Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory Shared Spatial Attention Neural Network for Reliable Beam Prediction

In this paper, we propose a memory shared spatial attention neural network for beam prediction based on a millimeter wave (mmWave) massive multiple input multiple output (MIMO) system. The proposed method learns temporal features based on the autoregressive model from the frequency meanwhile extract the spatial characteristics from the antenna indices. Specifically, we apply a weight sharing long-short term memory (LSTM) to explore inherent delay features from real and imaginary of mmWave channels among antenna indices. Due to the spatial coherence of massive MIMO, we further apply the attention mechanism to extract the spatial feature from the temporal features. To verify the proposal, we compare the proposed model with conventional deep neural network (DNN), Transformer, unshared weight, and shared weight proposal underlying different signal-to-noise ratio (SNR) levels. According to the experiment results, the accuracy can be improved from 66% to 92% comparing with the others under 20 dB SNR. And the average accuracy can achieve 65% under 0 dB SNR.
Reliability Assessment of Distribution Power Network

As renewable energy sources become more widely available, distributed generation (DG) is expected to grow in distribution networks. This research presents a methodology for analysing the reliability of such distribution networks, which can be used in early planning studies. The IEEE 33-bus radial distribution system's reliability is tested first without DG and subsequently with DG connected at various load sites. The reliability indices are calculated using an analytical method. The influence of DG location, number, and availability on reliability indices is examined. The effect of random load variation on system reliability is studied. Because different DG locations provide different reliability indices, the location with the lowest value is picked.
A Ku-Band Power Amplifier with 13dBm OP1dB in 40-nm CMOS

This paper presents a high linearity and broadband Ku-Band power amplifier (PA) in 40-nm CMOS process. On-chip transformers are used in the matching networks to provide optimum load impedance and achieve broadband matching. A two-stage PA is proposed for higher gain and output power. Neutralization capacitance is used for both stages to compensate the feedback effect due to the gate-drain parasitic capacitance CGD. The design and layout of the Driver stage and Output stage are optimized to achieve both high output power and gain. To improve both linearity and efficiency, transistors of the Output stage are biased in deep class-AB. The simulation results demonstrate that the PA chip achieves a saturated output power of 16.8-dBm, a $\mathrm{P}\mathrm{A}\mathrm{E}_{\max}$ of 24.5% and a 14.5-dBm $\mathrm{O}\mathrm{P}_{\mathrm{1}\mathrm{d}\mathrm{B}}$ with a maximum power gain of 25.5-dB. The chip area including all pads is 0.37 $\mathrm{m}\mathrm{m}^{2}$.
Finite element modelling and physics of remote field eddy current responses for axially aligned cracks

A simplified physical model for two-dimensional (2-D) finite element analysis of axially aligned crack responses for the remote field eddy current (RFEC) technique is proposed. Two formulations are applied to model the problems. Reasonable agreement between calculated results and some preliminary experimental results is achieved. A hypothesis, based on the physical model, is presented. It explains the RFEC signals from axially aligned cracks and makes some predictions of possible features for future verification. >
Adaptive Planar Foot with Compliant Ankle Joint and Multi-modal Sensing for Quadruped Robots

An adaptive sensorized robot foot that can adapt to uneven and rough terrains and have contact state sensing capability is vital for legged locomotion in exploration missions. Inspired by quadruped animals, we present an adaptive planar foot with large contact area to reduce sinkage, two degrees of freedom (2-DOF) compliant ankle joint for better terrain adaptation, in-foot multi-modal sensing capability. We propose customized ankle design with encoders instead of IMU for ankle joint angle measurement, in order to mitigate the noise injected by large impact forces. The foot also provides an accurate estimated force according to foot-shank relative orientation and the 6-axis force/torque sensor data. We develop a control algorithm for a quadruped robot equipped with our proposed robot feet and test its performance through simulation. Real-world experiments including foot orientation estimation, swing sensitivity, and force perception verify that our robot foot is suitable for dynamic quadruped locomotion.
Optimal AI-Enabled Secured NOMA Among Untrusted Users

To develop a cyber-physical artificial intelligence enabled wireless network, it is essential to support unprecedented high throughput and efficient spectrum utilization in a practically unknown channel. In this regard, we need to investigate the design aspects of the network exploiting deep learning-based non-orthogonal multiple access (NOMA) for a model-free environment. In this work, a model-free deep learning algorithm based on deep deterministic policy gradient is proposed that provides a continuous course of actions under the optimal policy for an untrusted NOMA network. Utilizing the concept of physical layer security, we focus on maximizing the sum secrecy rate of the system in terms of decoding order and transmitting power allocation to users under the limited energy constraint at the base station. Via extensive simulations, while training, we measure the performance of the deep learning algorithm in terms of cumulative sum secrecy rate, convergence rate and stability. Also, after the training, we obtain various insights on the performance of the obtained optimal policy by varying the independent system parameters and compare the algorithm against a benchmark that provides the improvement of nearly 55% in the noisy channel.
Improving MIMO Secrecy Rate through Efficient Power Allocation

We study the problem of maximizing the secrecy capacity in multiple input multiple output (MIMO) communication systems in the presence of an eavesdropper using optimal power allocation. One of the key bottlenecks arise in identifying the appropriate spatial streams to securely transmit data and the corresponding transmit powers to maximize capacity. We employ the generalized singular value decomposition (GSVD) technique to identify these spatial streams and propose a power allocation scheme over these spatial streams. We also present an upper bound for the maximum achievable secrecy rate under certain conditions. We show that the proposed power allocation technique not only achieves better secrecy, but also converges to the upper bound faster than those in the literature.
Balanced parametrization of classes of linear systems

Canonical forms and parametrizations are presented for several sets of minimal systems of given dimension: asymptotically stable systems, allpass systems, bounded real systems, positive real systems, minimum-phase systems, and the class of all minimal systems. The approach is based on balancing techniques for these classes of systems. Applications of these results to Hankel operators and model reduction are discussed.
Real-time Architecture for Audio-Visual Active Speaker Detection

Continuously measuring the speaking state of users with robot in a human-robot Interaction(HRI) system improves metrics of interaction quality. Meanwhile, mainstream active speaker detection (ASD) algorithms emphasize achieving high AUCs at frame level in the AVA-Active Speaker dataset and pay less attention to get real-time performance in robotic systems. In this paper, we propose a model named FSDNet to keep a high AUC score in the AVA-Active Speaker dataset while reducing time cost, our model increase AUC score by 0.1% compared with the State-Of-The-Art and need only 75% running time. Furthermore, we put forward an architecture with a time-related prediction function to make our algorithm more effective and generative in interactive robotic systems. The code is released at https://github.com/huangmin9966/FSDNet_RealTimeArch.
5G Antenna with Hemispherical Coverage for AR Glasses

This paper presents a novel approach for the development of compact 360° scanning antennas. The proposed antenna represents a cylindrical end-fire antenna array designed for 57-71GHz frequency range. In combination with an advanced approach of non-galvanic interconnection, this antenna provides a hemispherical coverage using a minimum number of active RF channels with no additional switching components. This is strongly required, for example, for AR Glasses and can be used in other devices, including embedded in the vehicle, operated in 5G, Beyond 5G, WiGig and 6G. Concept is successfully verified in the experiments.
Unsteady attached cavitation on an oscillating hydrofoil

A series of visualizations of non-cavitating and cavitating unsteady flows around an oscillating hydrofoil has been carried out in order to investigate the effect of unsteadiness on attached cavitation. The major conclusion of the present experimental analysis is that the strong interaction that was previously pointed out in the case of steady cavitation between an attached cavity and the boundary layer which develops upstream cavity detachment, still plays a prominent role in unsteady cavitation. We propose to generalize for the case of unsteady attached cavitation the two following points which were initially established under steady conditions and which constitute a cavitation detachment criterion: a cavity detaches behind laminar separtion of the boundary layer; transition to turbulence sweeps away an attached cavity.
Exploiting Honeypot for Cryptojacking: The other side of the story of honeypot deployment

Honeypots are a proactive mechanism to lure attackers into a pretentious setup. Until recently, honeypots have been applauded for discovering new attacks, attacker behavior patterns, and other findings related to the defensive mechanism. However, the presented work discussed how attackers could turn the honeypot mechanism into an offensive tool. The results are gathered from Cowrie - an open-source honeypot setup. The script is written to read commands executed by attackers from the Cowrie play log. In addition, the attack analysis documented attempts made by attackers to use honeypot resources for crypto mining. Along with exposing crypto-mining attempts made by attackers, the authors further analysed the log with custom written malware parser and IP address parser. The malware parser analysed details from all the files generated by the malware scanner. In addition, the IP parser did IP backtracing by analysing IPs in harmless, suspicious, and malicious categories.
A Delay Matching Technique for Relative Deterministic Jitter Reduction in 28GHz ADPLL

A technique for relative deterministic jitter (DJ) reduction in 28GHz all digital phase-locked loops (ADPLL) is proposed. The reference clock path and feedback clock path of the ADPLL are optimized in 28nm CMOS Technology, especially for CML-to-CMOS circuit, and a delay matching technique is realized to reduce the relative DJ caused by power supply noise between the two input signals of the phase frequency detector (PFD). The frequency of reference clock is 250MHz, while the output clock of ADPLL is 28GHz. The simulation results show that the relative DJ between the two input signals of the PFD is reduced from 1.71ps to 110fs after delay matching.
Generalized discriminant analysis based on distances

This paper describes a method of generalized discriminant analysis based on a dissimilarity matrix to test for differences in a priori groups of multivariate observations. Use of classical multidimensional scaling produces a low‐dimensional representation of the data for which Euclidean distances approximate the original dissimilarities. The resulting scores are then analysed using discriminant analysis, giving tests based on the canonical correlations. The asymptotic distributions of these statistics under permutations of the observations are shown to be invariant to changes in the distributions of the original variables, unlike the distributions of the multi‐response permutation test statistics which have been considered by other workers for testing differences among groups. This canonical method is applied to multivariate fish assemblage data, with Monte Carlo simulations to make power comparisons and to compare theoretical results and empirical distributions. The paper proposes classification based on distances. Error rates are estimated using cross‐validation.
Low complexity, diversity preserving hard decision decoder for CRC codes with IoT applications

As Cyclic Redundancy Check (CRC) codes offer the advantages of low power transmission and variable payload length, they have found applications in IoT standards like IEEE 802.15. 4 and Bluetooth low energy (BLE). Despite having redundant bits, CRC codes are merely used as error-detecting codes due to the unavailability of a suitable decoder. Several efforts have been made to design a decoder for CRC to use as error-correcting code. The recently proposed GRAND algorithm serves as an error-correcting algorithm for CRC but has huge complexity. In this paper, a low complexity hard decision decoder is proposed for CRC with $g(x)=1+x^{5}+x^{12}+x^{16}$ which is used in IEEE 802.15. 4 for IoT applications. The proposed decoder utilizes channel state information (CSI) for decoding in a Rayleigh fading channel and attained fourth-order diversity with very low complexity. The proposed decoder is especially effective at short block lengths; hence it serves as a sound decoder catering to IoT and URLLC services.
Fabrication and characterization of ultraviolet-emitting diodes composed of transparent p-n heterojunction, p-SrCu2O2 and n-ZnO

An ultraviolet light-emitting diode (UV-LED) was realized using a p-n heterojunction composed of the transparent oxide semiconductors p-SrCu2O2 and n-ZnO. A Ni/SrCu2O2/ZnO/ITO multilayered film was epitaxially grown on an extremely flat YSZ (111) surface by a pulsed-laser deposition technique. SrCu2O2 (112) was preferentially grown on ZnO (0001) at 350°C, while the preferential plane was changed into the (100) when the temperature was increased to 600 °C. The grown films were processed by conventional photolithography followed by reactive ion etching to fabricate heterojunction diodes. The resulting devices exhibited rectifying I-V characteristics inherent to p-n junctions. A relatively sharp electroluminescence band centered at 382 nm, attributed to transitions associated with exciton-exciton collision or electron-hole plasma in ZnO, was generated by applying a forward bias voltage greater than the turn-on voltage of 3 V. UV-LED performance characteristics such as threshold current and conversion efficie.
Galaxy groups: abundance by luminosity and by velocity dispersion

We present a reanalysis of groups in the Center for Astrophysics redshift survey, focusing on properties that can be readily compared with predictions of gravitational clustering theories. The grouping algorithm we employ is optimized using artificial catalogues constructed from N-body simulations that have similar low-order correlations to those of the original survey. We develop a method for estimation of the total luminosity of groups identified in magnitude-limited galaxy surveys, and use it to derive a luminosity function of galactic systems. This statistic measures the abundance of gravitationally bound structures as a function of their luminosity, independently of the detailed arrangement of the luminous material within them
Buffer Allocation for Exposed Datapath Architectures

Concurrent access to a given number of registers limits the instruction-level parallelism (ILP) used by conventional processors despite the use of many processing units (PUs). Many recent architectures expose their internal datapaths to compilers, allowing the compiler to move intermediate values from program execution directly between PUs, thus bypassing the use of registers. Buffered exposed datapath (BED) architectures additionally implement these inter-PU communication paths with scalable first-in-first-out (FIFO) buffers to avoid the use of registers and to prevent unnecessary synchronization between PUs. However, the BED compiler must ensure that the creation order of intermediate values in a buffer matches their consumption order so that the next executing instructions always find their operands at the heads of the corresponding buffers. In this paper, we present a novel buffer interference analysis that determines a criterion for allocating multiple program variables to the same buffer based on a given instruction schedule that specifies an access order for those variables. We then use the well-known dataflow analysis framework to compute a buffer interference graph whose coloring yields a valid buffer allocation for programs by considering the instructions in the given order. Preliminary experimental results show the effectiveness of our code generation approach compared to traditional register-based compilation. More importantly, the buffer interference graph should serve as the basis for future buffer allocation schemes that maximize ILP usage.
Level Control of a Conical Tank System Using Switched Fractional Order PI Controllers: An Experimental Application

This paper presents the design, tuning, validation and implementation at experimental level of switched fractional order proportional integral (PI) controllers for the level control of a conical tank system. The controller switches among a fractional order PI controller and an integer order PI controller, according to the control error level. Parameters of the switching strategy are tuned using particle swarm optimization. Results at simulation and experimental level show that switched controllers allow obtaining a best combination of controlled system behavior and control energy used, compared to the non switched strategies. Also, switched controllers present lower variance of the controlled variable at experimental level.
Design and implementation of vehicle oil online information monitoring system

With the popularization and application of vehicles, the safety of automobiles has gradually attracted widespread attention, among which the quality of oil is an important factor affecting vehicle safety. Nowadays, the monitoring and evaluation of oil is divided into offline and online ways. This paper is aimed at the application of obtaining and analyzing oil quality in real time for vehicles. And based on the online monitoring method, this paper designed and implemented a vehicle oil information monitoring system. In the system, hardware acquisition part consists of oil sensors and self-made STM32 board, and host computer monitoring software as an analysis display part. After experimental testing, the system can conduct online monitoring, early warning and evaluation of the dielectric constant, viscosity, water content, water activity, density and temperature indicators of oil, and can predict the soot content and diesel content with the given model, and can calculate the $100^{\circ}\mathrm{C}$ kinematic viscosity using the least squares fitting algorithm. The accuracy and measurement range of the system depend on the indicators of the oil sensors. This vehicle oil information monitoring system is conducive to collecting the actual parameters of vehicle oil operation and providing a reliable basis for vehicle safety maintenance.
Impacts of Obstacles and Jittering on Coverage and Throughput Performance of Large-Scale UAV Networks

Unmanned aerial vehicle (UAV) communications have been recognized as an important component of future wireless networks, due to the UAVs’ inherent maneuverability and flexibility. However, ultra-dense located buildings and the jittering of the UAVs may significantly degrade the performance of UAV wireless networks. Against this backdrop, this paper analyzes the coverage and throughput performance of three-dimensional UAV networks, taking the probabilistic line-of-sight (LoS) channel and the outdated channel state information introduced by the obstacles and the UAVs’ jittering, respectively, into account. By leveraging the tools from stochastic geometry, the analytical expressions for the coverage probability and throughput in large-scale UAV networks are derived. Through numerical results, the correctness of our derived expressions is validated. In addition, it is shown that the coverage probability and throughput performance of the considered UAV networks can be significantly improved by judiciously selecting the deployment density of the UAVs, even in the presence of blockage and jittering. The results presented in this work provide valuable insights into the design and deployment of large-scale UAV networks in practical implementations.
Systematic Review of Machine Learning Methods in Customer Satisfaction Prediction

Customer satisfaction is the key of a successful modern business. So customer satisfaction prediction becomes an important mission in Business Intelligence. Based on various studies on customer satisfaction research on different types of businesses, We reviewed machine learning methods used in these papers. The results show that customer satisfaction prediction can be analysed by different typical algorithms of machine learning. Due to the difference between data formats (such as review data or survey data), different models should be recommended respectively for different application fields.
Magnetic Field Active Canceling Single-Circuit System for Old Residential One-Story Buildings Closed to Double-Circuit Overhead Power Lines

First design and study effectiveness reducing magnetic field level double-circuit power lines in residential old one-story buildings using a single-circuit active canceling system with one compensation winding is conducted. During the design of an active shielding system, the geometric dimensions and spatial arrangement of the compensation winding are determined, as well as the phase shift and the magnitude of the current in the compensation winding. The design reduced to computing vector game solution, in which the game payoff vector calculated based on the Biot-Savart law. The game solution calculated based on multi-swarm stochastic multi-agent optimization algorithms. The results of modeling and experimental study of magnetic field level reducing effectiveness generated by double-circuit power lines in residential old one-story buildings, using a single-circuit active canceling system with one compensation winding are considered.
A Multi-stage Precision Landing Method for Autonomous eVTOL Based on Multi-marker Joint Localization

Electric vertical takeoff and landing aircraft (eVTOL) has drawn more and more attention from home and abroad in recent years. It is believed autonomous eVTOL will create a new era of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM). To autonomous eVTOL, precision landing is an extremely critical operation for it directly affects flight safety. In this paper, we analyze the special issues an eVTOL will encounter when it lands in the UAM applications. A multi-stage precision landing method based on multi-marker joint localization is proposed accordingly. Our method contains three key elements: a compatible vertiport with multiple visual markers; an accurate, fast detection and localization algorithm for the vertiport and a multi-stage landing strategy. We implement our method on an eVTOL prototype named ZJ-Copter developed by Zhejiang Lab. A series of real-world experiments have been conducted to validate the effectiveness and accuracy of the proposed method. Experiment results show that our method works well in real-world scenarios for autonomous eVTOL without GPS signal during landing process. The positioning accuracy is less than 0.1m (altitude $< \mathbf{10}\mathbf{m}$), while the landing accuracy is less than 0.5m.