Miracle-dz/UniFAR-FTUs huggingface dataset:
PROPOSTA DE ARQUITETURA DE PROCESSAMENTO DE DADOS PARA MANUTENÇÃO PROGNÓSTICA UTILIZANDO DATA ANALYTICS

O cenário tecnológico atual remete a indústria a integração denominada Cyber Physical System, considerando a interface entre o universo físico de produção e a conectividade em redes no ambiente virtual. Sensores de diversas finalidades, pulverizados por todo o ambiente fabril, permitem que controladores digitais e monitores computadorizados mapeiem e registrem todas as atividades fabris, gerando um enorme volume de dados, estocados em bancos de dados. Utilizando de Data Analytics, como ferramenta de apoio na Engenharia Manutenção, este artigo apresenta uma proposta de Pipe Line, em arquitetura de gestão de dados, para a realização de manutenção preditiva baseada em prognósticos, em uma estrutura pré-existente de uma Indústria 4.0. Com uso de técnicas de Machine Learning, baseado em um processo de Knowlegde Discovery in Databases, será apresentado análise de banco histórico de dados real, demonstrando a viabilidade e simplicidade da manutenção baseada em prognósticos, proporcionando uma antecipação da falha em 48h e 96h com desvio RMSE menor que 0,1.
Radio-over-fiber system with octuple frequency optical millimeter-wave signal generation using dual-parallel Mach–Zehnder modulator based on four-wave mixing in semiconductor optical amplifier

Abstract. We have proposed a scheme of radio-over-fiber (RoF) system employing a dual-parallel Mach–Zehnder modulator (DP-MZM) based on four-wave mixing (FWM) in a semiconductor optical amplifier (SOA). In this scheme, the pump and the signal are generated by properly adjusting the direct current bias, modulation index of the DP-MZM, and the phase difference between the sub-MZMs. Because of the pump and the signal deriving from the same optical wave, the polarization states of the two lightwaves are copolarized. The single-pump FWM is polarization insensitive. After FWM and optical filtering, the optical millimeter-wave with octuple frequency is generated. About 40-GHz RoF system with a 2.5-Gbit / s signal is implemented by numerical simulation; the result shows that it has a good performance after the signal is transmitted over 40-km single-mode fiber. Then, the effects of the SOA’s injection current and the carrier-to-sideband ratio on the system performance are discussed by simulation, and the optimum value for the system is obtained.
Threshold behavior in a stochastic HTLV‐I infection model with CTL immune response and regime switching

We investigate the stochastic HTLV‐I infection model with CTL immune response, which is disturbed by both white and telegraph noises. First, we obtain that the model solution is positive and global. Furthermore, we obtain the existence of ergodic stationary distribution of the solution by stochastic Lyapunov functions with regime switching, and we also establish sufficient conditions for the extinction of system with regime switching. Meanwhile, the threshold R0∗ between ergodic property and extinction of the stochastic system is acquired. Finally, our theoretical results are verified by numerical simulation.
A Word-Net Vector Space Frequecy Semantic Link Distance Model of Word-Meaning Equivalence

The ability to identify indices of semantic similarity among words is an important problem which has important applications in the fields of both artificial intelligence and experimental psychology. Unfortunately, the problem of rank-ordering words according to their semantic similarity measure is not a straightforward one even with powerful semantic network models of the lexicon such as WORDNET (Fellbaum, 1998). The problem arises because “word-meaning equivalence” is not some objective quantity but is a subjective context-dependent property. Two words that seem very different in one context might be judged semantically similar within another context (and viceversa). For example, a model of the lexicon such as WORDNET would predict the superordinates of CUP: “CROCKERY” or “DISHWARE” to be more consistent with the meaning of the word “CUP” than the subordinates of “CUP”: “TEA CUP” or “COFFEE CUP”. But such predictions might not be consistent with human performance. That is, people might simply be more likely to use the phrase “COFFEE CUP” instead of the word “CROCKERY” when they want to express the meaning “CUP”. The goal of this research is to compare the standard semantic similarity measure of distance in WORDNET which is based upon the number of links separating two words in WORDNET with two new algorithms for computing semantic distance.
On Symmetric Multilevel Diversity Coding System With Linear Computations

In a conventional Symmetric Multilevel Diversity Coding System (SMDCS), sources of varying importance are encoded by multiple encoders and a level-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> decoder, if given access to any <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> encoders, can decode the first <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> most important sources. In practical large-scale applications like Non-terrestrial Networks, sinks (e.g., land earth stations) may be only interested in some functions of the sources (e.g., orbiting satellites) rather than the sources themselves. This letter introduces linear network function computations into the SMDCS, where a level-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> decoder requests a linear function of the first <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> sources. The coding rate region of the 3-encoder (i.e., 3-level) SMDCS with linear computations (SMDCS-LC) was obtained. It is shown that when the coefficient vectors are dependent, coding between sources may help in reducing the information under transmission by encoders. However, when they are independent, superposition (i.e., sources-separated) coding is optimal. Furthermore, the minimum sum rate of the generic <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula>-level SMDCS-LC is obtained. This can find applications like federated learning aggregation in Non-Terrestrial Networks.
Impact of Macro-economic Variables on Stock Price on Nepal Stock Exchange

The purpose of this study is to investigate the relationship between macroeconomic variables and stock prices in Nepal Stock Exchange (NEPSE) Nepal. To find the impact of macroeconomic variables on stock price the analytical research is conducted. Secondary data were used in this study and the study considers annual data of several macroeconomic variables from 2001 to 2018. Stock price is considered as dependent variable and gross domestic product, exports, consumer price index, money supply, exchange rate, foreign direct investment and oil prices are treated as independent variable. The stationary of data is checked through Augmented Dickey Fuller test. All variables are stationary at zero lag. For the statistical result, descriptive statistics, correlation and, multiple regression analysis are used. The overall results revealed that oil price and money supply have significant positive impact on the stock price while other variables have adversely affects the stock price.
Convergence of a method based on the exponential integrator and Fourier spectral discretization for stiff stochastic PDEs

In this article, we propose and analyze some efficient numerical methods for the solution of a class of stiff stochastic partial differential equations (SPDEs) with additive noise. First, we apply the polynomial chaos (PC) expansion to treat the randomness, which results to a set of deterministic stiff PDEs. Then this system of PDEs is discretized in space by the Fourier pseudo‐spectral method, enabling us to use the FFT algorithm to reduce computational cost efficiently. To overcome the instability in discretizing time component of resulting system of ordinary differential equations (ODEs), we apply the exponential time differencing (ETD), integrating factor Runge‐Kutta (IFRK) and modified exponential time differencing Runge‐Kutta (ETDRKB) methods. We also analyze the strong error bound of numerical approximation in a framework of Lipschitz nonlinearities for the method based on the ETDRKB scheme. Some numerical experiments are included to demonstrate the performance and convergence of methods. Numerical results show that the method based on the ETDRKB scheme is more efficient for stiff SPDEs.
A fusion Siamese-ResNet network applied for low shot object detection in warehouses

Warehouses are a storage areas with high flow of goods. As part of the robotization of these areas, one of the major problems, attracting the attention of researchers, is defined by the automation of dispatching and renewing tasks when new products arrive. Indeed, having few information, automatic detection of these new products requires an update of the intelligent system, i.e. a new training step and therefore a stop in the warehouse production line. According to the literature, a novel branch of computer vision that consists in identifying and locating objects in an image with few information is called Low Shot Object Detection (LSOD). Using this solution, neural networks can automatically find new products with no need of any additional training step. To do so, neural networks architectures have been evolved by merging extracted features. This article presents a novel method that consists in merging layers convolution Siamese-ResNet network to include new products.
Feasibility study of direct spectra measurements for Thomson scattered signals for KSTAR fusion-grade plasmas

Feasibility study of direct spectra measurements of Thomson scattered photons for fusion-grade plasmas is performed based on a forward model of the KSTAR Thomson scattering system. Expected spectra in the forward model are calculated based on Selden function including the relativistic polarization correction. Noise in the signal is modeled with photon noise and Gaussian electrical noise. Electron temperature and density are inferred using Bayesian probability theory. Based on bias error, full width at half maximum and entropy of posterior distributions, spectral measurements are found to be feasible. Comparisons between spectrometer-based and polychromator-based Thomson scattering systems are performed with varying quantum efficiency and electrical noise levels.
Assessment of cattle welfare on Ghanaian farms

The objective of the study was to assess farm welfare conditions and the observance of welfare by cattle farmers in Ghana. The study applied field approaches to gather and analyze data. Data was collected from farms in the Northern, North East and Savanna regions. A total of three hundred and eighteen (318) cattle farmers were interviewed using semi-structured questionnaire. Observations and focus group discussions were also used to obtain data or verify some of the responses from the cattle farmers. Data collected was classified and summarized on the basis of the information provided. The study found evidence that most farmers were concerned about their animal’s welfare, but did not place equal weight on the five freedoms of animal welfare. Farmers placed the most premium on freedom from hunger, malnutrition and thirst (95%), and freedom from pain, injury and disease (90%). Farmers placed less premium on their animals freedoms from fear and distress (50%), and freedom from physical and thermal discomfort (50%). The freedom to express normal patterns of behaviour (0%) was not considered by the farmers. Observance of animal welfare by cattle farms was relatively below acceptable standards and government interventions are needed to improve animal welfare in Ghana.
Thermodynamic, transport, and optical properties of dense silver plasma calculated using the GreeKuP code

The transport and optical properties of a dense silver plasma are calculated using our parallel GreeKuP code. The code uses the results of Vienna ab initio simulation package (VASP) as input information and is based upon the Kubo–Greenwood formula. The calculation is performed at the normal density 10.5 g/cm3 and 3 kK ≤ T ≤ 20 kK. Under these conditions, the results are strongly influenced by the presence of the d‐electrons in silver: the real part of dynamic electrical conductivity has a non‐Drude shape, the temperature dependence of thermal conductivity is non‐monotonic, and the Wiedemann–Franz law is violated.
Values and sustainable behaviors of street runners: influence on purchase decision of sports products

Street running by amateurs athletes became a popular sports practice amongst adults around the world, who seeks healthy habit and a life quality. Prior evidence showed that the adoption of good practices is related to the development of an enhanced sustainable mindset. So far, few studies have examined the association between the healthy lifestyle of amateur runners and environmental values. The aim of this study was to examine the relationship between sports practice and environmental values. This investigation used survey data collected with amateur runners to examine the antecedents and consequences of healthy habits on sustainability practices using structural equation modeling. A sample of 208 amateur runners from Brazil, both male and female answered the questionnaire, with questions in a Likert scale adapted from current literature. Most participants reported a positive association between sports and sustainability, validating the proposed hypothesis. These findings provide support for additional studies on sustainability values and healthy habits, as an avenue for future research regarding consumer behavior.
A joint dynamic pricing and production model with asymmetric reference price effect

Reference price plays a significant role in influencing purchase decisions of customers. Due to loss aversion, the asymmetric reference price effect on market demand should be taken into account. This paper develops a joint dynamic pricing and production model with asymmetric reference price effect. In a finite planning horizon, the demand rate is time-varying and depends on price as well as reference price. The decision-making problem with the asymmetric reference price effect turns to be a nonsmooth optimal control problem, which cannot be solved by standard optimal control method. As a special case, we first obtain the joint optimal dynamic pricing and production strategy with symmetric reference price effect by solving the corresponding standard optimal control problem based on Maximum principle. For the case of asymmetric reference price effect, we propose a systematical method on basis of optimality principle to solve the nonsmooth optimal control problem, and obtain the joint strategy. Numerical examples are employed to illustrate the effectiveness of the proposed method. In addition, we assess the sensitivity analysis of system parameters to examine the impacts of asymmetric reference price on optimal pricing and production strategies and total profits.
A latent variable model to measure exposure diversification in the Austrian interbank market

We propose a statistical model for weighted temporal networks capable of measuring the level of heterogeneity in a financial system. Our model focuses on the level of diversification of financial institutions; that is, whether they are more inclined to distribute their assets equally among partners, or if they rather concentrate their commitment towards a limited number of institutions. Crucially, a Markov property is introduced to capture time dependencies and to make our measures comparable across time. We apply the model on an original dataset of Austrian interbank exposures. The temporal span encompasses the onset and development of the financial crisis in 2008 as well as the beginnings of European sovereign debt crisis in 2011. Our analysis highlights an overall increasing trend for network homogeneity, whereby core banks have a tendency to distribute their market exposures more equally across their partners.
Speckle reduction in PolSAR by multi-channel variance stabilization and Gaussian denoising: MuLoG

Due to speckle phenomenon, some form of filtering must be applied to SAR data prior to performing any polarimetric analysis. Beyond the simple multilooking operation (i.e., moving average), several methods have been designed specifically for PolSAR filtering. The specifics of speckle noise and the correlations between polarimetric channels make PolSAR filtering more challenging than usual image restoration problems. Despite their striking performance, existing image denoising algorithms, mostly designed for additive white Gaussian noise, cannot be directly applied to PolSAR data. We bridge this gap with MuLoG by providing a general scheme that stabilizes the variance of the polarimetric channels and that can embed almost any Gaussian denoiser. We describe MuLoG approach and illustrate its performance on airborne PolSAR data using a very recent Gaussian denoiser based on a convolutional neural network.
Super-Resolution Imaging via Spectral Separation of Quantum Dots

There has been significant progress in the optical resolution of microscopes over the last two decades. However, the majority of currently used methods (e.g. STED, PALM, STORM) have a number of drawbacks, including high intensities of light that result in damage to living specimens in STED, and long data acquisition time leading to limitations on live-cell imaging. Therefore, there is a niche for faster image acquisition at lower intensities while maintaining resolution beyond the diffraction limit. Here, we have developed a new methodology – Quantum Dot-based Optical Spectral Separation (QDOSS) – which relies on using Quantum Dots (QDs) as fluorophores, and on their separation and localisation based on their spectral signatures. We utilise the key advantages of QDs over the usual organic fluorophores: broad excitation, narrow emission spectra and high resistance to photobleaching. Besides, since QDOSS is based on spectral differences for separation, QDs can be deterministically localised in a relatively short time – milliseconds and, potentially, microseconds. Last but not least, QDOSS is suitable for obtaining super-resolution images using a standard confocal fluorescence microscope equipped with a single laser excitation wavelength and capable of spectral signal separation (e.g. Leica TCS SP series or Zeiss LSM series). First, we demonstrated resolution down to 60 nm using triangular DNA origami as a reference. Furthermore, we labelled and imaged the alpha-tubulin structure in HEK293T cells. We showed that using a mixture of standard off-the-shelf QDs of different sizes, resolution down to 40 nm could be achieved via spectroscopic separation of QDs. Finally, we demonstrated that QDOSS could also be used for multicolour imaging of synaptic proteins distributed around synapsis in neurons within diffraction limit. All in all, we believe that these features of QDOSS make it a potential method for long-term live super-resolution imaging, which is going to have a high impact in biological sciences.
Correlations among acoustic measurements of the Boltzmann constant

We review correlated uncertainties among the accurate determinations of the Boltzmann constant kB ? > that used the techniques of primary acoustic gas thermometry (AGT). We find correlated uncertainty contributions from four sources: (1) the uncertain chemical and isotopic compositions of the test gases that lead to an uncertain average molar mass, (2) measurements of the temperature, (3) measurements of the shape and dimensions of the cavity resonators, and (4) fitting acoustic resonance frequencies as a function of the pressure. Molar-mass-dependent uncertainties are correlated among those measurements that used argon with isotopic abundances determined using an isotopic standard prepared at the Korea Research Institute of Standards and Science in 2006. Correlated, cavity-dependent uncertainties result from using the same cavity for more than one measurement. Small, correlated uncertainties propagate into all the AGT determinations of kB ? > when acoustic resonance frequencies are fit for kB ? > using uncertain literature data for the Avogadro constant and for the thermal conductivity and the higher acoustic virial coefficients of helium or argon.
Analysis of NFIRS Data for Sensitivity to Foreclosure and Other Select Features

Arson is a grave threat to life and property. In the United States, fire information is collected and disseminated through the National Fire Incident Reporting System (NFIRS). Fire records obtained from NFIRS contain a full range of available information. This information includes the initial incident details in addition to investigative information regarding the cause of ignition and factors contributing to ignition. Combating the arson problem is accomplished in large part by understanding the motives and opportunities of those who commit arson. A common motive for arson is financial gain through insurance fraud. By connecting NFIRS data with mortgage and foreclosure information from RealtyTrac, insight into potential incidents of insurance fraud may be obtained. Understanding the features that intentional fires have in common is necessary to assess the vulnerability of structures to intentional burning. One historically utilized method of predicting arson prone structures is linear discriminant analysis (LDA). LDA is a method of separating objects or events into two or more categories using a combination of features. Through feature analysis and selection, a discriminant function is proposed that incorporates foreclosure as an independent variable to classify fires as intentional or unintentional. Additionally, graph theoretical algorithms for clustering are applied in support of the discovery of novel relationships between fires. In this thesis we leverage the paraclique algorithm, which has previously been applied to biological data, to help reveal latent associations within the NFIRS datasets.
Tables of the Distribution of Spearman's Footrule

Spearman's footrule D is the sum of the absolute values of the difference between the ranks in two rankings of n objects. For the case of equally likely permutations, tables of the exact distribution of D are given for 2 ≤ n ≤ 10 and approximate results are given for 11 ≤n ≤ 15. The normal approximation should be adequate for larger n. Exact expressions for some cumulative lower tail frequencies of D are given for general n.
Evaluating How Tenure Security in Disaster Management Depends on Land Governance Based on Indonesian Case Study

Tenure security is a critical variable in disaster management, yet is dependent on the rules and regulations of a country with regards to land ownership and use. This study draws on three disasters that occurred in Indonesia as case studies: the tsunami in Aceh in 2004, the Sidoarjo mudflow in 2006, and the tidal flood and permanent inundation in Kabupaten Demak, reported in 1997. Using literature review approach, we compare the government responses in these examples and evaluate how they affected tenure security in each case, and presented it qualitatively. We discovered that there were different responses in terms of the declaration of a national disaster, Central Government support, the presence of a responsible agency, and how the government threatened it as a 'pure natural disaster' or a 'human-induced disaster. ' We conclude that the Central Government plays an important role in ensuring tenure security during a disaster in terms of supporting laws and regulations, but the Local Government is also critical in the implementation process in land right reconstruction. Furthermore, for destroyed or lost land due to a disaster, the regulations on disaster management should distinguish between the root and cause of the disaster to ensure land rights protection and justice for the victims.