A document by Zeeshan Mumtaz . Click on the document to view its contents.

Abstract We illustrate the connection between image-texture and defined regions in a polar spatial frequency coordinate system. This is provided within the context of describing a non-parametric method for characterizing two-dimensional spectra of gray scaled images, described in part previously. The spectrum is divided into concentric radial bands of fixed bandwidth. Each band is summarized, producing a set of measures characterizing the image as a function of radial spatial frequency. This set of measures has a parallel multiscale description as texture in the image domain. This approach was modified to capture texture with directional attributes. This is a data reduction technique that gives a full accounting of the image variance as function of image texture and direction indexed to regions in the polar frequency plane. Application examples include analyzing the summarized spectrum graphically, making inter/intra image spectral comparisons, and evaluating spectral models. Simulated noise images, an image of peppers, and a gray scale image with well-defined linear structure were used to illustrate the principles.

In this paper an investigation into magnetic control (MC) of hard-switching (HS) DC-DC converters is carried out. The proposed control method is based on the modulation of the effective filter inductance of the converter when operating in discontinuous conduction mode (DCM). It is well known that the output characteristic of a HS DC-DC converter operating in DCM is dependent on the effective inductance of the output filter. This way, by using a variable inductance the output of the converter can be controlled. The proposed control method can be applied to any converter topology, namely buck, boost, buck-boost, flyback, forward, and so on. In this paper, the operation of the buck converter with MC is investigated in detail as a case study. This work proves that the proposed control method can be effectively used to control DC-DC converters on its own or by combination with other control parameters as duty cycle and/or frequency. An experimental prototype has been built to test the proposed control method and modeling process and to demonstrate its feasibility and possibilities.

This work develops a low-power and low-voltage differential Gm-C filter structure that effectively achieves selfcommon-mode control (SCC), including DC stabilization and common-mode (CM) rejection, without employing extra control circuitry. The structure relies upon an incorporation of voltageinverting amplifiers to make it inherently contain no CM positive feedback loops for DC stabilization, and to enable splitting of the core transconductors into pairs for CM signal rejection. A DC CM stability analysis reveals that stabilization of the SCC structure can be reached without any dedicated CM control circuitry. An analytical comparison on power consumption of a high-order lowpass Gm-C filter implemented using an inverter-based transconductor for the SCC structure and the same transconductor with a CM control network (the Nauta’s technique) for the conventional structure indicates theoretical overhead power saving by over 50%. Furthermore, an even higher overhead power saving at over 70Ên be achieved in the complex SCC Gm-C filter because no additional inverting amplifiers are required to eliminate CM positive feedback loops in the crossing transconductors for complexification. The impact of the inverting amplifiers on the noise and frequency characteristics as well as the compensation technique are outlined to enable design optimization. The SCC filter was verified via extensive simulations of a 5th-order 1.1-MHz elliptic complex filter in a 0.18-m CMOS process. As compared to the conventional filter counterpart with similar SNR (~63dB) and inband/out-of-band SFDRs (~52dB/56dB), the proposed structure yields an overhead power saving by 70% with an improved figure-of-merit over 40% under a 1-V supply.

This letter introduces a stochastic model to maximize the probability of message delivery over ever-changing communication scenarios in tactical networks. Our model improves modern tactical systems implementing store-and-forward mechanisms organized in a hierarchy of layers for messages, IP packets and radios. The goal is to compute close to optimal parameters for a transport protocol by computing the optimum redundancy for the user data-flow to overcome packet loss during changes in the link data rate, including disconnections. Experiments in a VHF network illustrate the numerical results from our model using messages with different sizes over two patterns of data rate change.

In this paper, we propose a distributed demand side management (DSM) approach for smart grids taking into account uncertainty in wind power forecasting. The smart grid model comprehends traditional users as well as active users (prosumers). Through a rolling-horizon approach, prosumers participate in a DSM program, aiming at minimizing their cost in the presence of uncertain wind power generation by a game theory approach. We assume that each user selfishly formulates its grid optimization problem as a noncooperative game. The core challenge in this paper is defining an approach to cope with the uncertainty in wind power availability. We tackle this issue from two different sides: by employing the expected value to define a deterministic counterpart for the problem and by adopting a stochastic approximated framework. In the latter case, we employ the sample average approximation technique, whose results are based on a probability density function (PDF) for the wind speed forecasts. We improve the PDF by using historical wind speed data, and by employing a control index that takes into account the weather condition stability. Numerical simulations on a real dataset show that the proposed stochastic strategy generates lower individual costs compared to the standard expected value approach. Postprint accepted for publication in IEEE Transactions on Control Systems Technology How to cite: P. Scarabaggio, S. Grammatico, R. Carli and M. Dotoli, (2021) “Distributed Demand Side Management With Stochastic Wind Power Forecasting, ”IEEE Transactions on Control Systems Technology, 2022. DOI: http://doi.org/10.1109/TCST.2021.3056751 © 2022 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Background The United Kingdom (UK) public sector has spent more than £3.2bn on digital, data and technology services since 2012. The UK public sector borrowing year ending March 2018 was at £41bn. The debt at the end of February 2019 was at £1785bn (Office of National Statistics, 2019) and because of this spiralling debt, the UK government had to implement austerity. Therefore, there was a need to address solutions to help the government implement austerity. For example, the NHS Digital (NHSD) annual report and accounts 2017 to 2018 reported an increase in expenditure for permanent staff, software development, IT maintenance and IT support. It is evident there is an increase in expenditure compared to their 2016 to 2017 report. This provides scope for reduction in expenditure. Objective This literature review aims to investigate if DevOps has the potential to transform public sector IT delivery and provide value for money to the taxpayer by reducing expenditure in software development, IT maintenance and IT support. We will also be reviewing the maturity of DevOps in its current form and address the benefits and downsides from a public sector perspective. Method Our literature review will apply the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P). We will accomplish a two-part study and apply thematic organisation of our literature. We will use databases recommended by the University of Portsmouth Library. Grey Literature will be included, but we will exclude untrustworthy literature, social media, broadcasting, and press media. Only literature with confirmed validity will be included for further research.

In this paper, we reveal the dynamic effects of time-varying plasma on low-frequency (LF) electromagnetic (EM) wave propagation. The time-varying attenuation, time-varying phase shift, and power spectrum of the LF EM waves are presented. By using the frequency division multiplexing method, LF EM waves at the four discrete frequencies simultaneously penetrate through a shared time-varying plasma in one shock tube experiment. The experimental results indicate that the time-varying attenuation and phase shift of the LF EM wave are determined by the time-varying behavior of the plasma, and they are positively related to the electron density and frequency of the LF EM waves. The theoretical results are well consistent with the experimental results. Moreover, in the frequency domain, the time-varying plasma causes spectrum expansion of the LF EM waves. These results help us deeply understand the propagation process of LF EM waves in time-varying plasma and design LF communication systems.

FPGAs are becoming a common sight in cloud environments and new usage paradigms, such as FPGA-as-a-Service, have emerged. This development poses a challenge to traditional FPGA security models, as these are assuming trust between the user and the hardware owner. Currently, the user cannot keep bitstream nor data protected from the hardware owner in an FPGA-as-a-service setting. This paper proposes a security model where the chip manufacturer takes the role of root-of-trust to remedy these security problems. We suggest that the chip manufacturer creates a Public Key Infrastructure (PKI), used for user bitstream protection and data encryption, on each device. The chip manufacturer, rather than the hardware owner, also controls certain security-related peripherals. This allows the user to take control over a predefined part of the programmable logic and set up a protected enclave area. Hence, all user data can be provided in encrypted form and only be revealed inside the enclave area. In addition, our model enables secure and concurrent multi-tenant usage of remote FPGAs. To also consider the needs of the hardware owner, our solution includes bitstream certification and affirming that uploaded bitstreams have been vetted against maliciousness.

Digital Audio Broadcasting via FM radio continues to be popular, even today, owing to its accessibility, especially in rural areas where even common feature phones and affordable radio receivers are able to freely receive both, mainstream and local vernacular transmissions without any subscription charge. Additionally, it is established that broadcasts undertaken at a local level can play an instrumental role in facilitating cultural expression and aiding information delivery at a local level However, local broadcasts via the current Community Radio Stations (CRS) are not only expensive but also unsuitable for remote, isolated regions with their rugged terrains. The authors hereby propose a novel approach to help address these current problems through a distributed system for Digital Audio Broadcasting. Multiple FM transmitting nodes (using VHF II: 87.5-100 MHz) form a WiFi Mesh Network to receive digital audio signals to broadcast from 1 hub node. The components used are off-the-shelf, cost-effective, and modular. It is more cost-effective than current CRS systems for mid-scale local broadcasts, with essentially no data loss between the transmitter units in deployment. Additionally, unlike relays, an existing alternative, built-in redundancy in the system ensures reliability, and caching protects against minor network disturbances when recordings are being broadcast. This approach allows for flexible and efficient deployments with wide, precise and accurate coverage, notably remaining equally effective in areas with an uneven terrain, thereby expanding its potential applications. Experiments involving the system were conducted by varying the audio samples and the conditions, for which the evaluation metrics included the PSNR, PSD spectrograms, DFTs, signal strength, and data transmission rate to gauge the transmission quality, range and scalability. Results included a moderate data rate of 12 mbits/s at a 100 metres separation with obstacles from the transmitter, which is sufficient for the broadcasting and fast caching of high-fidelity audio.

The recording performance of a new prototype magnetic tape based on perpendicularly oriented strontium ferrite particles is investigated using a 29 nm wide tunneling magnetoresistive reader. At a linear density of 702 kbpi, a post-detection byte-error rate of 2.8e-2 is demonstrated based on measured recording data and a software read channel. The read channel uses a 64-state implementation of an extended version of a data-dependent noise-predictive maximum-likelihood detection scheme that tracks the first and second order statistics of the data-dependent noise. At the demonstrated post-detection byte-error rate, a post-error-correction-coding byte-error rate of less than 1e-20 can be achieved using an iterative decoding architecture. To facilitate aggressive track-density scaling, we made multiple advances in the area of track following. First, we developed a new timing-based servo pattern and implemented a novel quad channel averaging scheme. Second, we developed a new field programmable gate array prototyping platform to enable the implementation of quad channel averaging. Third, we enhanced our low disturbance tape transport with a pair of 20 mm diameter air bearing tape guides and a prototype track-following actuator. Fourth, we developed a novel low friction tape head and finally, we designed a set of tape speed optimized track-following controllers using the model-based H∞ design framework. Combining these technologies, we achieved a position error signal (PES) characterized by a standard deviation ≤ 3.18 nm over a tape speed range of 1.2 to 4.1 m/s. This magnitude of PES in combination with a 29 nm wide reader enables reliable recording at a track width of 56.2 nm corresponding to a track density of 451.9 ktpi, for an equivalent areal density of 317.3 Gb/in2.

In this paper, we explore the use of an attention based mechanism known as Residual Attention for malware detection and compare this with existing CNN based methods and conventional Machine Learning algorithms with the help of GIST features. The proposed method outperformed traditional malware detection methods which use Machine Learning and CNN based Deep Learning algorithms, by demonstrating an accuracy of 99.25%.

These Event processing systems are much used in wide variety of applications in the processing of large stream of events. The most distinguished of applications is the time-series data management system with timely processing to identify trends, pattern matches and forecast future values.The complexity of event information, coupled with the fact that historical event data is being kept in the database, requires the use of an event processing model that provides the user with high-level abstractions. In this paper, I survey the StreamEPS to help developers and researchers alike to understand the conceptual view and processing of the event processing software system. StreamEPS forms part of Complex EventProcessing (CEP), Data Stream Management System (DSMS) and Information Flow Processing (IFP) domain.

This paper proposes an algorithm for the optimal operation of community energy storage systems (ESSs) using a machine learning (ML) model, by solving a nonlinear programming (NLP) problem iteratively to obtain synthetic data. The NLP model minimizes the network’s total energy losses by setting the operation points of a community ESS. The optimization model is solved recursively by Monte Carlo simulations in a distribution system with high PV penetration, considering uncertainty in exogenous parameters. Obtained optimal solutions provide the training dataset for a stochastic gradient boosting trees (SGBT) ML algorithm. The predictions obtained from the ML model have been compared to the optimal ESS operation to assess the model’s accuracy. Furthermore, the sensitivity of the ML model has been tested considering the sampling size and the number of predictors. Results showed an accuracy of 98% for the SGBT model compared to optimal solutions, even after a reduction of 83% in the number of predictors.

A new nonlinear circuit with frequency locking capability in the case of a generic quasi-periodic input, is presented. Due to this capability the circuit is called a Quasi-Periodic Locked Loop (Q-PLL). The locked frequency is parametrically selected from among those prescribed by the theory of resonances in dynamical systems. In particular, the locked frequency forms a three-frequency resonance with the frequencies of the quasi-periodic input. The circuit is able to lock also in case of deterministic perturbation (additional frequency components) and stochastic perturbation (wide-band noise). The circuit is closely related to the pitch perception of complex sound in humans and, as such, can be considered a bio-inspired device. From the point of view of applications, it may be considered as an extension of the Phase Locked Loop (PLL) with the additional ability of locking simultaneously to more than one frequency. Due to the dynamical and structural robustness of the locked states, the Q-PLL represents a tangible advance for the development of specific applications, for example, in medicine (hearing aids, and cochlear implants), in robotics (artificial senses), and in industrial and consumer electronics (improvement of speech intelligibility, pitch-based processing, etc.).

A document by Carlo Zannini . Click on the document to view its contents.

ABSTRACT Digital computing and allied communication tools have been phenomenal, but they are fast reaching their technical limits and also their capacity to solve certain extant complex problems. Quantum computing has now emerged with a touted potential to deal with aspects of the latter complex problems and also significantly transform extant computing and communication methods. Yet, little studies exist in the AEC industry related literature on quantum computing to boost awareness and also explore its prospective impact on the AEC industry. This paper discusses the underpinning basic concepts, technologies and trends in the quantum computing domain to build awareness to boost Architecture, Engineering and Construction (AEC) industry capacity on the topic. The paper dissects the challenges in this novel area. And also examines the near term practical opportunities and potential impact of quantum computing on the AEC industry. The paper concludes with suggestions for practice and future research.

The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.