Miracle-dz/UniFAR-FTUs huggingface dataset:
Extreme nonassociativity in order nine and beyond

The main concern of this paper are quasigroups of order nine that possess at most 18 associative triples. The order nine is the least order for which there exists a quasigroup (Q,*) such that x * (y * z)=(x * y) * z holds if and only if x=y=z . Up to isomorphism there is only one such quasigroup of this order. It has remarkable properties that bind it to a nearfield, to a PMD (9,4) and to a Sudoku division square.
Derivation of Formulas in Spherical Trigonometry Based on Rotation Matrix

The formulas of spherical triangle, which are widely used to solve various navigation problems, are the important basic knowledge of nautical mathematics. Because the sine rules and the cosine rules for the sides are the fundamental formulas to derive the other spherical triangle formulas, they are also called the genetic codes of the spherical triangle formulas. In the teaching process, teachers usually use the geometric method to derive and prove these fundamental formulas. However, the derivation of geometric methods is complicated and difficult to understand. To improve the teaching process, this paper proposes the three‐ dimensional rotation method, which is based on conversion of two cartesian coordinate frames using the rotation matrices. This method can easily and simultaneously derive the sine rules, the cosine rules for the sides, and the five‐part formulas (I), and is also helpful to solve different kinds of spherical navigation problems. http://www.transnav. eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 13 Number 3 September 2019 DOI: 10.12716/1001.13. 03.09
Compact Wideband Wide-Angle Polarization-Free Metasurface Lens Antenna Array for Multibeam Base Stations

A compact wideband wide-angle polarization-free metasurface lens (MSL) antenna array is proposed for a multibeam base station operating over the band of 1.71–2.2 GHz. The MSL element comprises of a planar wideband wide-angle polarization-free reflectionless MSL and three feeding sources of ±45° polarized cross-dipole antennas. With the shared lens aperture, the antenna achieves the three beams in the directions of 0° and ±30° in a horizontal plane. A five-layer patch-based metasurface loaded with metal poles are introduced to achieve consistent performance for wide-angle response. To reduce spillover loss, the feeding antennas are loaded with a metasurface and four directors for narrow beamwidth and low profile. With the optimized feeding antennas and MSL, a section of array with $1\,\,\times \,\,4$ MSL elements is prototyped for validation. The measured results show that an impedance bandwidth for return loss ≥ 10 dB is 1.63–2.24 GHz with the isolation larger than 22.3 dB. The measured gain ranges for 0° and 30° beams are 11.8–13.5 and 10–12.2 dBi with the sidelobe levels less than −22.6 and −13.6 dB, respectively.
Non-redundant frame identification and keyframe selection in DWT-PCA domain for authentication of video

This study is intended to protect video data and watermark from unauthorised access. The proposed methodology accentuates two new algorithms, namely structural similarity index metric–absolute difference metric (SSIM-AMD) based non-redundant frame identification (NRFI) and entropy–AMD based keyframe selection (KFS) to reduce the challenges posed by traditional discrete wavelet transform–singular value decomposition. Traditional techniques embed the entire watermark to all existing frames in the video, which is cumbersome and time-consuming. In this methodology, NRFI algorithm is applied to segregate the redundant and non-redundant frames to specific database. The KFS algorithm is used to identify suitable keyframes. DWT is applied into keyframes, which decomposes the frames into subbands. The middle band is selected for embedding. The principal component of watermark image block is embedded into identified keyframes in the video. The chaotic map is adapted to reorder the watermark block for improving the authentication level of the watermarking. The ant colony optimization (ACO) technique is adapted to select the suitable scaling factor for watermarking process. The principal component analysis technique is employed for avoiding false-positive attacks. Experimental results show the proposed methodology can withstand image processing, video processing, false-positive attacks and produces good results in terms of perceptual quality and robustness.
GONADAL DYSGENESIS – A CASE SERIES FROM A SINGLE VILLAGE

AIM: To describe the clinical features of patients presented with primary amenorrhoea and streak gonads from a single village and their response to treatment in a tertiary care hospital, thenceforth trace the source of genetic insult. METHODOLOGY: Patients attending outpatient department with primary amenorrhea and absent or poorly developed secondary sexual characters were examined clinically for height and genital development. They were evaluated with pelvic ultrasound, serum Follicle Stimulating Hormone, and karyotyping. RESULTS: Four patients presented at the age of more than 24 years with primary amenorrhea and poorly developed secondary sexual characters who were from a single village at Puducherry. On evaluation, pelvic ultrasound revealed steak gonads and serum FSH levels were elevated in all of them. Out of four, three of them had normal stature and one patient was short statured despite her genotype revealing 46XX. Among the patients with normal height, one had 45 X0 genotype. Thus they had unusual genotypic and phenotypic combinations. All of them responded well to hormone treatment. CONCLUSION: Diagnosis of pure gonadal dysgenesis must be done earlier for initiation of hormonal treatment. Search for teratogenic aetiologies for gonadal dysgenesis in that locality needs to be done.
Classical trajectory study of the photodissociation spectrum of H/sup +//sub 3/

The photodissociation spectrum of H/sup +//sub 3/ is studied using classical mechanical methods. Tunneling rates and product translational energies are computed for a large range of total angular momentum and energy. We predict that the experimentally measured spectrum of Carrington and Kennedy is dominated by low total angular momentum and low energy (relative to dissociation). There is an almost one to one correspondence between the measured product translational energy and the total angular momentum. The classical dipole spectrum of chaotic trajectories is found to be relatively structureless, changes slowly with total J, and does not show any correspondence or indication of the experimentally measured regular structure found in the coarse grained spectrum. We conclude that the regularity found in the coarse grained spectrum should be associated with a stable manifold of trajectories. We find that the horseshoe periodic orbit previously found to be stable at J = 0 exists also for nonzero J and is stable with respect to small perturbations in 3D. The rotational constant of the rotating horseshoe is 30 cm/sup -1/ in interesting agreement with the experiment. The properties of the rotating horseshoe are studied in detail, a novel adiabatic switching method is used to study themore » stability of the orbit. A quantum formalism of Taylor and Zakrzewski that shows how periodic orbits may cause structure in quantal spectra is used to indicate why the features of the rotating horseshoe orbit may appear in the coarse grained spectrum. The experimental coarse grained features are interpreted as an R branch of the . nu. /sub 3/ mode of the rotating horseshoe. « less
An Automatic Bad Band Pre-Removal Method for Hyperspectral Imagery

For most hyperspectral remote sensing applications, removing bad bands, such as low signal-to-noise ratio bands, is a required preprocessing step. Currently, the commonly used methods are by visual inspection and the sensor setting. The former is very time-consuming, and the latter is easy to either delete bands with tolerable quality or overlook some noisy bands. In this article, an inherent connection between bad band removal and target detection has been found. As we know, the result of target detection is the linear combination of all bands, and the weight coefficient of each band, i.e., the component of the filter vector, can be considered as the contribution of each band for the detection of targets of interest. Based on this fact, we develop an automatic bad band pre-removal method by using the matched filter (MF) weights of multiple targets within a scene, named the normalized MF weight method (NMFW). Experiments with three well-known hyperspectral data sets show that NMFW cannot only identify most reference bad bands but also extract other corrupted bands that are not labeled as reference bands.
Poststack Seismic Data Denoising Based on 3-D Convolutional Neural Network

Deep learning has been successfully applied to image denoising. In this study, we take one step forward by using deep learning to suppress random noise in poststack seismic data from the aspects of network architecture and training samples. On the one hand, poststack seismic data denoising mainly aims at 3-D seismic data. We designed an end-to-end 3-D denoising convolutional neural network (3-D-DnCNN) that takes raw 3-D cubes as input in order to better extract the features of the 3-D spatial structure of poststack seismic data. On the other hand, denoising images with deep learning require noisy–clean sample pairs for training. In the field of seismic data processing, researchers usually try their best to suppress noise by using complex processes that combine different methods, but clean labels of seismic data are not available. In addition, building training samples in field seismic data has become an interesting but challenging problem. Therefore, we propose a training sample selection method that contains a complex workflow to produce comparatively ideal training samples. Experiments in this study demonstrate that deep learning can directly learn the ability to denoise field seismic data from selected samples. Although the building of the training samples may occur through a complex process, the experimental results of synthetic seismic data and field seismic data show that the 3-D-DnCNN has learned the ability to suppress the Gaussian noise and super-Gaussian noise from different training samples. Moreover, the 3-D-DnCNN network has better denoising performance toward arc-like imaging noise. In addition, we adopt residual learning and batch normalization in order to accelerate the training speed. After network training is satisfactorily completed, its processing efficiency can be significantly higher than that of conventional denoising methods.
Applying Hybrid time series models for modeling bivariate time series data with different distributions for forecasting unemployment rate in the USA

Unemployment rate forecasting has become a particularly promising field of research in recent years because it's an important problem in state planning and management. Since the time series data are rarely pure linear or nonlinear obviously, sometimes contain both components jointly. Therefore, this study introduces new hybrid models contain Three commonly used, first is the Stochastic Linear Autoregressive Moving Average with eXogenous variable (ARMAX) model for modeled the relationship between the unemployment rate and exchange rate, second and third are a nonlinear Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and GARCH with eXogenous variable (GARCHX) used When the assumption of homoscedasticity error variance is violated for the purpose of capture the volatility in the residuals of ARMAX model and to enhance the Forecasting ability of ARMAX model by combining it with other nonlinear models. In this case, to have a better forecasting efficiency, we introduce a hybrid methodology of amalgamating the forecasts from a linear time series model (ARMAX) and from a nonlinear time series model (GARCH, GARCHX) with three different distributions (Normal Distribution, Student’s t-distribution and General Error Distribution (GED)), the last two distributions for capturing fat-tailed properties in residuals time series. The hybrid approach specifically (ARMAX-GARCH) and (ARMAX-GARCHX) have been used for modeling and forecasting the unemployment rate in the USA. Diverseapproacheshave beenemployed in the parameters vectorestimation. A comparison evaluation was as well been done based on mean absolute error (MAE), mean absolute percentage error (MAPE), as well as Root mean square error (RMSE) between the hybrid and their individual rival model in accordance with forecasting performance. From investigational results, it is perceived that the hybrid model (ARMAX-GARCHX) is more effectualthan other twin hybrid and individual rival models for the data under study. MATLAB, SAS, and EViews software packages have used for the data analysis
Broadband 180 Bit Phase Shifter Using a Coupled Line and Parallel Stubs

In this paper, a broadband 180 bit phase shifter using a new switched-network was presented. The new network is composed of a coupled line and parallel open and short stubs, which are shunted at the edge points of a coupled line, respectively. According to a desired phase shift, it provides a controllable phase dispersive characteristic by the proper determination of , and R values. The 180 bit phase shifter operated at 3 GHz was fabricated and experimented using design graphs which provide the required values, and I/O match and phase bandwidths. The experimental performances showed broadband characteristics.
Time-Domain Response of Damped Stochastic Multiple-Degree-of-Freedom Systems

Characterizing the time-domain response of a random multiple-degree-of-freedom dynamical system is challenging and often requires Monte Carlo simulation (MCS). Differential equations must therefore be solved for each sample, which is time-consuming. This is why polynomial chaos expansion (PCE) has been proposed as an alternative to MCS. However, it turns out that PCE is not adapted to simulate a random dynamical system for long-time integration. Recent studies have shown similar issues for the frequency response function of a random linear system around the deterministic eigenfrequencies. A Pade approximant approach has been successfully applied; similar interesting results were also observed with a random mode approach. Therefore, the latter two methods were applied to a random linear dynamical system excited by a dynamic load to estimate the first two statistical moments and probability density function at a given instant of time. Whereas the random modes method has been very efficient and accurate to evaluate the statistics of the response, the Pade approximant approach has given very poor results when the coefficients were determined in the time domain. However, if the differential equations were solved in the frequency domain, the Pade approximants, which were also calculated in the frequency domain, provided results in excellent agreement with the MCS results.
Solution formulas for the two-dimensional Toda lattice and particle-like solutions with unexpected asymptotic behaviour

The first main aim of this article is to derive an explicit solution formula for the scalar two-dimensional Toda lattice depending on three independent operator parameters, ameliorating work in [31]. This is achieved by studying a noncommutative version of the 2d-Toda lattice, generalizing its soliton solution to the noncommutative setting. The purpose of the applications part is to show that the family of solutions obtained from matrix data exhibits a rich variety of asymptotic behaviour. The first indicator is that web structures, studied extensively in the literature, see [4] and references therein, are a subfamily. Then three further classes of solutions (with increasingly unusual behaviour) are constructed, and their asymptotics are derived.
Pulmonary function tests in diagnosis of chronic obstructive pulmonary disease

Objective To know the status of pulmonary function tests(PFTs) used in the diagnosis of chronic obstructive pulmonary disease(COPD). Methods Totally 185 patients were diagnosed COPD and never performed PFTs before.Among those patients 35 were outpatients and 150 were inpatients.Pulmonary functions of those patients were analyzed.Results According to COPD guideline established by Chinese Medical Association,75 patients were consistent with COPD,all of which were in moderate to very severe condition.61. 5%(8/13) outpatients and 79.0%(49/62) inpatients were severe and very severe.Pulmonary functions of parts of patients diagnosed COPD were normal or mixed ventilation impairment.Parts of patients had positive bronchodilator test.Conclusion PFTs are infrequently used in clinical practice for diagnosis of COPD,which often leads to wrong or missed diagnosis of COPD.So extending PFTs performance is useful to diagnose and treat COPD earlier.
Development of hybrid artificial intelligence based automatic sleep/awake detection

Background and Objective: Obstructive Sleep Apnea is a disease that causes respiratory arrest in sleep and reduces sleep quality. The diagnosis of the disease is made by the physician in two stages by examining the patient records taken with the polysomnography device. Because of the negative aspects of this process, new diagnostic processes and devices are needed. In this article, a new approach to sleep staging, which is one of the diagnostic steps of the disease, was proposed. An artificial intelligence-based sleep/awake system detection was developed for sleep staging processing. Photoplethysmography (PPG) signal and heart rate variable (HRV) were used in the study. PPG records taken from patient and control groups were cleaned by the digital filter. The HRV parameter was then derived from the PPG signal. Then, 40 features from HRV signal and 46 features from PPG signal were extracted. The extracted features were classified by reduced machine learning techniques with F -score feature selection method. In order to evaluate the performances of the classifiers, the sensitivity and specificity values, the accuracy rates for each class were computed in the test set and receiver operating characteristic curve prepared. In addition, area under the curve (AUC), Kappa coefficient and F -score were calculated. According to the results obtained, the system can be realised with 91.09% accuracy rate using 11 PPG and HRV and with 90.01% accuracy rate using 14 HRV features. These success rates are quite enough for the system to work. When all these values are taken into consideration, it is possible to realise a practical sleep/awake detection system. This article suggests that the PPG signal can be used to diagnose obstructive sleep apnea by processing with artificial intelligence and signal processing techniques.
Resistance change of stretchable composites based on inkjet-printed silver nanowires

The fluctuation of the stretched resistance of composites based on inkjet-printed silver nanowires (AgNW) and polydimethylsiloxane (PDMS) is controlled by different ratios of a curing agent in PDMS, with an optimized normalized resistance change as low as 4.67% in a 50% tensile testing cycle. The results confirm that the properties of PDMS including the Young’s modulus and creep deformation play key roles in controlling the resistance changes of stretched AgNW–PDMS composites based on inkjet-printed AgNW, which opens up applications of inkjet-printable elastic AgNW conductors in stretchable electronics.
Exploração do Projeto de Sistemas Baseados em GPU ciente de Dark Silicon

Este artigo propõe uma infraestrutura para realizar a exploração do espaço de projetos de sistemas computacionais com unidades de processamento gráfico (GPUs) em conjunto com núcleos para processamento de propósito geral, com o objetivo de reduzir dark silicon e aumentar o desempenho do sistema em tempo de projeto. A ferramenta GPGPUSim de simulação e estimativa fı́sica de projeto foi estendida para realizar estimativas de dark silicon das plataformas de GPUs e, em seguida, foi integrada ao framework MultiExplorer. Adicionalmente, foi desenvolvida uma estratégia para estimativa de desempenho das plataformas de GPU e a modelagem de bases de dados que passaram a utilizar tanto núcleos de GPU quanto de plataformas multicore (núcleos de propósito geral), possibilitando, assim, a exploração do espaço de projeto buscando arquiteturas heterogêneas GP-GPUs.
Discriminative Eigenpixels-Based Dictionary Learning for Hyperspectral Image Classification

Sparse representation (SR) model has been applied to hyperspectral image (HSI) classification based on the observation that any spectral pixel could be approximately represented by a linear combination of several common pixels, but its discriminative ability is not deeply explored due to an insufficient description on spatial–spectral information and less emphasis on the dictionary structure. In this letter, we propose a new algorithm of HSI classification based on discriminative eigenpixels-based dictionary learning. Instead of using neighbor pixels directly, we define a new homogeneous region for each pixel, respectively, to exploit more spatial–spectral information and extract eigenpixels from homogeneous regions to preserve the essentials for each class. For the representation-based model, a discriminative eigenpixels-based dictionary is learned in homogeneous regions, where the locality of pixels is exploited to enhance the discriminative ability. Finally, we code a homogeneous region associated with a query pixel on the learned dictionary to determine its label by use of both the nearest neighbor (NN) classifier and majority voting. Experiments are conducted on four HSIs to demonstrate the effectiveness of the proposed method.
Chemical and phase equilibria through deterministic global optimization

Calculos de equilibrio quimico e de fases sao comumente realizados atraves da resolucao de um problema de otimizacao restrita conhecido como minimizacao da energia de Gibbs. O problema e, em geral, nao-convexo, o que faz com que a busca pelo minimo global nao seja trivial, ja que podem existir varios minimos locais. O minimo global e a unica solucao que tem significado fisico. Dentre as varias tecnicas encontradas na literatura, o algoritmo com analise de intervalosparece ser particularmente interessante devido a sua generalidade e ao fato de que ele e capaz de garantir matematicamente que o minimo encontrado sera o minimo global. Apesar disso, para que seja possivel aplica-lo diretamente ao problema de equilibrio, e necessario contornarde alguma forma o fato de que, em sua formulacao original, cotas inferiores muito proximas de zero podem causar underflow numerico, fazendo com que o algoritmo nao seja bem-sucedido. Um algoritmo baseado no original e apresentado e usado para resolver 8 problemas-teste de equilibrio extraidos da literatura. O algoritmo, apesar de nao mais garantir matematicamente que o otimo global e alcancado, foi capaz de corretamente resolver todos os problemas com relativa eficiencia.