Miracle-dz/UniFAR-FTUs huggingface dataset:
Silicon germanium materials for terahertz emission

Terahertz radiation has many uses in a broad range of fields including medicine and healthcare security, earth science, production monitoring and astronomy. The use of terahertz in many of these applications has been precluded by the lack of an inexpensive source that can operate without cryogenic cooling. If a Si-based terahertz quantum cascade laser could be developed, it is a likely candidate to fill this role. It is possible that the largest challenge facing the development of a Si-based quantum cascade laser is that of the demand requiring epitaxial growth. The main achievement of this study is the growth of challenging n-type Ge/Si1-xGex superlattice structures which are intended for terahertz emission. Comprehensive materials characterisation is presented for the structures. The final structures have been sent to collaborators for further characterisation and to be processed into devices. The results of which will be used to optimise future growth of Si-based QCL structures. The effects of the low temperature used in the growth of the QCL structures on the critical thickness is investigated and Si0.4Ge0. 6/Si layers grown far beyond the critical thickness predicted by theory are presented. These layers have applications in electronic devices such as field effect transistors (FETs). The fabrication and characterisation of flat, single crystal Ge membranes is presented. The strain, membrane thickness, crystalline tilt and crystalline quality are determined by micro-diffraction, performed on the membranes at Beamline B16 at the Diamond Light Source. These membranes are shown to be of high crystal quality which gives them many applications, including as a possible platform for Si-based quantum cascade laser structures.
Optical correlation recognition based on LCOS

Vander-Lugt correlator[1] plays an important role in optical pattern recognition due to the characteristics of accurate positioning and high signal-to-noise ratio. The ideal Vander-Lugt correlator should have the ability of outputting strong and sharp correlation peak in allusion to the true target, in the existing Spatial Light Modulators[2], Liquid Crystal On Silicon(LCOS) has been the most competitive candidate for the matched filter owing to the continuous phase modulation peculiarity. Allowing for the distortions of the target to be identified including rotations, scaling changes, perspective changes, which can severely impact the correlation recognition results, herein, we present a modified Vander-Lugt correlator based on the LCOS by means of applying an iterative algorithm to the design of the filter so that the correlator can invariant to the distortions while maintaining good performance. The results of numerical simulation demonstrate that the filter could get the similar recognition results for all the training images. And the experiment shows that the modified correlator achieves the 180° rotating tolerance significantly improving the recognition efficiency of the correlator.
Air target detection using airborne passive bistatic radar

Passive bistatic radar (PBR) research has traditionally focused on using a static ground based receiver for air target detection. Reported are the initial findings from a novel airborne PBR experiment using commercial FM transmissions between 88 and 108 MHz, as illuminators of opportunity. A two-channel PBR system was designed, constructed and installed on a light aircraft and the system flown with the intention of detecting low altitude commercial air targets in the vicinity of London s Heathrow and Gatwick airports. Analysis of the data has shown that the system has successfully detected high velocity air targets on established air routes around the southeast of England. These encouraging results provide the proof of concept necessary to stimulate further development of the radar demonstrator to give improved target localisation and sensitivity.
Smooth and Safe Nearness-Diagram (SSND) Navigation for Autonomous Mobile Robots

This paper addresses further enhancements of the earlier developed Smooth Nearness-Diagram Navigation (SND) method for mobile robots moving in complex and cluttered environments. The enhanced method, entitled SSND, improves the safety of paths generated by the SND and solves the problem of trapping the robot in narrow corridors, where the difference in the number of threats on its sides is high. This is achieved by adjusting the difference in the number of obstacles on the two sides of the robot heading direction. The power of our method is demonstrated by simulation results.
Optimization techniques for smart integrated sensor networks in environmental monitoring

Sensor networks are an emerging field of research which presents significant system challenges involving the use of large numbers of resource-constrained nodes operating essentially unattended and exposed to potential local communication failures. Current sensor networks address problems of meeting standards for accuracy and also delivering data from remote locations with an appropriate level of spatial and temporal resolution. Today advances in sensor technology, wireless communications and digital electronics make it possible to produce large amount of small-size, low-cost sensors which integrate together sensing, processing, and communication capabilities. The advantages are evident not only in the reduction of size, but also in the increase of functional performance and reliability, and a unit-cost reduction in mass production lines. In this work hybrid evolutionary algorithms are applied to optimize the design of cluster formation in wireless sensor networks, guaranteeing at the same time a full network connectivity and a minimum energy consumption. The proposed techniques have been tested in respect of the most known test functions with good results obtained in all the considered cases, especially for optimization of large domain objective functions. This feature makes these algorithms suitable for a wide range of applications, capable of outperforming classical procedures.
System Components and Design for OFDM-Based Broadcasting Receivers

Approaching the channel capacity limit has been the main goal of communication engineers since the pioneering work of Claude Shannon. This capacity depends primarily on the chosen schemes for channel coding and modulation, which need to be tailored to the specifics of the propagation environment. From an engineering perspective, it is important not only to maximize the channel capacity, but also to achieve this with the least complexity. In addition to noise, a major impairment in terrestrial transmissions is the multipath nature of the channel, which affects the receiver performance dramatically. Over the past decade, orthogonalfrequency-division multiplexing (OFDM) has emerged as the modulation of choice for such environments because of its inherent resilience to multipath effects and relative simplicity of the channel equalization, which allows for low-cost receivers. Nowadays, OFDM is a mature technology, being employed by various standards for both wireless networking and digital broadcasting. The present doctoral thesis deals specifically with baseband receiver architectures for OFDM digital broadcasting, focusing on digital OFDM demodulation and to a lesser extent on forward error correction. The research scope includes the architectural exploration and optimization of several blocks at algorithmic and structural level: channel equalizer, QAM demapper, and Viterbi decoder. Because of their critical role, the channel equalizer and the Viterbi decoder are each treated in a dedicated chapter. The proposed architectures are optimized for area and take advantage of the new features found in modern FPGA's, such as embedded memories, multipliers, and shift registers. Another important contribution of this thesis is the development of an efficient simulator for multipath channels with Doppler fading. Using an accurate channel simulator is essential for comparing simulation results between different teams. Especially critical is the modeling of the fading taps, since the fading process is much slower than the sampling rate. The proposed architecture is extremely scalable and suitable for both hardware and software implementation, the fading taps being generated by filtering white Gaussian noise. In this context, especially innovative are the solutions proposed for Gaussian noise generation and single-stage polyphase interpolation. A final chapter of the thesis is dedicated to the functional modeling of OFDM receivers in SystemC and to the hardware design optimized for FPGA. The FFT block, which is the core of an OFDM demodulator, has been selected as a case study.
Trending Algorithms in Machine Learning and issues along with Big data Context in real time Data Processing

Machine Learning (ML) is booming up and mandatory for many domains like banking, retail social media and online shopping platforms like amazon and flip kart. The article describes the importance of various algorithms along with the fundamental concept with simple code and the corresponding issues. The other dimension of this work is summary of various applications based on the algorithms and some of the observations which may help the researchers in the area of ML to come up with suitable methodologies and corrective measures. The work involves the description of regression, classification and recommender systems with suitable snippets of the coding in R programming. The discussion also provides various issues identified in the regression, classification and recommender systems which may be leading to the future scope for the researchers in the area of ML. We believe that the work helps to know the basic algorithms in the said context with the application areas and issues based on the application domains like social media (Facebook, Twitter), banking sector classification of the customers based on the Cibil score and recommender systems along with product recommendation to the customers while working with amazon and flip kart kind of the online shopping sites. The outcome of the work is a clear specification of algorithms with the help of R programming and working with issues which leads to the new research trends in ML. Integration of Hadoop and R is the best combination in the field of distributed computing and analytics point of view. The algorithms regression and classification along with the specific packages allows making use of the algorithms in the simple manner.
Performance of Environmental T-shape Noise Barriers Covered with Primitive Root Diffusers

There is a considerable increase in the use of noise barriers in recent years. Noise barriers as a control noise solution can increase the insertion loss to protect receivers. This paper presents the results of an investigation about the acoustic efficiency of primitive root sequence diffuser (PRD) on an environmental single T-shape barrier design. A 2D boundary element method (BEM) is used to predict the insertion loss of the tested barriers. The results of rigid and with a different sequence diffuser coverage are also predicted for comparison. Employing PRD on the top surface of T-shape barrier has been found to improve the performance of barriers in comparison with the use of rigid and QRD coverage at the examined receiver locations. It has been found that decreasing the design frequency of PRD shifts the frequency effects towards lower frequencies, and therefore the overall A-weighted insertion loss is improved. It was also found that using wire mesh with reasonably efficient resistivity on the top surface of PRD improves the efficiency of the reactive barriers; however utilizing wire meshes with flow resistivity higher than the specific acoustic impedance of air on the PRD top of a diffuser barrier significantly reduces the performance of the barrier within the frequency bandwidth of the diffuser. The performance of a PRD covered T-shape barrier at 200 Hz was found to be higher than that of its equivalent QRD barriers in both the far field and in areas close to the ground. The amount of improvement compared made by PRD barrier compared with its equivalent rigid barrier at far field is about 2 to 3 dB, while this improvement relative to the barrier model "QR4" can reach up to 4-6 dB.
Characterization of pressure wave propagation in biological tissues

A measurement technique using flexible PVDF gages for characterizing the propagation of pressure waves in biological tissues is developed. We demonstrated that experimental measurements, coupled with numerical simulations, represent a promising method to obtain reliable pressure histories in biomaterials and to calibrate constitutive models for these materials. Data that can be used for such calibration include the dependence of apparent wave velocity on pressure pulse amplitude and pressure pulse attenuation (and possibly shape changes) with propagation distance. We are currently developing an appropriate nonlinear (power) viscoelastic constitutive model that we will calibrate and test using the methodology described in this paper.
Coupled-inductor boost integrated flyback converter with high-voltage gain and ripple-free input current

DC–DC converters with high-voltage gain and low-input current ripple have attracted much attention in photovoltaic, fuel cells and other renewable energy system applications. Conventional boost–flyback converter can achieve high-voltage set-up ratio; however, its input current is pulsing and the voltage stress across output diode of flyback-cell is high. In this study, by incorporating coupled-inductor into the boost-cell of boost–flyback converter, the voltage stress across the output diode is effectively reduced. Passive snubber circuit is utilised to suppress the voltage spike across power switch, low-voltage-rated metal–oxide semiconductor field effect transistor (MOSFET) with low R ds_on can thus be used to reduce the conduction loss of power MOSFET. In addition, ripple-free input current can be achieved, which makes the design of electromagnetic interference filter easy. Steady-state characteristics of the proposed converter are analysed, and experimental results are given to verify the analysis results.
Aircraft power systems: technology, state of the art, and future trends

The fundamental issues faced in the aircraft electrical power systems are addressed. A brief description of the conventional and advanced aircraft power system architectures, their disadvantages, opportunities for improvement, future electric loads, role of power electronics, and present trends in aircraft power system research is given, followed by a brief outline of projected future advancements.
Experimental Characterisation of Neural Tissue at Collision Speeds

Mechanical characterization of brain tissue at high loading velocities is particularly important for modelling Traumatic Brain Injury (TBI). During severe impact conditions, brain tissue experiences a mixture of compression, tension and shear. Diffuse axonal injury (DAI) occurs in animals and humans when both the strains and strain rates exceed 10% and 10/s, respectively. Knowing the mechanical properties of brain tissue at these strains and strain rates is of particular importance, as they can be used in finite element simulations to predict the occurrence of brain injuries under different impact conditions. This research describes the design and operation of a High Rate Tension Device (HRTD) that has been used for tensile tests on freshly harvested specimens of porcine neural tissue at speeds corresponding to a maximum strain rate of 90/s. The authors investigate the effects of inhomogeneous deformation of the tissue during tension by quasi‐static tests (strain rate 0.01/s) and dynamic tests (strain rate 90/s) using different thickness specimens (4.0, 7.0, 10.0 and 13.0 mm) of the same diameter (15.0 mm). Based on a combined experimental and computational analysis, brain specimens of aspect ratio (diameter/thickness) S = 10/10 or lower (10/12, 10/13) are considered suitable for minimizing the effects of inhomogeneous deformation during tension tests. The Ogden material parameters were derived from the experimental data both at quasi‐static conditions (u = 440 Pa and a = ‐4.8 at 0.01/s strain rate) and dynamic conditions (u = 4238 Pa and a = 2.8 at 90/s strain rate) by performing an inverse finite element analysis to model all experimental data. These material parameters will prove useful for the nonlinear hyperelastic analysis of brain tissue.
Cavitation Detection Using a Fibre‐Optic Hydrophone: A Pilot Study

A fibre‐optic hydrophone has been used to detect broadband acoustic emissions associated with inertial cavitation activity. Its potential for this application has been investigated in tap water and in agar gels, and compared with signals from a passive cavitation detector (PCD) and a microphone detecting audible frequency emissions. Processing of the fibre‐optic hydrophone data to find the total RMS voltage over an integrated frequency range of 15–20 MHz gives a high signal to noise ratio, comparable with that of the PCD. The sensitivity and effective field of view of the fibre tip appear sufficient for detecting even low level cavitation activity, however the precise directional response has yet to be assessed. Emissions from acoustic cavitation in tap water and agar gel from peak negative pressures reaching 5.8 and 3.5 MPa respectively were detectable when the fibre was up to 20 mm and 2 mm respectively from the acoustic axis, whilst retaining a high signal to noise ratio.
Resolution requirements and the Johnson criteria revisited

Since the 1950s, numerous studies have been performed within the surveillance and reconnaissance (S&R) and target acquisition (TA) communities in an attempt to predict information extraction performance as a function of image collection and quality parameters. In general, the work followed two separate paths. The TA community developed models to predict probabilities of detection, recognition, and identification as a function of target size, range, and collection system design/performance parameters (e.g., MRT, FLIR92,NVTHERM,MRC). The S&R community developed models to predict National Imagery Interpretability Ratings (NIIRS) as a function of system design and collection parameters (e.g. IR GIQE). More recently, efforts have linked the two approaches such that NIIRS can be predicted from TA models and probabilities of identification can be predicted from NIIRS. With both approaches, resolution is a dominant term. A considerable amount of variability and uncertainty results from target differences. The criteria used to define the NIIRS generalize target type, size, and level of identification specificity. The TA predictions use the Johnson recognition criteria to relate lines on the target to recognition performance. A recent paper found that TA predictions differed substantially between the visible and IR. Further, the paper reported substantial differences among vehicles in terms of a confusion matrix. This finding was not surprising in light of other research, but suggested the need for a more detailed examination and explanation of results. Accordingly, the current effort was undertaken. Data from a variety of past studies dealing with target recognition were examined relative to the Johnson criteria, along with a more detailed analysis of data from two recent TA studies. A hypothesis of target recognition performance was generated and partially validated using available data.
Investigation of fluid flow and heat transfer characteristics for a thermal anti-icing system of a high-altitude and long-endurance UAV

This research performs a three-dimensional simulation to investigate the fluid flow and heat transfer characteristics for hot-air jets impinging on the wing leading-edge surface. Both the periodic model and the whole model are proposed to examine the thermal anti-icing performance for hot air ejecting from a piccolo tube onto the impinging surface. The results show that, for the periodic model, the enhancement of the average Nusselt number can be up to 94.4%, and the enhancement of the average heat flux is up to 29.7% for 100 ≦ uj ≦ 350 m/s and 300 ≦ Tj ≦ 550 K when compared with the results of the basic case of uj = 200 m/s and Tj = 450 K. The maximum enhancement of the $\overline {Nu} $ is 62.3% as the spacing decreases from Sn = 8 to Sn = 4 and the optimum Numax and $\overline {Nu} $ occur at Si = 5 and Si = 6 for the single-array holes with 3 ≦ Si ≦ 7 and 4 ≦ Sn ≦ 8. In addition, the θh for maximum $\overline {{{Nu}}} $ is 10° and the maximum enhancement of the $\overline {{{Nu}}} $ is ∼15.7% for double-array holes and staggered-array holes as compared with single-array holes. In addition, the nonuniformity of Nusselt number and heat flux distributions are significantly improved. For the whole model, the maximum enhancement of the average Nusselt number is ∼7.5% and the optimum configuration is θh = 40°, for cases with La = 60, Dp = 8, $\dot{m}$ = 0.15 kg/s, Si = 6, 1 ≦ Nh ≦ 5, 10 ≦ Sn ≦ 30 and 10° ≦ θh ≦ 60°.
Path Planning for Mobile Robots in 3D Dynamic Environments

Aiming at the robustness of the path planning of mobile robots in the 3D dynamic environment, an improved ARF (Artificial Potential Field) based path planning algorithm is proposed in this paper. Supposing that all the obstacles move regularly and the robot is on uniform motion in a grid 3D environment. Firstly, the algorithm computes the future statuses of the environment, such as the coordinate of all the obstacles and the goal, until a time step T in which there is at least one route between the start and goal. T is obtained by BFS (Breadth First Search) and environment configuration parameters. Secondly, because in every time step the environment can be consider as being static, ARF is used to determine the potential value of every space position in each time step. Finally, a route along the lowest potential values is found for the robot from the start to goal. Simulation results show that the algorithm makes the robot avoid obstacles effectively and reach the goal safely.
FC2: focus control technique for critical level i-line photolithography

In order to satisfy the focus control requirements for critical level i-line photolithography, the benefits of the focus calibration 2 (FC2) system was studied. This feature is standard on Nikon Step and Repeat (NSR) model 10 and above i-line steppers. As features shrink towards 0.35 /spl mu/m, so to will the focus control requirements on the steppers used to print them. For these types of geometries, typical usable DOF values of <1 /spl mu/m are seen. As a result, we have targeted focus control of +/- 0.05 /spl mu/m in order to satisfy these needs in a production environment. The FC2 system uses an in-situ sensor placed on the wafer stage which is capable of measuring the real focus of the projection lens. This focus position is cross-referenced to the auto focus system which maintains wafer best focus. By accurately measuring this position and updating the wafer auto focus system, the wafer is exposed closer to the best focus of the projection lens. In this manner the wafer auto focus system is calibrated to the best focus of the projection lens.
The Design of Spraying Manipulator Control System in Mines

In view of the present mining spraying manipulator operation is not flexible ,spraying effect is poor, susceptible to interference and other issues, this paper studies and realizes a kind of low cost, strong practicability of spraying manipulator control system. Using S7-200PLC and 2MA860H drive to control the 86BYG250A stepper motor open-loop control system, and the precise position control is realized. By controlling of the x-y axis mine spraying manipulator. Validate the system operation is simple, highly efficient and stable, energy conservation and environmental protection, strong anti-jamming capability, it can be widely used in all kinds of mining equipment.