Miracle-dz/UniFAR-FTUs huggingface dataset:
A Circularly Polarized Cylindrical Cavity backed Substrate Integrated Waveguide Antenna for Millimeter wave Applications

In this paper, a circularly polarized cylindrical cavity backed substrate integrated waveguide resonator for millimeter wave application is proposed. A feeding structure is designed and integrated on the same layer of circular cavity backed antenna. The feeding structure comprises of orthogonal feed, using substrate integrated waveguide technology. A circular ring slot is etched on the top plane of the cavity to radiate antenna in broadside direction. Two symmetrical rectangular slots are placed diagonally on the top metal plane of cavity and position of feed is optimized which improves the impedance matching. The dimensions of the proposed antenna with feeding structure is 3. 55λ x 3. 56λ x 0. 19λ, where λ is the guided wavelength. The antenna achieves a peak gain of 5.85dBi, peak directivity of 6.23dBi, radiation efficiency of 94.1% and an axial ratio of 120MHz bandwidth below 3dB. The proposed antenna maintains a low profile and is compatible with planar structures. A comparative study of microstrip feeding and substrate integrated waveguide feeding is done and results are plotted in Ansys high frequency structure simulator. The performance of antenna is measured in terms of reflection coefficient, radiation pattern, front to back ratio, gain and directivity. The proposed antenna provides high gain, circular polarization and high front-to-back ratio at the high frequency thus, it is suitable for various millimeter wave applications.
Addressing Irregular Patterns of Matrix Computations on GPUs and Their Impact on Applications Powered by Sparse Direct Solvers

Many scientific applications rely on sparse direct solvers for their numerical robustness. However, performance optimization for these solvers remains a challenging task, especially on GPUs. This is due to workloads of small dense matrices that are different in size. Matrix decompositions on such irregular workloads are rarely addressed on GPUs. This paper addresses irregular workloads of matrix computations on GPUs, and their application to accelerate sparse direct solvers. We design an interface for the basic matrix operations supporting problems of different sizes. The interface enables us to develop irrLU-GPU, an LU decomposition on matrices of different sizes. We demonstrate the impact of irrLU-GPU on sparse direct LU solvers using NVIDIA and AMD GPUs. Experimental results are shown for a sparse direct solver based on a multifrontal sparse LU decomposition applied to linear systems arising from the simulation, using finite element discretization on unstructured meshes, of a high-frequency indefinite Maxwell problem.
A Short Half-Cosine Slot Waveguide Leaky-Wave Antenna with Quasi Omni-Directional Beamwidth

This paper presents a short, conformal, half-cosine slot waveguide leaky-wave antenna at Ku-band. Antenna is flush mounted onto the cylindrical airframe. There are two antennas mounted onto the cylindrical airframe with a 180-degree angular separation. Omni directional coverage through this configuration needs to be achieved by designing each antenna for a 180-degree HPBW. Antenna design is also aimed for a beam tilt of 50 degrees from antenna broadside direction and sidelobe level of less than -20 dB. Low sidelobes are achieved by designing a half-cosine shaped longitudinal slot cut on the broad wall of the waveguide. HPBW of 180 degrees is achieved by designing an extended flange in the direction of E-plane. Length of the antenna is $\mathbf{2.75}{\lambda}$ at the center frequency. A short length of less than $\mathbf{3}{\lambda}$, E-plane coverage of 180 degrees, half-cosine shaped slot to achieve low sidelobe levels are the novelties of this work. Design, simulation and measurement results are presented. Measurement results are in correlation with the simulation results and met the aimed specifications.
Fingerprint Database Enhancement using Spatial Interpolation for IoT-based Indoor Localization

The widespread adoption of the internet of things (IoT) drives indoor location-based service (ILBS) applications forward. The core parameter of ILBS is indoor localization. Generally, indoor localization is divided into two techniques, distance-based, i.e., triangulation, and distance-free, i.e., fingerprint technique. This paper discusses the fingerprint technique because of some advantages, i.e., higher accuracy performance compared to the distance-based technique. However, the fingerprint technique has drawbacks in offline database construction: extraordinarily time-consuming and labor-intensive, which hinders its application in the real world. Furthermore, the fingerprint database needs to be updated regularly in a dynamic environment. Therefore, we propose fingerprint database enhancement based on various spatial interpolations to tackle the issues of fingerprint database construction. We apply Inverse Distance Weighted (IDW), Quadratic Spline, Cubic Spline, and Ordinary Kriging Interpolation methods to generate the synthetic database. We have conducted a measurement campaign to obtain Received Signal Strength Indicator (RSSI) as the fingerprint-based localization parameter. From our results, the interpolation methods show that the generated synthetic RSSI can provide a lower prediction error. Our proposed methods can have similar accuracy performance compared to manual fingerprints using actual data. Moreover, the synthetic RSSI data has a 0 dBm error for the best prediction and not more than 6 dBm for the worst prediction. Thus, we conclude that our proposed methods can enhance the fingerprint database and have proven to increase localization performance.
The number of conics tangent to five given conics: the real case

It ja clasaical result, fiat established by de Jonqui’eres (1859), tbat generically the number of conica tangent to 5 given conica in the complex projective plane is 3264. We show here the existence of configurationa of 5 real canica such that the number of real canica tangent to them ja 3264.
Analysis of SNR Enhancement in 1.5T MRI by Using Metasurfaces

Magnetic Resonance Imaging (MRI) is a clinical diagnostic tool for detection of malfunctional tissues and organs in a human body. The image resolution and scanning efficiency of MRI are directly dependent on signal-to-noise ratio (SNR). A higher SNR can be obtained by increasing the RF magnetic field which is accomplished by using metamaterials or metasurfaces. Here we present a thin metasurface which can be used as an ‘add-on’ in clinical 1.5T MRI for its SNR enhancement. A convoluted cross-type structure has been employed for increasing the magnetic flux density in the region of interest (ROI) by local confinement of electromagnetic fields in the near field region. A dielectric phantom made up of saline solution is integrated with the metasurface to demonstrate the enhancement of magnetic flux density up to a depth of 105 mm. The metasurface placed behind a human head bio-model, to emulate virtual brain-scan, results in SNR enhancement by a factor of 400 on the surface of the phantom.
Scalable Irregular Parallelism with GPUs: Getting CPUs Out of the Way

We present Atos, a dynamic scheduling framework for multi-node-GPU systems that supports PGAS-style lightweight one-sided memory operations within and between nodes. Atos's lightweight GPU-to-GPU communication enables latency hiding and can smooth the interconnection usage for bisection-limited problems. These benefits are significant for dynamic, irregular applications that often involve fine-grained communication at unpredictable times and without predetermined patterns. Some principles for high performance: (1) do not involve the CPU in the communication control path; (2) allow GPU communication within kernels, addressing memory consistency directly rather than relying on synchronization with the CPU; (3) perform dynamic communication aggregation when interconnections have limited bandwidth. By lowering the overhead of communication and allowing it within GPU kernels, we support large, high-utilization GPU kernels but with more frequent communication. We evaluate Atos on two irregular problems: Breadth-First-Search and PageRank. Atos outperforms the state-of-the-art graph libraries Gunrock, Groute and Galois on both single-node-multi-GPU and multi-node-GPU settings.
TD-NUCA: Runtime Driven Management of NUCA Caches in Task Dataflow Programming Models

In high performance processors, the design of on-chip memory hierarchies is crucial for performance and energy efficiency. Current processors rely on large shared Non-Uniform Cache Architectures (NUCA) to improve performance and reduce data movement. Multiple solutions exploit information available at the microarchitecture level or in the operating system to optimize NUCA performance. However, existing methods have not taken advantage of the information captured by task dataflow programming models to guide the management of NUCA caches. In this paper we propose TD-NUCA, a hardware/software co-designed approach that leverages information present in the run-time system of task dataflow programming models to efficiently manage NUCA caches. TD-NUCA identifies the data access and reuse patterns of parallel applications in the runtime system and guides the operation of the NUCA caches in the hardware. As a result, TD-NUCA achieves a 1.18x average speedup over the baseline S-NUCA while requiring only 0.62x the data movement.
Duality of Graph and Its Application in Electric Circuit

Graph theory is broadly used to verify many arithmetical theories and models. This assessment introduces the use of numerous graph concept theories to clear up difficulties in numerous sectors of technology and generations similarly to arithmetic. A number of them fields encompass computer technology, chemistry, biology, virtual image processing, webpage design, scientific technology and overall performance studies. In a mathematical idea take a look at of the graph, a double graph of the Gr is a plane with a vertex of one face of Gr. A twin graph has the rims of every pair of facets in Gr splits from the alternative via the edge, and a self-loop where the equal face appears on each facets of the image(2). Here we explain a scholar task in which we build a calculation answer for an electrical circuit primarily based on graph concept theory. This multidisciplinary technique includes abstract mathematics, linear algebra, circuit physics and computer programming, in order to achieve the automated aim-solving intentions(1).
Development of Multimodal Fusion Technique for Medical Images

Imaging technology plays a vital role in medical imaging, diagnosis and treatment using different modalities in imaging devices. Unfortunately, a single imaging device cannot create information rich images synchronously at the same time due to the difference between the fundamental imaging principles of these modalities. As a result, medical professionals have to spend a lot of energy and time to analyze the complete medical data information gathered from multiple devices. Hence a multimodal image fusion method is required in order to enhance the medical images which further can help medical professionals provide an accurate diagnosis in a timely manner. For which, we have gone thoroughly through the existing state-of-art techniques related to Medical Image Fusion and designed a multi-modal Image Fusion Technique based on GAN in order to enhance the quality of the medical image for better diagnosis of diseases and perform comparative evaluation and validation of proposed techniques using the standard datasets.
Millimeter-wave High-Gain and Highly Isolated Diversity MIMO Array Antenna for 5G Wireless Applications

The design of a wideband millimeter wave two-port multiple-input-multiple-output (MIMO) array antenna appropriate for 5G applications is presented in this work. The intended antenna wider impedance bandwidth (IBW), circular polarization radiation, and higher gain response are obtained due to the loading of a staircase-shaped circular polarization converter-based metasurface (MS). Using this concept, a two-port MIMO antenna is designed. The intended MIMO antenna provides a wider IBW of 34.1% (23.61 GHz to 33.3 GHz), a higher gain of 11 dBi at 26.1 GHz, and isolation is more than 30 dB due to the placement of modified mushroom-based MS. Furthermore, the antenna provides polarization diversity mechanism, with antenna-1 provides right-handed circular polarization (RHCP) and antenna-2 provides left-handed circular polarization (LHCP) radiation.
On-Body V-Band Leaky-Wave Antenna for Navigation and Safety Applications

The paper discusses an on-body V-band leaky-wave antenna for navigation and safety applications. The antenna is based on meandering microstrip line operating in V-Band with continuous beam scanning from backward-to-forward direction in the elevation plane. The width of the transverse line are alternatively varied to remove the open stop band (OSB) at the broadside frequency. The final antenna shows a scanning range in the elevation direction from -45° to 50° with no impact on performance at broadside direction. The antenna has a gain of more than 11 dB across the operating frequency range. The structure is simulated and the results and compared with the other leaky-wave antenna designs. The performance of the antenna is also verified for on-body conditions. The antenna is self matched at 50Ω hence removing the need for matching circuit. The requirements for an on-body antenna are also analysed for the designed structure.
COVID-19 Fake News Detection using Pre-Tuned BERT-Based Transfer Learning Models

The World Health Organization declared the Coronavirus disease in 2019; that was a very hard time for people, and every single day, a new crisis emerged. In that case, everyone shares their stories on the social media platform on a daily basis, but no one is sure that information is true or misleading, and that becomes a challenge to detect differences between them. And to tackle this problem, this paper has explored the veracity of social media stories using some machine learning models. The goal of this paper is to test three different BERT base pre-trained transform learning models (BERT, DistilBERT, and RoBERTa) on an English COVID-19 fake news dataset to detect the fake and true news separately. We explore their capability with precision, recall, and F1-score to achieve better results compared with the previous research.
Cancelable Face Biometric Verfication Algorithm Built on GoogLeNet and Characteristic Arbitrary Projection

Biometric pattern information securing is necessary for avoiding individual confidentiality and identity loss. Arbitrary projection built on cancelable face biometrics is an effective and efficient approach to accomplish biometric pattern securing. Nevertheless, standard arbitrary projection-built cancelable pattern design can be easily attacked by attackers. To resolve this problem, in this paper, a characteristic arbitrary projection built on a cancelable face biometric algorithm is proposed, in which the projection arrays are created from one fundamental array in integration with face biometric information. The created projection arrays are deleted after utilization which makes it impossible for the hacker to attack information. The proposed algorithm is tested on two known benchmarks, FEI and Georgia Tech face datasets. Experimental results illustrate the robustness of the proposed algorithm.
Dual Circularly Polarized Quad Band Ring Shaped Monopole Antenna for Wireless Applications

A ring shaped multiband integrated wideband monopole antenna is presented. The antenna attains quad band along with dual circular polarization. Half-moon shaped slots are replicated in the radiator. Due to the placement of L- shaped slot, asymmetric effect is attained and circular polarization is achieved. The proposed ring-shape antenna occupies 1.51-1.67 GHz (0.16 GHz), 2.19-2.53 GHz (0.34 GHz), 4.79-6.60 GHz (1.81 GHz), 6.60- 9.92GHz (3.32 GHz) and 9.7-10.41GHz (0.71 GHz) in -10 dB impedance BW with 3-dB axial ratio BW of 2.19-2.26 GHz (0.07 GHz) and 9.73-9.93 GHz (0.20 GHz). The measured and simulated results are illustrated and verified. The proposed antenna covers present day wireless communication applications.
Equalization Optimization for SerDes Channels with Constrained Bayesian Optimization

Assigning parameters of a feed-forward equalizer (FFE) can be a challenging and time-consuming task. In this work we introduce a machine learning algorithm to automatically optimize these parameters without the need to a domain expert. Conventional optimizers are not applicable to this problem because of a constraint over the FFE parameters. Therefore, we reformulate the problem and propose a modified Bayesian optimization algorithm to take this constraint into account. The proposed approach is validated with an example.
To Use a Quick R-CNN Algorithm—An Automated Strategy for Tooth Diagnostics

With the development of research in the Supervised learning field, artificial intelligence (AI) is extremely popular within in the health service. Only a few Deep Learning techniques, nevertheless, are able to find solutions within real-time applications. Data is the main worry in these types of valid medical systems, and the dentistry dataset had the same issue. The most accurate and optimal approach is presented in this study. 5 distinct datasets have been identified and assigned classifications. We propose a faster human brain using a fully convolutional model in this study. Convolution layer is a useful method in reinforcement learning for overcoming obstacles like picture segment and appropriate categorization with high levels of detection, as well as for accelerating convergence. lessens the local computation required for each outer loop. The Dense net model exhibits excellent classification in original picture classification issues when there is a large dataset, as we discovered from the current system. We have discovered three distinct maladies linked to various types of holes, including frontal gums cavities, inner pore gums, and esophageal cancer, which will distinguish between normal and diseased incisors in the sensing of teeth maladies and use this network design framework on real medical studies at various levels. To incorporate it into the web application, the created ML tree is being stored and translated into a JSON file format. The online application will serve as just an interface for identifying teeth with potential problems.
Circular Shape Dual Element MIMO Antenna for 5G (Sub-6GHz) Application

In this article, a two-element multiple-input multiple-output (MIMO) design is suggested for use in sub-6 GHz 5G wireless access points operating in the 3–4 GHz frequency range. The proposed antenna uses microstrip fed circular shape and the optimized bandwidth and isolation are obtained using an E-shaped stubs associated with partial ground plane. Ansys HFSS simulations are used to describe the proposed antenna's design process. Each antenna element has a peak gain of 2.12dBi. Simulated results are verified with measured results and found a good agreement between them. The diversity performance of MIMO antenna is also studied with envelop correlation coefficient (ECC) $<\ \mathbf{0.15},\mathbf{DG}\approx \mathbf{9.98}\mathbf{dB}$ and mean effective gain (MEG)-ratio within $\pm \mathbf{3}\ \mathbf{dB}$. The proposed antenna is designed on FR-4 substrate with a dimension of $\mathbf{30}\times \mathbf{20}\times \mathbf{1.6}$ cubic millimeter.
Review Based Rating Prediction using Machine Learning Techniques

Applications used in today's e-commerce, such as personalised marketing, targeted advertising, and information retrieval, heavily rely on recommendation systems. The value of contextual information has recently driven the creation of personalized suggestions based on the users' contextual information. In comparison to the traditional systems which mainly utilize users' review-based recommendations, and rating history and provide more relevant results to users. We proposed a Review Based Rating Prediction Using Machine Learning in this research paper. Techniques on the dataset provided by Yelp.
Design and Implementation of Switched Capacitor Cascaded Multilevel Inverter for Symmetric Sequence

The new nine-level multilevel inverter (MLI) topology that utilizes Unipolar Pulse Width Modulation is proposed. It provides maximum output voltage level while using the minimum dc source and switches. The concept is implemented on a 9-level symmetric MLI. Multi carrier unipolar pulse width modulation technique is adopted to create the switching pulses. Total harmonic distortion (THD) simulations for both voltage and current waveforms have been performed. Comparison is performed for different topologies with proposed topology. The simulation tests for new proposed MLI is done in a MATLAB/Simulink. The newly proposed topology of 9 level MLI is implemented in hardware.
A 2x4 microstrip antenna array for monopulse tracking radar at S-band

This paper proposes a 2x4 microstrip antenna array for mono-pulse tracking radar in the S-Band. In the proposed design, a rat-race coupler is paired with a 2x4 patch antenna array at 3GHz. The feed is given to the sum and difference ports of the rat-race coupler to obtain the sum and difference patterns. The design aims to help in tracking. The tracking is done in one-dimensional space, and the design has limited elements with better efficiency. In the proposed design, the simulated and measured results have a return loss of at least - 10 dB at 3 GHz and the sum pattern has a main lobe and side lobe difference of at least 12 dB, while a null depth of at least 20 dB is achieved in the difference pattern. A gain of 17 dB has been noted. The simulation of this design was done on Ansys HFSS and MathWorks Antenna Toolbox softwares with an epsilon value of 2.2 of the Rogers RT 5880 substrate with a thickness of 1.6 mm. The design also contains chamfered elements to decrease the side lobe levels.
Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation

Derivatives are key to numerous science, engineering, and machine learning applications. While existing tools generate derivatives of programs in a single language, modern parallel applications combine a set of frameworks and languages to leverage available performance and function in an evolving hardware landscape. We propose a scheme for differentiating arbitrary DAG-based parallelism that preserves scalability and efficiency, implemented into the LLVM-based Enzyme automatic differentiation framework. By integrating with a full-fledged compiler backend, Enzyme can differentiate numerous parallel frameworks and directly control code generation. Combined with its ability to differentiate any LLVM-based language, this flexibility permits Enzyme to leverage the compiler tool chain for parallel and differentiation-specitic optimizations. We differentiate nine distinct versions of the LULESH and miniBUDE applications, written in different programming languages (C++, Julia) and parallel frameworks (OpenMP, MPI, RAJA, Julia tasks, MPI.jl), demonstrating similar scalability to the original program. On benchmarks with 64 threads or nodes, we find a differentiation overhead of 3.4–6.8× on C++ and 5.4–12.5× on Julia.
Electronically Tunable Reflection Type Phase Shifter Using PIN Diode As A Variable Resistor

This paper presents a new attempt to utilize the PIN diodes as variable resistors to realize a continuously tunable phase shifter. A diode is used in parallel to a capacitor. Thus, the diode resistance and hence the imaginary part of the impedance can be varied. The tuning range of a varactor capacitance is usually limited to 1:2. However, the resistance of a diode can vary from a few Ohms to a few kilo Ohm. Therefore, a much wider tuning range is possible. The next challenge is to reduce the power lost in the real part of the impedance. As an example, a reflection-type phase shifter (RTPS) is designed and implemented at 2.4 GHz.