Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar facets.In this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff constructions.The competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985°C and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted pyramids.On the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

Core–Shell Microfiber Encapsulation Enables Glycerol‑Free Cryopreservation of RBCs with High Hematocrit

Cryopreservation of red blood cells(RBCs)provides great potential benefits for providing transfusion timely in emergencies.High concentrations of glycerol(20%or 40%)are used for RBC cryopreservation in current clinical practice,which results in cytotoxicity and osmotic injuries that must be carefully controlled.However,existing studies on the low-glycerol cryopreservation of RBCs still suffer from the bottleneck of low hematocrit levels,which require relatively large storage space and an extra concentration process before transfusion,making it inconvenient(time-consuming,and also may cause injury and sample lose)for clinical applications.To this end,we develop a novel method for the glycerol-free cryopreservation of human RBCs with a high final hematocrit by using trehalose as the sole cryoprotectant to dehydrate RBCs and using core–shell alginate hydrogel microfibers to enhance heat transfer during cryopreservation.Different from previous studies,we achieve the cryopreservation of human RBCs at high hematocrit(>40%)with high recovery(up to 95%).Additionally,the washed RBCs post-cryopreserved are proved to maintain their morphology,mechanics,and functional properties.This may provide a nontoxic,high-efficiency,and glycerol-free approach for RBC cryopreservation,along with potential clinical transfusion benefits.

Age of Information Based User Scheduling and Data Assignment in Multi-User Mobile Edge Computing Networks:An Online Algorithm

This paper investigates the age of information(AoI)-based multi-user mobile edge computing(MEC)network with partial offloading mode.The weighted sum AoI(WSA)is first analyzed and derived,and then a WSA minimization problem is formulated by jointly optimizing the user scheduling and data assignment.Due to the non-analytic expression of the WSA w.r.t.the optimization variables and the unknowability of future network information,the problem cannot be solved with known solution methods.Therefore,an online Joint Partial Offloading and User Scheduling Optimization(JPOUSO)algorithm is proposed by transforming the original problem into a single-slot data assignment subproblem and a single-slot user scheduling sub-problem and solving the two sub-problems separately.We analyze the computational complexity of the presented JPO-USO algorithm,which is of O(N),with N being the number of users.Simulation results show that the proposed JPO-USO algorithm is able to achieve better AoI performance compared with various baseline methods.It is shown that both the user’s data assignment and the user’s AoI should be jointly taken into account to decrease the system WSA when scheduling users.

Utilization of Logistical Regression to the Modified Sine-Gordon Model in the MST Experiment

In this paper, a logistical regression statistical analysis (LR) is presented for a set of variables used in experimental measurements in reversed field pinch (RFP) machines, commonly known as “slinky mode” (SM), observed to travel around the torus in Madison Symmetric Torus (MST). The LR analysis is used to utilize the modified Sine-Gordon dynamic equation model to predict with high confidence whether the slinky mode will lock or not lock when compared to the experimentally measured motion of the slinky mode. It is observed that under certain conditions, the slinky mode “locks” at or near the intersection of poloidal and/or toroidal gaps in MST. However, locked mode cease to travel around the torus;while unlocked mode keeps traveling without a change in the energy, making it hard to determine an exact set of conditions to predict locking/unlocking behaviour. The significant key model parameters determined by LR analysis are shown to improve the Sine-Gordon model’s ability to determine the locking/unlocking of magnetohydrodyamic (MHD) modes. The LR analysis of measured variables provides high confidence in anticipating locking versus unlocking of slinky mode proven by relational comparisons between simulations and the experimentally measured motion of the slinky mode in MST.

Design of Cold-Junction Compensation and Disconnection Detection Circuits of Various Thermocouples and Implementation of Multi-Channel Interfaces Using Them-A Secondary Publication

Cold-junction compensation(CJC)and disconnection detection circuit design of various thermocouples(TC)and multi-channel TC interface circuits were designed.The CJC and disconnection detection circuit consists of a CJC semiconductor device,an instrumentation amplifier(IA),two resistors,and a diode for disconnection detection.Based on the basic circuit,a multi-channel interface circuit was also implemented.The CJC was implemented using compensation semiconductor and IA,and disconnection detection was detected by using two resistors and a diode so that IA input voltage became-0.42 V.As a result of the experiment using R-type TC,the error of the designed circuit was reduced from 0.14 mV to 3μV after CJC in the temperature range of 0°C to 1400°C.In addition,it was confirmed that the output voltage of IA was saturated from 88 mV to-14.2 V when TC was disconnected from normal.The output voltage of the designed circuit was 0 V to 10 V in the temperature range of 0°C to 1400°C.The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel.The implemented multi-channel interface has a feature that can be applied equally to E,J,K,T,R,and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.

A Study on the Design Method of Hybrid MOSFET-CNTFET Based SRAM-A Secondary Publication

More than 10,000 carbon nanotube field-effect transistors(CNTFETs)have been successfully integrated into one semiconductor chip using conventional semiconductor design procedures and manufacturing processes.These transistors offer advantages such as high carrier mobility,large saturation velocity,low intrinsic capacitance,flexibility,and transparency.The three-dimensional multilayer structure of the CNTFET semiconductor chip,along with ongoing research in CNTFET manufacturing processes,increases the potential for creating a hybrid MOSFET-CNTFET semiconductor chip.This chip combines conventional metal-oxide-semiconductor field-effect transistors(MOSFETs)and CNTFETs in one integrated system.This paper discusses a methodology to design 6T binary static random-access memory(SRAM)using a hybrid MOSFET-CNTFET.This paper introduces a method for designing a hybrid MOSFET-CNTFET SRAM by leveraging existing MOSFET SRAM or CNTFET SRAM design approaches.Additionally,this paper compares its performance with conventional MOSFET SRAM and CNTFET SRAM designs.

Influence of an Electronic Field on the GMI Effect of Fe-based Nanocrystalline Microwire

In this work, a Fe-based nanocrystalline microwire of 20 mm in length and 25 μm in diameter was placed in the center of a 316 stainless steel pipe. The pipe was 500 μm in diameter and a little shorter than the microwire. A series of voltages were applied on the pipe to study the influence of the electrical field on the Giant-Magneto-Impedance(GMI) effect of the microwire. Experimental results showed that the electronic field between the wire and the pipe reduced the hysteresis of the GMI effect. The results were explained based on equivalent circuit and eddy current consumptions analysis.

Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each year.For this purpose,a proper condition monitoring system is essential to avoid accidents and heavy losses.Generally,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment.Therefore,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway track.The proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition process.The contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy regions.It works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black color.We have used the multiprocessing technique to overcome the massive processing and memory issues.This embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/h.The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults.An unhealthy frame’s onsite detection processing time was recorded at approximately 25.6ms.The proposed system can synchronize the acceleration data on specific railway track deformation.The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring,which is still being practiced in various developing or underdeveloped countries.

FPGA Implementation of Extended Kalman Filter for Parameters Estimation of Railway Wheelset

It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad vehicle.The proper estimation of adhesion conditions and their real-time implementation is considered a challenge for scholars.In this paper,the development of simulation model of extended Kalman filter(EKF)in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of track.Due to concurrent in nature,the Xilinx®System-on-Chip Zynq Field Programmable Gate Array(FPGA)device is chosen to check the onboard estimation ofwheel-rail interaction parameters by using the National Instruments(NI)myRIO®development board.The NImyRIO®development board is flexible to deal with nonlinearities,uncertain changes,and fastchanging dynamics in real-time occurring in wheel-rail contact conditions during vehicle operation.The simulated dataset of the railway nonlinear wheelsetmodel is tested on FPGA-based EKF with different track conditions and with accelerating and decelerating operations of the vehicle.The proposed model-based estimation of railway wheelset parameters is synthesized on FPGA and its simulation is carried out for functional verification on FPGA.The obtained simulation results are aligned with the simulation results obtained through MATLAB.To the best of our knowledge,this is the first time study that presents the implementation of a model-based estimation of railway wheelset parameters on FPGA and its functional verification.The functional behavior of the FPGA-based estimator shows that these results are the addition of current knowledge in the field of the railway.

Matching while Learning: Wireless Scheduling for Age of Information Optimization at the Edge

In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.

Electronic mobility in the high-carrier-density limit of ion gel gated IDTBT thin film transistors

Indacenodithiophene-co-benzothiadiazole（IDTBT） has emerged as one of the most exciting semiconducting polymers in recent years because of its high electronic mobility and charge transport along the polymer backbone. By using the recently developed ion gel gating technique we studied the charge transport of IDTBT at carrier densities up to 10^21cm^-3.While the conductivity in IDTBT was found to be enhanced by nearly six orders of magnitude by ionic gating, the charge transport in IDTBT was found to remain 3D Mott variable range hopping even down to the lowest temperature of our measurements, 12 K. The maximum mobility was found to be around 0.2 cm^2·V^-1·s^-1, lower than that of Cytop gated field effect transistors reported previously. We attribute the lower mobility to the additional disorder induced by the ionic gating.

Performance Analysis of the Packet-Based PNT Service in NGSO Broadband Satellite Communication Systems

Providing alternative PNT service to GNSS-challenged users will be an important function of next-generation NGSO broadband satellite communication systems.Herein,a packet-based PNT service architecture in NGSO broadband systems is proposed in which a primary satellite and selected assistant satellites work together to provide PNT service to requesting users.Its positioning performance bounds are mathematically formulated by rigorously analyzing the bounds constrained by different waveforms.Simulations are conducted on different configurations of Walker Delta MEO constellations and Walker Star LEO constellations for corroboration,revealing the following:(1)Both MEO and LEO constellations achieve sub-meter-level positioning precision given enough satellites.(2)Compared to the GNSS Doppler-based velocity estimation method,the position advance based velocity estimation algorithm is more precise and applicable to the PNT service in NGSO broadband systems.(3)To provide PNT service to users in GNSS-challenged environments,the primary and each assistant satellite need only∼0.1‰of the time of one downlink beam.

On Dynamic Channel Emulation in Sector MPAC for Over-the-Air Testing of Beamformed Massive MIMO Devices

In this article,novel emulation strategies for the sectored multiple probe anechoic chamber(SMPAC)are proposed to enable the reliable evaluation of the massive multiple-input multiple-output(MIMO)device operating at beamforming mode,which requires a realistic non-stationary channel environment.For the dynamic propagation emulation,an efficient closed-form probe weighting strategy minimizing the power angular spectrum(PAS)emulation errors is derived,substantially reducing the associated computational complexity.On the other hand,a novel probe selection algorithm is proposed to reproduce a more accurate fading environment.Various standard channel models and setup configurations are comprehensively simulated to validate the capacity of the proposed methods.The simulation results show that more competent active probes are selected with the proposed method compared to the conventional algorithms.Furthermore,the derived closedform probe weighting strategy offers identical accuracy to that obtained with complicated numerical optimization.Moreover,a realistic dynamic channel measured in an indoor environment is reconstructed with the developed methodologies,and 95.6%PAS similarity can be achieved with 6 active probes.The satisfactory results demonstrate that the proposed algorithms are suitable for arbitrary channel emulation.

Detecting While Accessing:A Semi-Supervised Learning-Based Approach for Malicious Traffic Detection in Internet of Things

In the upcoming large-scale Internet of Things(Io T),it is increasingly challenging to defend against malicious traffic,due to the heterogeneity of Io T devices and the diversity of Io T communication protocols.In this paper,we propose a semi-supervised learning-based approach to detect malicious traffic at the access side.It overcomes the resource-bottleneck problem of traditional malicious traffic defenders which are deployed at the victim side,and also is free of labeled traffic data in model training.Specifically,we design a coarse-grained behavior model of Io T devices by self-supervised learning with unlabeled traffic data.Then,we fine-tune this model to improve its accuracy in malicious traffic detection by adopting a transfer learning method using a small amount of labeled data.Experimental results show that our method can achieve the accuracy of 99.52%and the F1-score of 99.52%with only 1%of the labeled training data based on the CICDDoS2019 dataset.Moreover,our method outperforms the stateof-the-art supervised learning-based methods in terms of accuracy,precision,recall and F1-score with 1%of the training data.

Generation of hyperentangled photon pairs based on lithium niobate waveguide

Generation of hyperentangled photon pairs is investigated based on the lithium niobate straight waveguide.We propose to use the nonlinear optical process of spontaneous parametric down-conversion(SPDC)and a well-designed lithium niobate waveguide structure to generate a hyperentangled(in the polarization dimension and the energy-time dimension)two-photon state.By performing numerical simulations of the waveguide structure and calculating the possible polarization states,joint spectral amplitudes(JSA),and joint temporal amplitudes(JTA)of the generated photon pair,we show that the generated photon pair is indeed hyperentangled in both the polarization dimension and the energy-time dimension.

Data Analysis of Network Parameters for Secure Implementations of SDN-Based Firewall

Software-Defined Networking(SDN)is a new network technology that uses programming to complement the data plane with a control plane.To enable safe connection,however,numerous security challenges must be addressed.Flooding attacks have been one of the most prominent risks on the internet for decades,and they are now becoming challenging difficulties in SDN networks.To solve these challenges,we proposed a unique firewall application built on multiple levels of packet filtering to provide a flooding attack prevention system and a layer-based packet detection system.This study offers a systematic strategy for wrapping up the examination of SDN operations.The Mininet simulator examines the effectiveness of SDN-based firewalls at various network tiers.The fundamental network characteristics that specify how SDN should operate.The three main analytical measures of the network are jitter,response time,and throughput.During regular operations,their behavior evaluates in the standard SDN conditions of Transmission Control Protocol(TCP)flooding and User Datagram Protocol(UDP)flooding with no SDN occurrences.Low Orbit Ion Cannon(LOIC)is applied to launch attacks on the transmission by the allocated server.Wireshark and MATLAB are used for the behavioral study to determine how sensitive the parameters are used in the SDN network and monitor the fluctuations of those parameters for different simulated scenarios.

Compact generation scheme of path–frequency hyperentangled photons using 2D periodical nonlinear photonic crystal

Hyperentanglement is a promising resource for achieving high capacity quantum communication.Here,we propose a compact scheme for the generation of path-frequency hyperentangled photon pairs via spontaneous parametric down-conversion(SPDC)processes,where six different paths and two different frequencies are covered.A two-dimensional periodicalχ^((2))nonlinear photonic crystal(NPC)is designed to satisfy type-Ⅰquasi-phase-matching conditions in the plane perpendicular to the incident pump beam,and a perfect phase match is achieved along the pump beam's direction to ensure high conversion efficiency,with theoretically estimated photon flux up to 2.068×10^(5) pairs·s^(-1)·mm^(-2).We theoretically calculate the joint-spectral amplitude(JSA)of the generated photon pair and perform Schmidt decomposition on it,where the resulting entropy S of entanglement and effective Schmidt rank K reach 3.2789 and 6.4675,respectively.Our hyperentangled photon source scheme could provide new avenues for high-dimensional quantum communication and high-speed quantum information processing.

Junction matters in hydraulic circuit bio-design of microfluidics

Microfluidic channels are at micrometer scales;thus,their fluid flows are laminar,resulting in the linear dependence of pressure drop on flow rate in the length of the channel.The ratio of the pressure drop to flow rate,referred to as resistance,depends on channel size and dynamic viscosity.Usually,a microfluidic chip is analogous to an electric circuit in design,but the design is adjusted to optimize channel size.However,whereas voltage loss is negligible at the nodes of an electric circuit,hydraulic pressure drops at the nodes of microfluidic chips by a magnitude are comparable to the pressure drops in the straight channels.Here,we prove by experiment that one must fully consider the pressure drops at nodes so as to accurately design a precise microfluidic chip.In the process,we numerically calculated the pressure drops at hydraulic nodes and list their resistances in the range of flows as concerned.We resorted to machine learning to fit the calculated results for complex junctions.Finally,we obtained a library of node resistances for common junctions and used them to design three established chips that work for single-cell analysis and for precision allocation of solutes(in gradient and averaging concentration microfluidic networks).Endothelial cells were stimulated by generating concentrations of adriamycin hydrochloride from the last two microfluidic networks,and we analyzed the response of endothelial cells.The results indicate that consideration of junction resistances in design calculation brings experimental results closer to the design values than usual.This approach may therefore contribute to providing a platform for the precise design of organ chips.