Miracle-dz/UniFAR-FTUs huggingface dataset:
Interband and Intraband Absorption Coefficients of Silicon: Theoretical Frameworks and Formulations

Theoretical frameworks and formulations for calculating Si interband and intraband absorption coefficients arepresented and discussed in this work. They are based on the second-order time-dependent perturbation theory of quantum mechanics which incorporates interaction matrices between electrons, photons, phonons, and charged impurities. These frameworks include the interband and intraband processes of direct and indirect transitions. The intraband indirect-transition processes include phonon-assisted and charged-impurity-assisted intravalley processes, inter-non-equivalent-valley processes, inter-opposite-equivalent-valley g-processes, and inter-non-opposite-equivalent-valley f-processes. These theoretical formulations are verified with the interband absorption coefficients from Green's data and the Rajkanan-Singh-Shewchun formula. They are also verified with the intraband free-carrier absorption coefficients from the Spitzer-Fan data in n-type Si at different doping concentrations, Green's formula, the Schroder-Thomas-Swartz formula, the Soref-Bennett formula for 1.3 and 1.55 μm wavelengths, and Ridley's equations. The agreements and discrepancies between this theoretical work and other experimental data, empirical formulas, theoretical equations are examined and investigated. This work will provide a fundamental theoretical framework and formulation for calculating Si interband and intraband absorption coefficients which could be useful for the design and modeling of Si photonic devices.
SEMKC: Secure and Efficient Computation over Outsourced Data Encrypted under Multiple Keys

Cloud computing is a popular paradigm to facilitate massive data computation and storage. The issue is challenging as data owners outsource their data after encryption to preserve privacy. In this work, we propose two efficient techniques namely SEMKC<inline-formula><tex-math notation="LaTeX">$^+$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="nayak-ieq1-2859051.gif"/></alternatives></inline-formula> and SEMKC<inline-formula><tex-math notation="LaTeX">$^*$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>*</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="nayak-ieq2-2859051.gif"/></alternatives></inline-formula> to compute remotely over encrypted data. SEMKC<inline-formula><tex-math notation="LaTeX">$^*$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>*</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="nayak-ieq3-2859051.gif"/></alternatives></inline-formula> can be used for execution which has more number of multiplications and fewer additions, while SEMKC<inline-formula><tex-math notation="LaTeX">$^+$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="nayak-ieq4-2859051.gif"/></alternatives></inline-formula> would be used for the process with more number of additions and fewer multiplications. Both the schemes facilitate to compute over the data from multiple owners encrypted with different keys, without leaking the privacy. Further, the scheme is proved to be secure on “Real world-Ideal world” paradigm. The performance comparison has been made with existing schemes and observed that our scheme requires less computation and communication in comparison to the other popular existing schemes.
Coherent couplings between magnetic dipole transitions of quantum emitters and dielectric nanostructures

Here we study theoretically the optical responses of hybrid structures composed of dielectric nanostructures and quantum emitters with magnetic dipole transitions. Coherent couplings between magnetic dipole transitions and magnetic modes can occur, leading to giant modifications of the extinction spectra of the constituents in the hybrid structures. For a given hybrid structure, the extinction-cross-section spectra show linear or nonlinear behaviors depending on the strength of the excitation field. For a weak excitation, the extinction of the quantum emitters is greatly enhanced. The hybrid structure shows a dip on its extinction spectrum. For a strong excitation, the resonant extinction of the quantum emitters is weakly enhanced while the extinction spectrum is broadened obviously. The hybrid structure shows a Fano-like line shape on its extinction spectrum, which is different from that with a weak excitation. This difference is highly related to the behaviors of the magnetic polarizabilities of the quantum emitters in the hybrid structure. The optical responses of hybrid structures can be largely tuned by varying the geometric and material parameters.
A model of hardness and fracture toughness of solids

Hardness and fracture toughness are some of the most important mechanical properties. Here, we propose a simple model that uses only the elastic properties to calculate the hardness and fracture toughness. Its accuracy is checked by comparison with other available models and experimental data for metals, covalent and ionic crystals, and bulk metallic glasses. We found the model to perform well on all datasets for both hardness and fracture toughness, while for auxetic materials (i.e., those having a negative Poisson’s ratio), it turned out to be the only model that gives reasonable hardness. Predictions are made for several materials for which no experimental data exist.Hardness and fracture toughness are some of the most important mechanical properties. Here, we propose a simple model that uses only the elastic properties to calculate the hardness and fracture toughness. Its accuracy is checked by comparison with other available models and experimental data for metals, covalent and ionic crystals, and bulk metallic glasses. We found the model to perform well on all datasets for both hardness and fracture toughness, while for auxetic materials (i.e., those having a negative Poisson’s ratio), it turned out to be the only model that gives reasonable hardness. Predictions are made for several materials for which no experimental data exist.
Blockchain Transaction Protocol for Constraint Nodes

The goal of the blockchain transaction protocol for constraint nodes is to enable the generation of blockchain transactions by constraint nodes, according to the following principles: - transactions are triggered by Provisioning-Messages that include the needed blockchain parameters. - binary encoded transactions are returned in Transaction- Messages, which include sensors/actuators data. Constraint nodes, associated with blockchain addresses, compute the transaction signature.
Prediction Model Design for Vibration Severity of Rotating Machine Based on Sequence-to-Sequence Neural Network

Steam turbine rotor system is a main part of the power production process. Accurate prediction of the turbine rotor operation state leads to timely detection of the hidden danger and accordingly ensures the efficient power production. The vibration severity reflects the vibration intensity and the working condition as well. Since the accuracy of the normal prediction method is not enough, a new model is proposed in this paper that combines the sequence prediction model with the gated recurrent unit (GRU). According to the obtained results, the accuracy is improved through the proposed model. To verify the effectiveness of the model, simulations are performed on the steam turbine rotor unbalance fault data. The experimental results demonstrate that the proposed approach could be utilized for vibration severity prediction as well as state warning of the steam turbine.
CFD-DEM Modeling and Simulation Coupled to a Global Thermodynamic Analysis Methodology for Evaluating Energy Performance: Biofertilizer Industry

This work develops a methodology based on real chemical plant data collected from a Nitrogen-Phosphorus-Potassium fertilizer (NPK) cooling rotary drum. By blending thermodynamic variables given by global energy and mass balances with computational fluid dynamics-discrete element method (CFD-DEM) modeling and simulation, the methodology provides an initial approximation to the understanding of heat transfer inside industry rotary coolers. The NPK cooling process was modeled in CFD software Simcenter STAR − CCM + 13.06. 011 using a Eulerian–Lagrangian scheme through a coupled CFD-DEM method using one-way coupling. The average temperature of the NPK particles was obtained as well as the average mass flow of the particles dropping as the drum was rotating. The analysis was performed for two-particle diameters (8 and 20 mm) during 17.5 s. The average heat transfer coefficient between the fluid and the NPK particles during the simulated time was obtained. A thermodynamic analysis was carried out using instantaneous energy and mass balances. Prandtl, Nusselt, and Reynolds numbers were obtained for each simulated time step. Finally, through a non-linear regression using the Marquardt method, a correlation between Prandtl, Nusselt, and Reynolds number was developed that allowed analyzing the rotating drum. Results showed that the proposed methodology could serve as a useful tool during the design and analysis of any given rotary cooler, allowing calculation of the heat transfer coefficient and obtaining the process variables that could expand the machine operational capabilities due to the knowledge of the Nusselt number as a function of the drum working parameters.
Multivariate weighted recurrent network for analyzing SSMVEP signals from EEG literate and illiterate

Recently, the Steady-State Motion Visual Evoked Potential (SSMVEP)-based Brain Computer Interface (BCI) has attracted a lot of attention. We design a SSMVEP-based BCI, in which a ring-shaped motion checkerboard pattern is used to realize SSMVEP stimulation. In particular, we firstly conduct SSMVEP experiments to obtain electroencephalogram (EEG) signals from 10 subjects, including 5 EEG literates and 5 EEG illiterates. By using the Canonical Correlation Analysis (CCA) and Support Vector Machine (SVM) method, we find that the classification accuracies of EEG illiterates are relatively lower than that of EEG literates. Thus, in order to investigate the differences in brain cognitive processes between the two groups of subjects, we construct a multivariate weighted recurrence network and analyze the weighted local efficiency and the clustering coefficient of the two groups. The results indicate that in SSMVEP experiment, there are significant differences between the two groups of subjects in these two network indicators. Our approach and analysis provide novel insights into the cognitive behavior of the brain and understanding of the “BCI Illiteracy” problem.
Multialgorithm Fusion Image Processing for High Speed Railway Dropper Failure–Defect Detection

The dropper is one of the core components of the high speed railway catenary and dropper failure will lead to serious transportation accidents. It is very important to carry out dropper failure and defect detection. There are a large number of droppers installed in the catenary. The dropper images are collected by the high-definition camera installed on the top of the moving catenary inspection vehicles. The image quality and image consistency are poor, and it is very difficult to identify dropper defects automatically. The railway department and companies lack efficient and intelligent detection methods. This article innovatively proposes a multialgorithm fusion image processing technology, and builds a dropper recognition and failure–defect detection model based on a deep learning algorithm and subpixel level dropper defect detection model, and achieves high accuracy dropper failure and defect detection. The detection model based on the Faster R-CNN algorithm is studied to realize the positioning and recognition of the dropper and the failure detection of bending slack and broken dropper. The subpixel level dropper defect detection algorithm is based on the fusion of the image preprocessing, dropper fine positioning algorithm, edge fitting and bending zoom algorithms, the Hough transform algorithm, and so on. These can be used to realize detection of defects, such as microdeformation, dropper-strands loosened, dropper-strands broken, and foreign body adhesions. The test is verified by the catenary images taken from a practical high speed railway. The detection accuracy, real-time performance, and stability of the algorithm meet the needs of inspection and maintenance for a high speed railway.
Estimation non paramétrique de densités conditionnelles : grande dimension, parcimonie et algorithmes gloutons.

Nous considerons le probleme d’estimation de densites conditionnelles en moderement grandes dimensions. Beaucoup plus informatives que les fonctions de regression, les densites condi- tionnelles sont d’un interet majeur dans les methodes recentes, notamment dans le cadre bayesien (etude de la distribution posterieure, recherche de ses modes.). Apres avoir rappele les problemes lies a l’estimation en grande dimension dans l’introduction, les deux chapitres suivants developpent deux methodes qui s’attaquent au fleau de la dimension en demandant : d’etre efficace computation- nellement grace a une procedure iterative gloutonne, de detecter les variables pertinentes sous une hypothese de parcimonie, et converger a vitesse minimax quasi-optimale. Plus precisement, les deux methodes considerent des estimateurs a noyau bien adaptes a l’estimation de densites conditionnelles et selectionnent une fenetre multivariee ponctuelle en revisitant l’algorithme glouton RODEO (Re- gularisation Of Derivative Expectation Operator). La premiere methode ayant des problemes d’ini- tialisation et des facteurs logarithmiques supplementaires dans la vitesse de convergence, la seconde methode resout ces problemes, tout en ajoutant l’adaptation a la regularite. Dans l’avant-dernier cha- pitre, on traite de la calibration et des performances numeriques de ces deux procedures, avant de donner quelques commentaires et perspectives dans le dernier chapitre.
Simulation on Cooperative Changeover of Production Team Using Hybrid Modeling Method

In the multi-variety and small-quantity manufacturing environment, changeover operation occurs frequently, and cooperative changeover method is often used as a way to shorten the changeover time and balance the workload. However, more workers and tasks will be affected by cooperative changeover. As such, the effectiveness of the cooperative changeover is dependent on other factors, such as the scope of cooperation and the proportion of newly introduced products. For this reason, this paper proposes a hybrid modeling method to support the simulation study of the production team's cooperative changeover strategies under various environments. Firstly, a hybrid simulation modeling method consisting of multi-agent systems and discrete events is introduced. Secondly, according to the scope of cooperation, this paper puts forward four kinds of cooperative changeover strategies. This paper also describes the cooperative line-changing behavior of operators. Finally, based on the changeover strategies, the proposed simulation method is applied to a production cell. Four production scenarios are considered according to the proportion of newly introduced part. The performance of various cooperative strategies in different production scenarios is simulated, and the statistical test results show that the optimal or satisfactory strategy can be determined in each production scenario. Additionally, the effectiveness and practicability of the proposed modeling method are verified.
hr500k – A Reference Training Corpus of Croatian.

In this paper we present hr500k, a Croatian reference training corpus of 500 thousand tokens, segmented at document, sentence and word level, and annotated for morphosyntax, lemmas, dependency syntax, named entities, and semantic roles. We present each annotation layer via basic label statistics and describe the final encoding of the resource in CoNLL and TEI formats. We also give a description of the rather turbulent history of the resource and give insights into the topic and genre distribution in the corpus. Finally, we discuss further enrichments of the corpus with additional layers, which are already underway.
Hybrid excited permanent magnet machines for electric and hybrid electric vehicles

This paper reviews various hybrid excited (HE) machines from the perspective of location of PM and DC excitation, series/parallel connection of PM and DC excited magnetic fields, and 2D/3D magnetic fields, respectively. The advantages as well as drawbacks of each category are analyzed. Since an additional control degree, i.e. DC excitation, is introduced in the HE machine, the flux weakening control strategies are more complex. The flux weakening performance as well as efficiency are compared with different control strategies. Then, the potential to mitigate the risk of uncontrolled overvoltage fault at high speed operation is highlighted by controlling the field excitation. Since additional DC coils are usually required for HE machines compared with pure PM excitation, the spatial confliction inevitably results in electromagnetic performance reduction. Finally, the technique to integrate the field and armature windings with open-winding drive circuit is introduced, and novel HE machines without a DC coil are summarized.
UWB MIMO antenna implemented with orthogonal quasi‐circular slot dipole radiators

In this paper, a very low‐profile two‐port ultra‐wideband antenna for multiple input‐multiple output applications is proposed. The antenna is implemented by using two orthogonal quasi‐circular slot dipole radiators fed by coaxial lines. The antenna performs from 2 to 10 GHz, with an average peak‐gain of 4 dB, and high port isolation, with values around S21 = −20 dB and below. The radiation patterns of both antennas are opposite to each other and hence, the diversity gain reaches values around 20 dB. The low inter‐port coupling and low correlation are verified by obtaining the envelope correlation coefficient, which is lower than 0.003. These calculations were made by the S‐parameter and far‐field methods. The total active reflection coefficient shows that the antenna operative bandwidth does not change for different input signals with random phases, preserving the operation from 2 to 10 GHz. The antenna performance is compared to different state of the art slot configurations, showing advantages to previously published work.
Strategic goal interdependence approach to dynamic capability and the effects of customer integration and market dynamism: evidence from China

ABSTRACT Based on the theory of cooperation and competition, this study proposed goal interdependence with downstream company as an important enabler of firms’ dynamic capability. Moreover, we examined both how and when cooperative and competitive goals affect dynamic capability by considering customer integration as a mediator and market dynamism as an important contingency. We tested our moderated mediation model by using survey data from a cross-industry sample of 233 firms in China. Results of structural equation analyses suggest that firms and downstream companies that recognize strategic goal interdependence as cooperation rather than competition develop customer integration. With customer integration, firms’ dynamic capability is promoted. Additionally, the moderated mediation analysis revealed that the positive indirect relationship between cooperative goal and dynamic capability with the linkage of customer integration is weaker for higher levels of market dynamism, but the negative indirect effect of competitive goal on the dynamic capability through customer integration does not depend on market dynamism. Based on these findings, we discussed how our findings extend dynamic capability research, the theory of cooperation and competition and provide implications for practice.
On NACK-Based rDWS Algorithm for Network Coded Broadcast

The Drop when seen (DWS) technique, an online network coding strategy is capable of making a broadcast transmission over erasure channels more robust. This throughput optimal strategy reduces the expected sender queue length. One major issue with the DWS technique is the high computational complexity. In this paper, we present a randomized version of the DWS technique (rDWS), where the unique strength of the DWS, which is the sender’s ability to drop a packet even before its decoding at receivers, is not compromised. Computational complexity of the algorithms is reduced with rDWS, but the encoding is not throughput optimal here. So, we perform a throughput efficiency analysis of it. Exact probabilistic analysis of innovativeness of a coefficient is found to be difficult. Hence, we carry out two individual analyses, maximum entropy analysis, average understanding analysis, and obtain a lower bound on the innovativeness probability of a coefficient. Based on these findings, innovativeness probability of a coded combination is analyzed. We evaluate the performance of our proposed scheme in terms of dropping and decoding statistics through simulation. Our analysis, supported by plots, reveals some interesting facts about innovativeness and shows that rDWS technique achieves near-optimal performance for a finite field of sufficient size.
Nanoscale characterization of photonic metasurface made of lens-like SiGe Mie-resonators formed on Si (100) substrate

Submicrometer-sized high-index Mie resonators attract significant interest in photonic applications due to their capabilities to manipulate light. 2-dimensional metamaterials or metasurfaces consisting of arrays of such resonators on a device surface can be used in the flat optics, sensors, and other applications. Here, we report on the comprehensive nanoscale characterization and optical properties of nearly regular SiGe Mie resonator arrays on a Si surface fabricated using a simple and low-cost method. We achieved control on the surface morphology by depositing Ge on the Si(100) surface at elevated temperatures 890–960 °C and obtained arrays of submicrometer/micrometer low-Ge-content SiGe lenslike islands via dewetting when the Ge content was >4%. At the lower Ge content, we observed the formation of a continuous SiGe film via wetting. We used Raman microscopy not only for the Ge content and stress control but also for studying photonic properties of the islands and their coupling with the Si substrate. In contrast to the elastic light scattering, we clearly distinguished visible light Raman signals from the islands themselves and from the substrate areas under the islands enhanced compared to the signal from the open substrate. Calculation of the light electric field distribution in the islands and the substrate demonstrate how the islands trap the light and forward it into the high-index substrate. This explains the island-induced reflection suppression and Si substrate Raman enhancement, which we observe experimentally. Such an SiGe-island array is a promising metasurface for the improvement of Si photosensors and solar-energy device performance.Submicrometer-sized high-index Mie resonators attract significant interest in photonic applications due to their capabilities to manipulate light. 2-dimensional metamaterials or metasurfaces consisting of arrays of such resonators on a device surface can be used in the flat optics, sensors, and other applications. Here, we report on the comprehensive nanoscale characterization and optical properties of nearly regular SiGe Mie resonator arrays on a Si surface fabricated using a simple and low-cost method. We achieved control on the surface morphology by depositing Ge on the Si(100) surface at elevated temperatures 890–960 °C and obtained arrays of submicrometer/micrometer low-Ge-content SiGe lenslike islands via dewetting when the Ge content was >4%. At the lower Ge content, we observed the formation of a continuous SiGe film via wetting. We used Raman microscopy not only for the Ge content and stress control but also for studying photonic properties of the islands and their coupling with the Si substrate.