such as:• What general algorithmic characteristics do these novel approaches deem most importantwhen addressing dynamic problems? • What utility do these dynamic algorithms oﬀer over standard approaches? To address these questions several recent research papers have been reviewed and relevant ﬁndingspresented (see Tab. 1. The author assumes that the reader is familiar with the concepts of AntColony Optimisation and combinatorial optimisation (speciﬁcally Travelling Salesman Problemsand Quadratic Assignment Problems), if this is not the case, recommended references are [3, 2, 8]. Algorithm name OptimisationproblemDynamic variationFIFO-Queue ACO QAP, TSP Regular removal and introduction of avaried number of locations/cities at pe-riodic intervalsAS-DTSP TSP The weights of some edges in the TSPwhich are located on the current bestpath found are increased and after atime eventually decreased back to theiroriginal valueTable 1: ACO algorithms applied to dynamic problems
R-HINT-E: a realistic hearing in noise test environment

With the advent of cheap, low-power digital signal processors, it has been possible to develop hearing aids that utilize DSP technology. It is essential that the algorithms instantiated on these hearing aids be evaluated in a standard fashion with regards to both engineering and perceptual criteria. However, currently available hearing in noise tests do not allow for the range of signals or environments that are of interest to the designer of hearing aid algorithms. In addition, virtual audio environments have recently been suggested (Shinn-Cunningham, B.G., 20th Int. Conf. of the IEEE Engineering in Biology and Medicine Society, 1998) as a potential tool for the auditory science community. To address the needs of both engineering and clinical evaluation, we propose a flexible, software based virtual acoustic environment capable of realistically simulating a wide variety of scenarios.
Addition of serum sodium into the MELD score predicts waiting list mortality better than MELD alone

In this study, we investigated the prognostic value of serum sodium and hyponatremia (≤130 mEq/L) in 262 cirrhotic patients consecutively listed, 19 of which died (7%), 175 survived (67%), and 68 underwent liver transplantation (26%) during 3 months of follow‐up. Hyponatremia was present in 63% of patients who died, compared to 13% of those who survived (P < .001), whereas the proportion with elevated creatinine (≥1.4 mg/dL) was low and similar in both groups (10.5 vs. 3%). Prevalence of hyponatremia was higher than that of elevated serum creatinine across all model for end‐stage liver disease (MELD) categories. Using logistic regression, hyponatremia and serum sodium were significant predictors of mortality with concordance statistics (c‐statistics) . 753 for hyponatremia, . 784 for sodium, . 894 for MELD, . 905 for MELD plus hyponatremia (P = .006 vs. MELD alone), and . 908 for MELD plus serum sodium (P = .026 vs. MELD alone). Risk of death across all MELD scores was higher for patients with hyponatremia than without hyponatremia. Cox regression considering data within 6 months of follow‐up yielded qualitatively similar results, with hyponatremia being a significant predictor of greater mortality risk with an odds ratio of 2.65 (P = .015). Each increase of 1 mEq/L of serum sodium level was associated with a decreased odds ratio of . 95 (P = .048). Our results indicate that hyponatremia appears to be an earlier and more sensitive marker than serum creatinine to detect renal impairment and / or circulatory dysfunction in patients with advanced cirrhosis. In conclusion, addition of serum sodium to MELD identified a subgroup of patients with poor outcome in a more efficient way than MELD alone and significantly increased the efficacy of the score to predict waitlist mortality. (Liver Transpl 2005;11:336–343.)
On estimation efficiency of the central mean subspace

We investigate the estimation efficiency of the central mean subspace in the framework of sufficient dimension reduction. We derive the semiparametric efficient score and study its practical applicability. Despite the difficulty caused by the potential high dimension issue in the variance component, we show that locally efficient estimators can be constructed in practice. We conduct simulation studies and a real data analysis to demonstrate the finite sample performance and gain in efficiency of the proposed estimators in comparison with several existing methods.
How Teachers Can Avoid Being Sued: Law and American Education.

This paper explores what teachers can do to avoid potential lawsuits. Section 1 describes different types of laws for public and private schools. Section 2 discusses tort liability. Section 3 presents legal principles that apply to educators (in loco parents, intentional torts, strict liability, negligence, foreseeability, assigned duties, contributory negligence, assumption of risk, and federal torts). Section 4 discusses negligent conduct and supervision. Section 5 presents guidelines in supervision. Section 6 discusses responsibility for learning (accountability, curriculum, and new teaching methods and techniques). Section 7 presents guidelines in methodology. Section 8 discuses obscenity in the classroom. Sections 9 and 10 discuss libel, slander, and privacy and related guidelines. Sections 11 and 12 discuss teachers' civil liberties and related guidelines. Section 13 discusses before and after school. Sections 14 and 15 note that principals can also be sued, and offer guidelines for principals. Section 16 describes teachers as counselors. Section 17 explains child abuse reporting. Section 18 discusses classroom management. Section 19 examines prayer in school. Section 20 emphasizes field trips. Section 21 presents guidelines for corporal punishment. Section 22 discusses guidelines regarding discipline. Section 23 explains what teachers should do if they think they might get sued. (Contains 13 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document.
FEED-FORWARD NEURAL NETWORKS TRAINING: A COMPARISON BETWEEN GENETIC ALGORITHM AND BACK-PROPAGATION LEARNING ALGORITHM

This study discusses the advantages and characteristics of the genetic algo- rithm and back-propagation neural network to train a feed-forward neural network to cope with weighting adjustment problems. We compare the performances of a back-propagation neural network and genetic algorithm in the training outcomes of three examples by re- ferring to the measurement indicators and experiment data. The results show that the back-propagation neural network is superior to the genetic algorithm. Also, the back- propagation neural network has faster training speed than the genetic algorithm. How- ever, the back-propagation neural network has the shortcoming of overtraining, while the genetic algorithm does not. The experiment result proves that the back-propagation neu- ral network yields better outcomes than the genetic algorithm.
A comparison of dense transposon insertion libraries in the Salmonella serovars Typhi and Typhimurium

Salmonella Typhi and Typhimurium diverged only ∼50 000 years ago, yet have very different host ranges and pathogenicity. Despite the availability of multiple whole-genome sequences, the genetic differences that have driven these changes in phenotype are only beginning to be understood. In this study, we use transposon-directed insertion-site sequencing to probe differences in gene requirements for competitive growth in rich media between these two closely related serovars. We identify a conserved core of 281 genes that are required for growth in both serovars, 228 of which are essential in Escherichia coli. We are able to identify active prophage elements through the requirement for their repressors. We also find distinct differences in requirements for genes involved in cell surface structure biogenesis and iron utilization. Finally, we demonstrate that transposon-directed insertion-site sequencing is not only applicable to the protein-coding content of the cell but also has sufficient resolution to generate hypotheses regarding the functions of non-coding RNAs (ncRNAs) as well. We are able to assign probable functions to a number of cis-regulatory ncRNA elements, as well as to infer likely differences in trans-acting ncRNA regulatory networks.
Single Locus Maintains Large Variation of Sex Reversal in Half-Smooth Tongue Sole (Cynoglossus semilaevis)

Sex determination is a fundamental biological process for individual sex development and population sex ratios. However, for some species, the primary sex might be altered during development, and individuals can develop into the opposite sex. Sex reversal may happen in insects, reptiles, amphibians, and fishes. In half-smooth tongue sole (Cynoglossus semilaevis), some genetically female fish irreversibly reverse to pseudomales, resulting in higher costs in aquaculture owing to a lower growth rate of male fish during a 2-yr growth period. Here, we identified a locus with large controlling effect on sex reversal in the half-smooth tongue sole through genome-wide association study with high-density single nucleotide polymorphisms (SNPs). This SNP is located at the third intron of the F-box and leucine rich repeat protein 17 (FBXL17) gene on the Z chromosome, and it has two alleles, A and T. Genetic females with ZAW genotypes will never reverse into phenotypic males, but those with ZTW genotypes can sometimes undergo sex reversal. This SNP explains 82.7% of the genetic variation, or 58.4% of the phenotypic variation. Based on our results, a reproductive management program could be developed to improve the phenotypic female ratio in aquaculture, and elucidate the mechanism of sex reversal in half-smooth tongue sole. We expect that these findings will have a substantial impact on the population management in many harvested species where sex reversal occurs.
Adaptive Cn logics

Newton da Costa's \C{n} logics suggest a certain stratagem, which is related to the motivation behind inconsistency-adaptive logics. An adaptive approach turns out to allow for a more controlled solution than the stratagem. Two kinds of logics will be presented. Those of the first kind offer a maximally consistent interpretation of the premise set in as far as this is possible in view of logical considerations. At the same time, they indicate at which points further choices may be made on extra-logical grounds. The logics of the second kind allow one to introduce those choices in a defeasible way and handle them.
Task planning for human-robot interaction

Human-robot interaction requires explicit reasoning on the human environment and on the robot capacities to achieve its tasks in a collaborative way with a human partner.This paper focuses on organization of the robot decisional abilities and more particularly on the management of human interaction as an integral part of the robot control architecture. Such an architecture should be the framework that will allow the robot to accomplish its tasks but also produce behaviors that support its engagement vis-a-vis its human partner and interpret similar behaviors from him.Together and in coherence with this framework, we intend to develop and experiment various task planners and interaction schemes, that will allow the robot to select and perform its tasks while taking into account explicitly the constraints imposed by the presence of humans, their needs and preferences.We have considered a scheme where the robot plans for itself and for the human in order not only (1) to assess the feasibility of the task (at a certain level) before performing it, but also (2) to share the load between the robot and the human and (3) to explain/illustrate a possible course of action.