Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized Ambiguity Function Properties of Ground-Based Wideband MIMO Imaging Radar

The ability of multiple-input multiple-output (MIMO) radar to provide enhanced performance has been verified in both theoretical and practical level. Through applying orthogonal waveforms, this type of system can realize far more observation channels than the actual number of transmit and receive (T/R) elements. Generally, the azimuth one-dimensional (1-D) generalized ambiguity function (GAF) and resolution of a MIMO radar system are analyzed by pattern theory, which can only analyze the GAF along the equidistant curve to the radar's center. However, the two-dimensional (2-D) GAF of wideband MIMO radar system shows that its sidelobes are not along the equidistant curve accurately due to the coupling effect between the range-dimension and the azimuth one. Obviously, the traditional pattern theory becomes invalid in this case. To tackle this problem, the 2-D GAF and the spatial spectrum of far-field targets are derived in this paper. By analyzing the 2-D GAF, existence of three individual directions of sidelobes is revealed and it is proved that every sidelobes is along a straight line in the pseudopolar coordinate system. Furthermore, a method to calculate the 1-D GAF and resolution in the arbitrary direction is proposed. Finally, a simulation and two experiments have been carried out to validate the theoretic results.
Octagonal Shaped Metamaterial Absorber Based Energy Harvester

In this study, a novel octagonal shaped metamaterial based broadband absorber is proposed for energy harvesting at WIMAX wireless communication band. The proposal has an absorption of 99.97 % at 5.5 GHz with a bandwidth of 1 GHz between 5 GHz and 6 GHz in Transverse Electric (TE) mode. Transverse Electric (TE), Transverse Magnetic (TM) and Transverse Electromagnetic (TEM) modes are studied numerically in this paper. In TM and TEM modes, proposed structure has absorption of nearly 96 % and 98 % respectively at 6 GHz. The proposed structure is polarization angle independent which is important for energy harvesting applications. Energy harvesting application is realized by using resistive loads on the design, simulations are parametrically studied on resistive loads and experimental study is realized for reflection coefficient measurement and compared with simulated results. Both experimental and simulated results are complying with each other. The proposed structure has different usage areas in stealth areas, detection and imaging. DOI: http://dx.doi. org/10.5755/j01.ms.24.3. 18625
Inhomogeneous waves in solids and fluids

The book may be viewed as an introduction to time-hadronic waves in dissipative bodies, notably viscoelastic solids and fluids. The inhomogeneity of the waves, which is due to the fact that planes of constant phase are not parallel to planes of constant amplitude, is shown to be strictly related to the dissipativity of the medium. A preliminary analysis is performed of the propagation of inhomogeneous waves in unbounded media and of reflection and refraction at plane interfaces. Then emphasis is given to those features that are of significance for applications. In essence, they regard surface waves, scattering by (curved) obstacles, wave propagation in layered heterogeneous media, ray methods. The pertinent mathematical techniques are discussed so as to make the book reasonably self-contained.
Nonlinear Refractive Index in Rectangular Graphene Quantum Dots

Alongside its other favorable properties, the large refraction nonlinearity of graphene-related material makes it ideal for use in optoelectronics applications. Numerous experimental studies about nonlinear optical refraction have been conducted, but theoretical verification is lacking. In this paper the nonlinear refractive index for rectangular graphene quantum dots (RGQDs) was calculated using the relationship between nonlinear refractive index and the third-order nonlinear optical susceptibility. The third-order nonlinear optical susceptibility for third harmonic generation was derived employing the electronic states obtained from the Dirac equation around K point in RGQDs under hard wall boundary conditions. Results revealed that the calculated nonlinear refractive index, n 2 , was in the magnitude of 10−14 m2/W in the visible region, which is nearly five orders larger than conventional semiconductor quantum dots, while in the infrared region the nonlinear refractive index reached up to the magnitude of 10−11 m2/W for M = 3M0 sized RGQDs where the resonance enhancement occurred. The nonlinear refractive index could be tuned both by the edges and sizes.
Dewetting of thin wetting film supported by different solid substrates: a review

ABSTRACT Instabilities of thin wetting films show different dewetting dynamics when supported by different solid substrates. Unstable thin films on the homogeneous substrate are studied numerically and experimentally. This study extended to slipping films and density varying films analysing the variation in time of rupture and power-law exponents. However, none of the films are reported to produce smaller length scale patterns. One possible way to produce a smaller length scale pattern is by the heterogeneous substrate. A recent study confirms that thickness-dependent viscosity films on a homogeneous substrate produce smaller length scales due to the formation of a secondary set of satellite holes. Nevertheless, these films exhibit low power-law exponents compared to constant viscosity films and slipping films. Thin liquid films supported by a solid coated substrate, where film subjected to purely Lifshitz Van der Waals force describes the morphological phase separation and it reveals that the mechanism is different from classical nucleation.
A Refinement-based Formal Development of Cyber-physical Railway Signalling Systems

For years, formal methods have been successfully applied in the railway domain to formally demonstrate safety of railway systems. Despite that, little has been done in the field of formal methods to address the cyber-physical nature of modern railway signalling systems. In this article, we present an approach for a formal development of cyber-physical railway signalling systems that is based on a refinement-based modelling and proof-based verification. Our approach utilises the Event-B formal specification language together with a hybrid system and communication modelling patterns to developing a generic hybrid railway signalling system model that can be further refined to capture a specific railway signalling system. The main technical contribution of this article is the refinement of the hybrid train Event-B model with other railway signalling sub-systems. The complete model of the cyber-physical railway signalling system was formally proved to ensure a safe rolling stock separation and prevent their derailment. Furthermore, the article demonstrates the advantage of the refinement-based development approach of cyber-physical systems, which enables a problem decomposition and in turn reduction in the verification and modelling effort.
Room compensation using eigenspace adaptive and wave-domain adaptive filtering

It is always assumed that the listening room is a free-field conditions in previous acoustic experiments. However, a completely free-field conditions can impossibly be achieved due to reverberation of sound waves by the walls, which can adversely affect listening experience. So, room compensation is used to solve this problem. It can effectively reduce the influence of reverberation. Conventional adaptive filters fail to overcome the complexity of multi-channels. So, the first approach is introduced—eigenspace adaptive filtering which is based on decoupling of multiple-input-multiple-output system with generalized singular decomposition. But the varying feature of listening room alters related matrixes constantly, increasing the computational complexity of compensation processing. Then, another approach called wave domain adaptive filtering, mentioned here in the context of RLS algorithm, can be a feasible alternative to avoid computational difficulty. This paper also evaluates the performance of using circular harmonics as wave field representation.
A survey to applications of deep learning in autonomous driving

In this work, this paper discussed the maneuver of autonomous vehicles, the application of deep learning technology in autonomous driving and improvements in the recognition and training of autonomous driving. First, we discussed how the pure pursuit algorithm calculates the route to the destination. Then, for the maneuver of autonomous vehicles, we listed the use of fuzzy logic and actuator. For driving safety, we introduced eight factors that it depends on. To apply deep learning technology in autonomous driving, we introduced how deep learning is applied to autonomous driving by explaining the four main parts of the pipeline of autonomous driving: perception, localization, prediction and decision making. We also noted the KITTI dataset, popularly used in the deep learning academia. Finally, for improvements in the recognition and training of autonomous driving, we presented three ways: using neural networks, using more effective datasets, and virtual environments that simulate the real world.
An objective evaluation of the laryngeal roof

Aim: The anatomic measurements of the thyroid cartilage, which is an important part of the laryngeal roof, were calculated using computed tomography (CT) and the data obtained were compared in two groups of male and female. Material and Methods: A total of 148 adult patients were examined in this retrospective, cross-sectional study. All the patients were aged over18 year and presented to emergency ward between 2015 and 2016 due to trauma. Cervical vertebra CT was taken and the reformatted two-dimensional images were examined. Measurements were taken on the images at two separate levels of the interlaminar angle (ILA), thyroid prominence angle and the distance of the vocal cords from the lower edge of the thyroid. Results: The ILA in the glottis region was measured as 74.02°±17.23° for males and as 98.00°±12.78° for females. The difference between the genders was statistically significant (p<0.001). The distance of the vocal cords from the lower edge of the thyroid cartilage was measured as 7.12 ±2.29mm for males and 5.15±2.06mm for females. Conclusion: The results of the ILA measurements in this study were observed to be narrower in both genders than the measurements given in classic reference books. The ILA in both the regionsof glottis and supraglottiswas measured as a narrower angle in males than in females. These results show the presence of sexual dimorphism in the Kahramanmaraş region where the study was conducted.
Extensions to COST 2100 Channel Model for Extremely Large-Scale MIMO

Extremely large-scale multiple-input multiple-output (XL-MIMO) system providing more degrees of freedom and beamforming gain, can effectively increase the capacity and coverage of wireless networks, which has become one of the key technologies for 6G. However, the near-field and non-stationary effects will appear as the array aperture expands. Therefore, existing channel models such as COST 2100 are extended to model these propagation effects. Considering the actual deployment of extremely large-scale antennas, this paper further extends the COST 2100 channel, including a) extending BS VR to 3D modeling to support the non-stationary characteristics of large-scale arrays in vertical and horizontal dimensions; b) extending the distribution of MS VR in vertical height to support user equipments (UEs) which are distributed on floors at different heights; c) extending models to support spatially consistent propagation characteristics between multi-TRPs. Finally, we show that our modeling method is reasonable through parameter tuning and simulation, and it can be used to evaluate the system performance of large-scale MIMO with different deployment morphologies.
$H_{\infty}$ control for uncertain T-S fuzzy systems

This paper investigates the $H_{\infty}$ control problem for nonlinear systems with uncertainties and disturbances. Firstly, T-S fuzzy models are utilized to approximate the nonlinear systems. Then, an fuzzy control scheme with an adaptive mechanism is developed to compensate the effect of the uncertainties on the systems. In addition, to reduce the influence of the disturbance and further improve the performance of $H_{\infty}$ control, an adaptive membership function-dependent $H_{\infty}$ performance index is considered and the corresponding analysis conditions are obtained. Finally, a numerical example for 2-order systems is presented to show the advantage of the presented approach with the above-mentioned performance index.
Phase-Noise-Aware LLR Calculation for mmWave MIMO Systems with High-Order Modulation

This paper proposes a high reliable demodulation method via phase-noise-aware log-likelihood ratios (LLRs) in millimeter-wave (mmWave) multi-user multi-input multi-output (MU-MIMO) systems with higher-order quadrature amplitude modulation (QAM). When using high-order QAM schemes in mmWave wide-band wireless communication systems, the phase noise severely degrades the demodulation performance at the operating point in the high signal-to-noise ratio (SNR) region. Typical two-stage processing, which consists of MIMO signal separation (i.e., multi-user detection (MUD)) and phase noise compensation via LLR calculation, cannot properly solve this inherent problem, because the spatial fading correlation in mmWave channels causes phase noise enhancement during MUD. To circumvent this issue, we formulate an approximate probability density function (PDF) of the received signals including phase noise, which enables us to jointly perform MUD and phase noise compensation; this makes it possible to compute reliable LLRs to be input to the channel decoder, without phase noise enhancement. Numerical results demonstrate the efficacy of the proposed method in terms of the bit error rate (BER) performance in coded mmWave MIMO systems.
OSNR Monitoring Using Mean and Variance Values of Signal Amplitude Combination with DNNs

Optical Signal-to-Noise Ratio (OSNR) is one of the most important parameters in the physical layer of optical fiber communication system. It can directly reflect the operation and signal transmission state of the system. In order to ensure the reliability and stability of optical fiber communication system, an OSNR monitoring method using the mean and variance value in different regions of the received signal amplitude combination with deep neural networks is demonstrated. The OSNR-depended features are obtained by calculating the mean and variance value in different regions of the amplitude histogram firstly. Then, the OSNR depended specific features are extracted and corresponding OSNR value is estimated utilizing the DNN. The back-to-back simulation results show that the OSNR of 28-GBaud polarization multiplexing (PDM) QPSK, PDM-16QAM and PDM-32QAM signals can be accurately monitored within the OSNR range of 8~21dB, 12~25dB and 18~36dB, respectively. At the same time, the long-distance transmission results show that this method is robust to fiber nonlinearity.
Performance of V2N Communication System with Mixed RF and Hybrid FSO/RF Transmissions

Vehicular communications offer the ability to vehicles to communicate with other vehicles and the network infrastructures so that the information transfer can help in hassle-free and safe transportation. In particular, vehicle-to-network (V2N) communications can be realized directly or using an intermediary/relay node in the form of roadside infrastructure, depending on the distance between the vehicle and network infrastructure. In this paper, we propose a system to establish communication between vehicles and network (base station) with the help of roadside infrastructure, e.g., traffic light as an intermediary node, in two phases. In the first phase, information transfer between vehicle-to-infrastructure (V2I) uses the radio-frequency (RF) channel. In the second phase, communication between infrastructure and network is accomplished using hybrid free-space optics (FSO)/RF channel. We first derive the closed-form expression for the system outage probability for this system setup. Then, we formulate the expression for system throughput considering a delay-limited scenario. We validate the accuracy of analytical results with the simulations.
LiDAR-Camera Fusion for Depth Enhanced Unsupervised Odometry

This paper proposes a robust and safe perception system for an odometry framework based on the fusion of LiDAR data with an RGB image. These multi-modal sensor measurements are fused using their depth proposals and confidence measures in a Bayesian inference module. The resulting fused depth map enhances unsupervised odometry estimates. Experimental results show that the LiDAR-camera fused depth map is an accurate 3D structure representation of the environment. This method can be used in an online adaption of the learning-based odometry algorithms to increase their generalizability to different scenes. We perform experiments on the benchmark odometry datasets and obtain promising results compared to the previous approaches. Compared to the state-of-the-art methods, the average translation error shows a 44% reduction, and the average rotation error is better or comparable.
Efficient ODE Substructure Identification of the Acrobot under Partial Observability using Neural Networks and Direct Multiple Shooting

Motion control and automation can benefit from models that accurately predict the behavior of mechatronic systems to enhance efficiency and performance. Uncertain nonlinear physical phenomena however hinder to fully capture the system behavior with classical physics-based models. The emerging availability of data has caused a surge in the use of data-driven techniques, yet it is expensive to acquire a sufficiently rich data-set of a given system. This paper presents a hybrid model that integrates physical laws, in the form of ordinary differential equations (ODE), and neural network layers, as the unknown ODE substructures, for uncertain mechatronic systems. We focus to enhance the hybrid model’s predictive capabilities for systems that are subject to multiple unknown phenomena and partial state observations. To discover these unknown dynamics we use the framework of direct multiple shooting. This allows to formulate the problem of aligning observed time-series with model responses as a constrained optimization problem. Furthermore, this formulation allows to deal with incomplete state observations, which would otherwise be unattainable with classical approaches. We apply and validate the proposed methodology to identify the friction in both joints of an acrobot of which only measurements in one joint are available. Numerical experiments show that our model can discover detailed representations of the friction characteristics in both joints and has accurate multistep predictive capabilities.
Optimum LED semiangle and the receiver FOV selection for Indoor VLC System with Human Blockages

In this paper, we have determined the optimum pair of light-emitting diode (LED) semiangle and the receiver field-of-view (FOV) in the presence of human blockages for indoor visible light communication (VLC) system. Firstly, we have calculated the optimum value of LED semiangle and the receiver FOV independently, keeping others constant. Secondly, we have jointly optimized both the LED semiangle and the receiver FOV. In the analysis, both LoS and NLoS up to the second-order have been considered. We have also incorporated the reflections from the human body, essentially the skin and the clothes, in the analysis as it impacts the received power. In order to obtain the optimum value of the LED semiangle and the receiver FOV, we have used the quality factor (Q) as a performance metric. In addition, the analytical expression for the achieved quality factor is derived for both single variable and joint optimization formulation. Results shows that with 2 and 5 blockages, the optimum pair using single and joint optimization is (63°, 65°) and (63°, 70°) for a separation distance of $D_{1}=40~{\mathrm cm}$ and (65°, 70°) and (65°, 75°) for $D_{2}=20~{\mathrm cm}$ respectively which provide the highest quality factor with minimum delay spread shown. Furthermore, the optimization analysis can also be mapped to different room sizes and LED placement, with static and dynamic blockages inside the room.
CityCross: Transferring Attention-based Knowledge for Location-based Advertising Recommendation

With the rapid development of mobile networks and the widespread usage of mobile devices, Location-Based Adver-tising (LBA), which allows an advertiser to promote products or services to targeted customers in a suitable location, has drawn increasing attention. Recommending an optimal location by delivering appealing advertisements to potential customers is crucial for the advertiser. Existing recommendation models (such as collaborative filtering) are insufficient for solving the data sparsity and cold-start issue (e.g., no historical advertisement records in new domains) in LBA problems. To tackle the defi-ciency mentioned above, we propose a novel location-based ad-vertising recommendation framework: CityCross. The CityCross framework consists of a data extraction module and a learning module. The data extraction module conducts commercial and POI feature extractions from the LBA platform, and Gaode Map, respectively. The learning module is dedicated to learning the relevant knowledge of advertisement in a new domain by utilizing the attention-based semantic information, cross-city knowledge association, and the local neighbors' knowledge. The top-k locations are identified by a modified linear regression model based on the learned knowledge. Finally, we conduct extensive experiments on two real datasets to verify the superiority of the proposed approach.
Torsional vibration of cracked carbon nanotubes with torsional restraints using Eringen’s nonlocal differential model

Free torsional vibration of cracked carbon nanotubes with elastic torsional boundary conditions is studied. Eringen’s nonlocal elasticity theory is used in the analysis. Two similar rotation functions are represented by two Fourier sine series. A coefficient matrix including torsional springs and crack parameter is derived by using Stokes’ transformation and nonlocal boundary conditions. This useful coefficient matrix can be used to obtain the torsional vibration frequencies of cracked nanotubes with restrained boundary conditions. Free torsional vibration frequencies are calculated by using Fourier sine series and compared with the finite element method and analytical solutions available in the literature. The effects of various parameters such as crack parameter, geometry of nanotubes, and deformable boundary conditions are discussed in detail.