Search

This paper is a synopsis of the recent book [9]. The latter is dedicated to the stochastic Burgers equation as a model for 1d turbulence, and the paper discusses its content in relation to the Kolmogorov theory of turbulence.

Videos take a lot of time to transport over the network, hence running analytics on the live video on embedded or mobile devices has become an important system driver. Considering such devices, e.g., surveillance cameras or AR/VR gadgets, are resource constrained, although there has been significant work in creating lightweight deep neural networks (DNNs) for such clients, none of these can adapt to changing runtime conditions, e.g., changes in resource availability on the device, the content characteristics, or requirements from the user. In this article, we introduce ApproxNet, a video object classification system for embedded or mobile clients. It enables novel dynamic approximation techniques to achieve desired inference latency and accuracy trade-off under changing runtime conditions. It achieves this by enabling two approximation knobs within a single DNN model rather than creating and maintaining an ensemble of models, e.g., MCDNN [MobiSys-16]. We show that ApproxNet can adapt seamlessly at runtime to these changes, provides low and stable latency for the image and video frame classification problems, and shows the improvement in accuracy and latency over ResNet [CVPR-16], MCDNN [MobiSys-16], MobileNets [Google-17], NestDNN [MobiCom-18], and MSDNet [ICLR-18].

Distance education theories indicate the importance of learner–content interaction and discuss it in conjunction with learner–instructor and learner–learner interaction. The measures of learner–con...

Social networks are used by terrorist groups and people who support them to propagate their ideas, ideologies, or doctrines and share their views on terrorism. To analyze tweets related to terrorism, several studies have been proposed in the literature. Some works rely on data mining algorithms; others use lexicon-based or machine learning sentiment analysis. Some recent works adopt other methods that combine multi-techniques. This paper proposes an improved approach for sentiment analysis of radical content related to terrorist activity on Twitter. Unlike other solutions, the proposed approach focuses on using a dictionary of weighted terms, the Word2vec method, and trigrams, with a classification based on fuzzy logic. The authors have conducted experiments with 600 manually annotated tweets and 200,000 automatically collected tweets in English and Arabic to evaluate this approach. The experimental results revealed that the new technique provides between 75% to 78% of precision for radicality detection and 61% to 64% to detect radicality degrees.

In an increasingly connected world, consumer video experiences have diversified away from traditional broadcast video into new applications with increased use of non-camera-captured content such as computer screen desktop recordings or animations created by computer rendering, collectively referred to as screen content. There has also been increased use of graphics and character content that is rendered and mixed or overlaid together with camera-generated content. The emerging Versatile Video Coding (VVC) standard, in its first version, addresses this market change by the specification of low-level coding tools suitable for screen content. This is in contrast to its predecessor, the High Efficiency Video Coding (HEVC) standard, where highly efficient screen content support is only available in extension profiles of its version 4. This paper describes the screen content support and the five main low-level screen content coding tools in VVC: transform skip residual coding (TSRC), block-based differential pulse-code modulation (BDPCM), intra block copy (IBC), adaptive color transform (ACT), and the palette mode. The specification of these coding tools in the first version of VVC enables the VVC reference software implementation (VTM) to achieve average bit-rate savings of about 41% to 61% relative to the HEVC test model (HM) reference software implementation using the Main 10 profile for 4:2:0 screen content test sequences. Compared to the HM using the Screen-Extended Main 10 profile and the same 4:2:0 test sequences, the VTM provides about 19% to 25% bit-rate savings. The same comparison with 4:4:4 test sequences revealed bit-rate savings of about 13% to 27% for $Y'C_{B}C_{R}$ and of about 6% to 14% for $R'G'B'$ screen content. Relative to the HM without the HEVC version 4 screen content coding extensions, the bit-rate savings for 4:4:4 test sequences are about 33% to 64% for $Y'C_{B}C_{R}$ and 43% to 66% for $R'G'B'$ screen content.

The applications of the interval and standard probabilistic approaches for verifying the reliability of the results of an experiment studying the mechanical properties of nuclear materials are compared. The presence of “outliers” in a sample of hardness values for hafnium ingots is studied with for fixed oxygen mass content. The situation of measurement error limitation without reliable information about its distribution is considered. The correctness of the application of numerical methods of interval analysis for processing experimental data under conditions of uncertainty and noisy experimental data is shown. Determination of the dependence of the Brinell hardness of refined hafnium samples on the mass oxygen content was performed by a combination of methods: removal of anomalous measurements by interval analysis methods and approximation of data from truncated samples by the method Levenberg-Marquardt minimization.

The influence of alumina (Al2O3) content and diameter on the viscosity characteristics of the alumina/linear low-density polyethylene (Al2O3/LLDPE) composites was discussed. The composites were fabricated by melt mixing with the two-rotor continuous mixer. The equivalent surface average particle diameter ( d ¯ A {\bar{d}}_{\text{A}} ) of Al2O3 was calculated by the scanning electron microscopic (SEM) images of samples. The steady-state and dynamic rheological measurements were used to study the evolution of viscosity parameters. With the Carreau model fitting to the steady-rate rheological data, zero-shear viscosity η 0, time constant λ, and power law index n of composites were obtained. On this basis, an optimized Carreau model was established by studying the changes of these parameter values. The rheological result presented that the parameter values (η 0, λ, and n) were linearly proportional to the filling content of Al2O3 particles for nano-Al2O3/LLDPE composites. However, these parameters were, respectively, related to d ¯ A {\bar{d}}_{\text{A}} , d ¯ A 2 {\bar{d}}_{\text{A}}^{2} , and d ¯ A 3 {\bar{d}}_{\text{A}}^{3} for micron-Al2O3/LLDPE composites.

A procedure for measuring the rhenium content in radioactive ore rocks is tested. Samples of rhenium-containing rocks are irradiated with neutrons from a photoneutron source. Analysis of activation gamma spectra shows that rhenium can be identified against a background of accompanying elements, making neutron activation analysis an effective way of determining rhenium content.

We develop a flexible content-based search model that links the content preferences of search engine users to query search volume and click-through rates, while allowing content preferences to vary systematically based on the context of a search. Content preferences are defined over latent topics that describe the content of search queries and search result descriptions. Compared with existing applications of topic modeling in marketing and recommendation systems, our proposed approach can simultaneously capture multiple types of information and investigate multiple aspects of behavioral dynamics in a single framework that enables interpretable results for business decision making. To facilitate efficient and scalable inference, we develop a full Bayesian variational inference algorithm. We evaluate our modeling framework using real-world search data for TV shows from the Bing search engine. We illustrate how our model can quantify the content preferences associated with each query and how these preferences vary systematically based on whether the query is observed before, during, or after a TV show is aired. We also show that our model can help the search engine improve its ranking of search results as well as address the cold-start problem for new page links. This paper was accepted by Hamid Nazerzadeh, big data analytics.

Small scale social network platforms suffer from increased sparsity, both in the size of text posted by users and the number of posts, as well as the specific nature of kurtosis that affects all platforms, yet more so on an emerging platform. In this work we examine a dataset from such a platform, where the majority of the activity is in the form of user generated text; both posted content and comments left on those posts. We inquire into what techniques would present suitable recommendations for a platform with a similar characteristic dataset. We evaluate leading textual analysis techniques and show how topic-model based techniques present a viable means for recommendation on such a platform as compared to other simpler, or more advanced techniques.

Recommending video games can be trickier than movies. When it comes to selecting a video game, many factors are involved such as its genre, platform on which it’s played, duration of main and side quests, and more. However, recommending games based on just these features won’t suffice as a person who, for example, enjoys a certain genre of game can equally enjoy a vastly different genre. Therefore, a scoring mechanism is required which takes into account both, features of a game (contentbased filtering) and also studies the buying patterns of people playing a particular game (collaborative filtering). In this paper I have proposed a way to take into account both content-based and collaborative filtering into the final recommendation. I have used cosine similarity to quantify the similarity between the features of games. Along with this, I have employed a Deep fullyconnected AutoEncoder (DAE) to generalize the implicit data representation of an user’s buying patterns. Finally, I present a novel approach to combine the scores of these filtering techniques in such a way that it gives equal weightage to both. In other words, they both have equal influence over the final list of the top 10 games recommended to the user. Keywords: Hybrid Recommender, Collaborative filtering, Content-based filtering, Cosine similarity, AutoEncoder.

The massive volume of data stored in computer files and databases is rapidly increasing. Users of these data, on the other hand, demand more complex information from databases. The video data have exponential growth towards accessing and storing. The vital problem associated to video data is efficient, qualitative and fast accessing. We talk about how video pictures are clustered. We presume video clips have been divided into shots, each of which is denoted by a collection of key frames. As a result, video clustering is limited to still key frame pictures. In amble database finding the qualified data set (clusters) is quite time-taking job. The video data mining relate to multi–lingual text, numeric, image, video, audio, graphical, temporal, relational and categorical data. It may be any kind of information medium that can be represented, processed, stored, fast accessing or summarization of clusters are required due to which significant frame-set is formed. Due to sampling error and test reliability in video, substantial changes of more than one frame are predicted. The goal of this article is to show how to employ a familiar and easy nonparametric statistical approach (chi-square) to select eligible data/framesets for analysis. The chi-square model illustrated here is a straightforward, sensible, fast, reduce saddle, and easiest method. Skimming/ Summarization and clipping technique are further enhanced by this technique along with video database maintenance technique from simple descriptors to a complex description schemes like spatial and temporal or high dimensional indexing.&nbsp

With the promulgation of industry guidelines, near infrared spectroscopy (NIRS) monitoring the uniformity of solid oral preparations has become one of the most reported studies. The purpose of the present study is to develop a near infrared (NIR) method for the in-line assessment of the active pharmaceutical ingredient (API) content in the fluidized bed mixing process, as well as to introduce a portable NIR sensor to monitor the fluidized bed production visually. A portable NIR sensor was used to monitor the content of the API in the fluidized bed mixing process. An experimental fluidized bed was performed and the corresponding NIR spectra were collected in-line. The spectrum selection method of cosine distance for in-line spectra was performed, and four wavelength optimization methods were compared to improve the accuracy of the model. Throughout the mixing process, the content uniformity of the API was a critical quality attribute (CQA). The partial least squares regression (PLSR) quantitative model of API content was established. The results showed that the cosine distance combined with the multi-variable selection methods (CC, VIP, RATC, and UVE) could obtain more useful information than the single method. The root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) values of the optimal PLSR model were 1.8588% and 1.5296%, respectively. Based on the results obtained, this study could be used as a reference for the pilot of in-line monitoring of miniature NIR sensors and the connection of key process parameters to realize intelligent production of solid preparations.

Background: The Mathematics curriculum expresses the control and power materialised in the teaching programmes through the presentation and approach of the contents and in the didactic and methodological guidelines. Objective: To explore references that guide the meanings of content organisation in the form of activities in curriculum development. Design: Discussion from the perspective of theoretical study anchored in the qualitative research approach. Settings and participants: Theoretical discussion that did not involve participants as research collaborators. Data collection and analysis: Critical reading and theories of the curriculum field and its implications for the proposals to educate through mathematics, considering curricula as operators of principles and practices. Results: The linear organisation operates the technical curriculum, leading to experiences of control and maintenance of the power that knowledge provides, while the organisation as a rhizomatic network provides the curriculum as a product of social demands, placing mathematics at the service of learning. Conclusions: The contradictions of principles and practices when mathematically educating indicate the relevance of studying and discussing curricula and how to organise the contents to create the conditions for the production of thought and criticism by Mathematics.

Sea surface temperature (SST) in the Yellow Sea Warm Current (YSWC) pathway is sensitive to the East Asian Winter Monsoon (EAWM) and YSWC. However, the role of the YSWC in the evolution of regional SST remains unclear. Here, we present new $${\rm{U}}_{^{37}}^{{\rm{k}}\prime }$$ based SST and grain size sequences spanning the last 6 092 years in the sediment core Z1, which was retrieved from the central Yellow Sea muddy area. Overall, $${\rm{U}}_{^{37}}^{{\rm{k}}\prime }$$ -SST gradually increased since 6.1 ka BP, with a series of centennial-scale fluctuations. Its variation was mainly caused by EAWM when YSWC was weak between 6.1 and ∼3.9 ka BP, as shown by the end-member content of grain size. However, after YSWC was fully developed, i.e., since ∼3.9 ka BP, it exerted critical effects on SST evolution in its pathway. The 1 010, and 538-year cycles of the SST sequence indicated a basic control of solar activity on the oceanic conditions in the Yellow Sea. It is suggested that the variation of total solar irradiance was amplified by thermohaline circulation and then transmitted to the Yellow Sea through the EAWM. Meanwhile, the tropical Pacific signal of El Nino was transmitted to the YSWC through the Kuroshio Current. The dual properties of warm water transported by YSWC to compensate the EAWM and driving by Kuroshio Current closely linked the variation of SST in the YSWC pathway to the Northern Hemisphere high latitude climate and the tropical Pacific. These findings highlight the significance of YSWC on regional SST evolution and its teleconnection to high and low latitude forcing, which grains a better understanding of the long-term evolution of SST in the middle latitude Yellow Sea.

Laboratory experiment and thermodynamic calculation for the Ti-containing 24 mass pct Cr ferritic stainless steel with a CaO-SiO2-Al2O3-MgO system slag were performed to investigate the effect of slag addition on the inclusion characteristics in molten steel. The morphology, composition, and size evolution of inclusions in steel samples were analyzed in three-dimensional by the electrolytic extraction method and in two-dimensional by the automatic analysis method. The results showed that the Ti content significantly decreased after the slag addition. However, the change of the Si content showed an opposite tendency. The decrease of the Ti content in steel was due to the reduction of SiO2 and Al2O3 in the slag by dissolved Ti in steel. An increase of the TiO2 content in the slag can decrease the Ti loss in steel based on the slag-steel kinetic analysis. The total O content in the steel melt decreased from 62 to 26 ppm, and the steel cleanliness was improved, since the number density of inclusions decreased after the slag refining. The results of a kinetic analysis showed that the rate-determining step of the oxidation of Ti in the steel and the reduction of SiO2 in the slag were the mass transfer on the slag side. In addition, high Ti2O3-containing inclusions were found to be transformed to Cr2O3-Ti2O3-Al2O3 and Cr2O3-Ti2O3-SiO2 system inclusions after the slag addition. The Al2O3 contents in inclusions increased while the Ti2O3 contents decreased with time. However, there were some amount of high melting point inclusions with high Al2O3 content, which were not what we expected. When plotted on logarcxithmic scales, the mole ratio $$X_{{{\text{Al}}_{2} {\text{O}}_{3} }} /(X_{{{\text{Ti}}_2 {\text{O}}_{3} }} \cdot X_{{{\text{Cr}}_{2} {\text{O}}_{3} }} )$$ X Al 2 O 3 / ( X Ti 2 O 3 · X Cr 2 O 3 ) values of the inclusions were expressed as a linear function of the $$a_{\text{Al}}^{2} /(a_{Ti}^{2} \cdot a_{\text{Cr}}^{2} \cdot a_{\text{O}}^{3} )$$ a Al 2 / ( a Ti 2 · a Cr 2 · a O 3 ) values of the steel melts with a slope of unity, which was theoretically expected.

The Ag-mixed $${\text{Se}}_{70}{\text{Te}}_{30}$$ thermally deposited semiconducting thin films show interesting thermoelectric properties. As the Ag content in the structure of $${\text{Se}}_{70}{\text{Te}}_{30}$$ increases, the Seebeck coefficient increases. The semiconductive thin films reveal a p-type behavior. The dark conductivity increases at 300 K, whereas a reduction in $$\text{c}\text{o}\text{r}\text{r}\text{e}\text{s}\text{p}\text{o}\text{n}\text{d}\text{i}\text{n}\text{g}$$ activation energy for dark, photo and thermal response is observed with the increase in the Ag content. It is elucidated that the power factor for $${\left({\text{Se}}_{70}{\text{Te}}_{30}\right)}_{100-x}{\text{Ag}}_{x} (0.0\le x \le 8.0\; {\text{at}}.{\%})$$ semiconducting thin films can be tuned and enhanced at varied temperature ranges through adjusting the addition amount of Ag. These results indicate that these semiconducting thin films have remarkable potential as thermoelectric generators.

This paper presents a study on Chlef sand to examine the effect of fines content (Fc), relative density (RD) and initial conditions on the compressibility behavior. The interpretation of the results is based on the concept of the intergranular voids ratio (es) and two hypoplastic parameters model Hs and n for calculation of the maximum voids ratio. The œdometric tests results made in the laboratory show that the fines content transition (Fct) of Chlef sand is in good agreement with the results published in the literature. The results obtained indicate that the higher value of fines fraction (Fc) in the sand cause an increase in the compressibility coefficient (Cc) and the granular compressibility coefficient (Cc-s). Moreover increasing the density from 65 to 80% decreased both coefficients (Cc) and (Cc-s). The samples prepared with the moist tamping method (w = 3%) have compressibility coefficients greater than samples prepared by the dry pluviation method (w = 0%). We have shown that the fines content transition (Fct) depends on the initial state of the samples (relative density, preparation method and maximum void ratio). Finally the granulometric characteristics (D10, D50 and Cu) have a significant effect on compression behavior. Nevertheless a good exponential correlation has been found between the compressibility coefficient (Cc), the granular compressibility coefficient (Cc-s) and the effective diameter (D10), the average diameter (D50) and the uniformity coefficient (Cu).

This article proposes a hybrid symbolic aggregate approximation and vector space model (SAX-VSM) method for automatically classifying soil water content cycles. In the proposed method, a novel similarity measure, the distance weighted cosine (DWC) similarity measure, is introduced to improve the classification performance of the SAX-VSM. The DWC similarity measure incorporates both direction and distance information of feature vectors. Meanwhile, a mixed-integer optimization problem is formulated to determine hyperparameters. An extended Rao-1 algorithm, I-Rao-1 algorithm, is developed to solve such optimization problems. To verify the feasibility and effectiveness of the proposed method, three soil moisture data sets collected from the Florida research trials are employed. Compared with state-of-the-art methods, the proposed method has achieved the best performance based on all data sets in terms of the highest accuracy, precision, and recall values. Therefore, it is promising to apply the proposed method into real applications in the smart irrigation system.

As it is known, drought is one of the most important issues of recent years. On the other hand, agriculture is the sector that uses the most water. The impact of drought can be reduced by reducing the water used in agriculture. Therefore, it is very important to determine the application time and amount of irrigation water for a successful agricultural irrigation management. One of the most important ways to achieve this success is to accurately determine and monitor the water content in the plant root zone. Soil water content can be determined in two ways; direct and indirect methods. The direct measurement method is tedious, laborious and time consuming. Instead, a large number of indirect measurement methods are developed. One of these indirect measurement methods is the PR2 Profile Probe method. In this study, the possibilities of using PR2 method under different soil water content conditions were investigated. First, the calibration of the PR2 method was made within 40 cm of soil depth. Then, the water content in the soil was monitored by the PR2 method under three different soil water content (100%, 75% and 50%) conditions. R2 values for calibration relationships varied between 0.7947 and 0.9305. In the study, it was concluded that soil water content could be monitored with PR2 Profile Probe., Bilindiği gibi kuraklık, son yılların en önemli konularının başında gelmektedir. Öte yandan, tarım en fazla suyu kullanan sektör konumundadır. Tarımda kullanılan suyun azaltılmasıyla kuraklığın etkisi azaltılabilir. Bu nedenle, başarılı bir tarımsal sulama yönetimi için sulama suyunun uygulama zamanı ve miktarının belirlenmesi çok önemlidir. Söz konusu başarıya ulaşmanın en önemli yollarından biri, bitki kök bölgesindeki su içeriğinin doğru bir şekilde belirlenmesi ve izlenmesidir. Toprak su içeriği doğrudan ve dolaylı yöntemler olmak üzere iki şekilde belirlenebilmektedir. Doğrudan ölçüm yöntemi yorucu, zahmetli ve zaman alıcıdır. Bunun yerine çok sayıda dolaylı ölçüm yöntemleri geliştirilmektedir. Söz konusu dolaylı ölçüm yöntemlerinden biri de PR2 Profile Probe yöntemidir. Bu çalışmada, farklı toprak su içeriği koşullarında, PR2 yönteminin kullanılma olanakları araştırılmıştır. İlk olarak, 40 cm toprak derinliği içinde PR2 yönteminin kalibrasyonu yapılmıştır. Daha sonra üç farklı toprak su içeriği (% 100, % 75 ve % 50) koşullarında PR2 yöntemiyle topraktaki su içeriği izlemeye alınmıştır. Kalibrasyon ilişkileri için R2 değerleri 0.7947 ile 0.9305 arasında değişim göstermiştir. Araştırmada, PR2 Profile Probe ile toprak su içeriğinin izlenebileceği sonucuna varılmıştır.

We generalize leading-order asymptotics of a form of the heat content of a submanifold (van den Berg & Gilkey 2015) to the setting of time-dependent diffusion processes in the limit of vanishing diffusivity. Such diffusion processes arise naturally when advection–diffusion processes are viewed in Lagrangian coordinates. We prove that as diffusivity ɛ goes to zero, the diffusive transport out of a material set S under the time-dependent, mass-preserving advection–diffusion equation with initial condition given by the characteristic function 1 S , is ε / π d A ¯ ( ∂ S ) + o ( ε ) . The surface measure d A ¯ is that of the so-called geometry of mixing, as introduced in (Karrasch & Keller 2020). We apply our result to the characterisation of coherent structures in time-dependent dynamical systems.

In polymer-stabilised blue-phase liquid crystal (PSBPLC) display, we have obtained that the optimal content ratio of the polymer monomers RM257 and C12A is 1.225 according to the ideal bonding cond...

We generalize some characterizations of uniformly rectifiable (UR) sets to sets whose Hausdorff content is lower regular (and in particular, do not need to be Ahlfors regular). For example, David and Semmes showed that, given an Ahlfors $d$-regular set $E$, if we consider the set $\mathscr{B}$ of surface cubes (in the sense of Christ and David) near which $E$ does not look approximately like a union of planes, then $E$ is UR if and only if $\mathscr{B}$ satisfies a Carleson packing condition, that is, for any surface cube $R$, \[ \sum_{Q\subseteq R\atop Q\in \mathscr{B}} ({\rm diam} Q)^{d} \lesssim ({\rm diam} R)^{d}.\] We show that, for lower content regular sets that aren't necessarily Ahlfors regular, if $\beta_{E}(R)$ denotes the square sum of $\beta$-numbers over subcubes of $R$ as in the Traveling Salesman Theorem for higher dimensional sets [AS18], then \[ \mathscr{H}^{d}(R)+\sum_{Q\subseteq R\atop Q\in \mathscr{B}} ({\rm diam} Q)^{d}\sim \beta_{E}(R). \] We prove similar results for other uniform rectifiability critera, such as the Local Symmetry, Local Convexity, and Generalized Weak Exterior Convexity conditions. En route, we show how to construct a corona decomposition of any lower content regular set by Ahlfors regular sets, similar to the classical corona decomposition of UR sets by Lipschitz graphs developed by David and Semmes., Comment: 39 pages. To appear in Analysis & PDEs

Sand–cement stabilization is considered as one of the most common in situ methods in the soil improvement practices. Despite the importance of studying some fundamental characteristics such as the stress (q)–strain ( $$\varepsilon$$ ) and the pore pressure (u)–strain ( $$\varepsilon$$ ) behavior of the stabilized soils, very few studies have examined this so far. Hence, this paper aims at adopting an initiative approach which is group method of data handling (GMDH)-type neural network to specifically predict such behavior for cement-treated sands using the consolidated undrained (CU) triaxial test results. To do so, the q– $$\varepsilon$$ and u– $$\varepsilon$$ results from the CU tests are considered on the basis of different variables such as cement content (C), confining pressure (CP), porosity ( $$\eta$$ ) and curing time (D). The obtained data, regarding similar statistical characteristics, are randomly sorted into three groups namely training, validation and testing. Current modeling is based on the first group (80% of the data), whereas the comparisons are made among other approaches in terms of the last one. Moreover, to achieve more accurate predictions, parameters related to the stress ( $$q_{n - 1}$$ ) and pore pressure ( $$u_{n - 1}$$ ) in the previous strain level are assumed in the modeling. It can be concluded that the two-hidden layer model is capable of accurately predicting the q– $$\varepsilon$$ and u– $$\varepsilon$$ behavior for the testing data, compared to other machine learning methods. By and large, GMDH modeling is strongly suggested as a potent method to estimate the soil mechanical properties like brittle index (IB), maximum strength (qmax), failure strain $$(\varepsilon_{{\text{f}}} )$$ and stiffness (E50).

The Poly(vinyl alcohol) (PVA)/Silicon Carbide (SiC) nanocomposites thin films have been precipitated on glass substrates with different percentage content of SiC (1%, 2%, 3%, and 4% wt.) by utilizing the casting method. UV-Visible wavelength ranges from (200–800 nm) were used to compute the optical properties. The results of (PVA/SiC) nanocomposite thin films were used to calculate optical properties such as absorption, refractive, index, extinction factor, dielectric constants, and optical conductivity. The optical parameters increased with increasing the concentration of SiC nanoparticles. The energy gap for direct transition has decreased from 5.2 eV to 5.0 eV, while the indirect transition reduced from 4.3 eV to 4.0 eV. The direct forbidden dropped from 5.1 eV to 5.0 eV, but the value of indirect forbidden change from 4.0 eV to 3.6 eV. The results stated that increases in nano SiC in the structure of PVA lattice is accompanied with decreasing the energy gap value. The results have shown that the urbach energy of (PVA/SiC) increase with increasing SiC content. The dielectric constant high-frequency values were estimated at 3.534 to 2.755. Whereas carrier concentricity per the effective mass $$ \left(\frac{\boldsymbol{N}}{{\boldsymbol{m}}^{\ast }}\right) $$ declines from (7.905*1061 (m3. Kg)−1 to 2.408 × 1061 (m3. Kg)−1), while the unique oscillator energy range change from 6.073 eV to 20.685 eV. But regarding the energy of the dispersion decrease from 4.625 eV to 46.484 eV. The (PVA/SiC) thin films may be used in many fields of optoelectronics as: solar cells and electronic applications with low cost, which is used in spectroscopic features and electronics.

Deep science understanding is reflected in students’ ability to use content and skills when making sense of the world. Assessing deep understanding requires measuring complex constructs that combin...

Map load is a map property quantifying the amount of map content in cartographic products. Since the 1960s, various approaches have been examined to determine map-load value to assume the map compl...

Based on neural machine translation, this article introduced the ConvS2S system and transformer system, designed a semantic sharing combined transformer system to improve translation quality, and compared the three systems on the NIST dataset. The results showed that the operation speed of the semantic sharing combined transformer system was the highest, reaching 3934.27 words per second; the BLEU value of the ConvS2S system was the smallest, followed by the transformer system and the semantic sharing combined transformer system. Taking NIST08 as an example, the BLEU values of the designed system were 4.74 and 1.49 higher than the other two systems. The analysis of examples showed that the semantic sharing combined transformer had higher translation quality. The experimental results show that the proposed system is reliable in English content translation and can be further promoted and applied in practice.

We present the decadally averaged time series of the total ozone content and integrated aerosol backscattering coefficient over Tomsk in the period of 2000–2016, obtained using the М-124 ozonometer and lidar method, respectively. The relationship between them is studied. The time series for the period of time, considered here, were used to create the annual behaviors in the form of decadal values (36 points in all) of the parameters studied. These time series were analyzed to identify their differences and similarities.

Syntheses of the $$Y_3Ba_5Cu_8O_{18\pm \delta }$$ (noted Y-358) +x wt.% TiO2 (x = 0.00, 0.10, 0.30, 0.50 and 0.60 wt%) bulk superconducting material are prepared by the standard solid-state reaction process. Then, systematic electrical conductivity fluctuation in normal and superconducting state analyses on the samples is reported. X-ray diffraction (XRD) and scanning electron microscopy (SEM) are used to systematically assess stage formation and microstructures of the samples. XRD with the Rietveld refinement procedure showed that by cumulating the amount of TiO2 nanoparticle into Y358 substance, the crystal lattice constants altered slightly and the orthorhombicity reduced compared to the pure sample. The impact of TiO2 adding upon the superconducting characteristics with critical temperatures Tc analysis showed that as the inclusion of TiO2 nanoparticles content increases the critical temperatures are enhanced for all of the doped samples. Evaluations of excess conductivity fluctuation were conducted by Aslamazov–Larkin (AL) model. Inside the grains, dimensional fluctuation is depending on the Lawrence–Doniach (LD) temperature named $$T_{LD}$$ . This parameter ( $$T_{LD}$$ ) was increased in the mean-field area by rising TiO2 in Y358 substance compared to the non-added sample. However, analysing the excess conductivity based on the AL concept leads to the determination of thermodynamic fluctuation and some parameters values such as the critical temperature $$(T_{c\ zero})$$ , coherence length $$\xi _c(0)$$ , super-layer length d, critical magnetic fields $$B_{c1}(0)$$ , $$B_{c2}(0)$$ and critical current density $$J_c(0)$$ . These parameters which are significant by the TiO2 nanoscale doping show that the theory outlined in the chapter “Excess conductivity model” is sufficient to describe our results.

We present the serendipitous discovery of a galaxy group in the XMM-LSS field with MIGHTEE Early Science observations. 20 galaxies are detected in H i in this z ∼0.044 group, with a 3σ column density sensitivity of NHI = 1.6 × 1020 cm-2. This group has not been previously identified, despite residing in a well-studied extragalactic legacy field. We present spatially resolved H i total intensity and velocity maps for each of the objects which reveal environmental influence through disturbed morphologies. The group has a dynamical mass of log10(Mdyn/M⊙) = 12.32, and is unusually gas-rich, with an H i-to-stellar mass ratio of log10(f∗HI) = -0.2, which is 0.7 dex greater than expected. The group's high H i content, spatial, velocity, and identified galaxy type distributions strongly suggest that it is in the early stages of its assembly. The discovery of this galaxy group is an example of the importance of mapping spatially resolved H i in a wide range of environments, including galaxy groups. This scientific goal has been dramatically enhanced by the high sensitivity, large field-of-view, and wide instantaneous bandwidth of the MeerKAT telescope. © 2021 The Author(s)., The research of SR and RPD is supported by the South African Research Chairs Initiative (grant ID 77948) of the Department of Science and Innovation and National Research Foundation. SR, RPD, and MJJ acknowledge the financial assistance of the South African Radio Astronomy Observatory (SARAO) towards this research (www.ska.ac.za). The HSC instrumentation and software were developed by the National Astronomical Observatory of Japan (NAOJ), the Kavli Institute for the Physics and Mathematics of the Universe (Kavli IMPU), the University of Tokyo, the High Energy Accelerator Research Organization (KEK), the Academia Sinica Institute for Astronomy and Astrophysics in Taiwan (ASIAA), and Princeton University. Funding was contributed by the FIRST program from Japanese Cabinet Office, the Ministry of Education, Culture, Sports, Science and Technology (MEXT), the Japan Society for the Promotion of Science (JSPS), Japan Science and Technology Agency (JST), the Toray Science Foundation, NAOJ, Kavli IPMU, KEK, ASIAA, and Princeton University. AAP acknowledges the support of the STFC consolidated grant ST/S000488/1. WM is supported by the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation. RB acknowledges support from the Glasstone Foundation and from an STFC Ernest Rutherford Fellowship [grant number ST/T003596/1]. NM acknowledges support from the Bundesministerium für Bildung und Forschung (BMBF) award 05A20WM4. MJJ acknowledges support from the UK Science and Technology Facilities Council [ST/S000488/1 and ST/N000919/1]. MT and MJJ acknowledge support from the Oxford Hintze Centre for Astrophysical Surveys which are funded through generous support from the Hintze Family Charitable Foundation. LVM acknowledges financial support from the grants AYA2015-65973-C3-1-R and RTI2018-096228-B-C31 (MINECO/FEDER, UE), as well as from the State Agency for Research of the Spanish Ministry of Science, Innovation and Universities through the ‘Center of Excellence Severo Ochoa’ award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). This research made use of Astropy,4 a community-developed core PYTHON package for Astronomy. MG and JC acknowledge financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA).

The interaction parameters of Nb in Fe–C–Nb melts at 1873 K were measured using the chemical equilibrium method. The Fe–C melts were equilibrated with the CaO–MgO–Al2O3–NbO2 slags under a controlled oxygen potential for 24 h. In addition to acting as the protective gas, argon was adopted to control the oxygen potential. Based on the data obtained in the experiments, the activity interaction parameters were obtained by the multiple linear regression method. The first-order interaction parameters $$e_{{{\text{Nb}}}}^{{\text{C}}}$$ and $$e_{{{\text{Nb}}}}^{{{\text{Nb}}}}$$ are determined to be − 0.035 and − 0.134, respectively. The second-order interaction parameters $$r_{{{\text{Nb}}}}^{{\text{C}}}$$ , $$r_{{{\text{Nb}}}}^{{\text{Nb,C}}}$$ , and $$r_{{{\text{Nb}}}}^{{{\text{Nb}}}}$$ are determined to be 0.011, − 0.0063, and 0.0023, respectively. The thermodynamic data obtained are more reliable than those in previous publications for the Fe–C–Nb system when the Nb content range was 0.92–4.62 wt.%.

The effect of rare earth element Er addition on the microstructure and phase transformation behavior of Ni_{50}Ti_{50-x}Er_{x} (x =0, 1, 5) shape memory alloy was investigated experimentally. The results showed that the microstructure of Ni-Ti-Er ternary alloys consists of the NiEr precipitate and the NiTi matrix. A one-step martensitic transformation was observed in all alloys. The martensitic transformation temperature M_s increased gradually with increasing Er content.

IoT content usually comes from power-constrained sensors and requires applying different levels of protection. We design a bounded-error-pruned IoT content market (BIoTCM) framework with preserving privacy protection (BEPDPP) scheme using blockchain smart contract. According to payment level applied in smart contract of BIoTCM, our BEPDPP will prune original data within a given level of bounded-error to provide different resolutions of content for consumers. As the real data is intrinsically hidden, content protection is provided with privacy-preserving. Experimental results generated by five different types of IoT content demonstrate that our content protection solution is cost-effective in sensor lifetime.

Radical reform of the education system, rapid development of science, engineering and technology in the country, as well as consistent changes in the content of education are considered a priority "Improving the functioning of all links of the education system on the basis of modern requirements." modernization of the content of vocational education, teaching technologies and systems for assessing the results of mastering on the basis of a competency-based approach, the creation of didactic support for the formation of competencies is becoming increasingly important.