An intelligent Real-Time Sensing (RTS) system must continuously acquire, update, integrate, and apply knowledge to adapt to real-world dynamics. Managing distributed intelligence in this context requires Federated Continual Learning (FCL). However, effectively capturing the diverse characteristics of RTS data in FCL systems poses significant challenges, including severely impacting computational and communication resources, escalating energy costs, and ultimately degrading overall system performance. To overcome these challenges, we investigate how the data distribution shift from ideal to practical RTS scenarios affects Artificial Intelligence (AI) model performance by leveraging thegeneralization gapconcept. In this way, we can analyze how sampling time in RTS correlates with the decline in AI performance, computation cost, and communication efficiency. Based on this observation, we develop a novel Sample-driven Control for Federated Continual Learning (SCFL) technique, specifically designed for mobile edge networks with RTS capabilities. In particular, SCFL is an optimization problem that harnesses the sampling process to concurrently minimize the generalization gap and improve overall accuracy while upholding the energy efficiency of the FCL framework. To solve the highly complex and time-varying optimization problem, we introduce a new soft actor-critic algorithm with explicit and implicit constraints (A2C-EI). Our empirical experiments reveal that we can achieve higher efficiency compared to other DRL baselines. Notably, SCFL can significantly reduce energy consumption up to 85% while maintaining FL convergence and timely data transmission.

In personalized Federated Learning (pFL), high data heterogeneity can cause significant gradient divergence across devices, adversely affecting the learning process. This divergence, especially when gradients from different users form an obtuse angle during aggregation, can negate progress, leading to severe weight and gradient update degradation. To address this issue, we introduce a new approach to pFL design, namely Federated Learning with Layer-wise Aggregation via Gradient Analysis (FedLAG), utilizing the concept of gradient conflict at the layer level. Specifically, when layer-wise gradients of different clients form acute angles, those gradients align in the same direction, enabling updates across different clients toward identifying client-invariant features. Conversely, when layer-wise gradient pairs make create obtuse angles, the layers tend to focus on client-specific tasks. In hindsights, FedLAG assigns layers for personalization based on the extent of layer-wise gradient conflicts. Specifically, layers with gradient conflicts are excluded from the global aggregation process. The theoretical evaluation demonstrates that when integrated into other pFL baselines, FedLAG enhances pFL performance by a certain margin. Therefore, our proposed method achieves superior convergence behavior compared with other baselines. Extensive experiments show that our FedLAG outperforms several state-of-the-art methods and can be easily incorporated with many existing methods to further enhance performance.

This paper investigates double RIS-assisted MIMO communication systems over Rician fading channels with practical propagation conditions. Firstly, we derive the statistical channel information in closed form, which reveals the various influences of the system and the environment. Next, we study the active and passive beamforming designs for enhancing communication reliability. In particular, we propose a novel end-to-end design, where each 1-dimensional convolutional neural network (1D-CNN) represents a system entity that minimizes the symbol error rate by controlling the transceiver and RISs' phase shifts. Numerical results validate our analysis and demonstrate the superior improvements of phase shift designs to boost system performance. It is demonstrated that the proposed design can encode multiple data symbols simultaneously over different channel realizations and improve the SER performance without requiring channel information at the transmitter.

This paper investigates double RIS-assisted MIMO communication systems over Rician fading channels with finite scatterers, spatial correlation, and the existence of a double-scattering link between the transceiver. First, the statistical information is driven in closed form for the aggregated channels, unveiling various influences of the system and environment on the average channel power gains. Next, we study two active and passive beamforming designs corresponding to two objectives. The first problem maximizes channel capacity by jointly optimizing the active precoding and combining matrices at the transceivers and passive beamforming at the double RISs subject to the transmitting power constraint. In order to tackle the inherently non-convex issue, we propose an efficient alternating optimization algorithm (AO) based on the alternating direction method of multipliers (ADMM). The second problem enhances communication reliability by jointly training the encoder and decoder at the transceivers and the phase shifters at the RISs. Each neural network representing a system entity in an end-to-end learning framework is proposed to minimize the symbol error rate of the detected symbols by controlling the transceiver and the RISs’ phase shifts. Numerical results verify our analysis and demonstrate the superior improvements of phase shift designs to boost system performance.

This paper considers reconfigurable intelligent surface (RIS)-assisted point-to-point multiple-input multiple-output (MIMO) communication systems, where a transmitter communicates with a receiver through an RIS. Based on the main target of reducing the bit error rate (BER) and therefore enhancing the communication reliability, we study different model-based and data-driven (autoencoder) approaches. In particular, we consider a model-based approach that optimizes both active and passive optimization variables. We further propose a novel end-to-end data-driven framework, which leverages the recent advances in machine learning. The neural networks presented for conventional signal processing modules are jointly trained with the channel effects to minimize the bit error detection. Numerical results demonstrate that the proposed data-driven approach can learn to encode the transmitted signal via different channel realizations dynamically. In addition, the data-driven approach not only offers a significant gain in the BER performance compared to the other state-of-the-art benchmarks but also guarantees the performance when perfect channel information is unavailable.

Access and reuse of authoritative phylogenetic knowledge have been a longstanding challenges in the evolutionary biology community — leading to a number of research efforts (e.g. focused on interoperation, standardization of formats, and development of minimum reporting requirements). The Phylotastic project was launched to provide an answer to such challenges — as an architectural concept collaboratively designed by evolutionary biologists and computer scientists. This paper describes the first comprehensive implementation of the Phylotastic architecture, based on an open platform for Web services composition. The implementation provides a portal, which composes Web services along a fixed collection of workflows, as well as an interface to allow users to develop novel workflows. The Web services composition is guided by automated planning algorithms and built on a Web services registry and an execution monitoring engine. The platform provides resilience through seamless automated recovery from failed services.

This paper compares two types of channel modeling methods, which are the spatial channel modeling (SCM) and the Onering channel modeling method. These two well-known channel models are proposed for 4G wideband mobile communication networks. To compare the performance of these channel modeling methods, we analyze the properties of the spatial, temporal, frequency correlation functions simulated by using these methods. The correlation functions of the two channel models are compared in the same conditions of antenna arrangements. The simulation and calculation results show that the correlation functions of Onering and SCM channel models are very close to each other if the BS and the MS antenna arrays are parallel and perpendicular to the broadside of MS-BS. In other cases, the correlation functions of the two models are slightly different; however, their shapes are similar. These differences can be explained that the Onering model hardly fully describes all the characteristics of 4G channels as the performance SCM model does. The performance of these channel modeling methods is compared in system simulation level—MIMO-OFDMA systems. The combination SFBC-MMSE is used for spatial channel coding and the signal detection. The simulation results show that the system performance obtained by using these two channel models are comparable, given that the both modeled channels have same parameters and antenna directions. Copyright © 2016 John Wiley & Sons, Ltd.

The Doppler effect is caused by the relative movement between the transmitter (Tx) and the receiver (Rx) and/or the surface motion (waves) in underwater acoustic (UWA) communication systems. The inter-channel interference (ICI) caused by the Doppler effect degrades the performance of orthogonal frequency-division multiplexing (OFDM) systems over UWA channels. This paper is devoted to the ICI plus noise analysis of UWA-OFDM systems over a geometry-based channel model for shallow UWA channels. We carry out the exact calculation of the ICI power, ambient noise power, and required transmit power, as well as their effects on the performance of UWA-OFDM systems. The signal-to-interference ratio (SIR) and the signal-to-interference-plus-noise ratio (SINR) performance are analyzed for different relative speeds of the Tx and Rx, signal bandwidths, and carrier frequencies. The results show that the SIR not only depends on the maximum Doppler frequency but also on the signal bandwidth and the transmit power. The ICI power increases if the maximum Doppler frequency or the transmit power increases. If the bandwidth increases, the ICI power decreases, whereas the ambient noise power increases. Based on the simulation results, the system parameters can be optimized for the design of UWA-OFDM systems.

In this paper, a method for reducing false positive in computer-aided mass detection in screening mammograms is proposed. A set of 32 features, including First Order Statistics (FOS) features, Gray-Level Occurrence Matrix (GLCM) features, Block Difference Inverse Probability (BDIP) features, and Block Variation of Local Correlation coefficients (BVLC) are extracted from detected Regions-Of-Interest (ROIs). An optimal subset of 8 features is selected from the full feature set by mean of a filter-based Sequential Backward Selection (SBS). Then, Support Vector Machine (SVM) is utilized to classify the ROIs into massive regions or normal regions. The method’s performance is evaluated using the area under the Receiver Operating Characteristic (ROC) curve (AUC or AZ). On a dataset consisting about 2700 ROIs detected from mini-MIAS database of mammograms, the proposed method achieves AZ=0.938.

Abstract In this paper, we extend the geometrical one‐ring multiple‐input multiple‐output (MIMO) channel model with respect to frequency selectivity. Our approach enables the design of efficient and accurate simulation models for wideband space‐time MIMO channels under isotropic scattering conditions. Two methods will be provided to compute the parameters of the simulation model. Especially, the temporal, frequency and spatial correlation properties of the proposed wideband space‐time MIMO channel simulator are studied analytically. It is shown that any given specified or measured discrete power delay profile (PDP) can be incorporated into the simulation model. The high accuracy of the simulation model is demonstrated by comparing its statistical properties with those of the underlying reference model with specified correlation properties in the time, frequency and spatial domain. As an application example of the new MIMO frequency‐selective fading channel model, we study the influence of various channel model parameters on the system performance of a space‐time coded orthogonal frequency division multiplexing (OFDM) system. For example, we investigate the influence of the antenna element spacings of the base station (BS) antenna as well as the mobile station (MS) antenna. It turns out that an increasing of the antenna element spacing at the BS side results in a higher diversity gain than an increasing of the antenna element spacing at the MS side. Furthermore, the diversity gain brought in by space‐time block coding schemes is investigated by simulation. Our results show that transmitter diversity can significantly reduce the symbol error rate (SER) of multiple antenna systems. Finally, the influence of the Doppler effect and the impact of imperfect channel state information (CSI) on the system performance is also investigated. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper a novel decentralized and interference aware medium access control (MAC) protocol combined with a dynamic subchannel selection algorithm for OFDM (orthogonal frequency division multiplexing) is presented. The protocol resolves several drawbacks of the existing radio resource allocation techniques for OFDM systems, such as the hidden and exposed node problem, and the requirement for a time-invariant channel. The proposed scheme enables the transmitter to determine the level of interference it would cause to already active links prior to any transmission. This is achieved through a busyslot signaling that exploits the channel reciprocity offered by the TDD mode. Compared to existing radio resource allocation schemes the required signaling overhead is significantly reduced. The interference awareness allows the system to avoid significant co-channel interference (CCI) and to operate with full frequency reuse. When applied to a broadband OFDM air interface, this principle can also exploit the frequency selective fading channel on the intended as well as the interference links. This results in an autonomous subcarrier allocation algorithm which can dynamically adapt to time-varying channels. Due to its decentralized nature, the algorithm can be utilized in both cellular and ad hoc networks. Simulation results for a cellular system show that the new decentralized medium access and channel assignment algorithm is capable of achieving spectral efficiencies of up to 2.25 bits/Hz/cell using 16 QAM (quadrature amplitude modulation).

This paper proposes a new scheme based on information theoretical criteria to estimate the channel-impulse-response (CIR) length, whose accurate estimate represents one of the most important tasks for the realization of OFDM systems with adaptive guard interval. The difference between the statistical characteristics of the additive noise and the mobile radio channel is exploited for this task. In the proposed algorithm, the calculation of the autocorrelation matrix and their eigenvalues are not required. Therefore, the complexity of the proposed method is low. A modified penalty function is introduced to make the criteria more stable. Performance of the proposed method is evaluated for HiperLAN/2 channels. The simulation results show that the proposed algorithm is robust and delivers a precise estimate for the CIR length even at sever noisy environment with as low signal-to-noise ratio (SNR) as 0 dB. It delivers therefore reliable information for adaptive guard interval (GI) based OFDM systems and channel estimation

This paper proposes a new interference cancellation scheme which includes demodulation and modulation, and uses channel state information to enhance the cancellation performance. In the presence of strong additive noise, the available cancellers actually add more noise to the received signal than those that they removed (G.E.Bottomley et al., Dec. 25). However, the proposed canceller in no case generates additional symbol errors as compared to the case without cancellation. It yields better performance than the method presented in D. Kim and G.L. Stuber (Oct 1998), and improves the symbol error ratio for signal-to-noise ratios greater than 4.0 dB, instead of 6.5 dB in D. Kim and G.L. Stuber (Oct 1998).

This paper deals with the design of spatial simulation models for shadowing processes. Such processes are generally assumed to be lognormally distributed. The simulation model is derived from a reference model by using the sum-of-sinusoids principle. Analytical expressions are presented for the spatial autocorrelation function (ACF), probability density function (PDF), and the level-crossing rate (LCR) of both the reference and the simulation model. Two methods are discussed enabling the fitting of the simulation model to the reference model with respect to the PDF of the received signal strength as well as to a given spatial ACF with an exponential shape. The usefulness and the performance of the shadowing channel simulator is demonstrated by applying the proposed design method on two scenarios capturing the shadowing effects in suburban and urban areas.

In order to derive the mathematical description of interference and useful power in the case of insufficient guard length of an OFDM system, the channel impulse response is truncated into two parts, the so-called two truncated channels, in mathematical analysis. The first one describes the behaviour inside the guard interval, the other outside. Assuming the channel to be wide-sense stationary with uncorrelated scattering (WSSUS), the linear characteristic of Fourier transformation allows to be obtained exactly the mathematical expressions of intercarrier interference (ICI) power, P/sub ICI/, intersymbol interference (ISI) power, P/sub ISI/, and useful power, P/sub U/, in dependence of the correlation functions and the multipath channel profiles of the two truncated channels. We consider only the case of the time-invariant channel. The simulation results show a good agreement with the theoretical results.

In this paper, frequency and time interleaving algorithms used for soft decision Viterbi decoding for OFDM systems, performed on frequency-selective and time-selective channels respectively, are investigated. To achieve optimal performance in terms of the bit error rate (BER), the size of the interleavers must be specified depending on the properties of the channel and the characteristics of the code. Under these aspects, new frequency- and time interleaving algorithms are proposed. To get the lowest BER, we have found that the frequency interleaving length should be chosen in the range of the decoding constraint length. On the other hand, the time interleaving depth should be derived from the coherence time of the channel.

Manufacturing flaws of all types, shapes, and sizes can be exhaustively detected as abnormal pixels, if process and noise variations can be learned at every pixel in the inspection area. This statistical template approach to automated visual inspection is extremely fast, effective, and flexible, while achieving false negative rate <10/sup -6/. Critical to this approach are the following novel features: 1) represent both geometry and process information in a model template; 2) align 3D surfaces with subpixel accuracy; compensate for local deformation and texture; 4) estimate bimodal distribution robustly. This novel paradigm was applied to the automatic screening of X-ray images of turbine blades. It has been validated with over 50,000 images and shown to outperform regular inspectors looking at high-pass filtered images.

The concepts and design issues that provide the basis for the I/sup 2/F (image interpretation foundations) system are described. The I/sup 2/F system combines object-oriented design for machine vision software and constraint-based geometric modeling into a flexible and effective system for automatic template-guided visual inspection. Object-oriented design for 2-D geometry-based image analysis is discussed, and results from processing experimental X-ray data are presented.>

A generic polyhedral model is represented as a network of nodes and constraints. Nodes are 3-D vectors representing the location and orientation of the geometric entities, or measure variables such as length or cosine. Constraints are polynomial equations in the node parameters. Modeling and recognition are viewed as solving for values of the node parameters such that all the constraint equations are satisfied and the mean square error between the model and the observed shape is minimized. Buchberger's Grobner basis algorithm and Ritt-Wu's triangulation algorithm can be used for eliminating dependent parameters as well as for detecting inconsistency among constraints. Numerical techniques are used to find the best-fit model subject to constraints.>

Automation of the control of complex systems has been achieved through the application of computers using such tools as closed-loop control, finite-state machines, etc. However, a number of tasks in the control of such processes must still be performed by human operators, resisting conventional automation efforts. These tasks usually involve unforeseen circumstances, such as defective controller hardware or unusual behavior of the application being controlled. Operators often use experience or heuristic reasoning to cope with these types of process deviations. In this paper, we will describe the theory and design of a generic temporal/causal system called TEMPROS (TEMporal PROgramming System) used to perform intelligent real-time control, capable of assuming many of the responsibilities that are currently exclusively performed by human operators. The system uses temporal propositions as its reasoning mechanism, deviating from current temporal reasoning systems by adding the new state “potentially true” to the truth value of a proposition. In addition, the system employs a plan hierarchy and a “lazy instantiation” mechanism to achieve the performance needed to make intelligent decisions in real time. We shall also outline the application of TEMPROS to the domain of growing gallium arsenide crystals using the LEC process.

This paper presents fast and simple algorithms for directly constructing stable grasps in 3D. The synthesis of stable grasps constructs virtual springs at the contacts, such that the grasped object is stable, and has a desired stiffness matrix about its stable equilibrium. The paper develops a simple geometric relation between the stiffness of the grasp and the spatial configuration of the virtual springs at the contacts. The stiffness of the grasp also depends on whether the points of contact stick, or slide without friction on the edges of the object.

This paper presents fast and simple algorithms for directly constructing force-closure grasps based on the shape of the grasped object. The synthesis of force-closure grasps constructs independent regions of contact for the fingertips, such that the motion of the grasped object is totally constrained. A force-closure grasp implies equilibrium grasps exist. In the reverse direction, we prove that non-marginal equilibrium grasps with at least two soft-finger contacts, or three hard-finger contacts with friction are also force-closure grasps.

This paper addresses the problem of synthesizing stable grasps on arbitrary planar polygons. Each finger is a virtual spring whose stiffness and compression can be programmed. The contacts between the finger tips and the object are point contacts without friction. We prove that all force-closure grasps can be made stable, and it costs O(n) time to synthesize a set of n virtual springs such that a given force-closure grasp is stable. We can also choose the compliance center and the stiffness matrix of the grasp, and so choose the compliant behavior of the grasped object about its equilibrium. The planning and execution of grasps and assembly operations become easier and less sensitive to errors.

This paper addresses the problem of synthesizing planar grasps that have force closure. A grasp on an object is a force closure grasp if and only if we can exert, through the set of contacts, arbitrary force and moment on this object. Equivalently, any motion of the object is resisted by a contact force, that is the object cannot break contact with the finger tips without some non-zero external work. The force closure constraint is addressed from three different points of view: mathematics, physics, and computational geometry. The last formulation results in fast and simple polynomial time algorithms for directly constructing force closure grasps. We can also find grasps where each finger has an independent region of contact on the set of edges.