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General theory of holographic inversion with linear frequency modulation (GHI-LFM) has been proposed recently, providing the framework for further advances in the holographic methods for image reconstruction with millimeter-wave linear frequency modulation (LFM) radar. Here, accelerated holographic imaging (AHI)-LFM, an AHI method for LFM radar that exploits range stacking, is proposed. The method is developed and validated for the purpose of whole-body security screening. The image quality and the computational efficiency are compared with the original GHI-LFM algorithm. It is demonstrated that the AHI-LFM algorithm improves the reconstruction speed by at least an order of magnitude while preserving the same image quality for the image sizes arising in practical whole-body security screening. [ABSTRACT FROM AUTHOR]

We present a general theory of the holographic image reconstruction with linear frequency modulation (LFM) radars. For the first time, the system limitations in terms of the object extent and distance are derived and explicitly related to the LFM radar frequency-modulation slope $\gamma $. The holographic inversion formula is improved to account for the spherical spread of the scattered wave. The theory and the generalized holographic inversion algorithm are validated by synthetic benchmark data as well as experimental data from an in-house LFM-radar prototype operating at 29.9-GHz central frequency and bandwidth of 5.8 GHz. Experiments confirm that the lateral spatial resolution is about 5 mm. For optimal performance, the system is calibrated using a simple but effective calibration approach based on a measurement with a metallic plate. Experiments, with a volunteer carrying metallic and nonmetallic objects, demonstrate very good performance in realistic scenarios. [ABSTRACT FROM AUTHOR]

With the rapid development of intelligent transportation systems, enormous amounts of delay-sensitive vehicular services have been emerging and challenge both the architectures and protocols of vehicular networks. However, existing cloud computing-embedded vehicular networks cannot guarantee timely data processing or service access, due to long propagation delay and traffic congestion at the cloud center. Meanwhile, the current distributed network architecture does not support scalable network management, leading the intelligent data computing policies to be undeployable. With this motivation, we propose to introduce fog computing into vehicular networks and define the Multiple Time-constrained Vehicular applications Scheduling (MTVS) issue. First, to improve the network flexibility and controllability, we introduce a Fog-based Base Station (FBS) and propose a Software-Defined Networking (SDN)-enabled architecture dividing the networks into network, fog, and control layers. To address MTVS issue, instead of normal centralized computing-based approaches, we propose to distribute mobile delay-sensitive task in data-level over multiple FBSs. In particular, we regard the fog layer of SDN-enabled network as an FBS-based network and propose to distribute the computing task based on the FBSs along multiple paths in the fog layer. By Linear Programming, we optimize the optimal data distribution/transmission model by formulating the delay computation model. Then, we propose a hybrid scheduling algorithm including both local scheduling and fog scheduling, which can be deployed on the proposed SDN-enabled vehicular networks. Simulation results demonstrate that our approach performs better than some recent research outcomes, especially in the success rate for addressing MTVS issue. [ABSTRACT FROM AUTHOR]

In underwater acoustic sensor networks (UASNs), the sensors are deployed at different areas of the ocean, which perform information collection and delay-sensitive routing to the data center for further processing or industrial computing. However, in UASNs, the network states have spatiotemporal characteristics due to tides or autonomous underwater vehicles. To steadily route the traffic especially when the spatiotemporal characteristics of the UASNs are considered, a network architecture with intelligent traffic engineering or routing policies is indispensable. In this paper, we employ software-defined networking (SDN) technology and propose an SDN-enabled distributed architecture for UASNs. Based on the proposed architecture, we propose a scheme DSR-SDN for delay-sensitive spatiotemporal routing in SDN-enabled UASNs. The DSR-SDN includes three phases: First, topology awareness; second, spatiotemporal characteristics estimation; and third, routing computation. Particularly, with SDN features, DSR-SDN provides topology awareness based on a proposed software-defined beaconing scheme. Based on the detected topology, the spatiotemporal characteristics of the network states are estimated based on a proposed SDN-based hierarchical node localizing approach SDN-HL. Lead by the SDN controllers, SDN-HL makes use of the proposed “minimum weighted gap” formulation and Adam algorithm to optimize the localization and builds the indirect links to increase the localization rate. To route the traffic through the network with spatiotemporal characteristics, we adopt the time-expanded network approach, based on which a spatiotemporal route decision can be made before the routing starts. The simulation results demonstrate that the proposed scheme, i.e., DSR-SDN, can conduct accurate spatiotemporal characteristic estimation for the network states and provide delay-sensitive spatiotemporal routing for the sensed data. [ABSTRACT FROM AUTHOR]

With advanced ICT, the ever-rapid development of informatization has become an integral part of smart city services in healthcare, transportation, energy, education, business, community life, and so on. A huge amount of data, called big data, is generated from various sources, and effective analysis and utilization of big data has become a key factor in the success of smart city services. However, in order to achieve precise big data analytics and make real-time decisions, one of the challenging issues is how to efficiently deliver the huge amounts of collected data to the processing servers. In this article, we first propose a novel architecture to support smart city services based on SDN technology. Then we study the time-constrained big data transfer scheduling (TBTS) problem under the proposed architecture, and present an intelligent strategy to address the TBTS issue by utilizing the SDN controller to conduct dynamic flow control and multi-path transfer scheduling. Simulation results demonstrate that the proposed strategy can efficiently support big data transfer in terms of low transfer delay and high bandwidth utilization. [ABSTRACT FROM PUBLISHER]

A model describing the time constant of a transmission-line integrator is presented. By representing the formulations of integrators in the discrete-time (or Z) domain, we implement the integrators with equal-length transmission lines. Three integrators with different time constants and frequency bands are built and tested. The experimental results are in good agreement with theoretical values. [ABSTRACT FROM AUTHOR]

A new adaptive critic autopilot design for bank-to. turn missiles is presented. In this paper, the architecture of adaptive critic learning scheme contains a fuzzy-basis-function-network based associative search element (ASE), which is employed to approximate nonlinear and complex functions of bank-to-turn missiles, and an adaptive critic element (ACE) generating the reinforcement signal to tune the associative search element. In the design of the adaptive critic autopilot, the control law receives signals from a fixed gain controller, an ASE and an adaptive robust element, which can eliminate approximation errors and disturbances. Traditional adaptive critic reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment, however, the proposed tuning algorithm can significantly shorten the learning time by on-line tuning all parameters of fuzzy basis functions and weights of ASE and ACE. Moreover, the weight updating law derived from the Lyapunov stability theory is capable of guaranteeing both tracking performance and stability. Computer simulation results confirm the effectiveness of the proposed adaptive critic autopilot. [ABSTRACT FROM AUTHOR]

Simple and accurate formulations are employed to represent discrete-time infinite impulse response processes of both first- and second-order differentiators in the Z-domain. These formulations, in conjunction with the representations of transmission-tine elements in the Z-domain, lead to transmission-line configurations that are eligible for wide-band microwave differentiators. Both the first- and second-order differentiators in microstrip circuits are implemented to verify this method. The experimental results are in good agreement with simulation values. [ABSTRACT FROM AUTHOR]

A synthesizing method is presented to design and implement digital dual-band filters in the microwave frequency range. A dual-band filter consists of a bandstop filter and a wide-band bandpass filter in a cascade connection, wherein the transfer functions of both the bandpass filter and bandstop filter are expressed in the Z domain. The bandstop filter is implemented by using a couple-serial-shunted line configuration. In particular, the bandwidth of each passband of the dual-band filter is controllable by adjusting the characteristics of both the bandpass filter and bandstop filter. By neglecting the dispersion effect between microstrip lines of different widths over a wide bandwidth, a dual-band filter is realized in the form of microstrip lines and its frequency responses are measured to validate this method. [ABSTRACT FROM AUTHOR]

High-quality CPNT is a key technology for deep-sea vehicles that dive into the deep sea and for detecting and developing the deep sea. At present, however, CPNT services for deep-sea vehicles are provided by separate communication, positioning, and navigation systems as well as separate synchronous clocks (atomic clocks). This directly affects the operational efficiency, for example, update rates of up to 0.125 Hz, of deep-sea vehicles engaged in deep-sea scientific research, environmental investigation, and resource development. Therefore, a new design method and operating mode of CPNT is proposed herein to overcome the inherent flaws of the current communication/positioning/navigation modes of deep-sea vehicles; meet the actual demands of deep-sea vehicles in real time; achieve high update rates, low power consumption, and high precision positioning and navigation; and to be combined with the current development trends. The integration of CPNT can both unify time and space references, and reduce the difficulty of multi-sensor information fusion. Thus, the problems of poor navigation and the non-timing functions of deep-sea vehicles can be solved fundamentally. The integration of CPNT will improve the navigation and positioning accuracy as well as the information update rate (up to 1 Hz) of large deep-sea vehicles, such as deepsea human-occupied vehicles, deep-sea remotely operated underwater vehicles, and deep-sea autonomous underwater vehicles. [ABSTRACT FROM AUTHOR]

With the remarkable advances in wireless communications and mobile electronic technologies, traveling users have been demanding continuous and seamless Internet access to enjoy multimedia services such as video streaming, voice over IP, online gaming, and so on, through handheld smart devices. Providing ubiquitous wireless connectivity to mobile users is indispensable to support continuous online services when vehicles move across various kinds of access networks. However, the high vehicle velocity and complex user mobility in the urban environment impose great challenges on designing an efficient mobility management scheme. In this article, we study the packet loss issue in IP mobility support for vehicular networks. We first give detailed descriptions of some major mobility management solutions. Then, we analyze user mobility models in the urban environment and identify the packet loss issue when traveling users roam across various access networks. By flexibly utilizing tunneling and buffering technologies, we correspondingly design a comprehensive solution to eliminate packet loss in each handover scenario of the urban environment. Finally, performance comparisons between the proposed scheme and related proposals have been conducted, which demonstrate a noteworthy potential of the presented scheme in eliminating packet loss and improving handover performance in urban vehicular communications. [ABSTRACT FROM AUTHOR]

The emerging real-time and computation-intensive services driven by the Internet of Things, augmented reality, automatic driving, and so on, have tight quality of service and quality of experience requirements, which can hardly be supported by conventional cloud computing. Fog computing, which migrates the features of cloud computing to the network edge, guarantees low latency for location-aware services. However, due to the locality feature of fog computing, maintaining service continuity when mobile users travel across different access networks has become a challenging issue. In this article, we propose a novel software-defined-networking-based fog computing architecture by decoupling mobility control and data forwarding. Under the proposed architecture, we design efficient signaling operations to provide seamless and transparent mobility support to mobile users, and present an efficient route optimization algorithm by considering the performance gain in data communications and system overhead in mobile fog computing. Numerical results from extensive simulations have demonstrated that the proposed scheme can not only guarantee service continuity, but also greatly improve handover performance and achieve high data communication efficiency in mobile fog computing. [ABSTRACT FROM PUBLISHER]

As transmission speeds increase faster than processing speeds, the packet processing time (PPT) of a host is becoming more significant in the measurement of different network parameters in which packet processing by the host is involved. The PPT of a host is the time elapsed between the arrival of a packet at the data-link layer and the time the packet is processed at the application layer (RFCs 2679 and 2681). To measure the PPT of a host, stamping the times when these two events occur is needed. However, time stamping at the data-link layer may require placing a specialized packet-capture card and the host under test in the same local network. This makes it complex to measure the PPT of remote end hosts. In this paper, we propose a scheme to measure the PPT of an end host connected over a single- or multiple-hop path and without requiring time stamping at the data-link layer. The proposed scheme is based on measuring the capacity of the link connected to the host under test. The scheme was tested on an experimental testbed and in the Internet, over a U.S. inter-state path and an international path between Taiwan and the U.S. We show that the proposed scheme consistently measures PPT of a host. [ABSTRACT FROM AUTHOR]

Submarine pipelines are among the most efficient methods of marine oil transportation, and they are widely used in offshore oil exploitation. However, the complex environment of the ocean and malicious attackers may damage the pipeline. They can be efficiently monitored by deploying a multiplicity of sensor nodes, organized in underwater acoustic sensor networks (UASNs). UASNs is located near oil wells, so that UASNs can sense, broadcast, and receive data surveying the status of the submarine infrastructure timely. Inevitably, UASNs may experience security problems, owing to the open nature of the underwater environment. To address these security issues, this paper proposes a new source location privacy protection scheme based on an offshore oil acquisition platform. In the proposed scheme, the nodes are defined as pipeline and environment locations, and are allocated to different clusters. The concept of forming anonymous clusters by exchanging the identities of a source and a cluster head is introduced to determine fake confounding sources. In addition, a data fragmentation method is devised to reduce the energy consumption resulting from fake packet transmission. Particularly, we propose the deployment of disguised AUVs that collect data from fake sources, as to conceal and protect the location of the actual sources. Simulation results show that the safety time of the network is increased by about 6%. Due to the adoption of the data fragmentation method, the energy consumption of nodes is also decreased. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) have attacted much attention in the field of wireless communication due to its agility and altitude. UAVs can be used as low-altitude aerial base stations (UAV-BSs) to provide communication services for ground devices (GDs) in various scenarios, such as emergency communication and traffic offloading in hotspots. However, due to the limited communication ranges and high prices of commercial UAV-BSs, covering a target area all the time with sufficient UAVs is quite challenging, especially under dynamic environment. We need to design the trajectory of the UAV-BSs to optimize system performance. Most existing works focus on the energy-efficient coverage and throughput maximization but ignore the fairness of communication service, especially the fairness at user-level. Besides, reinforcement learning is suitable for solving decision problems in dynamic environments. However, most existing works use centralized deep reinforcement learning (DRL) approaches. Due to the scalability and low time complexity, a distributed DRL approach is more suitable for multiple UAV-BSs communication system in dynamic environment. Unlike previous works, we characterize the fairness at user-level based on proportional fairness scheduling and formulate a weighted-throughput maximization problem via designing UAV-BSs’ trajectory. Then we model the dynamic deploymentproblem of UAV-BSs as a Markov game and propose a multi-agent deep reinforcement learning-based distributed UAV-BSs control approach named MAUC. MAUC approach adopts the framework of centralized training with distributed execution. Simulation results show that the MAUC can improve fairness of communication service by sacrificing a small amount of throughput. [ABSTRACT FROM AUTHOR]

The design and the electric and emission characteristics of a handheld air plasma spray are presented. The plasma is generated by 60-Hz periodic discharges between two concentrically cylindrical electrodes. A ring magnet is used to rotate arc discharges, which sprays outward by an airflow. The rotation of arc discharges keeps the generated plasma in nonequilibrium state and at relatively low temperature (\sim \!\!55\ ^\circ\C). The plasma effluent still contains high-energy electrons which dissociate molecular oxygen into atomic oxygen. The emission spectroscopy of the plasma plume reveals that the plasma effluent, which carries abundant atomic oxygen, extends from the cap of the plasma spray about 25 mm. Using pigs as the animal model, in vivo tests of stopping wound bleeding and postoperative observation of wound healing by this air plasma spray were performed. The results show that the bleeding from a cut to an ear artery is stopped swiftly; this air plasma spray also shortens wound healing time to about half (from 14 days to 8 days) after stopping the bleeding of a cross-cut wound in the ham area. [ABSTRACT FROM AUTHOR]

We have fabricated a high-Tc electronic planar gradiometer composed of dc SQUIDs on a 10 mm × 10 mm SrTiO3 bicrystal substrate. The SQUIDs were patterned in a single-layer YBa2Cu3Oτ-δ thin film which is prepared by pulsed laser deposition. The outputs of the magnetometers are added and subtracted by analog electronic circuits to form the gradiometer. These magnetometers could be used to construct two sets electronic planar first-order gradiometers or an electronic planar second-order gradiometer, which could measure the elements ∂Bz/∂x and ∂Bz/∂y or ∂² Bz/∂x∂y, respectively. The noise spectra of each magnetometer and a first-order electronic planar gradiometer were measured. [ABSTRACT FROM AUTHOR]

A space and terrestrial integrated network (STIN) converges satellite communication networks, mobile wireless networking, and the Internet, has greatly extended the scope of cyberspace. The STIN is composed of diverse network elements and supports various access technologies, and the coordinations in the hybrid networks can better support complex and changeable communication tasks. Furthermore, the STIN takes advantage of the merits of low delay and large bandwidth in terrestrial networks, and achieves global coverage without the limitation of geographic conditions, which can support positioning and navigation, emergency relief, space exploration, and so on. However, the research on STIN is still confronted with some fundamental challenges including time-varying network topology, high satellite mobility, large end-to-end delay, scalability, and so on. In this article, we present a composite architecture that integrates space and terrestrial network components for providing anytime anywhere communications by utilizing the software defined networking and mobile edge computing paradigms, which not only facilitates the network management and increases network flexibility, but also provides improved quality of service for global multimedia services. Additionally, we identify a number of challenging issues associated with the proposed STIN architecture, including mobility management, resource management, routing, traffic steering, security, and so on, a [ABSTRACT FROM AUTHOR]

A space and terrestrial integrated network (STIN) converges satellite communication networks, mobile wireless networking, and the Internet, has greatly extended the scope of cyberspace. The STIN is composed of diverse network elements and supports various access technologies, and the coordinations in the hybrid networks can better support complex and changeable communication tasks. Furthermore, the STIN takes advantage of the merits of low delay and large bandwidth in terrestrial networks, and achieves global coverage without the limitation of geographic conditions, which can support positioning and navigation, emergency relief, space exploration, and so on. However, the research on STIN is still confronted with some fundamental challenges including time-varying network topology, high satellite mobility, large end-to-end delay, scalability, and so on. In this article, we present a composite architecture that integrates space and terrestrial network components for providing anytime anywhere communications by utilizing the software defined networking and mobile edge computing paradigms, which not only facilitates the network management and increases network flexibility, but also provides improved quality of service for global multimedia services. Additionally, we identify a number of challenging issues associated with the proposed STIN architecture, including mobility management, resource management, routing, traffic steering, security, and so on, a [ABSTRACT FROM AUTHOR]