Miracle-dz/UniFAR-FTUs huggingface dataset:
Underwater Jamming Attacks as Incomplete Information Games

Autonomous Underwater Vehicles (AUVs) have several fundamental civilian and military applications, and Denial of Service (DoS) attacks against their communications are a serious threat. In this work, we analyze such an attack using game theory in an asymmetric scenario, in which the node under attack does not know the position of the jammer that blocks its signals. The jammer has a dual objective, namely, disrupting communications and forcing the legitimate transmitter to spend more energy protecting its own transmissions. Our model shows that, if both nodes act rationally, the transmitter is able to quickly reduce its disadvantage, estimating the location of the jammer and responding optimally to the attack.
State estimation for uncertain discrete-time nonlinear systems via the coding-decoding scheme

The state estimation problem is investigated for a class of discrete-time networked systems with uncertainty and nonlinearity via a coding-decoding communication approach. The signal is transmitted through digital channels, which means that only the sequence of finite coded data is sent to the estimator. To be specific, the observation must be encoded to certain codewords by designing a coder, and then the received codewords are decoded by the relevant decoder. The purpose of the addressed problem is to design a proper coding-decoding procedure such that the estimator error is asymptotically stable across the limited capacity of the communication channel. By applying a modified uniform quantization approach, sufficient detection conditions involving the size of the coding alphabet and the coding period are obtained. Subsequently, the estimator parameter is explicitly determined in terms of the solutions to a set of matrix inequalities. Finally, a simulation example is provided to demonstrate the effectiveness of the obtained results.
Investigation of the Accuracy of Depression Prediction Based on Speech Processing

The present study investigates the accuracy of prediction of depression based on speech processing. Depression is one of the most widespread psychiatric disorders, but early detection of depression is difficult. The Beck Depression Inventory II (BDI) is a self-assessment questionnaire and can accurately predict the severity of depression. BDI is most often used for early detection. There is no known objective biomarker for depression, but the state alters the speech of the individual suffering from it, providing an opportunity for speech-based detection. In the current study, we investigated the accuracy of prediction of depression severity based on speech signal processing, and how accurately it can predict the severity of depression compared to the Beck Depression Inventory.
Attack Detection on the Software Defined Networking Switches

Software Defined Networking (SDN) is disruptive networking technology which adopts a centralised framework to facilitate fine-grained network management. However security in SDN is still in its infancy and there is need for significant work to deal with different attacks in SDN. In this paper we discuss some of the possible attacks on SDN switches and propose techniques for detecting the attacks on switches. We have developed a Switch Security Application (SSA)for SDN Controller which makes use of trusted computing technology and some additional components for detecting attacks on the switches. In particular TPM attestation is used to ensure that switches are in trusted state during boot time before configuring the flow rules on the switches. The additional components are used for storing and validating messages related to the flow rule configuration of the switches. The stored information is used for generating a trusted report on the expected flow rules in the switches and using this information for validating the flow rules that are actually enforced in the switches. If there is any variation to flow rules that are enforced in the switches compared to the expected flow rules by the SSA, then, the switch is considered to be under attack and an alert is raised to the SDN Administrator. The administrator can isolate the switch from network or make use of trusted report for restoring the flow rules in the switches. We will also present a prototype implementation of our technique.
MEM: A Multi-Staged Eviction Mechanism of Flowtable for Software-Defined Datacenters

In a Software-Defined Datacenter (SDDC), the explosive and instantaneous short-lived flows severely degrade the utilization of flowtable storage and the efficiency of packet forwarding in OpenFlow-enabled switches. To improve this situation and ensure network performance, a multi-staged eviction mechanism (MEM) of flowtable based on the traffic characteristics of SDDC is proposed, containing classification, identification, and eviction stages. The classification is performed twice on flow entries according to the persistent state and basic statistics information of flows. We then introduce a time series prediction model, called Autoregressive Moving Average (ARMA), to predict the future state of flow entries in the next period. Finally, the predicted recently-unused flow entries will be evicted to alleviate the stress on flowtable storage. Simulation experiments were conducted based on two datacenter datasets, and the results show the proposed MEM outperforms the existing mechanism based on the original ARMA in terms of flow entry compression ratio and packet forwarding ratio while interactions between massive short-lived flows are rising in SDDC.
A Bluetooth Low Energy DCO in 28nm FDSOI

A 2.4 GHz digital-controlled oscillator (DCO) based on a novel capacitor tank suitable for all-digital Bluetooth Low Energy (BLE) transmitter is proposed in this paper. The capacitive element which is responsible for Gaussian Frequency Shift Keying (GFSK) modulation is constructed by a single nMOS device with simple topology, designed in a fully depleted silicon on insulator (FDSOI) process. The proposed capacitive element can offer capacitance difference in the range of a few aF with constant step. Consequently, it can provide accurate linear changes in frequency of a few KHz as required by the standard. The DCO circuit has been designed and simulated on a 2S nm FDSOI CMOS process, operating with 1V supply voltage and dissipating 1.5 mA. The phase noise is around -113 dBc at 1 MHz.
A Deep Neural Network Combined CNN and GCN for Remote Sensing Scene Classification

Learning powerful discriminative features is the key for remote sensing scene classification. Most existing approaches based on convolutional neural network (CNN) have achieved great results. However, they mainly focus on global-based visual features while ignoring object-based location features, which is important for large-scale scene classification. There are a large number of scene-related ground objects in remote sensing images, as well as Graph convolutional network (GCN) has the potential to capture the dependencies among objects. This article introduces a novel two-stream architecture that combines global-based visual features and object-based location features, so as to improve the feature representation capability. First, we extract appearance visual features from whole scene image based on CNN. Second, we detect ground objects and construct a graph to learn the spatial location features based on GCN. As a result, the network can jointly capture appearance visual information and spatial location information. To the best of authors' knowledge, we are the first to investigate the dependencies among objects in remote sensing scene classification task. Extensive experiments on two datasets show that our framework improves the discriminative ability of features and achieves competitive accuracy against other state-of-the-art approaches.
Phytogeography and Floristic Survey of a Relic Area in the Marianna Lowlands, Florida

The Florida Caverns State Park, an area which is unique both in its flora and its physiography, is treated floristically with emphasis upon its geologlic history and past climates. Evidence is presented which supports the theory that the area has been continuously available for occupancy by plants throughout the period of Pleistocene glaciations, possibly since the deposition of early Pliocene alluvia. Discussions of disjunct and endemic populations of both vascular plants and mosses point out the importance of fluctuating glacial and interglacial climates as well as the significance of edaphic and genetic factors in the synthesis and preservation of the relic flora. Disjunction and endemism are also discussed in the light of recent collections in the southeastern United States, and distribution maps are provided for many species. A check list of the Bryophytes and an annotated check list of the vascular plants of the 1187-acre park supplement the text.
Topology Identification and Inner Desynchronization of Hindmarsh-Rose Neural Networks

Topology identification of biological neural networks has received great attention in recent years. But most existing researches ignored the importance of linear independence condition. Once network occurs inner synchronization, such a condition would inevitably break, which could lead to the failure of topology identification. However, synchronous firing between neurons is unavoidable in biological neural network. This phenomenon makes it difficult to identify the topology of neural networks. In this paper, we proposed a new method to identify Hindmarsh-Rose Neural Networks. By this method, the original neural network can implement inner desynchronization and the topology observers can successfully identify the unknown topology. It is worth mentioning that the our method can ensure that the linear independence condition naturally holds. This means that topology identification will not meet with failure. Finally, the effectiveness of the proposed method is successfully validated by numerical simulations.
An Improved Coupled-Inductor Impedance Source Network With More Freedom in Winding Match

In this paper, an improved coupled-inductor impedance source network (CL-ISN) with more freedom in winding match is proposed. Through introducing three-winding coupled-inductor cells, the proposed CL-ISN can produce the same voltage gain by using different turn ratios among three windings, which will largely increase the freedom in winding match. Also, the proposed CL-ISN can produce the higher boost ability, realize the continuous input current and suppress the start-up inrush current. The topology derivations, math calculations and parameter design of proposed CL-ISN are given out. The proposed CL-ISN is applied for DC-AC converter, and a full comparison between proposed CL-ISN and other impedance source networks are made based on DC-AC converter. Finally, the experiment prototype is built to verify the validity of the theoretical analysis.
Circle Involute-Based Path Planning and Tracking for Impact Angle Control

In this paper, a guidance law considering impact angle constraint for missiles with time-varying velocity is proposed via geometric methods. The guidance concept is based on the geometric property of the circle involute. A simple path planning approach is proposed to find the desired involute trajectory that connects the missile and target while satisfying the impact angle constraint. Once the desired involute trajectory is determined, the reference line-of-sight (LOS) profiles with respect to the downrange are obtained consequently. Then, a robust guidance law is constructed to achieve the precise tracking of the reference LOS profiles that finally guides missiles with time-varying velocity to meet the impact angle constraint. Nonlinear simulations under various scenarios are conducted to validate the proposed guidance law.
Command Filter Backstepping Control with Error Compensation for Flexible-Joint Manipulator

This paper presents a modified position tracking control strategy using command filtering backstepping for the flexible-joint manipulator. First, the second-order command filter is adopted in the backstepping procedure to derive the virtual control function and its derivatives. The problem of "explosion of complexity" caused by the calculation of the partial derivatives of virtual control inputs is avoided. Second, to reduce the filtering error caused by adopting the command filter, the filtering error compensation is designed, and the stability of the tracking error closed-loop system is verified based on Lyapunov stability theory. Finally, simulation results on single-link flexible-joint manipulator show that the tracking accuracy is increased by about 12.8%, which indicate the position tracking accuracy is guaranteed by the proposed control method.
Genetic Differences in Resistance to Newcastle Disease

D EMONSTRATIONS of genetic susceptibility or resistance to specific disease-producing agents aid in focusing attention upon the important role that genetic constitution of a stock plays in its over-all performance. Differences in resistance to Newcastle disease are to be expected, but no clear-cut evidence has yet been published. This report presents evidence that such differences do exist between strains and among sire families within a susceptible strain.
Latency and Reliability Oriented Collaborative Optimization for Multi-UAV Aided Mobile Edge Computing System

Intelligent emergency rescue equipment increasingly plays an important emergency rescue, which can greatly enhance the capability and efficiency of the rescue activities. In this paper, we construct a multi-UAV enabled latency and reliability guaranteed mobile edge computing framework (LR-UMEN) to provide on-demand computing services, where both the latency and the reliability are considered. Moreover, being different from the existing work about the latency and reliability, we propose a joint optimization of communications, computing and caching to decrease the latency as well as enhance the reliability relying on the novel definition of ‘expected latency’, which effectively benchmarks the characteristic of both the latency and reliability considered. Finally, a hybrid binary particle swarm optimization (HBPSO) algorithm is conceived for solving the non-convex optimization problem, followed by a range of simulations.
Simulation of Electromagnetic Fields at Sharpening of the Impulse Front in Nonlinear Dielectric

An approach to mathematical modeling of electromagnetic waves propagation through inhomogeneous media with non-linear parameters is described. The problem was formulated in terms of the modified vector magnetic potential with regard of magnetic and electric losses. The results of mathematical modeling of electrophysical processes accompanying an electromagnetic wave front sharpening as it propagates through ferroelectric media with nonlinear dependences of permittivity on the level of the electric field strength are presented.
Bias Voltage DAC Operating at Cryogenic Temperatures for Solid-State Qubit Applications

A scalable eight channel DAC designed in a TSMC 65-nm CMOS technology for generation of solid-state quantum bit (qubit) bias voltages is presented. Measurement results of the DAC and some additional auxiliary components like an on-chip amplifier and sigma–delta modulator at 6 K are discussed. With a low-power consumption of <inline-formula> <tex-math notation="LaTeX">$2.7~\mu \text{W}$ </tex-math></inline-formula> per channel, the DAC fulfills the requirements to be placed next to qubits inside a mixing chamber of a dilution refrigerator, showing a promising way for scaling qubit numbers toward a quantum computer.
Secure Correct Control for Cyber-Physical Systems under Multiple Stochastic Physical Attacks

Secure correct control problem is discussed for Cyber-Physical Systems (CPSs) under multiple stochastic physical attacks. In particular, the attack signals considered are designed to directly destruct the security of the CPSs, which consists of three components. One is the stochastic attack signal injected into the actuator. The other one is bounded stochastic attack signal that can realize coupling with state to invade the sensor. And the third one is completely unknown attack by wireless network, aiming at tampering with the state information of CPSs. To online detect the stochastic attack signals acting on actuator, a adaptive stochastic attacks detector (ASAD) is constructed. As for the stochastic sensor attacks coupled with state, the feedback stabilizer is introduced to correct the sensor signal. An secure correct control (SCC) scheme is proposed by integrating ASAD with feedback stabilizer and robust technology. It is proved that the security control performance of the CPSs is realized. Finally, a simulation examples is given to shows the effectiveness of the proposed scheme.
Broadband Microstrip Antenna for C-band, X-band, and KU-band Applications

In this research a novel design of monopole microstrip antenna is introduced. The proposed antenna has a compact size of 2.1 × 1.5 × 3.175 cm3 with a simple structure consisting of semi-triangular patch shape with a coplanar waveguide (CPW) feed line. The antenna provides a wide bandwidth covering frequencies from 4. 5 GHz to 15 GHz with an input reflection coefficient (S11) smaller than –10 dB over the entire range. The obtained percentage bandwidth is 107% at the center frequency 9.8 GHz. The radiation pattern of the antenna is directional in E plane with realized gain 5.3 dB. This property makes the proposed antenna suitable for many crucial applications including medical, radar and satellite applications.
Usage of Operating System Kernel Paradigms to Build Modern Simulation Platforms for Autonomous Driving

Compared to existing intelligent vehicles software such as Advanced Driver Assistance Systems (ADAS) the complexity of Autonomous Driving (AD) software exploded. As a result of that also the development and testing complexity increased proportionally. To master this challenge modern simulation based testing approaches are an essential element. Some of the main challenges for the underlying simulation platform are the large set of simulation use cases, the huge amount of simulation runs and the great testing depth even to the level of unit tests. To find an adequate architectural paradigm for simulation platforms we first analyse the simulation requirements. From this perspective we compare simulation platforms with the established Operating System (OS) Kernel platform. We propose a concept that maps terminology of such simulation kernel and the general architecture itself to an AD simulation platform. Finally, we discuss how design principles known from operating system kernels can be reused for the development of sustainable and modular simulation platforms.
Handling Device Heterogeneity in Wi-Fi based Indoor Positioning Systems

Wi-Fi Received Signal Strength (RSS) based indoor localization is promising and widely investigated due to the pervasive deployment of Wi-Fi Access Points (APs). However, one major challenge to build a practical Indoor Positioning System is that end users usually carry different devices with different received signal characteristics, and thus the performance can be degraded due to this device heterogeneity. Existing solutions are either not practical or have limited accuracy. We propose two novel solutions to mitigate device heterogeneity for representative localization approaches using Gaussian Process regression and neural network, respectively. The first solution is built upon Gaussian Process regression by jointly calibrating and localizing a target device. The second solution utilizes adversarial training with neural network. Real world experiments show that both solutions are effective and achieve higher accuracy than that of two baseline approaches in most cases.
Mathematical Methods for the Analysis of Electrospark Alloying of Metal Surfaces

There are considered the phase state and chemical composition of the aluminized coatings obtained by the method of electrospark alloying (ESA) on the specimens made of 20 steel. At low discharge energies, there is formed a layer predominantly consisting of α-Fe and aluminum oxides. It has been stated that increasing discharge energy results in obtaining the layer consisting of iron and aluminum intermetallics and free aluminum as well. A kinetic analysis of the system describing this process has been carried out, phase portraits have been constructed, which confirm the developed theory of a three-layer system.
5G-TRANSFORMER meets Network Service Federation: design, implementation and evaluation

5G networks require flexibility, automation and programmability to satisfy the requirements of verticals industries. 5G-TRANSFORMER project proposes an SDN/NFV based network platform to enable this vision. Among its features, this platform allows the end-to-end deployment of parts of a network service (NS) in multiple administrative domains, which is known as network service federation (NSF). This feature increases network flexibility, opening the door to new business models. This paper complements our previous work by providing a detailed description of the 5G-TRANSFORMER NSF workflow, its interface and a profiling of the operations involved in the deployment of an NS between multiple administrative domains in a real experimental setup. Experimental results reveal i) that a federated NS can be deployed in the order of few minutes (less than 5 minutes), in line with the 5G target of reducing service setup to minutes, and ii) the impact of the NSF procedure in the deployment time is reduced when compared with the deployment of the same NS in a single administrative domain.
A New Approach to a Service Oriented Internet Protocol

Previous work on service oriented networking has mainly focused on the requirements of network operators and other service providers. This document proposes a new, backwards-compatible, approach to the topic that is directly aimed at end users and their requirements, but also has significant benefits for operators. It describes a proposed new mechanism for packet forwarding in edge networks, where the service required rather than an IP address acts as the vector for routing packets. Deeper in the network, the user's traffic is dispatched to specific services using conventional mechanisms.
Cluster-based Penalty Scaling for Robust Pose Graph Optimization

Robust pose graph optimization is essential for reliable pose estimation in Simultaneous Localization and Mapping (SLAM) system. Due to the nature of loop closures, even one spurious measurement could trick the SLAM estimator and severely distort the mapping results. Existing methods to avoid this problem mostly focus on ensuring local measurement consistency by evaluating measurements independently, often requiring parameters that are difficult to tune. This letter proposes a cluster-based penalty scaling (CPS) method to ensure both the local and global consistency by first evaluating the edge quality locally, and then integrating this information into the optimization formulation.
An SDR-in-the-Loop Carla Simulator for C-V2X-Based Autonomous Driving

In this demo, we showcase an integrated hardware-software evaluation platform for collaborative autonomous driving. The vehicle control and motion dynamics are simulated by SUMO [1], and the communications among vehicles are realized by software defined radios, which are programmed to run the standardized Cellular Vehicle-to-Everything (C-V2X) Mode 4 protocol. We implement our parallel communication scheme [2] and demonstrate a platooning autonomous driving system. The platform can be extended to run more advanced collaborative autonomous driving applications in the future.