Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental study on collision avoidance procedures for plastic waste cleaner USV

Sea plastic waste is a big issue and cleaning them is very important. We are developing a USV cleaner that collects plastic waste for cleaning at the port. There are many ships in the port and the USV needs to design a collision avoidance procedure appropriately. To develop a collision avoidance procedure, several experiments must be performed. In this paper, we will first introduce a low-cost tank experiment system to study USV collision avoidance procedures. This system consists of a ceiling camera and a robotic ship. The ceiling camera is installed above the tank and uses image processing to calculate the heading and COG coordinates of each ship. This is intended to emulate GNSS indoors. The catamaran was designed and manufactured using a 3D printer, taking into account the size of the tank and the capacity of the ship. The catamaran has a single board computer and a wireless communication device. Each ship receives coordinates via wireless communication from a computer that calculates the coordinates in the tank. Next, the results of tank experiments using the above system are introduced. When the experiment starts, the ceiling camera calculates the ship's position and sends the position data to each ship in increments of 10 [Hz]. When the ship receives the position, it moves forward while maintaining the bow and speed until a collision is detected. When each ship finds a possible collision, it changes the navigation mode from normal mode to collision avoidance mode. This experiment confirmed that the ceiling camera position detection, catamaran thrust, and wireless communication were all functioning properly. Finally, we introduce the conceptual design of the Catamaran USV used to clean plastic waste in port areas.
Design of a Printed Broadband Cross-Dipole Antenna

A broadband dual-polarized antenna fed by 50 ohm microstrip line is presented in this letter. The proposed antenna consists of four patches, two short pins and two feed structures. When two patches excite one polarized wave, the other patches are working as a parasitic structure. By the introduce of the short pins as a compensating component, the isolation and the cross polarization of the purposed antenna is improved. The proposed antenna achieves a 35.4% (3.9-5.6 GHz) relative bandwidth is achieved. Normalized cross polarization level is lower than -30 dB and isolation between ports is higher than 27 dB.
Kubestorage: A Cloud Native Storage Engine for Massive Small Files

Cloud Native, the emerging computing infrastructure has become a new trend for cloud computing, especially after the development of containerization technology such as docker and LXD, and the orchestration system for them like Kubernetes and Swarm. With the growing popularity of Cloud Native, the following problems have been raised: (i) most Cloud Native applications were designed for making full use of the cloud platform, but their file storage has not been completely optimized for adapting it. (ii) the traditional file system is designed as a utility for storing and retrieving files, usually built into the kernel of the operating systems. But when placing it to a large-scale condition, like a network storage server shared by thousands of computing instances, and stores millions of files, it will be slow and even unstable. (iii) most storage solutions use metadata for faster tracking of files, but the metadata itself will take up a lot of space, and the capacity of it is usually limited. If the file system store metadata directly into hard disk without caching, the tracking of massive small files will be a lot slower. (iv) The traditional object storage solution can't provide enough features to make itself more practical on the cloud such as caching and auto replication. This paper proposes a new storage engine based on the well-known Haystack storage engine, optimized in terms of service discovery and Automated fault tolerance, make it more suitable for Cloud Native infrastructure, deployment and applications. We use the object storage model to solve the large and high-frequency file storage needs, offering a simple and unified set of APIs for application to access. We also take advantage of Kubernetes' sophisticated and automated toolchains to make cloud storage easier to deploy, more flexible to scale, and more stable to run.
A Decoupling Method for Two PIFAs by Using Bridged Two Parasitic Elements

In this study, we investigate a simple method to reduce the mutual coupling between two planar inverted-F antennas (PIFAs). The method shows that by using a parasitic element (PE) which is linked with a bridge line (BL) and loaded upon the PIFAs, good impedance matching and low mutual coupling around resonant frequency can be obtained without the necessity of adjusting dimensions of the PIFAs. This method is also expected to be an effective method to reduce mutual coupling of the larger PIFA arrays in future works.
Research and Analysis of User Behavior Fingerprint on Security Situational Awareness Based on DNS Log

Before accessing Internet websites or applications, network users first ask the Domain Name System (DNS) for the corresponding IP address, and then the user's browser or application accesses the required resources through the IP address. The server log of DNS keeps records of all users' requesting queries. This paper analyzes the user network accessing behavior by analyzing network DNS log in campus, constructing a behavior fingerprint model for each user. Different users and even same user's fingerprints in different periods can be used to determine whether the user's access is abnormal or safe, whether it is infected with malicious code. After detecting the behavior of abnormal user accessing, preventing the spread of viruses, Trojans, bots and attacks is made possible, which further assists the protection of users' network access security through corresponding techniques. Finally, analysis of user behavior fingerprints of campus network access is conducted.
Research on Social Network Inference Method Based on ConNIe Algorithm

In recent years, Internet technology and online social networks have developed rapidly, enabling people to express their opinions, ideas, emotional exchanges and economic exchanges randomly. Inferences about social networks are made possible by observational data exchanged by people on the Internet. In this paper, through the analysis of ConNIe algorithm, the effects of sparse parameter, propagation time distribution model and its parameters on the inferred results of this algorithm are studied. Then, based on the research, this paper use perceptron algorithm to classify the propagation time distribution model and use particle swarm optimization algorithm to optimize the sparse parameter and the parameters of propagation time distribution model. Finally, a social network inference framework based on ConNIe algorithm is proposed to make up for ConNIe. Some of the shortcomings of the algorithm have gotten over. The research in this paper helps people to understand the social network itself, and it has a wide range of practical value in the fields of social public opinion control and marketing.
Glide symmetries and their application for electromagnetic periodic structures

In this paper, we summarize the latest discoveries on glide symmetry for electromagnetic devices. Glide symmetries have demonstrated the ability to improve the response of conventional periodic structures. In particular, they have been proposed to increase the bandwidth and isotropy of unit cells, which can be used for lenses. Additionally, glide symmetry has been used to increase the bandwidth of electromagnetic band gaps, which can be used to produce filters, flange interconnections and gap waveguide technology. Recently, glide symmetries have also been proposed for reducing the size of Luneburg lenses based on transformation optics. In this specific case, unit cells possessing glide symmetry provide a broadband anisotropic response. Finally, glide symmetry has been employed to improve the radiation control in leaky-wave antennas and to reduce their cost of manufacturing. Due to the numerous examples of the virtues of glide symmetries for electromagnetic purposes, the number of investigations on the topic is increasing every year and new discoveries are continuously arising.
A Coordinated Path Planning Algorithm for Multi-Robot in Intelligent Warehouse*

In this paper, we study the coordinated path planning problem of multi-robot in intelligent warehouse. We first describe the problem of the multi-robot path planning and analyze the basic structure of the intelligent warehouse system. Then we discuss the adjustment of multi-robot path planning algorithm from two aspects. We reserve the path information of the continuous time period in the reservation table of the Windowed Hierarchical Cooperative A* (WHCA*) algorithm, and analyze whether to reuse the path information each time the algorithm is invoked. Then on the basis of this, we introduce the turning factor as a measure when expanding a path, and hope to find the path with fewer turns to reduce the travel time of the robot. Finally, we do some experiments and make the analysis. The results show that the methods we used can improve the path planning efficiency of the robot and increase the order throughput of the intelligent warehouse system.
Low Complexity Architecture of N-Path Mixers for Low Power Application

The complexity of harmonic rejection N-path mixer based receivers is studied in this paper. A solution to improve harmonic rejection without increasing the complexity is presented and compared with conventional LNA-first receivers. This solution is based on π-delayed driving signals that enable a N-path mixer to present the same harmonic rejection than its 2N-path counterparts while reducing by 2 the frequency of operation and showing a reduced number of differential gain stages and switches. A 5-path mixer is thus proposed. It allows rejecting up to the 8th harmonic with only 3 differential gain stages whereas only the 6th harmonic would be rejected with conventional topologies having the same number of amplifier stages.
A Coordinated Optimal Feedback Control of Distributed Generators for Mitigation of Motor Starting Voltage Sags in Distribution Networks

This article proposes a coordinated optimal feedback control approach to mitigate the induction motor starting voltage sag and support the transient restoration in distribution networks. The proposed technique is expected to reduce the starting high current to maintain the network voltage using neighboring voltage supporting distributed generation. An optimal feedback-based coordinated controller (CC) has been designed to estimate the reactive power to be injected at different locations of the network based on the motor loads. The CC on top of the existing local controller (LC) uses motor voltage feedback signals, thereby adjusting the reactive power support based on the voltage sag. The proposed voltage sag mitigation strategy is tested in both 12.4 kV network and 123 bus larger distribution networks containing single and multiple motor and distributed generation units. From simulation results, it is revealed that the proposed coordinated optimal feedback control of VSDGs can provide a fast restoration of the motor starting transient voltage dip.
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues

Following the success of deep learning in a wide range of applications, neural network-based machine-learning techniques have received interest as a means of accelerating magnetic resonance imaging (MRI). A number of ideas inspired by deeplearning techniques for computer vision and image processing have been successfully applied to nonlinear image reconstruction in the spirit of compressed sensing for both low-dose computed tomography and accelerated MRI. The additional integration of multicoil information to recover missing k-space lines in the MRI reconstruction process is studied less frequently, even though it is the de facto standard for the currently used accelerated MR acquisitions. This article provides an overview of the recent machine-learning approaches that have been proposed specifically for improving parallel imaging. A general background introduction to parallel MRI is given and structured around the classical view of image- and k-space-based methods. Linear and nonlinear methods are covered, followed by a discussion of the recent efforts to further improve parallel imaging using machine learning and, specifically, artificial neural networks. Image domain-based techniques that introduce improved regularizers are covered as well as k-space-based methods, where the focus is on better interpolation strategies using neural networks. Issues and open problems are discussed and recent efforts for producing open data sets and benchmarks for the community are examined.
Drone Detection with Linear Chirp Pulse Radar using Coherent Pulse Integration

This paper discusses the detection of small drone with linear chirp pulse radar system. The system employs 14.1GHz as RF center frequency with bandwidth 200MHz to cover Linear Chirp Pulse (LCP) whose chirp rate is 80MHz. The LCP is radiated and received through quasi-monostatic antennas with the gain of 16dBi. The system also includes digital down converter to obtain IQ signal from LCP received at RX antenna. Finally, Matched filtering of the LCP is performed to maximize the SNR of the signal reflected from the drone. In the actual performance measurement, the drone signal was detected up to 400m distance in real-time using Coherent Pulse Integration (CPI). The raw data is obtained as csv file and then later processed with MATLAB.
Design of a Morphable Multirotor Aerial-Aquatic Vehicle

The design of any aerial-aquatic vehicle faces the unique challenge of vastly different fluid dynamics of air and water. Due to the demands of aerial propulsion, most existing solutions are fundamentally aerial vehicles with an auxiliary capability to operate underwater. Instead of using standard aerial platforms directly, we propose a novel morphable design for a multirotor-based vehicle inspired by the thruster layouts of regular aerial quadrotors and underwater remotely operated vehicles (ROVs). By adding the ability to rotate each motor about its respective arm, the proposed mechanical linkage allows for direct actuation in all six translation and rotational directions. The proposed concept is demonstrated in a proof of concept prototype and the details of the design and physical implementation are shown in this paper.
A 0.5-V 180-nm CMOS Switched-Capacitor Temperature Sensor with 319 nJ/measurement

In this paper an ultra-low-power switched-capacitor (SC) temperature sensor realized in a 180 nm CMOS process is introduced. The sensor is operational at supply voltages down to 0.5 V, equivalent to the threshold voltages of the available MOS transistors. Using bipolar transistors for reference and temperature dependent voltage generation in a SC band-gap core, the overall temperature sensor is formed by a combination of the band-gap with a time-discrete pseudo-differential single-slope analog-to-digital converter. The temperature sensor has a power consumption of 2.62 µW (4.56 µW) including all biasing and clock generation at supply voltages of 0.5 V (0.8 V), and achieves an estimated 3σ accuracy of 2.42°C (1.36°C) using a two-point trim for the temperature range of 10°C to 100°C (−20°C to 100°C). Besides the temperature sensing functionality, the presented circuitry additionally provides a 24 kHz clock signal and stable reference voltage for other circuit blocks.
A Trend Prediction Method for Failures Time Series Data by Exploring Singular Spectrum Analysis and Support Vector Machines Regression

Recently, reliability prediction problems have been sufficiently studied by applying various failures time series prediction models. However, these models' performance could easily reach the bottleneck on account of the noise interference of the failures data. This paper focuses on the trend component of failures time series data as we believe its noiseless curve will achieve better prediction results and help to provide scientific guidance for reliability activities. We propose a trend prediction method which mainly involves two steps, trend extraction by singular spectrum analysis (SSA) and noise test, and trend prediction by support vector machines regression (SVR). Moreover, we further develop a multi-layer grid search algorithm to obtain optimized parameters of SSA and SVR models. The performance of the proposed method is measured against other time series processing techniques such as seasonal-trend decomposition procedure based on loess (STL), Holt-Winters, autoregressive moving average (ARMA), multiple linear regression (MLR) and k-nearest neighbors (KNN). The comparison results indicate that the proposed method outperforms other techniques and can be utilized as a promising tool for failures time series trend prediction.
Service Function Chain Optimization Deployment Mechanism Based on Node and Link Influence

The deployment of the service function chain is usually restricted by network resources, better allocation of network resources can help improve the service capabilities of the entire network. In this paper, we believe that the cost of resource occupancy is related to the location of nodes and links. We first propose a way to calculate the cost which takes into account the influence and the reuse of network functions, and then an algorithm based on dynamic planning is proposed to find the deployment plan with the least cost. The simulation results show that our algorithm can make full use of network resources and can serve more network requests while ensuring high request acceptance rate.
Bundle Adjustment for Monocular Visual Odometry Based on Detections of Traffic Signs

The technology for simultaneous localization and mapping (SLAM) has been well investigated with the rising interest in autonomous driving. Visual odometry (VO) is a variation of SLAM without global consistency for estimating the position and orientation of the moving object through analyzing the image sequences captured by associated cameras. However, in the real-world applications, we are inevitably to experience drift error problem in the VO process due to the frame-by-frame pose estimation. The drift can be more severe for monocular VO compared with stereo matching. By jointly refining the camera poses via several local keyframes and the coordinate of 3D map points triangulated from extracted features, bundle adjustment (BA) can mitigate the drift error problem only to some extent. To further improve the performance, we introduce a traffic sign feature-based joint BA module to eliminate and relieve the incrementally accumulated pose errors. The continuously extracted traffic sign feature with standard size and planar information will provide powerful additional constraints for improving the VO estimation accuracy through BA. Our framework can collaborate well with existing VO systems, e.g., ORB-SLAM2, and the traffic sign feature can also be replaced with feature extracted from other size-known planar objects. Experimental results by applying our traffic sign feature-based BA module show an improved vehicular localization accuracy compared with the state-of-the-art baseline VO method.
Multiband UWB Antenna for On-Body Wireless Body Area Networks

Wireless Body Area Networks (WBAs an emerging technology due to its many possible applications in the society especially in the field of health monitoring. With the increase of communications standards utilizing the Ultra Wide Band (UWB), there tends to be interference on WBAN applications. In this work, a multiband antenna was implemented covering frequencies from 5.9 – 6.6 GHz and 8.45 – 9.25 GHz to minimize the interference caused by known standards. The designed antenna was able to achieve an S11 of less than −10 dB at the operating frequencies. It was also determined that placing a distance of at least 10mm between the designed antenna and human body phantom would substantially remove the degradation caused by the human body. The designed antenna is able to isolate the defined interferences by using multiple bands and allows more efficient usage of the UWB for on-body wireless body area networks.
A Novel F-shaped Hybrid Isolator Employed by Tx/Rx Antennas to Improve Antenna Performance

A novel F-shaped hybrid isolator is proposed to reduce mutual coupling between two horizontally polarized X-band Tx/Rx microstrip antennas. The proposed configuration is composed of EBG-mushroom structure and two F-shaped metallic walls on both sides of EBG structure. The EBG-mushroom structure is designed for suppressing the surface wave propagation between the Tx/Rx antennas. The novelty of the F-shaped metal wall lies in its improvement of antenna radiation characteristics. The isolation level and radiation pattern performance of the Tx/Rx antennas with the hybrid isolator is simulated and compared to other isolation methods applied. The obtained result shows a maximum increase of 44.4dB in the isolation level, and main lobe direction is modified, comparing with original Tx/Rx antennas.
Compact Antenna Using Novel Finger-Connected Interdigital Capacitor-Based Substrate Integrated Waveguide Cavity

A electrical small antenna using a novel finger-connected interdigital capacitor (FC-IDC), based on composite right/left handed (CRLH) unit cell, is proposed in this paper. The proposed CRLH antenna consists of a thin rectangle substrate integrated waveguide (SIW) cavity with the etched interdigital slot on the top metal surface and two etched slot rings on the bottom metal surface, which is fed by a grounded co-planar waveguide (GCPW). The interdigital slot acts as a series capacitor as well as a radiator leading to a CRLH antenna application. Compared to other conventional CRLH antenna, the proposed one has a lower -1st-order resonant mode. thus, the present design has a smaller electrical size. The results show that the antenna using a novel CRLH-TL unit cell based on FC-IDC achieves 30.5% reductions in operating frequencies compared with the conventional CRLH antennas with the same size. In addition, the novel designed antenna can be easily fabricated by printed circuit board technology, which is of important significance in the miniaturization of communication system.
Wetting of soap bubbles on soft elastomers with surface stress and gravity

Surface stress and gravitational force have significant effects on the deformation of soft elastomers. By considering surface stress and gravity of the soft elastomer, we study wetting behaviors of soap bubbles on a semi-space elastomer through the surface Green’s function method. The normal surface displacement of the elastomer caused by the surface tension and Laplace pressure is calculated. The normal surface displacement in the contact zone monotonously increases from the center to the triple line, and the contact zone is divided into concave zone and convex zone. The results show that surface stress and gravity have significant influence on the normal surface deformation caused by the wetting of the soap bubble. In general, surface stress and gravity suppress the amplitude of the normal surface displacement. With the increase of surface stress, the amplitude of the normal surface displacement in the concave and convex zones decreases. However, with the increase of gravity, the amplitude of the normal surface displacement in the concave zone decreases, while that in the convex zone increases. This counterintuitive phenomenon can be understood by the superimposition of displacements. The results have potential applications in the fields of adhesion, indentation, evaporation, cell migration on soft materials, etc.