Interference suppression using a COLT signal processor

A new configuration of nonuniformly spaced array is presented. The array elements are placed on a line and arranged exponentially. The array characteristics are obtained in both the absence and presence of mutual coupling between the elements and clutter. Then, the transformation matrix is generated from both the virtual and the real array manifolds. Through this interpolation technique we perform signal of interest (SOI) estimation in the presence of interferers and clutter using a single snapshot of voltages computed at the feed points of the proposed array elements. This is very useful to reach a real time or near to real time situation. We can estimate SOI using the direct data domain least square (D3LS) method. This technique is applicable to narrowband and wideband signals. The performance and accuracy of the proposed technique is observed through simulated numerical examples

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

In radiotherapy and particle therapy, the stability of the beam energy must be checked routinely during quality assurance. This is of particular importance when varying the dose rate via the beam intensity of the accelerator in order to study the FLASH effect when comparing irradiations with conventional and ultra-high doserates. The standard method of energy verification based on the measurement of percent depth-dose curves in a water phantom is time-consuming and in the case of ultra-high dose-rate beams, may also present a non-negligible radiation protection problem. A compact, portable multileaf Faraday cup (MLFC) with 128 channels was developed for energy determination based on the measurement of depth-charge curves. Its design is optimized for clinical electron beams in a range between 3 and 25MeV. The read-out unit of the MLFC displays the beam energy in real time. The device was tested in strongly pulsed electron beams such as those present in irradiations with ultra-high doses per pulse as well as in conventional clinical electron beams. The same detector was used for proof of concept in a single measurement campaign in pulsed beams of therapeutical protons (conventional dose rates) from a synchrotron source using a suitable range shifter. The MLFC was calibrated with monoenergetic electron beams as well as against depth-dose curves. Simulations were carried out forcomparison. The MLFC works well under ultra-high pulse dose rate conditions as well as in conventional electron beams generated by a medical accelerator. Changes in the beam energy of below 20keV (0.1% of 20MeV) can be clearly identified by means of the MLFC. For proton beams, well-defined peaks in the depth-charge curves are observed for each single synchrotron spill with a total charge of only about 1nC. The energy values resulting from MC simulations of the measured MLFC data agree with the actual proton energies within 2 . The MLFC can be used for quick validation of the energy stability when carrying out experiments comparing electron beams of conventional and ultra-high dose rates. The same device can be used in the pulsed ion beams from asynchrotron.

An enzymatic microfluidic fuel cell was constructed to produce energy from lactate and oxygen preset in the sweat. In this case, laccase (Lc) connected to anthracene modified carbon nanotubes (An-MWCNT) to facilitate the direct electron transfer (DET) as the biocathode and lactate oxidase (LOx) as the bioanode, both enzymes were immobilized on Toray Carbon Paper (TCP). The oxygen reduction reaction (ORR) showed better results in a pH acid, which agrees with the slightly acid pH of sweat. On the other hand, the Lc showed to have good catalytic activity towards ORR in the presence of sweat, since only about 10% was inhibited after having added 660 µl of sweat. Finally, the enzymatic microfluidic fuel cell was capable to generate 64 µW cm-2 when sweat was fed into both electrodes, this confirms the high selectivity of the LOx and Lc towards lactate oxidation and oxygen reduction, respectively. These results are the first step to design an stamped device to produce energy in real time taking advantage of the sweat produced during workouts.

This position paper advocates for digital sobriety in the design and usage of wireless acoustic sensors. As of today, these devices all rely on batteries, which are either recharged by a human operator or via solar panels. Yet, batteries contain chemical pollutants and have a shorter lifespan than electronic components: as such, they hinder the autonomy and sustainability of the Internet of Sounds at large. Against this problem, our radical answer is to avoid the use of batteries altogether; and instead, to harvest ambient energy in real time and store it in a supercapacitor allowing a few minutes of operation. We show the inherent limitations of battery-dependent technologies for acoustic sensing. Then, we describe how a low-cost Micro-Controller Unit (MCU) could serve for audio acquisition and feature extraction on the edge. In particular, we stress the advantage of storing intermediate computations in ferroelectric random-access memory (FeRAM), which is nonvolatile, fast, endurant and consumes little. As a proof of concept, we present a simple-minded detector of sine tones in background noise, which relies on a fixed-point implementation of the fast Fourier transform (FFT). We outline future directions towards bioacoustic event detection and urban acoustic monitoring without batteries nor wires.

5 - Seismology-based acoustic emission techniques for the monitoring of fracture processes in concrete structures

Energy use has increased dramatically in recent years. As the world’s population grows, so does the need for electricity. The LSTM Algorithm is used to anticipate energy management and manage real-time energy in this paper and ANF control algorithm based smart grid to solve power quality issues is investigated in this paper. To maximize both power generations, back-to-back voltage source converters (VSC) are operated with an intelligent ANN controller. Optimal power converters are adopted this proposed methodology and improved overall performance of the system in a acceptable limit. The simulation results are obtained for different mode of smart grid and non-linear fault condition and proven proposed control algorithm works well. The information is presented as data sets. It has been discovered that a significant quantity of energy will be required in the future to train data, depending on the amount of energy consumed in the future. It has the ability to track training progress in real time. In order to forecast future events, this article used 440 daily energy consumption estimates and 250 iterations. MATLAB/Simulink is used to validate the results.

This article discusses the physical capabilities the building equipment must have in order to participate in real-time energy and reliability service markets. It also discusses the decision process the building operator will want to go through to minimize its energy costs, considering all of its options and costs. Since energy and contingency reserve prices are volatile, building owners and operators will want to move between these markets dynamically. It is likely that the decision process, while remaining under the building operators control, can be automated. Similarly, the requirements for price disclosure, communications, aggregation, monitoring, and certification on the bulk power system side are discussed. Finally, we discuss how the entire system could operate to the benefit of both the building owner and the power system. Restructuring of the electric power industry is presenting new opportunities that building owners and operators may wish to exploit. There are now more options than just average, seasonal, or time-of-use electricity prices. Bulk power markets now recognize that electricity prices change dramatically in real-time. Ancillary services (reliability services, such as short term contingency reserves) are also priced in real time. There are benefits to both the bulk power system and the individual customers when these markets are opened to participation by buildings. The bulk system benefits through the increased availability of reliability resources. Building owners and operators benefit through reduced energy costs, increased choice, and increased control over their own destiny. Les proprietaires ou exploitants de bâtiments peuvent reduire leur facture energetique, en utilisant les nouvelles possibilites du marche dereglemente. Ils peuvent concevoir et construire des systemes energetiques ayant une grande flexibilite, negocier des contrats tres flexibles pour leur approvisionnement energetique, gerer leur demande energetique en fonction de la variation en temps reel du prix de l'electricite, developper de petites capacites de production distribuee d'electricite ou d'accumulation de chaleur, qui peuvent etre revendues aux compagnies d'electricite lorsque le prix de l'electricite est eleve ou etre utilisees en cas de delestage.

Microgrid is a key enabling solution to future smart grids by integrating distributed renewable generators and storage systems to efficiently serve the local demand. However, due to the random and intermittent characteristics of renewable energy, new challenges arise for the reliable operation of microgrids. To address this issue, we study in this paper the real-time energy management for a single microgrid system that constitutes a renewable generation system, an energy storage system, and an aggregated load. We model the renewable energy offset by the load over time, termed net energy profile, to be practically predictable, but with finite errors that can be arbitrarily distributed. We aim to minimize the total energy cost (modeled as sum of time-varying strictly convex functions) of the conventional energy drawn from the main grid over a finite horizon by jointly optimizing the energy charged/discharged to/from the storage system over time subject to practical load and storage constraints. To solve this problem in real time, we propose a new off-line optimization approach to devise the online algorithm. In this approach, we first assume that the net energy profile is perfectly predicted or known ahead of time, under which we derive the optimal off-line energy scheduling solution in closed-form. Next, inspired by the optimal off-line solution, we propose a sliding-window based online algorithm for real-time energy management under the practical setup of noisy predicted net energy profile with arbitrary errors. Finally, we conduct simulations based on the real wind generation data of the Ireland power system to evaluate the performance of our proposed algorithm, as compared with other heuristically designed algorithms, as well as the conventional dynamic programming based solution.

The subject of research in this article is the process of building a mobile communication system that operates under electronic countermeasures. The aim is to develop recommendations for building a wireless mobile communication system that operates effectively in a complex interfering electromagnetic environment. The strategy for building a mobile wireless communication system is based on the use of a grouping of low-altitude UAVs with ultra-wideband signal technology circulating in control and communication channels, with the integration of artificial intelligence elements into its structure. The objective of this study is to ensure the stable and secure operation of a wireless mobile communication system despite electronic countermeasures. The methods of analytical, temporal positional pulse coding, and fuzzy logical inference were used to make decisions on the transfer of service in the network. The following results were obtained. A strategy for building a wireless mobile communication system despite electronic countermeasures has been developed. It is shown that in order to obtain high noise immunity of control and communication channels and to protect information from interception, wireless ultra-wideband communication technology should be used. This will provide large volumes and speeds of information transmission. A technical solution for the design of an ultra-wideband transceiver antenna system is proposed. Moreover, it is recommended to use the results of data processing in a fuzzy decision-making system for the transfer of service between mobile network nodes in conditions of interference. Conclusions. The scientific novelty of the obtained results is as follows. The use of ultra-wideband channels makes it possible to increase the number of control and communication channels in a wireless mobile system almost unlimitedly. The preliminary distribution of orthogonal codes between the channels realizes the process of control and communication without the interception of information and mutual interference. The use of the time-position-pulse coding method prevents the occurrence of intercharacter distortions of the encoding ultrashort pulses. This also reduces the level of distortion of information signals caused by multipath propagation, which guarantees the security of information in the system. The use of a fuzzy decision-making system for the transfer of services between mobile network nodes allows dynamically changing the network topology in real time and maintaining high quality of service under electronic countermeasures.

<p>Digital water and energy maps allow fast information retrieval, big data analysis and resources demand prediction for real time responses in 5-G networks. A regulatory systems framework is needed to enable and promote integrated actions grounded on map-based feedback information, to facilitate resources movements and knowledge transfer for water and energy security. At the same time, the proposed regulatory system needs to safeguard national security and personal privacy when general public and the private sectors have access to big databases.</p><p>The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China is an initiative on regional economic development involving nine mainland cities and two Special Administrative Regions (SARs). As central policies cannot be efficiently executed in the whole regions, institutional fragmentation could be a prominent barrier to achieve regional water and energy optimum rather than individual city maxima for the water and energy nexus.</p><p>In this study, we propose a systems regulatory framework that integrates natural, urban and social systems across multiple scales in which the relevant laws, policies, decisions and actions are supported by digital maps. On a planning scale, our new regulatory system based on spatial map information promotes optimum uses of natural capitals and ecosystem services (ES). For linking different urban spatial processes on different scales, satellite images and Local Climate Zone (LCZ) maps are used to describe natural environment and urban characteristics from 200km to 10km resolutions for supporting land-use planning laws and estimating regional development carrying capacity to mitigate water and energy insecurity.</p><p>On an operational scale, smart meters and remote sensor systems provide real time water and energy information from a fast developing 5-G network for the proposed digital maps. Forecasted energy and water demands from the digital maps can be used for regional or local environment regulation reinforcement. Proposed spatial maps also improve transboundary collaboration by providing visualisation of legal targets and emission limits. Through digital maps, key agencies and sectors will have a capacity to share transboundary knowledge, information and responsibility, to foster smooth system flows in terms of culture, economy, policy and technology, by active participations and decentralized actions.</p><p>On an evaluation scale, open map information increases the transparency of legal targets and pollution limits. By rapid information retrieval and big data analysis from digital maps, regulators can assess the performance of water and energy security practices.</p><p>In summary, the proposed framework based on LCZ maps for the GBA can be applied to other rapidly developing regions with emerging 5-G networks. The integrated regulatory framework also guides water and energy security practices and transfer central policies to local actions by rapid information retrieval, big data analysis and prediction of demand for real time responses based on digital water and energy maps.</p><p></p><p></p><p></p><p></p><p></p>

Day-ahead load and wind power forecasts provide useful information for operational decision making, but they are imperfect and forecast errors must be offset with operational reserves and balancing of (real time) energy. Procurement of these reserves is of great operational and financial importance in integrating large-scale wind power. We present a probabilistic method to determine net load forecast uncertainty for day-ahead wind and load forecasts. Our analysis uses data from two different electric grids in the US with similar levels of installed wind capacity but with large differences in wind and load forecast accuracy, due to geographic characteristics. We demonstrate that the day-ahead capacity requirements can be computed based on forecasts of wind and load. For 95% day-ahead reliability, this required capacity ranges from 2100 to 5700 MW for ERCOT, and 1900 to 4500 MW for MISO (with 10 GW of installed wind capacity), depending on the wind and load forecast values. We also show that for each MW of additional wind power capacity for ERCOT, 0.16–0.30 MW of dispatchable capacity will be used to compensate for wind uncertainty based on day-ahead forecasts. For MISO (with its more accurate forecasts), the requirement is 0.07–0.13 MW of dispatchable capacity for each MW of additional wind capacity.

Human behavior, both individually and socially, is aimed at maximizing some objective functions, and this is directly reflected in energy dynamics. New issues are emerging now, such as the unpredictability of some renewable sources generation and the new technologies enabling real time energy optimized use in smart cities. Here the role of the Future Internet in the smart grids is addressed, in particular enlightening how the anticipatory knowledge of the future occurrences of the energy consumption dynamics may be effectively promptly exchanged between competing actors.

Class I major histocompatibility complex (MHC) heterodimer, composed of human leukocyte antigen (HLA)-A2 heavy chain and human beta(2)-microglobulin (beta(2)m), was produced by denaturation and gel filtration of the recombinant water-soluble HLA-A2/beta(2)m/peptide ternary complex in 8 M urea Tris-HCl buffer, followed by refolding of the separated chains without peptide. Peptide affinity and kinetics of the ternary complex formation and dissociation were investigated in real time by monitoring the fluorescence resonance energy transfer (FRET) from intrinsic HLA-A2 heavy-chain tryptophans to a dansyl fluorophore conjugated to the bound peptide. Peptide binding to the heterodimer was a second order process with rate constants linearly dependent upon temperature in Arrhenius coordinates over 0-20 degrees C. The binding rate constant of pRT6C-dansyl [ILKEPC(dansyl)HGV] at 37 degrees C evaluated by extrapolation of the Arrhenius plot was (2.0 +/- 0.5) x 10(6) M(-1) s(-1). Association of the heavy chain with beta(2)m was a first order process, apparently controlled by a conformational transition in the heavy chain. One of these conformations bound to beta(2)m to form the heavy chain/beta(2)m heterodimer whereas the second conformer oligomerized. Peptide dissociation from the ternary complex was a first-order reaction over the temperature range 20-37 degrees C, suggesting that the ternary complex also exists in two conformations. Taken together, the present data suggest that association of beta(2)m changes the HLA-A2 heavy-chain conformation thereby promoting peptide binding. Peptide dissociation from the ternary complex induces dissociation of the heavy-chain/beta(2)m heterodimer thereby causing oligomerization of the heavy chain. The lability of the HLA-A2/beta(2)m heterodimer and the strong tendency of the "free" heavy chain to oligomerize may provide an efficient mechanism for control of antigen presentation under physiological conditions by reducing the direct loading of HLA with exogenous peptide at the cell surface.

Smart energy technologies, services, and business models are being developed to reduce energy consumption and emissions of CO2 and greenhouse gases and to build a sustainable environment. Renewable energy is being actively developed throughout the world, and many intelligent service models related to renewable energy are being proposed. One of the representative service models is the energy prosumer. Through energy trading, the demand for renewable energy and distributed power is efficiently managed, and insufficient energy is covered through energy transaction. Moreover, various incentives can be provided, such as reduced electricity bills. However, despite such a smart service, the energy prosumer model is difficult to expand into a practical business model for application in real life. This is because the production price of renewable energy is higher than that of the actual grid, and it is difficult to accurately set the selling price, restricting the formation of the actual market between sellers and consumers. To solve this problem, this paper proposes a small-scale energy transaction model between a seller and a buyer on a peer-to-peer (P2P) basis. This model employs a virtual prosumer management system that utilizes the existing grid and realizes the power system in real time without using an energy storage system (ESS). Thus, the profits of sellers and consumers of energy transactions are maximized with an improved return on investment (ROI), and an intelligent demand management system can be established.