Miracle-dz/UniFAR-FTUs huggingface dataset:
A Metasurface-Based Broadband Circularly Polarized Microstrip Antenna at X-Band

A metasurface-based broadband circularly polarized microstrip antenna is proposed in this paper. The antenna consists of two layers of radiation structure, the upper layer is a circular patch with a rectangular gap, and a coaxial line is used to feed the upper patch, while the lower layer is metasurface, which is composed of 4 by 4 square patches to generate additional resonance. After simulation optimization, the final optimized working frequency band is 8.6-11.S8GHz (the bandwidth is 29.8%). In this frequency band, S11 < −10 dB, AR < 3 dB, and the maximum gain is 7.7dBi with the gain fluctuation less than 2dB. The proposed antenna mainly radiates the right-handed circular polarization wave. In addition, the antenna does not need complicated feeding structure such as a hybrid, and has the advantages of simple structure, small volume, light weight, low cost, convenient processing and easy integration.
A Surface Potential Based Compact Model for β-Ga2O3 Power MOSFETs

For the first time, an analytical surface-potential-based drain current model is developed for beta-phase gallium oxide (β-Ga2O3) power metal-oxide-semiconductor field-effect transistors (MOSFETs). The surface potential solution is deduced by solving Poisson’s equation with appropriate simplification assumptions in accumulation, partial-depletion, and full-depletion mode. Then, the drain current expression is derived from Pao-Sah’s dual integral. The validity of the model is verified by comparing the results of the model with numerical simulations carried out with the technology computer-aided design (TCAD) tool. A good agreement between the proposed model and TCAD simulations is observed.
A Phase Error Elimination Method in Asynchronous Communication System

Previous ranging or localization systems achieve an accurate time of flight (TOF) estimation based on strict time synchronization between transmitter and receiver, which is difficult to realize in a practical communication system. To tackle this problem, we propose a phase error elimination method to achieve accurate ranging in an asynchronous manner. We implement the proposed method using a software radio platform, and the real experimental results show that the proposed method can achieve a ranging accuracy of 5.6 cm,
Research Opportunity of Insider Threat Detection based on Machine Learning Methods

Insider threats have been a known threat since a long time ago in the information technology field and many researchers tried to create novel methods to solve this threat. The purpose of this paper is to find research opportunities for insider threat detection. This was done by finding and reviewing papers related to insider threat detection. The papers reviewed were only the ones that utilized machine learning algorithms because they were the most common method used by researchers to detect malicious insiders. A systematic literature review by Kitchenham, which consisted of planning, selection, extraction, and execution, was employed as the methodology. The detection method was classified into three categories: combination, selection, and singular focus. Each category discussed and recommended a research direction to create a potentially better solution for insider threat problems.
Hall assisted forced magnetic reconnection

The role of the Hall effect in forced magnetic reconnection is investigated analytically for the so-called Taylor problem. In the latter, a tearing stable slab plasma equilibrium, which is chosen here to be a simple magnetic field reversal, is subjected to a small-amplitude boundary deformation that drives magnetic reconnection (hence the adjective “forced” ) at the neutral surface within the plasma. It is shown that such reconnection becomes substantially accelerated by the Hall effect when the nondimensional parameter di=(c∕ωpi)∕a exceeds S−1∕5. Here, c∕ωpi is the ion inertial skin depth, a is the width of the plasma slab, and S≫1 is the Lundquist number of a highly conducting plasma. Two different types of external perturbation are considered. In the case of continuous quasistatic driving, with a frequency ω such that ωτA≪1, τA being the Alfven transit time, various reconnection regimes are identified. The corresponding heating rates, which are determined by the parameters di, S, and ωτA, are derived.
Kernelization of Tensor Discriminant Analysis with Application to Image Recognition

Multilinear discriminantanalysis (MLDA), a novel approach based upon recent developments in tensor-tensor decomposition, has been proposed recently and showed better performance than traditional matrix linear discriminant analysis (LDA). The current paper presents a nonlinear generalization of MLDA (referred to as KMLDA) by extending the well known "kernel trick" to multilinear data. The approach proceeds by defining a new dot product based on new tensor operators for third-order tensors. Experimental results on the ORL, extended Yale B, and COIL-100 data sets demonstrate that performing MLDA in feature space provides more class separability. It is also shown that the proposed KMLDA approach performs better than the Tucker-based discriminant analysis methods in terms of image classification.
A threshold AR(1) model

We consider the model where φ 1, φ 2 are real coefficients, not necessarily equal, and the at ,'s are a sequence of i.i. d. random variables with mean 0. Necessary and sufficient conditions on the φ 's are given for stationarity of the process. Least squares estimators of the φ 's are derived and, under mild regularity conditions, are shown to be consistent and asymptotically normal. An hypothesis test is given to differentiate between an AR(1) (the case φ 1 = φ 2) and this threshold model. The asymptotic behavior of the test statistic is derived. Small-sample behavior of the estimators and the hypothesis test are studied via simulated data.
Modified Modular Multilevel Inverter topology for Photovoltaic Applications

Solar power plant replaces the conventional power generation due to the development of recent technologies and climate change. So, there is a need for appropriate inverter topology for integrating solar Photovoltaic system with the grid. Multilevel Inverter (MLI) is suitable for power transformation, which overcomes the limitations of square wave inverter such as Harmonic distortion, higher voltage stress and Electro Magnetic Interference (EMI). This paper proposes a seventeen-level modified asymmetrical inverter topology to convert DC power which consists of solar photovoltaics, fuel cell or battery to AC power for industrial and domestic loads. The proposed topology composes of nine IGBT semiconductor devices, one bidirectional switch and four asymmetrical solar PV System to produce seventeen level staircase type waveform and it is identical to sinusoidal shape. The pulse for the switches is produced by Nearest Voltage Level (NVL) algorithm which shows higher efficiency and reliability compared to other PWM techniques at the higher levels. The proposed topology for Solar PV system is validated by simulating in MATLAB/Simulink and harmonic spectrum of output current and voltage are analyzed. The Total Harmonic Distortion (THD) of current (I) is 0.35 % and voltage (V) is 1.33 % which follow IEEE519 standards.
Preliminary Analysis of Dietary Management Support Method for Improving the Symptoms in Irritable Bowel Syndrome

Irritable bowel syndrome (IBS) is a syndrome of chronic abdominal discomfort and abnormal bowel movements such as diarrhea and constipation, despite the absence of inflammation or ulcers in the intestines on normal examination. Dietary therapy is one of the treatment options for IBS, and is recommended to reduce symptoms by avoiding stimulants, high-fat foods, high-fiber foods, and fermented foods. However, because the intestinal environment varies from person to person, some foods are suitable for some people and others are not. We thought that if patients could find foods that suit their bodies, their symptoms could be improved. In this study, we propose machine learning based methods to predict whether IBS symptoms appear or not based on the data of patients daily meals and their stomach condition. In addition, we describe our experimental results and evaluation of the proposed method.
Wideband Millimeter-Wave SIW Two-Channel Crossover Based on Homogeneous Cylindrical Lens

A compact and wideband millimeter-wave crossover employing an embedded homogeneous cylindrical lens (HCL) is proposed in this paper. Compared with traditional crossover designs, such a design introduces a HCL within the substrate integrated waveguide (SIW) crossover cavity to direct the incident waves in the desired direction. The simulated fractional bandwidth (FBW) of the proposed crossover is 33%. The size of the core area is only 0.74 λ*0.74 λ (λ is the free-space wavelength at the center frequency).
Close Correlation among Hα Surges, Magnetic Flux Cancellations, and UV Brightenings Found at the Edge of an Emerging Flux Region

Surge activities were observed at the edge of an emerging flux region. We studied the relations between the features around the surges in various data sets: magnetogram, Hα, G-band, UV, EUV, and soft X-rays. We showed that the surge activities in Hα and the brightenings in TRACE 1600 u A images correlate well in both time and space with the cancellation of magnetic fluxes around an emerging flux region. In particular, at the onset of surge activity, a close correlation among them was clearly found. These facts are consistent with the magnetic reconnection model. The released energy through magnetic reconnection, which is estimated to be 10 28 erg, is sufficiently large to produce surge activities. No prominent brightenings were observed in soft X-ray and EUV images during the surge activities. This may suggest that the energy releases occurred at a layer of high densities.
A Novel Multiband Patch Antenna Based on Mandelbrot Fractal

This paper investigates the effects of fractal parameters on the performance of Mandelbrot fractal patch antennas and a four-band patch antenna is proposed based on the 5th-order Mandelbrot fractal structure. It is found that the antennas can easily acquire a multi-band characteristic by using a high-order structure but the overall size can be relatively small. The proposed antenna can well work at the frequencies of 5.5 GHz, 10.9 GHz, 12.2 GHz and 16.7 GHz, respectively, but only has the size of $30\times 30\times 2$ mm. The simulation results have demonstrated its good performance.
Experimental Investigations on Short-Circuit Capability of a New Structure Planar SiC MOSFETs

In this paper, a new structure named plasma spreading layer (PSL) is introduced into planar SiC MOSFETs to improve the short-circuit robustness. The short-circuit performance under 400V, 600V, and 800V bus voltage is tested. And two failure modes are discovered. The 3D TCAD simulations, Emission Microscope (EMMI), and Focused ion beam (FIB) are used to investigate the short-circuit failure mechanisms. Under 400V and 600V bus voltage, the interlayer dielectric between the source and the gate is damaged due to the high temperature generated in the short-circuit process, and the melted source metal Al is connected to the gate polysilicon, causing short circuit of the gate and source electrodes. Compared with commercial devices, the short-circuit capability of the device with PSL is improved by 3 to 7μs under 400V bus voltage. Under 800V bus voltage, the thermal power is almost twice that of 400V, which reduces the short circuit withstanding time (SCWT) of the device rapidly to just over 5µs. Due to such high instantaneous power, the device failure is characterized by the short circuit between the three electrodes, and thermal runaway is the cause of failure in this situation.
D-Shield: Enabling Processor-side Encryption and Integrity Verification for Secure NVMe Drives

Ensuring the confidentiality and integrity of data stored in storage disks is essential to protect users’ sensitive and private data. Recent developments of hardware-based attacks have motivated the need to secure storage data not only at rest but also in transit. Unfortunately, existing techniques such as software-based disk encryption and hardware-based self-encrypting disks fail to offer such comprehensive protection in today’s adversarial settings. With the advances of NVMe SSDs promising ultralow I/O latencies and high parallelism, architecting a storage subsystem that ensures the security of data storage in fast disks without adversely sacrificing their performance is critical.In this paper, we present D-Shield, a processor-side secure framework to holistically protect NVMe storage data confidentiality and integrity with low overheads. D-Shield integrates a novel DMA Interception Engine that allows the processor to perform security metadata maintenance and data protection without any modification to the NVMe protocol and NVMe disks. We further propose optimized D-Shield schemes that minimize decryption/re-encryption overheads for data transfer crossing security domains and utilize efficient in-memory caching of storage metadata to further boost system performance. We implement D-Shield prototypes and evaluate their efficacy using a set of synthetic and real-world benchmarks. Our results show that D-Shield can introduce up to 17× speedup for I/O intensive workloads compared to software-based protection schemes. For server-class database and graph applications, D-Shield achieves up to 96% higher throughput over software-based encryption and integrity checking mechanisms, while providing strong security guarantee against off-chip storage attacks. Meanwhile, D-Shield shows only 6% overhead on effective performance on real-world workloads and has modest in-storage metadata overhead and on-chip hardware cost.
Towards Secure Communications in Heterogeneous Internet of Things

Machine-to-Machine (M2M) communications in the Internet of Things (IoT) which are built over the wireless spectrum can easily be intercepted or eavesdropped by adversaries. While there are various solutions for enhancing the security of communications in IoT, they may incur significant overhead to the network. In this paper, we introduce several security methods at the communication protocol level, in which are based on the Constraint Application Protocol (CoAP), Datagram Transport Layer Security (DTLS), and Advanced Encryption Standard (AES). Additionally, we introduce a light-weight M2M communicating integrity approach with CoAP and bloom filter, as well as the decentralized Virtual Private Network (VPN). Via extensive performance evaluation, we validate the efficacy of our approach with respect to the impact on the overall network performance of the heterogeneous Internet of Things (HIoT) and provide some recommendations when our approach is adopted.
A Wideband Air-Filled Slot Antenna for Millimeter-Wave Applications

In this paper, a air-filled slot antenna with simple structure is proposed for wideband millimeter-wave (mmW) applications. It is a novel structure that utilizes an air-filled slot excited by a substrate-integrated-waveguide (SIW). Due to the characteristic of Q-factor in the slot, the proposed antenna can achieve wider bandwidth. Moreover, the proposed antenna is constructed on a single-layer substrate and has a simple structure, which is easy to fabricate and low cost. For validation, the proposed antenna is designed and experimented. The results show that a wide bandwidth of 47% from 54 to 88 GHz is obtained, with the peak gain of 8.9 dBi. Across the operating band, stable and symmetric radiation patterns can be observed. With the above performances, the proposed antenna is attractive to mmW applications.
Frequency Reconfigurable Planar Filtering Dipole Antenna with Omnidirectional Radiation Pattern

A frequency reconfigurable filtering monopole antenna with omnidirectional radiation characteristics is presented in this paper. The low-frequency radiation null is introduced by a dumbbell-shaped defect ground structure. The high-frequency radiation null is obtained by adding a V-shaped slot to the monopole radiation arm. The radiation arm is divided in two parts and connected by two varactor diodes. By controlling the capacitance value of the varactor, the equivalent electric length of the antenna is changed, and the function of frequency reconfigurability of the antenna is realized. The reconfigurable filtering antenna has the advantages of small size and low-profile. The test results show that the frequency can be tuned from 2.2GHz to 2.81GHz. The maximum antenna gain is 4.31dBi.
A Low-profile Quadrifilar Helix Antenna for Beidou Navigation System

Ahstract-A new low-profile quadrifilar helical antenna (QHA) is proposed and investigated. Four spiral arms of the QHA are divided and connected to for a sleeve structure to reduce the height of the antenna. In this case, four spiral arms on the inner cylindrical sleeve are connected with the ground, while the upper ends of the four spiral arms on the outer cylindrical sleeve are short-circuited, and inner and outer spiral arms are connected in the middle. The QHA has a beam width reaches to above $120 ^{\circ}$ and a cardioid pattern at 1.575 GHz. As a result, the QHA has a very low profile of only 22 mm. The simulation and optimization from the CST show that the center frequency of the QHA is 1.575 GHz, which is used for the satellite navigation system, with axis ratio in the operating band less than 3 dB.
22.6 ANP-I: A 28nm 1.5pJ/SOP Asynchronous Spiking Neural Network Processor Enabling Sub-O.1 μJ/Sample On-Chip Learning for Edge-AI Applications

With the development of on-chip learning processors for edge-AI applications, energy efficiency of NN inference and training is more and more critical. As on-chip training energy dominates the energy consumption of edge-AI processors [1], [2], [4], [5], reduction is of paramount importance. Spiking neural networks (SNNs) offer energy-efficient inference and learning compared with convolutional neural networks (CNNs) or deepneural networks (DNNs), but SNN-based processors have three challenges that need to be addressed (Fig. 22.6.1). 1) During on-chip training, some factors involved in ΔW computation are zeros resulting in ΔW=O, leading to redundant ΔW computation and memory access for weight update. 2) After reaching a certain accuracy, more data cannot improve the accuracy significantly, and 95% of the energy is wasted on the unnecessary processing of the input spike events afterwards. 3) In the case of sparse input-spike events, the number of spike events in each time step is different. If spike processing is synchronized by time step, the worst-case scenario needs to be considered. As a result, energy and time are wasted.
Influence of Dummy Elements on the Performance of Array Antennas

The influence of dummy elements on the performance of array antennas is studied in this paper. Two array antennas with the same element are designed and simulated. One of them has dummy elements and the other has no dummy elements. Comparing the active standing-wave ratios of them, the introduction of dummy elements can effectively improve the characteristics of marginal excited elements, especially when the antenna scans at a large angle. Comparing the radiation performance of them, dummy elements weaken the radiation fields of marginal excited elements and reduce the gain because the energy coupling from marginal excited elements to dummy elements is largely absorbed by the load.
HIRAC: A Hierarchical Accelerator with Sorting-based Packing for SpGEMMs in DNN Applications

The state-of-the-art deep neural network (DNN) models use pruning to avoid over-fitting and reduce the number of parameters. In order to improve storage and computational efficiency, only nonzero elements are stored, and their locations are encoded into a sparse format. Sparse General Matrix Multiplication (SpGEMM) is the kernel computation of DNN-based applications. One challenge of computing SpGEMM is to avoid multiplying zero elements while keeping hardware utilization high in hardware accelerators that consist of processing element (PE) arrays. Prior work tackling this challenge typically requires complex interconnection networks, which adds high area and energy costs.This work proposes a HW/SW co-design architecture to compute SpGEMM efficiently without requiring complex interconnection networks. A novel fast packing algorithm, SorPack, is proposed to convert a sparse matrix into a dense matrix that increases PE utilization. The key idea is to sort columns and rows inside each submatrix based on the number of nonzero elements. The goal is to keep the partial sums that need to be added together close to each other, hence can be added locally and avoid the use of complex interconnection networks. In addition, a new tile-based hierarchical architecture, HIRAC, is proposed to provide a scalable system that maximizes the parallelism of the PEs. The HIRAC architecture consists of a novel PE array design and interconnection network tailored for DNN applications. The SorPack algorithm complements the HIRAC to further improve hardware utilization and overall system performance. Based on the evaluation results, HIRAC achieves an average of 3.2× speedup on a single layer of DNN as compared to the state-of-the-art sparse DNN accelerator SIGMA. In addition, HIRAC has a 9.5% area reduction and a 32% power reduction as compared to SIGMA. An end-to-end evaluation on a DNN model shows an 8.2× runtime reduction over the TPU.
Molecular Graph Matrices and Derived Structural Descriptors

Abstract A number of recently graph matrices encoding in various ways the topological information is presented. Four graph operators are used to compute 19 topological indices for a set of 306 alkanes. The intercorrelation coefficients of the 19 topological indices are computed and used to identify highly intercorrelated indices.
AVGI: Microarchitecture-Driven, Fast and Accurate Vulnerability Assessment

We propose AVGI, a new Statistical Fault Injection (SFI)-based methodology, which delivers orders of magnitude faster assessment of the Architectural Vulnerability Factor (AVF) of a microprocessor chip, while retaining the high accuracy of SFI. The proposed methodology is based on three key insights about the way that faults traverse complex out-of-order microarchitectures: (1) the distribution of the different ways that hardware faults manifest at the software (i.e., the first effects of faults to the software layer) is relatively uniform across workloads, (2) the final effects of faults in a specific hardware structure (i.e., their effect on the program execution) is relatively uniform for different workloads and depends on the distribution of the above fault manifestations, and (3) the majority of first manifestations occur in certain timeframe from the fault occurrence, which is significantly shorter than the complete execution of the workload, and depends on the type of hardware structure. Based on these insights, the proposed AVGI methodology accurately estimates the complete cross-layer vulnerability (i.e., AVF) for every hardware structure in fine granularity (SDCs and Crashes). Our experimental analysis shows that preserving high levels of accuracy, the proposed AVF assessment methodology is up to 337x and 440x faster than an accelerated exhaustive SFI, for two different microarchitectures of 64-bit Armv8 and 32-bit Armv7 CPU models, respectively.