Miracle-dz/UniFAR-FTUs huggingface dataset:
An Effective Image Denoising Method for UAV Images via Improved Generative Adversarial Networks

Unmanned aerial vehicles (UAVs) are an inexpensive platform for collecting remote sensing images, but UAV images suffer from a content loss problem caused by noise. In order to solve the noise problem of UAV images, we propose a new methods to denoise UAV images. This paper introduces a novel deep neural network method based on generative adversarial learning to trace the mapping relationship between noisy and clean images. In our approach, perceptual reconstruction loss is used to establish a loss equation that continuously optimizes a min-max game theoretic model to obtain better UAV image denoising results. The generated denoised images by the proposed method enjoy clearer ground objects edges and more detailed textures of ground objects. In addition to the traditional comparison method, denoised UAV images and corresponding original clean UAV images were employed to perform image matching based on local features. At the same time, the classification experiment on the denoised images was also conducted to compare the denoising results of UAV images with others. The proposed method had achieved better results in these comparison experiments.
Cooperative and out‐of‐core execution of the irregular wavefront propagation pattern on hybrid machines with Intel® Xeon Phi™

The Irregular Wavefront Propagation Pattern (IWPP) is a core computing structure in several image analysis operations. Efficient implementation of IWPP on the Intel Xeon Phi is difficult because of the irregular data access and computation characteristics. The traditional IWPP algorithm relies on atomic instructions, which are not available in the SIMD set of the Intel Phi. To overcome this limitation, we have proposed a new IWPP algorithm that can take advantage of non‐atomic SIMD instructions supported on the Intel Xeon Phi. We have also developed and evaluated methods to use CPU and Intel Phi cooperatively for parallel execution of the IWPP algorithms. Our new cooperative IWPP version is also able to handle large out‐of‐core images that would not fit into the memory of the accelerator. The new IWPP algorithm is used to implement the Morphological Reconstruction and Fill Holes operations, which are operations commonly found in image analysis applications. The vectorization implemented with the new IWPP has attained improvements of up to about 5× on top of the original IWPP and significant gains as compared to state‐of‐the‐art the CPU and GPU versions. The new version running on an Intel Phi is 6.21× and 3.14× faster than running on a 16‐core CPU and on a GPU, respectively. Finally, the cooperative execution using two Intel Phi devices and a multi‐core CPU has reached performance gains of 2.14× as compared to the execution using a single Intel Xeon Phi.
Bayesian variable selection logistic regression with paired proteomic measurements

We explore the problem of variable selection in a case‐control setting with mass spectrometry proteomic data consisting of paired measurements. Each pair corresponds to a distinct isotope cluster and each component within pair represents a summary of isotopic expression based on either the intensity or the shape of the cluster. Our objective is to identify a collection of isotope clusters associated with the disease outcome and at the same time assess the predictive added‐value of shape beyond intensity while maintaining predictive performance. We propose a Bayesian model that exploits the paired structure of our data and utilizes prior information on the relative predictive power of each source by introducing multiple layers of selection. This allows us to make simultaneous inference on which are the most informative pairs and for which—and to what extent—shape has a complementary value in separating the two groups. We evaluate the Bayesian model on pancreatic cancer data. Results from the fitted model show that most predictive potential is achieved with a subset of just six (out of 1289) pairs while the contribution of the intensity components is much higher than the shape components. To demonstrate how the method behaves under a controlled setting we consider a simulation study. Results from this study indicate that the proposed approach can successfully select the truly predictive pairs and accurately estimate the effects of both components although, in some cases, the model tends to overestimate the inclusion probability of the second component.
Intensity output and effectiveness of light curing units in dental offices

Background The aims of the study were measuring the light intensity of light curing units used in Qazvin’s dental offices, determining the relationship between the clinical age of these units and their light intensity, and identifying the reasons for repairing them. Material and Methods In this cross-sectional study, the output intensity of 95 light curing devices was evaluated using a radiometer. The average output intensity was divided up into four categories (less than 200, 200-299, 300-500, and more than 500 mW/cm2). In addition, a questionnaire was designed to obtain information mainly about the type, clinical age, and frequency of maintenance of the units and the reasons for fixing them. Data were analyzed using Kolmogorov-Smirnov, chi-squared, and t-tests (p< 0.05) on SPSS 24. Results A total of 95 light curing units were examined, with 61 (64.2%) of them being of the LED type and 34 (35.8%) of the QTH type. While average light intensity in LED units was significantly higher than in QTH devices, the two device types were not significantly different regarding desirable light intensity (i.e., ≥ 300 mw/cm2). A negative correlation was observed between clinical age and light intensity. In addition, bulb replacement in QTH devices was over three times as much as in LED units. Also, repairing QTHs was more than twice as much frequent as fixing LEDs. The most common reason for repair was the breakage of the tip of the device. Conclusions The light intensity of LED units is significantly higher than that of QTH devices, and the frequency of repairing in QTHs was significantly more than in LEDs. Furthermore, light intensity decreases with aging, and dentists should regularly monitor the conditions of light units. Key words:Light curing unit, radiometer, light intensity, dental equipment, dental offices.
Optimal Model Order Reduction for Fault Detection and Isolation

Model order reduction is a very useful technique for obtaining reduced sized models that are mathematically equivalent to the original one, with a reasonably small error. However this reduction is done in a generalized manner, without considering the purpose of the application. Reduced models obtained in such a way, in most cases, are not accurate enough for fault isolation. This paper presents a method that takes the faults into consideration during the model order reduction process in an optimal way, allowing proper fault detection and isolation to be achieved.
iNEXT: a European facility network to stimulate translational structural biology

iNEXT, “Infrastructure for NMR, EM and X-rays for Translational research”, is a EC-funded Horizon2020 network of national infrastructures aiming to facilitate EC-supported, trans-national user access to several high-end structural biology infrastructures and to expand the use of structural biology technologies towards new research communities. iNEXT has developed different access routes offering cutting edge technologies and expertise, thus targeting the diverse needs of research groups that desire to perform X-ray crystallography, small-angle X-ray scattering, solution or solid-state Nuclear Magnetic Resonance, single particle or cell tomography electron microscopy, biophysics, and imaging experiments. Specific Joint Research Activities aim at improving the user experience in ever advancing methods, and are focused on structure-based drug discovery, membrane protein characterization, and structural cell biology initiatives. Structural biology has proven indispensable for research and development in the life sciences, biotechnology and biomedical fields. High-end equipment is essential for structural biology: synchrotrons to produce intense, tunable and focused X-ray beams for Macromolecular X-ray Crystallography (MX) and Small-Angle X-ray Scattering (SAXS) studies; high-field superconducting magnets for Nuclear Magnetic Resonance (NMR); and new-generation electron microscopes with powerful optics and fast direct readout electron detectors for cryo-Electron Microscopy (cryo-EM) applications in single particle studies and cell imaging. The use of such structural very expensive.
The Association between Mental Wellbeing, Levels of Harmful Drinking, and Drinking Motivations: A Cross-Sectional Study of the UK Adult Population

Mental well-being and excessive alcohol consumption each represent a significant public health concern, and evidence suggests an association between them. Furthermore, drinking motivations associated with harmful drinking have been studied, but not systematically in the UK population. A representative sample of 6174 UK adults aged 18–75 were surveyed online. Low risk drinkers were found to have higher mental well-being than hazardous, harmful, and, probable, dependence drinkers. Using a hierarchical multiple regression analysis, it was found that just over 5% of the variance in well-being scores was accounted for by the level of harmful drinking and drinking motivation; the most significant contribution was drinking to cope. Among people drinking to cope, those drinking in more harmful ways were statistically significantly more likely to have low well-being compared to less harmful drinkers. In the UK adult population there is a clear association between poor mental well-being and harmful drinking. Furthermore, coping was a significant motivation to drink for many with low mental well-being. While mental well-being was found to be directly linked with levels of harmful drinking, the motivation for drinking was a stronger predictor of mental well-being.
Typical interval-valued hesitant fuzzy probability

The interval-valued hesitant fuzzy probability theory is investigated. The concepts of typical interval-valued hesitant fuzzy event and its probability have been introduced. The basic properties and Borel-Cantelli Lemma of classical probability are generalized to that of the probability of typical interval-valued hesitant fuzzy event. The continuity of the probability of interval-valued hesitant fuzzy event and ordering property for interval-valued hesitant fuzzy probability have been discussed.
How many fish? Comparison of two underwater visual sampling methods for monitoring fish communities

Background Underwater visual surveys (UVSs) for monitoring fish communities are preferred over fishing surveys in certain habitats, such as rocky or coral reefs and seagrass beds and are the standard monitoring tool in many cases, especially in protected areas. However, despite their wide application there are potential biases, mainly due to imperfect detectability and the behavioral responses of fish to the observers. Methods The performance of two methods of UVSs were compared to test whether they give similar results in terms of fish population density, occupancy, species richness, and community composition. Distance sampling (line transects) and plot sampling (strip transects) were conducted at 31 rocky reef sites in the Aegean Sea (Greece) using SCUBA diving. Results Line transects generated significantly higher values of occupancy, species richness, and total fish density compared to strip transects. For most species, density estimates differed significantly between the two sampling methods. For secretive species and species avoiding the observers, the line transect method yielded higher estimates, as it accounted for imperfect detectability and utilized a larger survey area compared to the strip transect method. On the other hand, large-scale spatial patterns of species composition were similar for both methods. Discussion Overall, both methods presented a number of advantages and limitations, which should be considered in survey design. Line transects appear to be more suitable for surveying secretive species, while strip transects should be preferred at high fish densities and for species of high mobility.
Emission reduction with spread spectrum clocking for switched capacitor buck converter

The reduction of electromagnetic emissions (EME) in switch mode power supplies (SMPS) has high importance especially in automotive applications. The main methods to influence the switching behaviour of SMPS are external filters, spread spectrum techniques and output driver circuits. This paper presents the application of the spread spectrum technique for a 1.25 V and 1.851 MHz switched capacitor buck converter with a digital control loop to reduce the conducted emissions. The frequency modulated sawtooth and pseudo-random profiles are implemented in the digital controller and discretized by a 100 MHz system digital clock. The work investigates the influence of the profile's modulation frequency and the effect of the pulse width modulation (PWM) resolution limitation on the EME reduction. The improvement using a sawtooth profile of 10 dBuV in comparison to the non-modulated PWM signal is seen and discussed. The comparison between modulated and non modulated output voltage ripple is also presented.
A Multiresolution Gray-Scale and Rotation Invariant Descriptor for Texture Classification

Texture classification algorithms using local binary pattern (LBP) and its variants usually can achieve attractive results. However, the selected rotation invariant structural patterns in numerous LBP variants are not absolutely continuous invariant to any rotation angle. To improve the classification effectiveness on this occasion, in this paper, we introduce a robust descriptor based on the principal curvatures (PCs) and rotation invariant version of CLBP_Sign operator in completed LBP (CLBP), namely PC-LBP. Different from the original LBP and many LBP variants, PCs are employed in this paper to represent each local structure information due to their continuous rotation invariance. Simultaneously, both micro-and macro-structure texture information can also be captured through PCs, which comprise maximum and minimum curvatures. Inspired by the similar coding strategy of the CLBP_Sign operator, a new operator CLBP_PC is developed. By exploiting complementary information resulting from the two operators combination, the final PC-LBP descriptor has the properties of conspicuous rotation invariance, strong discriminativeness, gray scale invariance, needless of pretraining, and high computational efficiency. In addition, to improve the robustness of texture classification with multiresolution, a multiscale sampling approach is designed by adjusting three parameters accordingly. Experimental results demonstrate that the proposed multiresolution PC-LBP approach achieves comparable performance or outperforms a large number of state-of-the-art methods. Impressively, the classification accuracy of the proposed method performed on Outex_TC_00010 test suite is 100%.
Online Exemplar-Based Fully Convolutional Network for Aircraft Detection in Remote Sensing Images

Convolutional neural network obtains remarkable achievements on target detection, due to its prominent capability on feature extraction. However, it still needs further study for aircraft detection task, since intraclass variation still restricts the accuracy of aircraft detection in remote sensing images. In this letter, we adopt regularity of aircraft circle response to design our end-to-end fully convolutional network (FCN), and embed online exemplar mining into our network to handle intraclass variation. The mined exemplars are employed to capture different intraclass characteristics, which effectively reduces the burden of network training. Specifically, we first select basic exemplars based on labeled information and initialize the relationships between exemplars and aircraft examples. Then, these relationships will be updated by the similarity of these examples in high-level features space. Finally, aircraft examples will be used to train different exemplar detectors according to updated relationships. Motivated by the geometric shape of aircraft, a circle response map is developed to construct our FCN to achieve more efficient aircraft detection. The comparative experiments indicate that superior performance of our network in accurate and efficient aircraft detection.
A study on different factors influencing customer satisfaction on industrial market

Article history: Received Feb 25, 2013 Received in revised format 19 September 2013 Accepted 23 October 2013 Available online November 18 2013 Customer satisfaction plays essential role on the success of industrial products such as milk in todays’ marketing planning. In this paper, we present a conceptual model to measure the relative impact of various factors on customer satisfaction. The proposed study of this paper designs a questionnaire and distributes it among managers of a dairy producer named Pegah in city of Esfahan, Iran. Using Pearson correlation ratio as well as stepwise regression technique, the study has found positive and meaningful relationship between customer satisfaction and price, quality of product, distribution and compatibility with customer expectation. In addition, the study detects a negative and meaningful relationship between conflict and customer satisfaction. © 2014 Growing Science Ltd. All rights reserved.
Using autoencoder network to implement non-intrusive load monitoring of small and medium business customer

Recently, issues such as the greenhouse gas emission, depletion of fossil fuels, and safe use of nuclear energy led many countries and governments to focus on problems of energy economy. Improving energy efficiency of small- and medium-(S&M) business customers has become a challenge. To monitor the energy usage of appliances used by S&M business customers given the advanced metering infrastructure (AMI) meter's data and to establish a cost-effiective energy system, this study employs a deep learning network, the denoise autoencoder, to propose a nonintrusive load montoring system for data granularity of 1 sample/min. By implementing the system and analyzing actual data acquired from 12 test sites, the feasibility of the proposed system is demonstrated, and future research venues are discussed.
Enantiomeric separation of β-blockers and tryptophan using heparin as stationary and pseudostationary phases in capillary electrophoresis.

The separation methods of the enantiomers of two β-blockers and tryptophan were studied using capillary electrochromatography with heparin covalently as well as non-covalently, bonded onto the capillary inner wall as stationary phase and electrokinetic chromatography with heparin as pseudostationary phase. In the case of heparin, used as a stationary phase, the method was unable to resolve enantiomers in both cases β-blockers and tryptophan. On the other hand, when heparin was used as a pseudostationary phase, the resolution of the enantiomers was obtained only with 3-aminopropyltriethoxysilane which were immobilised onto the inner phase of the capillary. The results of this study let us infer that the electrostatic, hydrophobic, and steric interactions were involved in the separation mechanisms. The separation was achieved in less than 10 minutes under the optimized conditions: 30 mM phosphate buffer (pH 2.5) with the adding of 15 mg/mL of heparin at 15°C and 10 kV. The usefulness of heparin as a chiral selector both in electrokinetic chromatography using 3-aminopropyltriethoxysilane attached to the capillary was demonstrated for the first time. The developed method was powerful, sensitive, and fast, and it could be considered an important alternative to conventional methods used for chiral separation.
Nonsynonymous Variants in PAX4 and GLP1R Are Associated With Type 2 Diabetes in an East Asian Population

We investigated ethnicity-specific exonic variants of type 2 diabetes (T2D) and its related clinical phenotypes in an East Asian population. We performed whole-exome sequencing in 917 T2D case and control subjects, and the findings were validated by exome array genotyping in 3,026 participants. In silico replication was conducted for seven nonsynonymous variants in an additional 13,122 participants. Single-variant and gene-based association tests for T2D were analyzed. A total of 728,838 variants were identified by whole-exome sequencing. Among nonsynonymous variants, PAX4 Arg192His increased risk of T2D and GLP1R Arg131Gln decreased risk of T2D in genome-wide significance (odds ratio [OR] 1.48, P = 4.47 × 10−16 and OR 0.84, P = 3.55 × 10−8, respectively). Another variant at PAX4 192 codon Arg192Ser was nominally associated with T2D (OR 1.62, P = 5.18 × 10−4). In T2D patients, PAX4 Arg192His was associated with earlier age at diagnosis, and GLP1R Arg131Gln was associated with decreased risk of cardiovascular disease. In control subjects without diabetes, the PAX4 Arg192His was associated with higher fasting glucose and GLP1R Arg131Gln was associated with lower fasting glucose and HbA1c level. Gene-based analysis revealed that SLC30A8 was most significantly associated with decreased risk of T2D (P = 1.0 × 10−4). In summary, we have identified nonsynonymous variants associated with risk of T2D and related phenotypes in Koreans.
Linear System Identification Based on a Kronecker Product Decomposition

Linear system identification is a key problem in many important applications, among which echo cancelation is a very challenging one. Due to the long length impulse responses (i.e., echo paths) to be identified, there is always room (and needs) to improve the performance of the echo cancelers, especially in terms of complexity, convergence rate, robustness, and accuracy. In this paper, we propose a new way to address the system identification problem (from the echo cancelation perspective), by exploiting an optimal approximation of the impulse response based on the nearest Kronecker product decomposition. Also, we make a first step toward this direction, by developing an iterative Wiener filter based on this approach. As compared to the conventional Wiener filter, the proposed solution is much more attractive since its gain is twofold. First, the matrices to be inverted (or, preferably, linear systems to be solved) are smaller as compared to the conventional approach. Second, as a consequence, the iterative Wiener filter leads to a good estimate of the impulse response, even when a small amount of data is available for the estimation of the statistics. Simulation results support the theoretical findings and indicate the good results of the proposed approach, for the identification of different network and acoustic impulse responses.
Android (Nougats) security issues and solutions

Android mobile operating system, Google developed, Linux Kernel based with basic motive to serve for devices with touchscreen like tablets and smartphones. Due to weak OS security it is vulnerable to various security attacks therefor to restrict access of third-party applications off critical resources the security has been built upon a permission based mechanism. Permissions are declarations by developers and user is demanded to accept. This paper highlights Share User ID permission misuse following two-factor authentication failure etc.