DOA estimation of incoherently distributed sources using importance sampling maximum likelihood

In this paper, an importance sampling maximum likelihood(ISML) estimator for direction-of-arrival(DOA) of incoherently distributed(ID) sources is proposed. Starting from the maximum likelihood estimation description of the uniform linear array(ULA), a decoupled concentrated likelihood function(CLF) is presented. A new objective function based on CLF which can obtain a closed-form solution of global maximum is constructed according to Pincus theorem. To obtain the optimal value of the objective function which is a complex high-dimensional integral,we propose an importance sampling approach based on Monte Carlo random calculation. Next, an importance function is derived, which can simplify the problem of generating random vector from a high-dimensional probability density function(PDF) to generate random variable from a one-dimensional PDF. Compared with the existing maximum likelihood(ML) algorithms for DOA estimation of ID sources, the proposed algorithm does not require initial estimates, and its performance is closer to CramerRao lower bound(CRLB). The proposed algorithm performs better than the existing methods when the interval between sources to be estimated is small and in low signal to noise ratio(SNR)scenarios.

Optimal Operation of Electric Vehicles and Distributed Generation Resources in Smart Grid Considering Load Management

Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply.Despite the complexity of their protection,as well as the operation of distributed generation resources in the distribution network,factors such as improving reliability,increasing production capacity of the distribution network,stabilizing the voltage of the distribution network,reducing peak clipping losses,as well as economic and environmental considerations,have expanded the influence of distributed generation(DG)resources in the distribution network.The location of DG sources and their capacity are the key factors in the effectiveness of distributed generation in the voltage stability of distribution systems.Nowadays,along with the scattered production sources of electric vehicles with the ability to connect to the network,due to having an energy storage system,they are known as valuable resources that can provide various services to the power system.These vehicles can empower the grid or be used as a storage supply source when parked and connected to the grid.This paper introduces and studies a two-stage planning framework for the concurrent management of many electric vehicles and distributed generation resources with private ownership.In the first stage,the aim is to increase the profit of electric vehicles and distributed generation sources;finally,the purpose is to reduce operating costs.The proposed scheduling framework is tested on a distribution network connected to bus 5 of the RBTS sample network.Besides distributed generation sources and electric vehicles,we integrate time-consistent load management into the system.Due to distributed generation sources such as photovoltaic systems and wind turbines and the studied design in the modeling,we use the Taguchi TOAT algorithm to generate and reduce the scenario to ensure the uncertainty in renewable energy.MATLAB software is used to solve the problem and select the optimal answer.

Source,migration,distribution,toxicological effects and remediation technologies of arsenic in groundwater in China

Groundwater with high arsenic(As) content seriously threatens human life and health. Drinking high-As groundwater for a long time will lead to various pathological changes such as skin cancer, liver cancer,and kidney cancer. High-As groundwater has become one of the most serious environmental geological problems in China and even internationally. This paper aims to systematically summarize the sources,migration, distribution, toxicological effects, and treatment techniques of As in natural groundwater in China based on a large number of literature surveys. High-As groundwater in China is mainly distributed in the inland basins in arid and semi-arid environments and the alluvial and lacustrine aquifers in river deltas in humid environments, which are in neutral to weakly alkaline and strongly reducing environments.The content of As in groundwater varies widely, and As(Ⅲ) is the main form. The main mechanism of the formation of high-As groundwater in China is the reduced dissolution of Fe and Mn oxides under the action of organic matter and primary microorganisms, alkaline environment, intense evaporation and concentration, long-term water-rock interaction, and slow groundwater velocity, which promote the continuous migration and enrichment of As in groundwater. There are obvious differences in the toxicity of different forms of As. The toxic of As(Ⅲ) is far more than As(V), which is considered to be more toxic than methyl arsenate(MMA) and dimethyl arsenate(DMA). Inorganic As entering the body is metabolized through a combination of methylation(detoxification) and reduction(activation) and catalyzed by a series of methyltransferases and reductases. At present, remediation methods for high-As groundwater mainly include ion exchange technology, membrane filtration technology, biological treatment technology, nanocomposite adsorption technology, electrochemical technology, and so on. All the above remediation methods still have certain limitations, and it is urgent to develop treatment materials and technical means with stronger As removal performance and sustainability. With the joint efforts of scientists and governments of various countries in the future, this worldwide problem of drinking-water As poisoning will be solved as soon as possible. This paper systematically summarizes and discusses the hot research results of natural high-As groundwater, which could provide a reference for the related research of high-As groundwater in China and even the world.

Passive Decoy-State Reference-Frame-Independent Quantum Key Distribution with Heralded Single-Photon Source

Reference-frame-independent(RFI)quantum key distribution(QKD)is a protocol which can share unconditional secret keys between two remote users without the alignment of slowly varying reference frames.We propose a passive decoy-state RFI-QKD protocol with heralded single-photon source(HSPS)and present its security analysis.Compared with RFI QKD using a weak coherent pulse source(WCPS),numerical simulations show that the passive decoy-state RFI QKD with HSPS performs better not only in secret key rate but also in secure transmission distance.Moreover,our protocol is robust against the relative motion of the reference frames as well as RFI QKD with the WCPS.In addition,we also exploit Hoeffding’s inequality to investigate the finite-key effect on the security of the protocol.

Using the KISO's Framework to Integrate Knowledge Sources

In complicated application environment such as CIMS (Computer Integrated Manufacture System) enterprise, it will bring great benefits to integrate distributed knowledge sources. But the difficulties of knowledge sharing and reuse seriously encumbrance the implementation of knowledge integration. In this paper, we describe how a framework of knowledge-integrated system based on ontology (KISO) can be used to support integrating distributed knowledge sources.

Temperature field model in surface grinding: a comparative assessment

Grinding is a crucial process in machining workpieces because it plays a vital role in achieving the desired precision and surface quality.However,a significant technical challenge in grinding is the potential increase in temperature due to high specific energy,which can lead to surface thermal damage.Therefore,ensuring control over the surface integrity of workpieces during grinding becomes a critical concern.This necessitates the development of temperature field models that consider various parameters,such as workpiece materials,grinding wheels,grinding parameters,cooling methods,and media,to guide industrial production.This study thoroughly analyzes and summarizes grinding temperature field models.First,the theory of the grinding temperature field is investigated,classifying it into traditional models based on a continuous belt heat source and those based on a discrete heat source,depending on whether the heat source is uniform and continuous.Through this examination,a more accurate grinding temperature model that closely aligns with practical grinding conditions is derived.Subsequently,various grinding thermal models are summarized,including models for the heat source distribution,energy distribution proportional coefficient,and convective heat transfer coefficient.Through comprehensive research,the most widely recognized,utilized,and accurate model for each category is identified.The application of these grinding thermal models is reviewed,shedding light on the governing laws that dictate the influence of the heat source distribution,heat distribution,and convective heat transfer in the grinding arc zone on the grinding temperature field.Finally,considering the current issues in the field of grinding temperature,potential future research directions are proposed.The aim of this study is to provide theoretical guidance and technical support for predicting workpiece temperature and improving surface integrity.

An image compression method for space multispectral time delay and integration charge coupled device camera

Multispectral time delay and integration charge coupled device(TDICCD) image compression requires a lowcomplexity encoder because it is usually completed on board where the energy and memory are limited.The Consultative Committee for Space Data Systems(CCSDS) has proposed an image data compression(CCSDS-IDC) algorithm which is so far most widely implemented in hardware.However,it cannot reduce spectral redundancy in multispectral images.In this paper,we propose a low-complexity improved CCSDS-IDC(ICCSDS-IDC)-based distributed source coding(DSC) scheme for multispectral TDICCD image consisting of a few bands.Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient.The output of bit plane extractor will be encoded by a first order entropy coder.Low-density parity-check-based Slepian-Wolf(SW) coder is adopted to implement the DSC strategy.Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.

Three-dimensional sound source localization using distributed microphone arrays

To improve the performance of sound source localization based on distributed microphone arrays in noisy and reverberant environments,a sound source localization method was proposed.This method exploited the inherent spatial sparsity to convert the localization problem into a sparse recovery problem based on the compressive sensing(CS) theory.In this method two-step discrete cosine transform(DCT)-based feature extraction was utilized to cover both short-time and long-time properties of the signal and reduce the dimensions of the sparse model.Moreover,an online dictionary learning(DL) method was used to dynamically adjust the dictionary for matching the changes of audio signals,and then the sparse solution could better represent location estimations.In addition,we proposed an improved approximate l_0norm minimization algorithm to enhance reconstruction performance for sparse signals in low signal-noise ratio(SNR).The effectiveness of the proposed scheme is demonstrated by simulation results where the locations of multiple sources can be obtained in the noisy and reverberant conditions.

Triboelectric-electromagnetic hybrid generator with swing-blade structures for effectively harvesting distributed wind energy in urban environments

The wind energy in cities cannot be exploited effectively because natural wind is unstable and complex.Therefore,a triboelectricelectromagnetic hybrid generator with swing-blade structures(SBS-TEHG)was designed to effectively harvest intermittent and continuous wind energy in an urban environment.First,the spring structure and base were considered to realize the maximum output performance of triboelectric nanogenerators.Then,the computational fluid dynamics method was applied to optimize the structure of the SBS-TEHG to improve its aerodynamic performance.The starting wind speed of the SBS-TEHG was 2 m/s,and its energy conversion efficiency was 9.04%,159%higher than that of the SBS-TEHG without guide plates at 4 m/s.The results demonstrated that the SBS-TEHG lit 105 light-emitting diodes(LEDs)under the intermittent-wind harvesting mode at a wind frequency of 1 Hz when the single swing blade operated,while a wireless PM_(2.5)&PM_(10)sensor was powered by the SBS-TEHG after a period of operation under the continuous-wind harvesting mode.The findings of this study provide a novel solution for lowspeed wind energy harvesting in cities and demonstrate the potential of SBS-TEHG as a distributed energy source.

Sources, distribution, and risk assessment of organochlorine pesticides in Nairobi City, Kenya

The distribution and sources of organochlorine pesticides (OCPs) in air and surface waters were monitored in Nairobi City using triolein-filled semipermeable membrane devices (SP-MDs).The SPMDs were extracted by dialysis using n-hexane,followed by cleanup by adsorption chromatography on silica gel cartridges.Sample analysis was done by GC-ECD and confirmed by GC–MS.Separation of means was achieved by analysis of variance,followed by pair-wise comparison using the t-test (p≤0.05).The total OCPs ranged between 0.018–1.277 ng/m^3 in the air andKibera>Industrial Area>City Square>Ngong’Forest.However,these were lower than the USEPA acceptable risks,10^(-6)–10^(-4).This study concluded that atmospheric OCPs did not pose significant cancer risks to the residents.

Proposed framework for blockchain technology in a decentralised energy network

The integration of distributed renewable energy sources into the conventional power grid has become a hot research topic, all part of attempts to reduce greenhouse gas emission. There are many distributed renewable energy sources available and the network participants in energy delivery have also increased. This makes the management of the new power grid with integrated distributed renewable energy sources extremely complex. Applying the technical advantages of blockchain technology to this complex system to manage peer-to-peer energy sharing, transmission, data storage and build smart contracts between network participants can develop an optimal consensus mechanism within the new power grid. This paper proposes a new framework for the application of blockchain in a decentralised energy network. The microgrid is assumed to be private and managed by local prosumers. An overview description of the proposed model and a case study are presented in the paper.