Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Spatio-Temporal 3D Convolutional Encoder-Decoder Network for Dynamic Saliency Prediction

As human beings are living in an always changing environment, predicting saliency maps from dynamic visual stimulus is of importance for modeling human visual system. Compared with human behavior, recent models based on LSTM and 3DCNN are still not good enough due to the limitation in spatio-temporal feature representation. In this paper, a novel 3D convolutional encoder-decoder architecture is proposed for saliency prediction on dynamic scenes. The encoder consists of two subnetworks to extract both spatial and temporal features in parallel with intermediate fusion, respectively. The saliency map is produced in decoder by firstly enlarging features in spatial dimensions and then aggregating temporal information. Specially designed structures can transfer pooling indices from encoder to decoder, which helps the generation of location-aware saliency maps. The proposed network can be trained and inferred in an end-to-end manner. Experimental results on benchmark DHF1K show that the proposed model achieves the state-of-the-art performance on key metrics including both normalized scanpath saliency and Pearson’s correlation coefficient.
Yb-doped F-rich aluminophosphosilicate LMA-25/400-YDF laser fiber with high efficiency and excellent stability

Yb-doped F-rich aluminophosphosilicate LMA-25/400-YDF laser fiber was fabricated by chelate precursor doping technique. 3.03 kW@1080nm laser output was achieved in an oscillator configuration with an optical-to-optical efficiency of 71.5% and shown excellent stability. © 2020 The Author(s)
Research on Logistics Relevance for SMEs in Context of Organization Size, Costs and Outsourcing Level

The main objective of this research is to empirically verify working hypotheses on logistics role in the SMEs context. The survey was conducted among small and medium-sized business units in Bulgaria. The statistical calculations demonstrated that the conducted testing methodology is reliable in terms of selected variables and conceptual model. The main analysis factors were properly evaluated and indicate validity for further research. The tests evidenced that the developed linear regression model is statistically significant and it can be used to evaluate the influence of the analysis factors on role and relevance of the logistics for Bulgarian SMEs.
A Compact Conical Shape Patch Antenna for Micro-Wave and Millimeter-Wave Applications

In this paper, a compact, simple, high performance multi-band antenna is presented for WLAN and millimeter-wave applications. As compared to the available reported designs the proposed antenna has improved characteristics in terms of size, bandwidth and multiband operation. Rogers RT5880 substrate is used for designing of the proposed antenna with microstrip feeding. The overall dimension of the designed antenna is 30*30*0.5 mm3which is smaller than (0.35λ*0.35λ) at its lowest frequency of operation i.e., 2.4 GHz. According to the criteria of -10 dB matching bandwidth the designed antenna resonating at three different frequency bands in both microwave band and millime-ter-wave band which are (2.45 GHz - 2.495 GHz), (5 GHz - 6.3 GHz) and (23 GHz - 28 GHz). The antenna gives gain of 1.5 dBi, 3.58 dBi, 4.42 dBi and 4.79 dBi at 2.4 GHz, 5.2 GHz, 5.8 GHz and 27.5 GHz respectively. The reduced size, simple design, multiband operation and high bandwidth are some of the advantages of the proposed antenna over the available designs which make it an ideal candidate for WLAN and millimeter-wave applications.
Analysis on the Applications of AI in Vehicles and the Expectation for Future

Vehicles have become one of the most popular transportation tools. More and more vehicles occur with different AI-based systems. In order to make this mainstream transportation more comfortable, efficient, and safer for people to use, artificial intelligence technologies are applied in vehicles, leading vehicles to become much smarter and intelligent. In this paper, three main applications of AI in vehicles including the AI in Vehicle-to-Everything(V2X), AI in the vehicle control system, and AI diagnostic device for vehicles will be shown. The current technical issues when applying AI in V2X and challenges for all the AI application have to overcome. This article also analyzes the future expectations for the improvement of the application of AI in vehicles.
Augmented reality for assist apron operation safety supervisor in aircraft inspection processes

With the development of aviation, the issue of aviation safety is become more and more important. Especially for airplane maintenance and inspection task. As processes in the aircraft inspection after the plane take off are error prone and time consuming, efforts are made to implement these technologies to support apron operation safety supervisors during the inspection process. In this paper, we will show a concept to facilitate efficiency of assisting airport supervisor in aircraft inspection process. We propose a graphical user interface that contain the menu-guided instructions and digital inspection document, which will increase the efficiency of manual process. Furthermore, in order to help supervisor have an better understanding of inspecting processes, by attaching the 3D model of aircraft physical components, they can see corresponding hint information. Seeing instructional graphics overlaid directly on the actual task environment can significantly improve a user’s understanding compared to viewing instructions displayed on a nearby monitor or in a paper manual. In order to get the better view display effect, we used the one of the most advanced Augmented Reality (AR) glasses, the Microsoft Hololens2. In the inspector’s views, the part of airplane’s 3D model will immediately overlaid on the physical component. This Augment Reality Vision can be used for inspection purpose. And any inspection relate information can be directly attached to the aircraft component. For example, following the instruction, 3D model animation and inspection guide document information will appear on the aircraft component’s surface, which will improve the efficiency of inspection process. In addition, remote collaboration is discussed applying augmented reality devices in an inspection process, which will ensure inspector and expert has same vision in different site, that can improve the efficiency of dealing complicate problem.
6.5 A 3dB-NF 160MHz-RF-BW Blocker-Tolerant Receiver with Third-Order Filtering for 5G NR Applications

The introduction of the fifth-generation (5G) New Radio (NR) standard has imposed several challenges in the design of sub-6GHz receivers (RX). Firstly, the maximum channel bandwidth(2BW) increases to 100MHz, while a -15dBm continuous-wave (CW) blocker can be located only $\Delta$ f=85MHz away from the desired band edge. Such a small $\Delta$ f/BW($\sim$2) places a stringent linearity requirement on an RX, thus demanding the use of higher-order filtering. Secondly, in-band (IB) linearity also becomes critical, since the band of interest may contain many signals resulting from carrier aggregation and digital beamforming 0peration. Finally, a sub-3dB noise Figure (NF) is required to achieve the highest possible link budget, which allows to maximize the spectral efficiency and data rate.
Reduced-Length Tandem Directional Couplers Composed of Coupled-Line Sections With Fixed Coupling Coefficient

A novel concept of tandem coupled-line directional couplers has been proposed. The proposed couplers consist of coupled-line sections having different electrical lengths and fixed identical coupling coefficients regardless of the required nominal coupling of the entire tandem coupler. It is proved that the available coupling in coupled-line sections constituting tandem directional couplers can be used for overall electrical length reduction of the entire network. As shown, this allows not only for reduction of the circuit’s size but also enables flexible design of such couplers, since tuning of the coupling characteristics can be easily achieved by change in solely electrical lengths of the coupled sections with no change in their coupling coefficients. The thorough theoretical investigation has been presented of such tandem couplers composed of two and three coupled-line sections having fixed coupling coefficients followed by measurements of four manufactured networks operating at a center frequency of 2 GHz.
A 140GHz Power Amplifier in 0.13μm SiGe HBT technology

A 3-stage, 4-way D-band single-ended cascode power amplifier (PA) in a 130nm SiGe BiCMOS process is designed and simulated. In order to reduce the loss, microstrip lines is used to divide and combine the output power. T-matching with higher isolation is adopted in inter-stage matching. The post-simulation results show that the PA has an saturation output power of 9.6dBm at 140 GHz. The small signal gain is 12dB and the supply voltage is 3 V. The peak power added efficiency (PAE) is 2.5% in D-band. The chip size is 0.71 mm2 (0.36 mm2without pads).
Application of U-Net Based Multiparameter Magnetic Resonance Image Fusion in the Diagnosis of Prostate Cancer

Medical image fusion technology has been widely used in clinical practice by doctors to better understand lesion regions through the fusion of multiparametric medical images. This paper proposes an automated fusion method based on a U-Net. Through neural network learning, a weight distribution is generated based on the relationship between the image feature information and the multifocus training target. The MRI image pair of prostate cancer (axial T2-weighted and ADC map) is fused using a strategy based on local similarity and Gaussian pyramid transformation. Experimental results show that the fusion method can enhance the appearance of prostate cancer in terms of both visual quality and objective evaluation.
A Dual Frequency Tuning Method for Improved Coupling Tolerance of Wireless Power Transfer System

This letter proposes a dual-frequency tuning method for improved coupling tolerance of an inductively coupled wireless power transfer (WPT) system by exploiting the fundamental and third-order harmonic components of a square-wave voltage out of a full-bridge inverter. A dual-frequency hybrid compensation topology is designed to simultaneously utilize the characteristics of series-series (SS) and LCL-S networks under the two different frequencies. Consequently, the output power of the proposed system under a fixed load is maintained approximately constant against coupling variations. A practical hybrid WPT system with a 100 kHz square-wave excitation and a 10.5 Ω resistive load is built to verify the theoretical modeling and analysis. Experimental results show that the system achieves an approximately constant output voltage and power of around 39 V and 150 W against a coupling coefficient variation from 0.52 to 0.72, with maximum fluctuations less than 5% and 10%, respectively.
Three-Dimensional Split-Ring Resonators-Based Sensors for Fluid Detection

This paper presents a sensitive microwave near-field sensor based on utilizing a three-dimensional capacitor within a planar split-ring resonator. The planar resonator is etched in the ground plane of a microstrip line, where the resonator’s length is relatively smaller than the guided wavelength. The sensor was fabricated utilizing PCB technology and used to detect the presence of dielectric fluids. The numerical analysis shows that the three-dimensional capacitor significantly enhances the electric field in the sensing area (free space) leading to an increase in the sensitivity. The electric field enhancement was quantitatively investigated using numerical analysis. The analysis shows that a loaded-quality factor of 1556 can be achieved using a three-dimensional capacitor with a length of 29 mm, which is significantly higher than what can be achieved by using planar resonators working in the same range of frequency. In addition, the utilization of the high-dielectric substrate can enhance coupling to the resonator. The proposed sensor was experimentally tested on two fluids, chloroform and dichloromethane with the relative permittivity of 4.81 and 8.93, respectively. The proposed sensor shows higher sensitivity of 700% and 374.5% in detecting the presence of chloroform and dichloromethane, respectively. Furthermore, the proposed sensor was utilized to detect the changes in fluid levels.
Lidar Boosts 3D Ecological Observations and Modelings: A Review and Perspective

The advent of lidar has revolutionized the way we observe and measure vegetation structure from the ground and from above and represents a major advance toward the quantification of 3D ecological observations. Developments in lidar hardware systems and data processing algorithms have greatly improved the accessibility and ease of use of lidar observations in ecological studies. A wide range of studies has been devoted to accurately measuring and modeling vegetation structural and functional attributes from lidar data across a range of spatial scales (from individual organs to global scales) and ecosystem types (e.g., forest, agricultural, grassland, and urban ecosystems).
Research on Modeling of Power Grid Information System Based on Knowledge Graph

The knowledge graph is a relatively general formal representation framework for semantic knowledge, with rich semantic expression and open interconnection capabilities. Aiming at the data model in the power grid field, the paper proposes a model diagnosis method based on the knowledge graph by treating the data model as an entity in the knowledge graph, combining semantic analysis technology and entity similarity calculation technology, the compliance of the data model and consistency for diagnosis. Research shows that this method can make fuller use of the data model’s relevant information and expand the thinking for traditional diagnosis methods.
Evolutionary Random Access Game With Objective and Subjective Players

We consider an evolutionary game on a graph under the condition that players perception of uncertainty and decision making can follow either an objective expected utility theory (EUT) model or a subjective prospect theory (PT) model. Each player chooses one of two strategies with probabilities <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$1-x$ </tex-math></inline-formula>, where the subjective players bias their choices of the probabilities to be <inline-formula> <tex-math notation="LaTeX">$w(x)$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$w(1-x)$ </tex-math></inline-formula> to reflect the probability weighting effect of PT. We derive the conditions to achieve a locally asymptotically stable Nash equilibrium (NE) and the necessary conditions to achieve an evolutionary stable strategy (ESS). We illustrate these results through a simple random access channel game. We find that players’ behavior is affected by the total number of players as well as the number of each type of players (objective or subjective). We show that increasing the number of interacting players induces an aggressive transmission strategy and the behavior becomes similar for both types of players. Moreover, we let the objective and subjective players adjust their transmission under throughput rewards, delay penalties, and energy costs. The EUT players’ throughput is higher than the PT players’ throughput for a small number of interacting players and equal to if the number of interacting players increases.
A Novel Predictive-Collaborative-Replacement (PCR) Intelligent Caching Scheme for Multi-Access Edge Computing

Multi-Access Mobile Edge Computing (MEC) is proclaimed as a key technology for reducing service processing delays in 5G networks. One of the use cases in MEC is content caching as a way of bringing resources closer to the end-users. Consequently, both latency and QoE are reduced. However, MEC has a limited storage space compared to the cloud. Therefore, there is a need to effectively manage the cache storage. This article proposes and evaluates a novel scheme (PCR) that combines proactive prediction, collaboration among MECs and replacement algorithm to manage content caching in MEC. Results show that the proposed replacement scheme outperforms conventional baseline content caching algorithms LFU, LRU, MQ, FBR, LFRU. This has been validated with experimental results using a real dataset (MovieLens20M dataset) and comparison with contemporary Long Short Term Memory (LSTM) based caching algorithm.
Heterogeneous Wet Chemical Synthesis of Superlattice-Type Hierarchical ZnO Architectures for Concurrent H2 Production and N2 Reduction

Two wet chemical methods, namely, wet etching (heterogeneous) and chemical precipitation (homogeneous), have been exploited for the formation of hierarchical ZnO architectures without any specific templates, catalysts, or capping agents. As-synthesized ZnO have been extensively characterized by X-ray diffraction, UV−visible absorbance studies, Fourier transform infrared analysis, scanning electron microscopy, high-resolution transmission electron microscopy, energy-dispersive analysis of X-rays, selected area electron diffraction, photoluminescence (PL), and textural analysis. Wet etching resulted in the formation of self-assembled hexagonal plates with a disordered superlattice-type texture and ultimately ended up in crystallites with high-defect concentration showing a red PL emission. Mechanistic aspects of the growth process in both the methods have been analyzed, and a rational explanation is presented for their observed morphologies. ZnO prepared by both methods have been tested for their photocatal.
Multifractal Texture Analysis of Salivary Fern Pattern for Oral Pre-Cancers and Cancer Assessment

Saliva has emerged as an efficient screening sample for early stage detection of oral cancer (OC) owing to non-invasiveness coupled with high sensitivity and specificity. Although spectroscopic characterization of saliva in oral potentially malignant disorders OPMDs) and OC is extensively studied, its potential as imaging biomarker is sparsely explored. Further, the literature on crystalline pattern of saliva for other diseases or different physiological conditions is mostly qualitative. This paper proposed multifractal based methodology to quantitatively study alteration of the salivary fern pattern in different OPMDs and OC in relation to normal counterpart. The fern pattern of dried saliva is captured by stereo-zoom microscope in reflective mode and an image dataset is developed. We resort to two dimensional multi-fractal detrended fluctuation analysis (2d MFDFA) to elucidate the complexity and heterogeneity of these micro-structured patterns. Existence of multifractal nature embedded in salivary fern has been validated for the first time. Long range spatial correlation is found to be the origin of multifractality. Variation in multi-scale self-similarity of irregular pattern in different study groups is demonstrated by four features extracted from MFDFA. Statistical analysis shows discriminating nature of these features for combinations of pairwise interclass classification. This study sheds light on acceptability of microscopic images of arborized saliva in fast and cost effective screening of different oral lesions.
Variation-Aware SRAM Cell Optimization Using Deep Neural Network-Based Sensitivity Analysis

Under process, voltage, and temperature variations, SRAM cell stability largely fluctuates from the nominal value. In the design step, SRAM cell optimization while ignoring the fluctuation induces the yield loss for the stability. Variation-aware optimization of an SRAM cell can prevent the yield loss problem by considering the mean and variance of SRAM cell stability when finding optimal design parameters. This paper proposes a novel SRAM optimization method that uses a deep neural network (DNN). Multiple DNNs from ensemble techniques represent the mean and variance of SRAM cell stability for the nominal design parameters. Subsequent sensitivity analysis of DNN extracts the <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> design parameters that have the most dominant effects on the mean and variance of SRAM cell stability. Then multidimensional optimization is used to find the optimal values of these <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> parameters to maximize the mean stability while minimizing its variance. The proposed method achieved an average of 2% error compared to MC simulation. The proposed optimization method takes only 561 s to provide the most optimal design parameter values of an SRAM cell.
An Impedance Decoupling-Based Tuning Scheme for Wireless Power Transfer System Under Dual-Side Capacitance Drift

High performance of a wireless power transfer system is related to the resonance. However, the capacitance drift caused by temperature variation leads to detuning. In this article, a tuning scheme against dual-side capacitance drift using the impedance decoupling algorithm is investigated. First, the impact of the capacitance drift on transmission efficiency and output power are analyzed. Second, it is difficult to compensate for the dual-side capacitance drift quickly since the primary and secondary sides are coupled. Therefore, the impedance decoupling algorithm is introduced. The primary and secondary reactances are decoupled from the total impedance. The two independent reactances are only determined by the capacitance drift of the corresponding side. Then, by adjusting system frequency and the phase-shift angle of the semiactive rectifier, the reactances of both sides can be eliminated, respectively. Compared with the existing tuning methods focusing on total input impedance, the continuous adjustment on two sides is avoided, so the tuning time is significantly reduced. The experimental results prove that the proposed method can improve the system efficiency by 5%–40% and reduce the tuning time by 67% under different capacitance drift.
Pulsed-Power Load Monitoring for an All-Electric Ship: Utilizing the Fourier Transform Data-Driven Deep Learning Approach

Future Naval Advanced Weapon and sensor loads require high power density power electronic distribution systems (PEDs) to be viable. The mission-defined electronic loads, such as advanced radar and pulsed-power weapons, tend to have an irregular power draw, consume a significant amount of power, and would require significant additional generation equipment well beyond the existing power system. A legacy low-voltage ac power grid on a destroyer is already at capacity and because space is at a premium, it is unlikely that any new power-hungry pulse load could be included without a significant paradigm shift. Furthermore, most of the potential power within the vessel is locked to the mechanical drive system and not readily usable as electrical power. As such, the all-electric ship is the intended option to unlock the mechanical power for various high power pulse loads.