Miracle-dz/UniFAR-FTUs huggingface dataset:
Caracterização de argilas de novos jazimentos situados em Parelhas/RN, Brasil, visando aplicação na indústria cerâmica

RESUMO O Estado do Rio Grande do Norte, mais especificamente no município de Parelhas, Brasil, a indústria cerâmica já é bastante consolidada, crescendo ano após ano. Entretanto, o estímulo do setor tem provocado acelerada exaustão das jazidas de argilas locais utilizadas pela indústria e, por conseguinte, ameaçando a manutenção da indústria cerâmica no município e na região Seridó. Por esta razão, tem-se aprofundado o interesse de buscar novos jazimentos de argilas, a fim de suprir as suas demandas atuais e futuras. Recentemente, foram descobertos novos jazimentos no município, todavia, estas argilas não têm sido devidamente caracterizadas, causando prejuízos tanto a qualidade final do produto, como ao seu pleno aproveitamento industrial. Assim, este trabalho tem como objetivo caracterizar física, química e mineralogicamente argilas extraídas de três novos jazimentos do município de Parelhas/RN, com a finalidade de classificá-las visando sua aplicação na indústria de cerâmica vermelha da região. As amostras foram beneficiadas por secagem a 60 °C, seguida de moagem e peneiramento em malha de 200 mesh. Então, foram caracterizadas por fluorescência de raios-x, difração de raios-x, análise termogravimétrica e diferencial, análise granulométrica, perda ao fogo e plasticidade. Os constituintes das amostras identificados por fluorescência de raios X foram SiO2, Al2O3, Fe2O3, MgO, K2O, CaO e TiO2. Os difratogramas de raios-X revelaram a presença predominante dos argilominerais esmectita, feldspato, caulinita e quartzo nas amostras. A perda de massa total para as amostras variou entre 14% a 22,65%. A distribuição de partículas variou entre 0,2 a 40 µm, com diâmetro médio entre 6 e 16 µm. As amostras são classificadas como altamente plásticas e apresentam viabilidade para serem utilizadas na indústria de cerâmica vermelha.
Friction reducing performance of carbon nanotubes covered pistons in internal combustion engines – engine test results

This article discusses the posibility of reducing friction losses in internal combustion engines by using carbon nanotubes, pointing out the large potential of this application. Experimental pistons were made of standard aluminum alloy and coated with a layer of nanotube deposits by spraying them with an aqueous solution containing the binder. The proposed technology of applying layers of nanotubes can be adopted in industrial-scale production. Engine tests were carried out showing a significant reduction of the engine motoring torque, up to 16% for the experimental pistons, thus confirming the favorable tribological properties of nanotubes observed in tribological research and reported by many authors. Supplementary tests were carried out: SEM, EDS, coordinate measuring technique, and x-ray tomography. An alternative technology for hierarchical nanotube multilayer coatings electro-deposition was proposed.
Secure Medical Internet of Things Framework based on Parkerian Hexad Model

Medical Internet of Things (MIoT) applications enhance medical services by collecting data using devices connected to the IoT. The collected data, which may include personal data and location, is transmitted to mobile device and to health care provider via Internet Service Provider (ISP). Unfortunately, connecting a device to a network or sending data via wide network may make those devices and data vulnerable to unauthorized access. In this research, a secure 3-tier MIoT framework is proposed. Tier 1 includes the devices and sensors that will collect data. Those devices and sensors are based upon limited resources; therefore, they cannot apply complex security and privacy algorithms. Tier 2 includes the devices that will collect data from Tier 1 and submit it to Tier 3 via Internet Service Provider (ISP). Tier 3 includes the Health Information System. The framework defines the controls that are needed between layers to secure user privacy and data based on the Parkerian Hexad Model. Keywords—MIoT; Perkerian Hexad; PRMS; Lightweight Encryption
Penerapan Metode K-Means Untuk Clustering Produk Online Shop

ABSTRAK Manajemen stok yang dilakukan secara tidak akurat dan asal-asalan akan menyebabkan biaya simpan yang tinggi dan tidak ekonomis, karena bisa terjadi kekosongan atau kelebihan produk tertentu. Hal ini tentu akan sangat merugikan semua pelaku usaha seperti halnya online shop. Penelitian ini bertujuan untuk mengelompokkan produk yang dijual pada online shop Ragam Jogja menjadi beberapa cluster untuk mengetahui produk mana yang paling diminati sehingga jumlah stok harus banyak, produk diminati untuk jumlah stok sedang dan produk kurang diminati untuk jumlah stok sedikit. Metode yang digunakan pada penelitian ini adalah metode K-Means yang merupakan salah satu metode terbaik dan paling popular dalam algoritma clustering dimana K-Means mencari partisi yang optimal dari data dengan meminimalkan kriteria jumlah kesalahan kuadrat dengan prosedur iterasi yang optimal. Variabel yang digunakan adalah kode produk, jumlah transaksi, volume penjualan dan rata-rata penjualan. Penelitian juga didukung dengan software Rapidminer untuk pengolahan data dengan metode K-Means. Hasil akhir dari penelitian adalah berupa suatu program aplikasi yang dapat mengelompokkan produk menjadi kategori jumlah stok banyak, sedang dan sedikit berdasarkan transaksi penjualan. Kata kunci : clustering, manajemen stok, metode K-Means, program aplikasi
User Interest Model at Multiple Dimensions and Multiple Granularities

-Finding user’s interest and pushing related resources to user would be the best solution to aim the problem of ”Information Overload” and ”Lost in Internet”. This paper designs a user interest model with multiple dimensions and multiple granularities, named UIM. In UIM, the interest concepts are kept by a hierarchical concept tree at different granularities, the history of interest are maintained with titled time window at multiple time granularities, and moreover current interest are discriminated from history ones by gradually fading the weights of interests. The results of simulations show that UIM is efficient to be maintained, can quickly extract users important interests in different time windows, and the correctness of finding user interest is prior to analogous methods.
Supporting Wayfinding Through Mobile Gaze-Based Interaction

Wayfinding in unfamiliar environments often requires the use of assistance aids. Humans utilize navigation aids to make the correct spatial decisions in order to reach their destination. The main purpose of these aids is to minimize the complexity (e.g., cognitive load) of a decision, which varies according to the number of possible options to follow at a decision point, as well as based on the abilities of the wayfinder and the available environmental information that can be incorporated in a wayfinding instruction. Several wayfinding assistance aids require the user’s visual attention in order for her to obtain the provided information. The interaction with such assistance aids might increase the complexity of decision making having an impact on wayfinding performance. Furthermore, wayfinding aids that require the user’s visual attention distract her from the surrounding environment having an impact on safety as well as on spatial knowledge acquisition. The focus of this dissertation lies in the investigation of selflocalization and navigation in urban environments utilizing eye tracking technology as well as in the investigation, implementation, and evaluation of gaze-based wayfinding assistance systems. The main aim was to identify problems that occur during aided wayfinding, focusing on the visual interaction with mobile devices and the environment. Through novel gazebased interaction approaches with mobile devices and the environment, it was possible to address problems concerning visual attention switches away from the surrounding environment and provide solutions and directions for novel assistance systems that minimize the interaction with the device to a minimum, redirecting the visual attention to the surrounding environment, increasing spatial knowledge acquisition, performance as well as usability aspects.
Sensing Solution for Airborne Carbon Nanotube Exposure in Workplaces Based on Surface-Enhanced Raman Spectroscopy

Today’s advances in man-made nanomaterials pose new and unprecedented health risks, arising especially from airborne, inhalable fiber-shaped nanomaterials, like carbon nanotubes (CNTs). In vivo studies indicate that inhalation of CNTs can cause adverse pulmonary effects including inflammation, granulomas and pulmonary fibrosis [1, 2]. As a result, the National Institute of Occupational Health and Safety (NIOSH) recommends an exposure limit of 1μg/m of CNTs as a respirable mass 8-hour time-weighted average concentration [3]. However, detecting this amount is extremely challenging with the current sensing solutions. In this paper, we present a wearable compact sampler and an integrated, highly selective optical reader which enables automated monitoring of personal occupational exposure to CNTs.
Deep vision networks for real-time robotic grasp detection

Grasping has always been a great challenge for robots due to its lack of the ability to well understand the perceived sensing data. In this work, we propose an end-to-end deep vision network model to predict possible good grasps from real-world images in real time. In order to accelerate the speed of the grasp detection, reference rectangles are designed to suggest potential grasp locations and then refined to indicate robotic grasps in the image. With the proposed model, the graspable scores for each location in the image and the corresponding predicted grasp rectangles can be obtained in real time at a rate of 80 frames per second on a graphic processing unit. The model is evaluated on a real robot-collected data set and different reference rectangle settings are compared to yield the best detection performance. The experimental results demonstrate that the proposed approach can assist the robot to learn the graspable part of the object from the image in a fast manner.
E FFECTS OF SIMULTANEOUS ADMINISTRATION PROBIOTIC AND ANTIBIOTIC ON DIGESTIBILITY IN PIGLETS

In our 13-day experiment, piglets weaned at the age of 28 days and divided into two groups of six piglets each were used. The piglets were fed ad libitum with a commercial mix for early weaning of piglets, and had unrestricted access to water. For the experimental group (E), a feed mix with Bacillus toyoi spores in the final concentration 1.10 CFU per 1 g of feed mixture was used. A total of 8g Colistin sulphas per 100 kg live weight were administered in 2 daily doses by adding them to the feed in the trough. Piglets in the control group (C) received feed mix with no supplements. During the experiment, weight of piglets was monitored individually and the amount of feed consumed was monitored per group. Digestibility was determined by an analysis of faeces collected in boxes on days 5, 6 and 7 of the experiment, and adjusted according to the content of sand in the faeces and the feed. During the experiment, the incidence and intensity of diarrhoeas and changes in health were monitored in individual piglets. At weaning and on subsequent days, rectal swabs were taken to monitor the incidence of selected bacterial agents of infections and of the probiotic strain B.toyoi. Bacteriological examination was made by selective cultivation. The comparison of parameters monitored in the two groups of piglets clearly shows that experimental piglets received more feed (505g) compared with the control group (346 g), which is a difference of 46.5 %. While the mean weight gain of piglets in the experimental group was 209.2 g/day, it was only 205.4 g/day in the control group. All the parameters of feed mix digestibility determined at the end of the first week of experiment were higher in the controls. The admixture of tyocerin and colistin had the greatest effect on the digestibility of crude fat (C= 56.32 %, E= 47.85 %) and crude fibre (C= 52.58 %, E= 48.24 %), but the differences found are not statistically significant. No case of diarrhoea was reported in any of the piglets from either group during the experiment. It is no surprise that no weight increases in piglets receiving toyocerin and colistin simultaneously with their feed were found in the feeding experiment and that substantially higher feed consumption per kg of weight gain was found instead.
Multi-objective optimization of interatomic potentials with application to MgO

The parameterization of a functional form for an interatomic potential is treated as a problem in multi-objective optimization. An autonomous, machine-learning approach based on the identification of the Pareto hypersurface of errors in predicted properties allows the development of an ensemble of parameterizations with high materials fidelity and robustness. The efficacy of this approach is illustrated for the simple example of a Buckingham potential for MgO. This approach also provides a strong foundation for uncertainty quantification of potential parameterizations.
Attentive Action and Context Factorization

We propose a method for human action recognition, one that can localize the spatiotemporal regions that `define' the actions. This is a challenging task due to the subtlety of human actions in video and the co-occurrence of contextual elements. To address this challenge, we utilize conjugate samples of human actions, which are video clips that are contextually similar to human action samples but do not contain the action. We introduce a novel attentional mechanism that can spatially and temporally separate human actions from the co-occurring contextual factors. The separation of the action and context factors is weakly supervised, eliminating the need for laboriously detailed annotation of these two factors in training samples. Our method can be used to build human action classifiers with higher accuracy and better interpretability. Experiments on several human action recognition datasets demonstrate the quantitative and qualitative benefits of our approach.
Kramers-Kronig Anomalous Dispersion on Single-Mode Fiber-Optic Couplers and Tapers

KRAMERS-KRONIG ANOMALOUS DISPERSION ON SINGLE-MODE FIBER OPTIC COUPLERS AND TAPERS Amel Cabasa Lavarias Old Dominion University, 1997 Director: Dr. Sacharia Albin The Kramers-Kronig relations couple the real and imaginary part of the dielectric constant of a medium, namely the refractive index n(co) and the extinction coefficient k ( q ). Changes in n(o) due to normal and anomalous dispersion (Kramers-Kronig effect) are investigated for the first time using fiber optic couplers and tapers. Kramers-Kronig effect is induced by evanescent wave absorption in these devices. Couplers and tapers have oscillatory spectral outputs that are highly sensitive to the refractive index of the surrounding medium. Theoretical modeling of the Kramers-Kronig effect on couplers and tapers shows two distinct effects. First, the spectral outputs of these devices show a decrease in intensity due to evanescent wave absorption. Second, the spectral maxima and minima are shifted in wavelength due to Kramers-Kronig effect. Experimental studies clearly demonstrate Kramers-Kronig anomalous dispersion on fiber optic couplers and tapers. These devices are shown to be useful as chemical sensors. R eproduced with perm ission of the copyright owner. Further reproduction prohibited without perm ission.
Personalized route finding in multimodal transportation networks

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Blockchain Testing : Tools , Techniques , and Considerations

Since the release of the cryptocurrency Bitcoin in 2008 [28], the technology behind Bitcoin, blockchain, has received a large amount of attention. In this paper we will explain what blockchain and cryptocurrency are, and how they work. We will also give an introduction to Ethereum, a flexible blockchain implementation that enables users to create their own decentralized applications through the use of smart contracts. Finally, we will discuss the current functional and performance testing practices of Ethereum, and blockchain in general.
Effect of Steel fibre profile on the fracture characteristics of steel fibre reinforced concrete beams

The present study investigated on the mechanical characteristics of different types of steel fibre substituted high strength concrete. Influence of steel fibre volume fraction and its complex profile characteristics on the strength properties of various fibre substituted concretes had been systematically studied in slender concrete beam sections. Reinforcing efficiency of concrete incorporating four types of steel fibres having same aspect ratio with varying fibre profile - single hooked ends, crimped, double hooked ends and kinked had been experimentally analyzed in flexural bending and fracture studies. Test results showed higher flexural post crack toughness (23.48 N-m) and fracture toughness (39.62MPa√mm) for double hooked steel and crimped steel fibres substituted concretes. Steel fibre concretes containing double hooked and kinked geometry exhibited higher ductility ratio and overall performance index. Also, high volume steel fibre substitutions (1.5% V f ) in slender concrete beams showed improved post crack ductility and characteristic length.
An Artificial Neural Network Model for Neonatal Disease Diagnosis

The significance of disease diagnosis by artificial intelligence is not obscure now a day. The increasing demand of Artificial Neural Network application for predicting the disease shows better performance in the field of medical decision making. This paper represents the use of artificial neural networks in predicting neonatal disease diagnosis. The proposed technique involves training a Multi Layer Perceptron with a BP learning algorithm to recognize a pattern for the diagnosing and prediction of neonatal diseases. A comparative study of using different training algorithm of MLP, Quick Propagation, Conjugate Gradient Descent, shows the higher prediction accuracy. The Backpropogation algorithm was used to train the ANN architecture and the same has been tested for the various categories of neonatal disease. About 94 cases of different sign and symptoms parameter have been tested in this model. This study exhibits ANN based prediction of neonatal disease and improves the diagnosis accuracy of 75% with higher stability.
Vibrational dynamics in semiconductor compounds and alloys

In this work, the binary III-V semiconductors GaP, GaAs, GaSb, InP, InAs, und InSb, and the ternary alloys (In,Ga)P and (In,Ga)As were studied using temperature dependent extended x-ray absorption fine structure spectroscopy (EXAFS) measurements. In the alloy systems, the element-specific effective bond-stretching force constants were determined as a function of composition. To broaden the fundament of the conclusions, literature values of the ternary II-VI alloy Zn(Se,Te) were incorporated in the discussion. Different trends with composition are visible for (In,Ga)P on the one hand and (In,Ga)As and Zn(Se,Te) on the other hand. Strikingly, most of the six bond species under study (Ga-P, In-P, Ga-As, In-As, Zn-Se, and Zn-Te) exhibit the same relative change in bond-stretching force constant as a function of the relative change in bond length. Additionally, exactly the same relation is known from the literature as describing pressure-dependent EXAFS measurements of CdTe. The composition-dependent change of bond-stretching force constants in ternary zinc-blende semiconductor alloys is therefore caused mainly by the forced bond length change occurring in these materials. In addition to the bond-stretching force constants, effective bond-bending force constants were determined for the binary materials. Either type of force constants can be described as a function of ionicity and reduced mass of the interatomic bond. In the analysis great care has been taken to properly assess the uncertainties of the results. The comprehensive testing scenarios required to do this, also enable a general evaluation of the potential of the determination of bond force constants from temperature-dependent EXAFS measurements.
Online evaluation of recommender system with MovieLens dataset

The purpose of this paper is to explore the advantages of recommender systems based on the matrix factorization in respect to classical first neighbor recommender systems to real users through A/B test, as these studies are more significant. The results presented in this paper confirms the hypothesis that the recommender systems based on the models of matrix factorization are superior in relation to classical nearest-neighbor recommender systems.
Hand and torso pre-cooling does not enhance subsequent high-intensity cycling or cognitive performance in heat

ABSTRACT The purpose of this study was to compare the separate and combined effects of two practical cooling methods (hand and torso) used prior to exercise on subsequent high-intensity cycling performance in heat. Ten trained male cyclists (V̇O2peak: 65.7 ± 10.7 ml.kg−1.min−1) performed four experimental trials (randomised within-subjects design) involving 30-min of pre-cooling (20-min seated; PRE-COOL, 10 min warm-up; PRE-COOL+WUP), while using a: (1) hand-cooling glove (CG); (2) cooling jacket (CJ); (3) both CG and CJ (CG+J); or (4) no-cooling (NC) control, followed by a cycling race simulation protocol (all performed in 35.0 ± 0.6°C and 56.6 ± 4.5% RH). During the 30-min of pre-cooling, no reductions in core (Tc) or mean skin temperature (Tsk) occurred; however, Tsk remained lower in the CJ and CG+J trials compared to NC and CG (p = 0.002–0.040, d= 0.55–1.01). Thermal sensation ratings also indicated that participants felt “hotter” during NC compared to all other trials during both PRE-COOL and PRE-COOL+WUP (p = 0.001–0.015, d= 1.0–2.19), plus the early stages of exercise (sets 1–2; p = 0.005–0.050, d= 0.56–1.22). Following cooling, no differences were found for absolute Tc and Tsk responses between trials over the entire exercise protocol (p > 0.05). Exercise and cognitive (working memory) performance also did not differ between trials (p = 0.843); however, cognitive performance improved over time in all trials (p < 0.001). In summary, pre-cooling (20-min seated and 10-min warm-up) in heat did not improve subsequent high-intensity cycling performance, cognitive responses and associated thermoregulatory strain (Tc and Tsk) compared to control.