Miracle-dz/UniFAR-FTUs huggingface dataset:
A Remote Monitoring System for Water Quality Based on GPRS in Poor Signal Environment-Poyang Lake for Example

The role of sensor network technology in remote environmental monitoring and data collection have long been recognized especially for environmental monitoring, which can realize real-time, continuous and efficient monitoring. Now, most research on the application of sensor networks have focused on the application of sensor networks in different industries, but they all have neglected the application of sensors in different conditions in the same industry. In this paper, the main objective is remote monitoring of water quality in poor signal environment and the correspond novel approach is proposed. An experiment is conducted to validate the proposed approach and the result indicates that the proposed approach is effective for remote monitoring of water quality in areas with poor signals in terms of the continuity and effectiveness of monitoring results.
DFM: A Distributed Flocking Model for UAV Swarm Networks

Flocking of the unmanned aerial vehicle (UAV) network refers to utilize the node’s autonomous mobility to satisfy the principle of cohesion, separation, and alignment. A network with flocking ensures the connectivity between high-speed UAV nodes and simplifies the design of various swarm applications. In this paper, we propose a novel distributed flocking model for UAV swarm networks. The model follows the Boid principle and establishes the master–slave transmission mode among the nodes. The slave node performs the distributed autonomous regulation. An effective flocking method is proposed, which is based on the positioning and communication capabilities of Wi-Fi. The slave node can sense and adjust their distance and direction from the master node. The simulation and experimental results show that our model can guarantee the connectivity between all nodes and has $1.4\times $ the network goodput gain outperforms the traditional flying ad hoc network.
Network Topology Reconfiguration for FSO-Based Fronthaul/Backhaul in 5G+ Wireless Networks

Using free-space optics (FSO) in the mobile fronthaul/backhaul networks is a promising solution that can potentially enhance the capacity of mobile networks. The main challenge of establishing FSO-based fronthaul/backhaul networks is the dynamic feature of the networks, i.e., the fragile links under adverse weather conditions and the dynamic traffic demands among small cells. Topology reconfiguration is proposed to dynamically rearrange the FSO links. In this paper, two types of network reconfigurations are investigated, in which the proactive network reconfiguration is to proactively optimize the topology of the FSO-based fronthaul/backhaul networks for each specific time period based on the statistics of the network, and the reactive reconfiguration is to actively adjust the topology when traffic demands and link states are changed. The proactive network reconfiguration is formulated as a mixed integer nonlinear programming (MINLP) problem, which jointly optimizes the network throughput and power consumption of the FSO-based fronthaul/backhaul networks. A greedy algorithm is proposed to derive the solution of the proposed problem. After the network topology having been reconfigured by solving the MINLP problem, two reactive reconfiguration algorithms are designed to optimally adjust the network topology once a link failure and demand explosion occur, respectively, to further enhance the network throughput and reduce the power consumption. The performance of the algorithms is demonstrated via extensive simulations.
PHE: An Efficient Traitor Tracing and Revocation for Encrypted File Syncing-and-Sharing in Cloud

Recently, many enterprises have moved their data into the cloud by using file syncing and sharing (FSS) services, which have been deployed for mobile users. However, Bring-Your-Own-Device (BYOD) solutions for increasingly deployed mobile devices have also in fact raised a new challenge for how to prevent users from abusing the FSS service. In this paper, we address this issue by using a new system model involving anomaly detection, tracing, and revocation approaches. The presented solution applies a new threshold public key based cryptosystem, called partially-ordered hierarchical encryption (PHE), which implements a partial-order key hierarchy and it is similar to role hierarchy widely used in RBAC. PHE provides two main security mechanisms, i.e., traitor tracing and key revocation, which can greatly improve the efficiency compared to previous approaches. The security and performance analysis shows that PHE is a provably secure threshold encryption and provides following salient management and performance benefits: it can promise to efficiently trace all possible traitor coalitions and support public revocation not only for the users but for the specified groups.
Novel Design of a Dual-Band Rat-Race Coupler with Large Power Division Ratio

This paper proposed a novel design of a compact dual-band rat-race coupler with large power division ratio. The closed-form design formulas are analytically derived using the even-odd-mode analysis. The proposed dual-band structure demonstrates compact size and ideal port isolation due to adding phase inverter to branches. The high impedance microstrip lines are the key for obtaining large power division and there is no need to insert additional shunt stubs for the dual-band operation. For verification, using the analytical design method, the power division ratio $k=10$ rat-race coupler operating at 1/6.16GHz is designed and fabricated. There are excellent agreement between the measured results and the simulated results.
Model based control of a high precision dual gantry platform with elastic cross coupling

In many cases handling processes rely on precise and fast pick-and-place operations. This may be achieved by means of so-called H-gantry systems. In order to increase the throughput of such devices they are often extended by a second, asynchronously working gantry. Due to the finite stiffness of the mounting base of the linear motors and vibrations of the base frame an interaction of both gantries can be observed. The contribution proposes a flatness based approach to compensate for this effect. This approach is based on a simplified quasi-stationary model of the base frame and relies on the parameterization of the system trajectories by a so-called flat output. This allows on the one hand for a significant decrease of the base frame vibrations and, thus, for a better performance of the position control. On the other hand a more precise compensation of the coupling effect can be achieved compared to standard trapezoid acceleration trajectories. Simulation studies and experimental results show the efficiency of the proposed algorithms.
Implementing IoT for Development of a Low-Cost Environmental Monitoring System

This paper presents a proposal for the development of a web system based on the Internet of Things (IoT) concepts, focused on the environmental monitoring and low cost. The need to carry out such a study is solidified by accelerated technological advancement and widespread concern with the alarming environmental conditions that the world presents today. In this system, groups of sensors are responsible for, through embedded systems, send the data to a server that stores them and also provides graphical interface models on a web page. The implementation of such a procedure allows for a better understanding of relevant environmental characteristics of certain locations, as well as the research for better solutions to environmental issues.
Crowd-Based Mobile Sensor Cloud Services — Issues, Challenges and Needs

As an important part of IoT infrastructures, sensors have become essential elements of today and future connected smart world. The fast advance of sensor and mobile sensor technologies and the increasing deployments of connected sensor networks bring a strong demand and many business opportunities in develop new mobile sensor cloud infrastructures and related services applications. Mobile sensor clouds based on crowd sensors from users is one of them. This paper focuses on this topic by discussing the trend and opportunities first. Then it presents an overview of crowd-based mobile sensors in terms of its concepts, features, process and applications. Moreover, it discusses a reference infrastructure on a crowd-based mobile sensor cloud. Finally, it discussed its issues, challenges and needs.
Shape recovery from robot contour-tracking with force feedback

A process for shape recovery from robot contour-tracking operations with force feedback is described. Shape recovery is an important task for self-teaching robots and for exploratory operations in unknown environments. An algorithm which directs a position controlled robot around an unknown planar contour using the steady-state contact force information is described. A compensation process is explored for purposes of planar shape recovery. It is found through experimentation that the joint compliance is most conveniently compensated for in practice. Improvements in the shapes recovered from robot contouring are seen with the compensations. Experimental details and difficulties are also discussed. <<ETX>>
Design of a Novel Ultra-Wideband Planar Magic-T

An implementation method of a novel ultrawideband planar magic-Tis proposed. The magic-Tis composed of an ultra-wideband 90° phase shifter and an ultra-wideband 3dB 90° hybrid coupler. A wider transmission band and a better coupling degree achieves through narrow side coupled, broadside coupled manner and etc. Three-dimensional modeling performs via the circuit simulation and software of HFSS. The simulation results are consistent with designed indices. The novel planar magic-T has a central frequency of 9 GHz with a bandwidth from 5 to 13 GHz. The relative bandwidth reaches up to 89%. Comparing output signal of sum end and difference end, the amplitude unbalance is less than 0.5dB with phase unbalance less than 3° while the input and output VSWRs are less than 1.3. The isolation between input and output ports is more than 20dB. The size of magic-Tis only $\pmb{13\mathrm{mm}\times 5\mathrm{mm}\times 1.5\mathrm{mm}}$.
All-Optical Wavelength Multicasting in Quadruple Resonance-Split Coupled Silicon Microring Cavity

We demonstrate an all-optical four-channel wavelength multicasting in a coupled silicon microring resonator system. The scheme is based on two-photon-absorption-induced free carrier dispersion in silicon. The coupled cavity facilitates resonance splitting that is utilized as individual channels for multicasting. Using the split resonances, we achieve an aggregate multicasted data rate of 48 Gbps (4 × 12 Gbps). Moreover, we also present a detailed analysis and performance of the multicasting architecture using bit error rate and eye diagram measurements.
Reconstructing Individual Activity Trajectories by Hidden Semi-Markov Model

The individual trajectory of human activity collected through crowdsourcing implies the characteristic regularity of individual activity. There are always data gaps, and it introduces negative influence of individual activity pattern analyses. By extracting the internal regularity of known data, the incomplete relationship between location and time can be imputed and reconstructed. In this paper, a method of trajectory reconstruction based on individual behavior pattern and Hidden Semi-Markov Model (HSMM) is presented. It introduces behavior state variables and a discrete representation of locations to facilitate explanation of real-world meaning of the model parameters in individual daily activities. In HSMM, the interaction between various parameters imitates the behavior state transition and spatiotemporal variation. The relationship between the individual locations and behavior states is captured as an individual activity pattern. This pattern is used to derive individual state change sequence in the studied period of time. The state sequence can be resolved to obtain the final individual activity trajectory. Experiment on an individual track data set including Weibo check-ins and mobile phone GPS records showed that the accuracy of the trajectory reconstruction was 84.2%.
Selection of the Band-Pass Range of the Normalizing Signal Transducer of the Sensing Element in the Instrumentation and Control Systems

In automatic control systems (ACS), the unifying (normalizing) converter (UC) of the physical magnitude sensor amplifies the signal of the sensing element (SE) to a standard value. In this case, the band-pass range of the UC specifies the value of signal delay time of the SE in the UC. It is shown that the dynamic error of the UC is determined by the signal delay time of the SE and the first derivative of the SE. The response of the UC was approximated by the Butterworth filter response. The use of the Filter Solution application programs in the NI Lab VIEW software environment (Lab View 8.6) enabled to obtain the numeric evaluations of the signal delay time of the SE in the UC. It is shown that for the case of an infinite spectrum the first signal derivative of the SE does not differ from the value obtained with the Bernstein inequality. The final calculations showed a significant effect of the dynamic error on the total error of the sensor, which causes the increase tenfold the band-pass range of the UC in comparison with the signal band of the UC.
Mobile Underwater Acoustic Communication with Constantly Changing Doppler Effect

Recently an underwater acoustic communication (UWA) experiment with a mobile source was conducted in downward-refracting shallow water environment. During this experiment, the source moved towards and then away from the receiving array repeatedly, Doppler effect kept changing in this process due to the time-varying radial velocity between the source and receiving array. In this paper, a three-stage data processing method is proposed in order to effectively decode the experimental data with severe Doppler interference. In the first stage, fractional Fourier transform (FrFT) is used to estimate the delay-Doppler function of the underwater channel based on the linear chirp signal at the front of the received data sequence. Large Doppler effect are coarsely removed according to the Doppler estimation result by resampling and delay estimation is used to determine the number of channel taps. Then the resampled data are demodulated and downsampled to the baseband. In the second stage, data are divided into small blocks and block-based passive time reversal (PTR) is adopted to suppress the mutipath in a block by block manner. Fine Doppler is also compensated in each block by maximum likelihood estimation method. In the third stage, decision feedback equalizer (DFE) is used to remove the residual inter symbol interference (ISI) and Doppler effect. Data proceesing results show that this proposed three-stage equalization method can realize effective trakcing and compensation for time-varying channels. The output signal-to-noise ratio (OSNR) after equalization is greatly improved and the bit error rate (BER) is significantly reduced.
Local obstacle avoidance for mobile robots based on the method of artificial potentials

In the method of artificial potentials, the robot behaves like a charged particle that is attracted by the goal position and repelled by the obstacles. An overview of the method is presented which describes the common variations in a unified framework, compares the performances of the different algorithms, and corrects some common misunderstandings. It is shown that force control algorithms with generalized potentials (which depend on velocity as well as position) offer advantages over other alternatives. Also discussed are the problems of stability and convergence. <<ETX>>
Unmanned Surface Vehicle Course Tracking Control Based on Neural Network and Deep Deterministic Policy Gradient Algorithm

The paper combines the Deep Deterministic Policy Gradient (DDPG) algorithm with neural network control, which is more stable, accurate, smoother, and faster than the usual neural network control. The plan is applied to the unmanned surface vehicle(USV) course tracking control, which overcomes the shortcomings of usual intelligent algorithm learning, which requires a certain number of samples. For online learning and adjustment of the parameters of the controller can solve the uncertainty problem of ship motion in a certain extent. The simulation results show that basing on neural network and DDPG algorithm can achieve satisfactory results for the unmanned surface vehicle course tracking control, indicating that the algorithm is effective and feasible.
Effects of thermal properties on tracking and erosion resistance of micro-ATH/AlN/BN filled silicone rubber composites

Silicone rubber is a hydrophobic polymer which is widely employed for high voltage outdoor insulation. The material offers excellent electrical performance under contaminated environments. However, pristine silicone rubber has low thermal properties and this may cause tracking and erosion failure due to severe dry band arcing and ohmic heating on the insulating surface. This work investigates the effect of material thermal characteristics on the tracking and erosion resistance of silicone rubber filled with micron sized alumina tri-hydrate (ATH), aluminum nitride (AlN) and boron nitride (BN) particles. Composites with different loading were synthesized by dispersing particles in pristine room temperature vulcanizing (RTV) silicone rubber and IEC 60587 inclined plane test (IPT) was conducted to evaluate tracking and erosion resistance. Apart from physical parameters and leakage current, an infrared thermal imager was used to measure the surface temperature distribution during the course of IPT. Experimental results showed tracking and erosion resistance is significantly enhanced with addition of BN particles followed by ATH. AlN composites exhibit poor tracking and erosion resistance, similar to pristine silicone rubber. It is concluded that addition of BN-composites improves ability to impede the tracking and erosion process, the reasons being better thermal stability and enhanced thermal conduction in the discharge region. On the other hand, infrared analysis revealed thermal accumulation is remarkably higher in AlN-composites which promotes dry band arcing and results in tracking and erosion failure.
Whole-Genome Sequences of Two Pseudomonas fluorescens Strains Isolated from Roots of Tomato and Cucumber Plants

Pseudomonas fluorescens strain EC1 was isolated from Cucumis sativus (cucumber) roots, and P. fluorescens SC1 was isolated from Solanum lycopersicum (tomato) roots. The P. fluorescens SC1 genome has a total sequence length of 6,157,842 bp, and the P. fluorescens EC1 genome has a total sequence length of 6,125,428 bp. ABSTRACT Pseudomonas fluorescens strain EC1 was isolated from Cucumis sativus (cucumber) roots, and P. fluorescens SC1 was isolated from Solanum lycopersicum (tomato) roots. The P. fluorescens SC1 genome has a total sequence length of 6,157,842 bp, and the P. fluorescens EC1 genome has a total sequence length of 6,125,428 bp.
Path planning by optimal-path-map construction for homogeneous-cost two-dimensional regions

Algorithms to construct optimal-path maps for single isolated homogeneous-cost convex-polygonal regions are discussed. Assuming the ability to construct optimal paths for a certain set of key points, a complete analysis is given of one of the four possible single-region situations, showing how to partition the map into regions of similar path behavior. An algorithm is then proposed for constructing optimal-path maps for multiple such regions, in the case that they meet certain decomposability constraints. This algorithm is of O(n/sup 4/) time complexity and O(n) space complexity, where n is the number of vertices in a polygonal model of the terrain as homogeneous-cost regions. The algorithm greatly simplifies planning of paths through areas of terrain with near-uniform characteristics, allowing a robot to exploit optimal paths but still have significant time for other matters. <<ETX>>
A 23-30 GHz LNA with Noise-Cancelling in 28nm CMOS

This paper presents a 23-30 GHz low-noise amplifier (LNA) with noise-cancelling technique in 28nm CMOS. An improved common gate and common source (CG-CS) noise-cancelling topology is proposed to optimize the noise figure (NF). In addition, the bandwidth is extended and gain ripple is reduced by using second-order L-C band-pass networks and inductively coupling techniques. The post simulation results show that over the entire band of 23-30 GHz, we obtain 3.8-4.8dB NF and 16.9-17.7dB power gain with 0.8dB in-band ripple, and input matching better than −12dB. It consumes 22.2mW from 0.9V power supply and occupies 0.315mm2 without pad.
An Indoor Positioning Method Based on Regression Models with Compound Location Fingerprints

An indoor positioning method is proposed and evaluated. The method combines location fingerprinting and dead reckoning differently from conventional combinations. It utilizes a compound location fingerprint, which is composed of radio fingerprints at multiple points of time, that is, at multiple positions, and displacements between them estimated by dead reckoning. To avoid accumulated errors from dead reckoning, the method uses short-range dead reckoning. The method was evaluated in a student room whose size was $11 \times 5 \mathrm{m}$ and had furniture. Six Bluetooth beacons were placed in the room. The received signal strength indicator (RSSI) values of the beacons were collected at 28 measuring points, which were points of intersection on a 1-m by 1-m grid where no obstacles existed. A compound location fingerprint is composed of RSSI vectors at two points and a displacement vector between them. A support vector machine (SVM) and random forests (RF) were used to build regression models. The root mean square error (RMSE) of position estimation with SVM and (RF) was respectively 2.35 and 0.80m. These errors were lower than those with a single-point baseline model, where a feature vector is composed of only RSSI values at one location. The results suggest that the proposed method is effective in indoor environments. We also discuss the relationship between the permissible error tolerance and cumulative percentages of correct answers, and the influence of dead reckoning errors on RMSE.
Limit Cycle Suppression Technique Using Random Signal In Delta-Sigma DA Modulator

The delta-sigma digital-to-analog converter (ΔΣDAC) generates a DC/low frequency analog signal with high resolution and high linearity, whereas there is a limit cycle problem where spurious components are periodically generated in the output signal for small amplitude, due to the nonlinear operation of the modulator. This paper studies a limit cycle suppression technique in the ΔΣDA modulator. It is shown in simulations that the investigated method can reduce the limit cycle, while keeping the overall linearity, thanks to the fact that the random noise is noise-shaped. We show that these are valid for various types of the modulators: low-pass (LP), high-pass (HP), band-pass (BP) and multi-BP types.