Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of UWB Microstrip Patch Antenna with Variable Band Notched Characteristic for Wi-MAX Application

Microstrip patch antenna (MPA) having UltraWide Band characteristics is a worthy applicant in wireless communications. Mitigating EMI with the narrowband such as 5G lower band, Wi-MAX, WLAN, Satellite band lies in UWB region is a major research concern. This paper presents an UWB antenna containing variable band rejection for avoiding interference with Wi-MAX application. A simple rectangle patch antenna with defective ground structure is used to design UWB characteristics operating from 2.7 GHz – 13 GHz. Band rejections from 3.25 GHz to 3.8 GHz are obtained by utilizing semi-circular slot on radiating patch. Variable band rejection characteristic can be achieved in between 2.75 GHz – 4.4 GHz through altering the value of width of patch. The return loss and VSWR values over the band rejection frequency are close to 0 dB and greater than 2 respectively. In addition, the proposed UWB antenna obtained 85% radiation efficiency over the operating frequency, on the other hand, less than 53% radiation efficiency achieved over band rejection frequency. The proposed antenna is simple in design, compact in size, and efficient in radiation. Hence it is a good candidate on UWB antenna with band notch characteristic for Wi-MAX application.
Comparative Analysis of Permanent Magnet Synchronous Machines Designed for Electric Power Steering Applications

Plenty electrical machines are used in modern vehicles due to the strong electrification of car auxiliaries required by the intensifying awareness about their safety and comfort features. A typical trend is to replace the classical hydraulic steering systems with those actuated by electrical machines (the so-called electric power steering systems). For such applications, two permanent magnet synchronous machines (with surface and interior permanent magnets) were proposed. In the paper, their design and comparative numerical analysis is detailed.
3D Shape Classification Using a Single View

View-based 3D shape classification is widely used in machine vision, information retrieval and other fields. However, there are two problems in current methods. First, current 3D shape classifiers fail to make good use of pose information of 3D shapes. Secondly, many views are required to obtain good classification accuracy, which leads to low efficiency. In order to solve these problems, we propose a novel 3D shape classification method based on Convolutional Neural Network (CNN). In the training stage, this method first learns a CNN to extract features, and then uses features of views from different viewpoint groups to train six 3D shape classifiers which fully mine the pose information of 3D shapes. Meanwhile, an additional class is adopted to improve the discrimination of 3D shape classifiers. In the recognition stage, the weighted fusion of image clarity evaluation functions is used to select the most representative view for the 3D shape recognition. Experiments on the ModelNet10 and ModelNet40 show that the classification accuracy of the proposed method can reach up to 91.18% and 89.01% when only using a single view and the efficiency is improved substantially.
Applications of AI in cybersecurity

Issues related to digital security are, there is no doubt for this, of utmost importance in the development of methods and support measures for organisations to successfully prepare for as well as realise their digital transformation. While big organisations and businesses may afford to buy services or develop their own in-house know-how and tools, small and medium-sized businesses are not having the means for this, be them financial resources, human resources or technology itself. This dystopic situation may on the other hand offer an unexpected and – as of today – yet unprecedented chance for innovations in terms of bridging the gap and addressing the need with use of AI technologies and services. In the paper we elaborate on a scenario that we have been developing as part of a European project that is part of the European Horizons 2020 project CS-AWARE.
Tri-State Nanoelectromechanical Memory Switches for the Implementation of a High-Impedance State

Tri-state nanoelectromechanical (NEM) memory switches are proposed for the implementation of high-impedance state 0 in addition to low-impedance states 1 and 2 for the improvement of conventional complementary metal-oxide-semiconductor-NEM (CMOS-NEM) reconfigurable logic (RL) operations. Although it is well known that the high impedance state of routing switches is essential to prevent the unnecessary data throughput of RL circuits, previously proposed NEM memory switches have only implemented binary states: states 1 and 2. On the contrary, our proposed NEM memory switches can have tri-states, which are achieved by modifying their operation methods and design guidelines.
The Self-Assembly Composite Photonic Crystal: Toward Easy Humidity Detection by a Smartphone

We report a self-assembly composite photonic crystal with humidity-controlled structure color, towarding to easy humidity detection by a smartphone. As the key issue, the composite photonic sensor is developed via quasi-coating the silica colloidal photonic crystal (SPC) with hydrophilic metal-organic-framework (MOF). Thus the sensor combines the complementary adsorption properties between SPC and MOF, so that realizes a sensitive humidity sensor with wide dynamic detection range. The performance of the sensor was validated via water vapor testing, that its reflection spectrum shifts ~9 nm towards to longer wavelength with the concentration from 500ppm to 20000ppm under room temperature. The humidity-controlled structure color of the sensor paves a way for smartphone detection, so that a simple yet powerful smartphone spectrometer is established to analyze the reflection spectrum of the sensor. Thus, a lab-on-a-phone humidity measurement platform is developed. Thanks to the portability, low-cost and user-friendliness, this platform is promising to be a powerful tool for humidity IoT application, from personal health monitoring to environment monitoring.
On Modelling of Computer Cluster Optimization Problem With Applications

A decision-making problem of reasonability of upgrading a computer network by adding new connections between nodes is investigated. As a basic topology, a well-known hypercube topology is chosen. The expediency of its upgrading by links corresponding to edge sets of hypercube cuts by parallel hyperplanes is investigated. It is done by graph-theoretic approaches and tolls of polyhedral combinatorics. In the course of solving the problem, key structural characteristics of a new graph Q'n, which is a complemented by edges the hypercube graph, are studied. The offered methodology can be applied to other problems of optimization of computer networks, aiming to improve their reliability and efficiency.
Joint Beamforming and PAPR Reduction in Massive MIMO: Analysis of Gain in Energy Efficiency

The main goal of this article is to accurately quantity the gain in energy efficiency that can be obtained by combining PAPR reduction techniques with beamforming in the context of massive MIMO communications. To this purpose, we first derive and analyze the expressions of sum capacity, power consumption, and energy efficiency for hybrid, digital and analog beamforming for massive MIMO systems in the millimeter wave frequency range. Then, we use these results to derive and quantity the gain in energy efficiency at system level that can be obtained by combining PAPR reduction for improved power amplifier efficiency with beamforming in massive MIMO systems. In addition, we derive the expressions allowing to determine the optimal amount of antennas M that should be connected to each RF chain in a partially connected hybrid beamforming scheme in order to maximize the systems energy efficiency. Evaluation of the derived expressions clearly show that a noticeable gain in the systems energy efficiency is obtained when PAPR reduction is added, and allows to analyze the advantages and disadvantages of each approach from an energy efficiency point of view.
Ensemble Monte-Carlo simulation of resistive switching in HfO2/TaN/TiN stack

In this paper, we present the ensemble Monte Carlo simulation of resistive switching for the Pt/HfO2/TaN/TiN structure. In simulation, we found that in oxide thickness 10 nm conductive filament formed at -4.4 V which was close to obtained experimental value -4.2 V. Detailed description of used Monte-Carlo algorithm is also presented.
The Use of Stochastic Parameter Identification in the Separation of Mixtures of Correlated Deep Gaussian Models

An important task in the processing of different types of data is to identify different internal patterns in these data, allowing you to identify hidden objects and areas, as well as to evaluate the parameters of these areas. To solve this problem, we propose to use deep Gaussian processes that make it possible to describe non-stationary multidimensional signals. Combining a sequence of deep Gaussian processes with Markov random fields makes it possible to describe multidimensional signals using the correlation relationships of a sequence element with its vicinity. The paper formulates the necessary mathematical apparatus for describing mixtures of correlated deep Gaussian models. To identify the parameters of such constructions it is proposed to use a modification of the Stochastic Expectation Maximization (SEM) algorithm. The necessary relations for the implementation of this approach are determined and the consistency of the method is shown.
Performing of the FDTD method calculations on "Sergey Korolev" GPUs via MATLAB language

The paper deals with the FDTD-method block algorithm efficiency and with its implementation in MATLAB language on the high performance computer called Sergey Korolev. Block algorithms with one-dimensional and two-dimensional decomposition are considered. As a result of the study, it was found that the one-dimensional decomposition efficiency is 3 times higher than the two-dimensional decomposition efficiency. The average performance of the FDTD-method block algorithm implementation with one-dimensional decomposition is 190 million nodes per second, which corresponds to 15 times speedup on the considered system. The maximum possible domain discretization in GPU computing has been expanded from 50 million to 410 million nodes. Also, it exceeded the maximum discretization in CPU computing by 60 million nodes.
Fast Logistics Vehicle Localizing Based on EMVS-MIMO Radar and Edge Computing

This article focus on logistics vehicle active localizing using multiple-input multiple output (MIMO) radar, and a fast localizing architecture that integrates edge computing and cloud platform is proposed. The core of the proposed methodology is to measure the angles of logistics vehicle using bistatic MIMO radars, which are configured with coprime electromagnetic vector sensors (EMVS). Unlike the existing localization systems, the proposed localizing architecture provides two-dimensional (2D) angle estimation, i.e., 2D direction-of-departure (DOD) estimation and 2D direction-of-arrival (DOA) estimation, and it offers additional polarization status of the logistics vehicle. A parallel factor (PARAFAC) estimator is developed. Firstly, it estimate the factor matrices via PARAFAC decomposition. Thereafter, the elevation angle estimation is accomplished via least squares (LS) technique, which are ambiguous due to the coprime property of the EMVS. The azimuth angle estimation are followed via vector cross-product. Besides, the polarization information of the targets can be obtained estimated via LS approach. The above process is accomplished at cloud platform. Finally, the localization of the logistics vehicle is achieved with the estimated 2D angles, which is computationally friendly and achieved via edge computing. Detailed analyses concerning degree-of-freedom, identifiability, complexity as well as Cramér-Rao bound (CRB) are provided. To show the effectiveness of the proposed architecture, numerical simulations have been designed.
Double-Resonant Plasmonic Molecule: Enhanced Vibrational Induced Scattering Modulation

The present publication investigates the optical scattering behavior of an artificial near-field coupled double-resonant plasmonic molecule on a glass substrate formed by a linear arrangement of three gold nanobars. The aim of the proposed symmetrical structure arrangement is to achieve a significant increase in the feedback of optically induced coherent mechanical oscillations on the scattering cross-section. Based on the description of isolated dipole-like plasmonic nanostructures, it is shown how an increase of the modulation strength can be achieved by systematic utilization and modification of the inherent near-field coupling effect. It is shown which differences exist compared to an isolated plasmonic nanostructure, especially for the NIR spectral range. To the best of our knowledge, this is the first investigation showing the behavior of coherent acoustic vibrations in such artificial plasmonic molecules at an optical carrier wavelength of 1560 nm which is particularly interesting for applications in the field of optical communication.
Practical Prescribed-Time Event-Triggered Bipartite Consensus of Linear Multi-Agent Systems

In this paper, the practical prescribed-time bipartite consensus problem of linear multi-agent systems with a connected structurally balanced signed graph is investigated by using event-triggered mechanism. Novel event-triggered control law and triggering condition are proposed for each agent, in which the sampled states of agent and its neighbors are needed. By using the algebraic graph theory and Lyapunov stability theory, it is verified that the practical bipartite consensus can be achieved at fully prespecified time with an adjustable neighborhood range. Moreover, a theoretical discussion is provided to illustrate that Zeno behavior can be avoided during the whole time span. The feasibility of the presented control strategy is validated by a simulation result.
Asymmetry of «Speed Spot» clouds as a marker of hidden cardiac abnormalities

The use of graphical methods to determine hidden heart disorders is quite successfully used in analytical systems for Holter monitoring. In this case, the traditional method is the analysis of Poincare Plots, as well as visualization of various components of heart rate variability. Recently, attempts to relate the change in heart rate dynamics (acceleration and deceleration) to the presence of hidden pathologies of the cardiovascular system. Along with traditional methods, much attention is paid to the search and study of parameters that describe the nonlinear dynamics of the processes of heart rhythm formation. Among these characteristics, the degree of asymmetry of the geometrically interpreted parameters of cardiac activity. The asymmetry dynamics can be determined by the parameters of the Poincare Plot. Previously, the authors proposed a method for determining the state of cardiac activity, based on the use of the so-called “Speed Spot” - a geometric interpretation of the function of changing the heart rhythm and its derivative. This work is a continuation of the study of the informative parameters of “Speed Spot” and is devoted to the analysis of their asymmetry, as well as a comparative assessment of this approach with existing methods for the analysis of the asymmetry of Poincare's spots.
Dual-Polarized Microstrip Patch Antenna Array with Dual-Feed for Target Detection

A planar antenna is designed to replace complex structures of many rat-race couplers and 90° hybrids used in conventional target detection antennas. The proposed antenna has 2 × 2 microstrip patch antenna arrays with dual feeding to radiate symmetric polarizations in the 9.375 GHz (X-band). The sum pattern with circular polarization is implemented through a sequence feeding at port 1. The simultaneous feeding of port 2 radiates a difference pattern in all polarizations. Thus, a target detection antenna is designed with features that have fewer ports than the conventional monopulse antennas. The proposed antenna is compact, planar, and has a simple comparator circuit and equal sum and difference levels. Also, in the last section, the antenna feeding network which can be receive the dual-CP (RHCP and LHCP) is proposed.
Orlando Tools: Supporting High-performance Computing in Distributed Environments

Nowadays, scientific applications based on a workflow are actively used. Such applications are one of the forms of distributed applied software packages. The modern tools for designing packages do not fully support continuous integration for both the system and applied software for a heterogeneous distributed computing environment. The software quality, its design time, and experiment conduct time can be improved through expanding the scope of continuous integration for packages. To this end, we provide a new approach to ensuring the continuous integration for both the applied and system software within package designing. In practice, the approach applying enables us to significantly decrease in the number of errors and failures when packages are designed and used. Thus, we substantially reduce the time of conducting computing experiments in a heterogeneous distributed computing environment and increase the efficiency for the use of its resources.
Analysis on the Cogging Torque of Permanent Magnet Machine for Wind Power Applications

This paper deals with the analysis of cogging torque of permanent magnet machine for wind energy application. For the purpose of study, a 24-slot and 18-pole pairing of permanent magnet machine is selected. In order to reduce the cogging torque of permanent magnet machine based on the wind power requirement, a combining of shaping in magnet edge with three dummy slots in stator core of machine is studied in the paper. The combining of shaping in magnet edge with three dummy slots in stator core give a high value of cogging torque reduction of the model of PMM proposed. For the analysis of the entire machine structure, the finite element analysis is employed in the study. Using the finite element analysis based on FEMM, the cogging torque value of PMM models is analyzed. It is found that the cogging torque reduction value of the model of the PMM proposed can be increased to 98.74 % compared to the conventional PMM model. In conclusion, it can be said that the PMM can be developed and proposed in wind power application.
Three-photon Absorption Process In Organic Dyes Enhanced By Surface Plasmon Resonance

Multi-photon absorption processes have received significant attention from the scientific community during the last decade, mainly because of their potential applications in optical limiting, data storage and biomedical fields. Perhaps, one of the most investigated processes studied so far has been two-photon absorption (2PA). These investigations have resulted in successful applications in all the fields mentioned above. However, 2PA present some limitations in the biomedical field when pumping at typical 2PA wavelengths. In order to overcome these limitations, three-photon absorption (3PA) process has been proposed. However, 3PA in organic molecules has a disadvantage, typical values of σ3’ are small (10 cms/photon), therefore, 3PA excitation requires high irradiances to induce the promotion of electrons from the ground state to the final excited state. To overcome this obstacle, specific molecules that exhibit large 3PA cross-section must be designed. Thus far, there is a lack of systematic studies that correlate 3PA processes with the molecular structure of organic compounds. In order to fill the existent gap in 3PA molecular engineering, in this dissertation we have investigated the structure/property relationship for a new family of fluorene derivatives with very high threephoton absorption cross-sections. We demonstrated that the symmetric intramolecular charge transfer as well as the π-electron conjugation length enhances the 3PA cross-section of fluorene derivatives. In addition, we showed that the withdrawing electron character of the attractor groups in a pull-pull geometry proved greater 3PA cross-section. After looking for alternative ways to enhance the effective σ3’ of organic molecules, we investigated the enhancement of twoand three-photon absorption processes by means of Surface Plasmon. We demonstrated an enhancement of the effective twoand three-photon absorption cross-section of an organic compound of 480 and 30 folds, respectively. We proved that the enhancement is a direct consequence of the electric field enhancement at a metal/buffer interface. Next, motivated by the demands for new materials with enhanced nonlinear optical properties, we studied the 3PA of Hematoporphyrin IX and J-aggregate supramolecular systems. As a result, we were able to propose the use of 3PA in photodynamic therapy using Photofrin, the only drug approved by the FDA for PDT.
Physical Chemistry for the Chemical Sciences

Introduction and Gas Laws Kinetic Theory of Gases The First Law of Thermodynamics The Second Law of Thermodynamics Gibbs and Helmholtz Energies Nonelectrolyte Solutions Electrolyte Solutions Chemical Equilibrium Electrochemistry Quantum Mechanics Application of Quantum Mechanics to Spectroscopy Electronic Structure of Atoms Molecular Electronic Structure and the Chemical Bond Electronic Spectroscopy and Magnetic Resonance Spectroscopy Photochemistry Chemical Kinetics Intermolecular Forces The Solid State The Liquid State Statistical Thermodynamics Appendices Glossary Answers to Even-Numbered Computational Problems Index
ON THE USE OF THREE DIMENSIONAL MATERIAL LAWS IN THE ANALYSES OF FUNCTIONALLY GRADED SHELLS

This work deals with the extension of the so-called 7-parameter shell model previously developed by Büchter et al. [Int. J. Numer. Meth. Engng. (1994) 37:2551-2568] to its usage in Functionally Graded Materials. Particularly, the material properties vary continuously through the thickness of the shell body according to a power law distribution that relates the volume fraction of the constituents. This structural model is implemented into the commercial FE code ABAQUS and tested by means of standard benchmark examples including geometrically nonlinear cases.
Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge

We propose a novel Bayesian approach that robustifies genomic modelling by leveraging expert knowledge through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and non-additive genetic variation, which leads to an intuitive model parameterization that can be visualised as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which expert knowledge is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates expert knowledge through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of expert knowledge in the context of plant breeding. A simulation study shows that the proposed priors implementing expert knowledge improve the robustness of genomic modelling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study expert knowledge increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of expert knowledge priors for genomic modelling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modelling.