Cross layer cooperative protocol which exploits the benefits of physical layer cooperative communication, is one of the widely recognized MAC layer protocol design strategies for future wireless networks. This paper presents performance analysis of a cooperative mac and these performance parameters are compared those of the legacy IEEE 802.11 DCF MAC. Appropriate relay station selection is the main hurdle in designing efficient cooperative MAC protocol for wireless networks. This cooperative mac demonstrated that intermediate relay nodes themselves can initiate cooperation for relaying data frame to the receiver on behalf of the sender. This procedure makes the selection process of a “helper node” more distributed in nature as well as it contributes to increase throughput of a wireless network by reducing the overheads that are usually incurred in the helper selection process. It has been shown by thorough analytical analysis that the proposed cooperative MAC protocol offers higher throughput and lower frame transmission delay in both ideal and error prone wireless environment. These performance metrics are also evaluated while the wireless nodes are mobile as well.
The article refers to the idea of using the software defined network (SDN) as an effective hardware and software platform enabling the creation and dynamic management of distributed ICT infrastructure supporting the rapid prototyping process. The authors proposed a new layered reference model remote distributed rapid prototyping that allows the development of heterogeneous, open systems of rapid prototyping in a distributed environment. Next, the implementation of this model was presented in which the functioning of the bottom layers of the model is based on the SDN architecture. Laboratory tests were carried out for this implementation which allowed to verify the proposed model in the real environment, as well as determine its potential and possibilities for further development. Thus, the approach described in the paper may contribute to the development and improvement of the efficiency of rapid prototyping processes which individual components are located in remote industrial, research and development units. Thanks to this, it will be possible to better integrate production processes as well as optimize the costs associated with prototyping. The proposed solution is also a response in this regard to the needs of industry 4.0 in the area of creating scalable, controllable and reliable platforms.
Human brain is “the perfect guessing machine” (James V. Stone (2012) Vision and Brain, Cambridge, Mass: The MIT Press, p. 155), trying to interpret sensory data in the light of previous biases or beliefs. Bayesian inference is carried out by three complex networks of the human brain: salience network, central executive network, and default mode network. Their function is analysed both in neurotypical person and Attention Deficit Disorder. Modern human being having predictive brain and overloaded mind must develop social identity, whose evolution went probably through three stages: social selection based on punishment, sexual selection based on reputation, and group selection based on identity.
The level of sales of a given good depends largely on the distribution network. An analysis of the distribution network allows companies to optimize business activity, which improves the efficiency and profitability of a company’s sales with an immediate effect on profit growth. The so-called spatial analysis is highly useful in this regard. The paper presents an analysis of the network of authorized dealers of the Polish Mining Group for the Opolskie Province. The analysis was done using GIS (SIP) tools. The purpose of the analysis was to present tools that could be used to verify an existing distribution network, to optimize it, or to create a new sales outlet. The prresented tools belong to GIS operations used to process data stored in Spatial Information System resources. These are so-called geoprocessing tools. The article contains several spatial analyses, which results in choosing the optimum location of the distribution point in terms of the defined criteria. The used tools include a spatial intersection and sum. Geocoding and the so-called cartodiagram were also used. The presented analysis can be performed for both the network of authorized retailers within a region, a city or an entire country. The presented tools provide the opportunity to specify the target consumers, areas where they are located and areas of potential consumer concentration. This allows the points of sale in areas with a high probability of finding new customers to be located, which enables the optimal location to be chosen, for example, in terms of access to roads, rail transport, locations of the right area and neighborhood. Spatial analysis tools will also enable the coal company to verify its already existing distribution network.
A gigantic amounts of data and information on molecules that constitute the very complex cell machinery have been collected, classified and stored in data banks. Although we posses enormous amount of knowledge about the properties and functions of thousands of molecular entities, we are still far from understanding how they do work in a living cell. It is clear now that these molecules (genes, proteins) are not autonomous, that there is no direct linear relation between genotype and phenotype, and that the majority of functions are carried and executed by concerted molecular activity, and that the majority of diseases are multifactorial. A basic property of the matter in a living cell (both normal and pathologic) is an interaction between variety of macromolecules, mainly proteins, genes (DNA) etc. In a process of self-organization they are able to form an active molecular biologic system – a complex, labile and dynamic network which integrity is secured by non-covalent bounds. In this essay some basic properties of network structure and the universal rules that govern them are described. Network or system biology is promising new research approach in biology and medicine.
Rockburst is a common engineering geological hazard. In order to evaluate rockburst liability in kimberlite at an underground diamond mine, a method combining generalized regression neural networks (GRNN) and fruit fly optimization algorithm (FOA) is employed. Based on two fundamental premises of rockburst occurrence, depth, σθ, σc, σt, B1, B2, SCF, Wet are determined as indicators of rockburst, which are also input vectors of GRNN model. 132 groups of data obtained from rockburst cases from all over the world are chosen as training samples to train the GRNN model; FOA is used to seek the optimal parameter σ that generates the most accurate GRNN model. The trained GRNN model is adopted to evaluate burst liability in kimberlite pipes. The same eight rockburst indicators are acquired from lab tests, mine site and FEM model as test sample features. Evaluation results made by GRNN can be confirmed by a rockburst case at this mine. GRNN do not require any prior knowledge about the nature of the relationship between the input and output variables and avoid analyzing the mechanism of rockburst, which has a bright prospect for engineering rockburst potential evaluation.
The paper presents the concept of vital cities in the context of mechanisms of sustainable development, networking and creativity. The vital city was presented as: - a city belonging to the inhabitants – a city managed and developed with advanced processes of participation, - a city of reasonable management – a city that uses and at the same time protects its key potentials, - a city of creation – a city of creating and implementing new ideas, - a city of opportunities – a city that creates the conditions for the use of energy and creativity residents, - a city in the surround – a city with a strong position in the environment.
This paper presents a new OpenFlow controller: the Distributed Active Information Model (DAIM). The DAIM controller was developed to explore the viability of a logically distributed control plane. It is implemented in a distributed way throughout a software-defined network, at the level of the switches. The method enables local process flows, by way of local packet switching, to be controlled by the distributed DAIM controller (as opposed to a centralised OpenFlow controller). The DAIM ecosystem is discussed with some sample code, together with flowcharts of the implemented algorithms. We present implementation details, a testing methodology, and an experimental evaluation. A performance analysis was conducted using the Cbench open benchmarking tool. Comparisons were drawn with respect to throughput and latency. It is concluded that the DAIM controller can handle a high throughput, while keeping the latency relatively low. We believe the results to date are potentially very interesting, especially in light of the fact that a key feature of the DAIM controller is that it is designed to enable the future development of autonomous local flow process and management strategies.
In the last decade, Poland has become one of the most active markets for unconventional hydrocarbon deposits exploration. At present, there are twenty concessions for the exploration and/or discovery of reserves, including shale gas. The area covered by exploration concessions constitutes ca. 7.5% of the country’s area. Four main stages can be distinguished In the shale gas development and exploitation project: the selection and preparation of the place of development of the wells, hydraulic drilling and fracturing, exploitation (production) and marketing, exploitation suppression and land reclamation. In the paper, the concept of cost analysis of an investment project related to the exploration and development of a shale gas field/area was presented. The first two stages related to the preparatory work, carried out on the selected site, as well as drilling and hydraulic fracturing were analyzed. For economic reasons, the only rational way to make shale gas reserves available is to use horizontal drilling, either singly or in groups. The number of drilling pads covering the concession area is a fundamental determinant of the development cost of the deposit. In the paper, the results of the cost analysis of various types of reaming method with an area of 25,000,000 m2 were presented. Cost estimates were prepared for two variants: group drilling for three types of drilling pads: with three, five and seven wells and for single wells. The results show that, as the number of horizontal wells increases, the total cost of the development of the deposit is reduced. For tree-wells pad, these costs are 7% lower than in the second variant, for five-well pads they are 11% lower, and for seven-well pads they are 11.5% smaller than in the second variant. Authors, using applied methodology, indicate the direction of further research that will enable the optimization of shale gas drilling operations.
This article analyses a hierarchical structure of academia within two academic social media networking sites, i.e. Academia.edu and ResearchGate. In this study, I investigate profiles (in these two services) of all academic staff members of Adam Mickiewicz University in Poznań (N = 2661). I use the concept of prestige to analyse whether the hierarchical structure of academia is being reproduced in analysed services. Since prestige is an unobservable construct, I use two indicators to measure it: the number of followers and the number of views. My findings show that the hierarchical structure differs between Academia.edu and Research- Gate. While the structure of ResearchGate is explicitly hierarchical in reference to degrees of the researchers (a higher degree is related to a higher value of the prestige indicators), the structure of Academia.edu resembles a reversed pyramid (a higher degree is related to a lower value of the prestige indicators). The article concludes with a discussion concerning possible causes of differences between services in terms of reproducing the hierarchical structure. Moreover, I provide potential implications of the results as well as the justification of the necessity of using the concept of prestige to determine hierarchical structure of academia.
In the last few years, a great attention was paid to the deep learning Techniques used for image analysis because of their ability to use machine learning techniques to transform input data into high level presentation. For the sake of accurate diagnosis, the medical field has a steadily growing interest in such technology especially in the diagnosis of melanoma. These deep learning networks work through making coarse segmentation, conventional filters and pooling layers. However, this segmentation of the skin lesions results in image of lower resolution than the original skin image. In this paper, we present deep learning based approaches to solve the problems in skin lesion analysis using a dermoscopic image containing skin tumor. The proposed models are trained and evaluated on standard benchmark datasets from the International Skin Imaging Collaboration (ISIC) 2018 Challenge. The proposed method achieves an accuracy of 96.67% for the validation set .The experimental tests carried out on a clinical dataset show that the classification performance using deep learning-based features performs better than the state-of-the-art techniques.
Usually, cellular networks are modeled by placing each tier (e.g macro, pico and relay nodes) deterministically on a grid. When calculating the metric performances such as coverage probability, these networks are idealized for not considering the interference. Overcoming such limitation by realistic models is much appreciated. This paper considered two- tier twohop cellular network, each tier is consisting of two-hop relay transmission, relay nodes are relaying the message to the users that are in the cell edge. In addition, the locations of the relays, base stations (BSs), and users nodes are modeled as a point process on the plane to study the two hop downlink performance. Then, we obtain a tractable model for the k-coverage probability for the heterogeneous network consisting of the two-tier network. Stochastic geometry and point process theory have deployed to investigate the proposed two-hop scheme. The obtained results demonstrate the effectiveness and analytical tractability to study the heterogeneous performance.
Mining ventilation should ensure in the excavations required amount of air on the basis of determined regulations and to mitigate various hazards. These excavations are mainly: longwalls, function chambers and headings. Considering the financial aspect, the costs of air distribution should be as low as possible and due to mentioned above issues the optimal air distribution should be taken into account including the workers safety and minimization of the total output power of main ventilation fans. The optimal air distribution is when the airflow rate in the mining areas and functional chambers are suitable to the existing hazards, and the total output power of the main fans is at a minimal but sufficient rate. Restructuring of mining sector in Poland is usually connected with the connection of different mines. Hence, dependent air streams (dependent air stream flows through a branch which links two intake air streams or two return air streams) exist in ventilation networks of connected mines. The zones of intake air and return air include these air streams. There are also particular air streams in the networks which connect subnetworks of main ventilation fans. They enable to direct return air to specified fans and to obtain different airflows in return zone. The new method of decreasing the costs of ventilation is presented in the article. The method allows to determine the optimal parameters of main ventilation fans (fan pressure and air quantity) and optimal air distribution can be achieved as a result. Then the total output power of the fans is the lowest which makes the reduction of costs of mine ventilation. The new method was applied for selected ventilation network. For positive regulation (by means of the stoppings) the optimal air distribution was achieved when the total output power of the fans was 253.311 kW and for most energy-intensive air distribution it was 409.893 kW. The difference between these cases showed the difference in annual energy consumption which was 1 714 MWh what was related to annual costs of fan work equaled 245 102 Euro. Similar values for negative regulation (by means of auxiliary fans) were: the total output power of the fans 203.359 kW (optimal condition) and 362.405 kW (most energy-intensive condition). The difference of annual energy consumption was 1 742 MWh and annual difference of costs was 249 106 Euro. The differences between optimal airflows considering positive and negative regulations were: the total output power of fans 49.952 kW, annual energy consumption 547 MWh, annual costs 78 217 Euro.
The establishment of the Research Network Lukasiewicz (RNL) is aimed at strengthening the research potential and knowledge transfer from research institutes to enterprises. The article presents the results of the research potential analysis of 38 research institutes that are to form the RNL, based on data on scientific publications in 2013–2016. The number of publications of RNL institutes was similar to the number of publications of TNO and VTT institutes but smaller than that of Fraunhofer institutes. The publications of RNL institutes had lower values of indicators of international collaboration and collaboration with business as well as lower values of citation indices. Co-authors of RNL publications were mainly affiliated with national scientific units, whereas co-authorship with Fraunhofer, TNO and VTT institutes was marginal. The article also outlines the limitations and challenges of the adopted research method and future research orientations in this area.
The article summarizes panel discussions led at the Polish Scientific Networks conference. It covers the topics of social and (un)social innovations, their sources, and applications, as well as the new approaches to the concept of the wisdom of the crowds (as opposed to swarm mentality). The article draws on academic research on trust and distrust, declining reliance on formal expertise and a turn against the science, and posttruth society phenomenon. The article concludes with observations about risk aversion in different cultures, to suggest some practical solutions in education programs, needed to address the challenges of the future.
The petrographic composition of coal has a significant impact on its technological and sorption properties. That composition is most frequently determined by means of microscope quantitative analyses. Thus, aside from the purely scientific aspect, such measurements have an important practical application in the industrial usage of coal, as well as in issues related to the safety in underground mining facilities. The article discusses research aiming at analyzing the usefulness of selected parameters of a digital image description in the process of automatic identification of macerals of the inertinite group using neural networks. The description of the investigated images was based on statistical parameters determined on the basis of a histogram and co-occurrence matrix (Haralick parameters). Each of the studied macerals was described by means of a 20-element feature vector. An analysis of its principal components (PCA) was conducted, along with establishing the relationship between the number of the applied components and the effectiveness of the MLP network. Based on that, the optimum number of input variables for the investigated classification task was chosen, which resulted in reduction of the size of the network’s hidden layer. As part of the discussed research, the authors also analyzed the process of classification of macerals of the inertinite group using an algorithm based on a group of MLP networks, where each network possessed one output. As a result, average recognition effectiveness of 80.9% was obtained for a single MLP network, and of 93.6% for a group of neural networks. The obtained results indicate that it is possible to use the proposed methodology as a tool supporting microscopic analyses of coal.
Speech enhancement is fundamental for various real time speech applications and it is a challenging task in the case of a single channel because practically only one data channel is available. We have proposed a supervised single channel speech enhancement algorithm in this paper based on a deep neural network (DNN) and less aggressive Wiener filtering as additional DNN layer. During the training stage the network learns and predicts the magnitude spectrums of the clean and noise signals from input noisy speech acoustic features. Relative spectral transform-perceptual linear prediction (RASTA-PLP) is used in the proposed method to extract the acoustic features at the frame level. Autoregressive moving average (ARMA) filter is applied to smooth the temporal curves of extracted features. The trained network predicts the coefficients to construct a ratio mask based on mean square error (MSE) objective cost function. The less aggressive Wiener filter is placed as an additional layer on the top of a DNN to produce an enhanced magnitude spectrum. Finally, the noisy speech phase is used to reconstruct the enhanced speech. The experimental results demonstrate that the proposed DNN framework with less aggressive Wiener filtering outperforms the competing speech enhancement methods in terms of the speech quality and intelligibility.
In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides the capabilities of MLP NNs, it uses Back Propagation (BP) and Gradient Descent (GD) for training; therefore, MLP NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well as lowconvergence speed. To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the bestcollected masses within iterations and expediting exploitation phase. To test the proposed classifier, this algorithm along with the GSA, GD, GA, PSO and compound method (PSOGSA) via three datasets in various dimensions will be assessed. Assessed metrics include convergence speed, fail probability in local minimum and classification accuracy. Finally, as a practical application assumed network classifies sonar dataset. This dataset consists of the backscattered echoes from six different objects: four targets and two non-targets. Results indicate that the new classifier proposes better output in terms of aforementioned criteria than whole proposed benchmarks.
In this paper, a modified sound quality evaluation (SQE) model is developed based on combination of an optimized artificial neural network (ANN) and the wavelet packet transform (WPT). The presented SQE model is a signal processing technique, which can be implemented in current microphones for predicting the sound quality. The proposed method extracts objective psychoacoustic metrics including loudness, sharpness, roughness, and tonality from sound samples, by using a special selection of multi-level nodes of the WPT combined with a trained ANN. The model is optimized using the particle swarm optimization (PSO) and the back propagation (BP) algorithms. The obtained results reveal that the proposed model shows the lowest mean square error and the highest correlation with human perception while it has the lowest computational cost compared to those of the other models and software.
This work aims to comprehensively describe the current state of the concept of green infrastructure. It is thus meant to fill in a gap in Polish literature as no comprehensive works concerning green infrastructure have been published in our country even though we have witnessed several such works in other places in the world. The book is mostly addressed to urban planners, spatial planners and landscape architects and it focuses on issues related to developing strategies or green nalyzingture network designs. It is difficult to establish when (and by whom) the term “green infrastructure” was actually coined. The performed literature search indicates that various authors attribute its beginnings to different publications. There is, however, much more consensus regarding the origins of the idea of green infrastructure. Among the concepts regarded as the bases for the notion of green infrastructure we can discern two principal ones: the concept of ecological networks and the concept of greenways (in the US). In Poland, such concepts included the Ecological System of Protected Areas (in Polish: Ekologiczny System Obszarów Chronionych) and System of Open Spaces (in Polish: System terenów otwartych). There is some disagreement regarding the origins of green infrastructure in cities. Analysis of defi nitions of green infrastructure seen in both scientific publications as well as guides and formal documents leads to a single conclusion – we should accept the diversity of interpretations and approaches. A similar diversity in approaches can also be found when looking at the presented typologies. By analyzing the rationale behind the typologies, we can discern three major criteria used by the authors: land cover, land use and ecological value, which is usually associated with formal protection of specifi c areas. The principles of green infrastructure development can be divided into planning-related (multi-functionality, connectivity, multi-scale approach, multi-object approach, cost-effective approach) and governance-related (strategic approach, integration, social inclusion, transdisciplinarity, stakeholder inclusion). Green infrastructure provides people with a multitude of more or less measurable benefits. For the last several years they have been identified and quantified using a concept of ecosystem services. These services are always provided in certain confi gurations, which means that it is only possible to obtain the benefits if the services generating those benefi ts are not contradictory to each other. For several years now, the European Commission has been conducting research on the scope, possibilities and methods of implementing the concept of green infrastructure in the member states. However, the EU’s offi cial position on this subject was declared only in 2013 via Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions – Green Infrastructure (GI) — Enhancing Europe’s Natural Capital. In both EU member states and the United States, non-governmental organizations are the main advocates of the concept of green infrastructure. They have been recently joined by governmental and self-government agencies. The case studies of already developed strategies and designs of the concept of green infrastructure presented in this book illustrate a great diversity of approaches. It is particularly noticeable in the way of identifying specific components and principles of planning and implementation of green infrastructure networks. These differences come mainly from the varying scale of development, adopted interpretations of the notion of green infrastructure as well as specifi c natural, social and sometimes economic conditions in particular areas. Based on the knowledge and experience gathered from the analysis of those cases, we can point out the following problems that Polish planners need to face in order to develop and implement green infrastructure for Polish rural communes, cities and regions: • good selection of the formula and defi nition of green infrastructure that is appropriate for the scale, specifi c conditions of the area, needs of the inhabitants and ambitions of the authorities; • good identification of areas with potential for green infrastructure development that is appropriate for the scale and problems of a specific area (city, village, region) • identification of the scope and degree of confl ict between ecosystem services provided by individual components of green infrastructure; • development of a spatial concept that includes the problem of the inherent conflict between the expected benefits (especially regulation and maintenance versus cultural) coming from individual components of green infrastructure; • proposal of appropriate instruments for implementing the concept and resolving the problem of its coexistence with other concepts of shaping the ecological structure of cities, rural communes and regions in Poland. Summing up, the concept of green infrastructure can be viewed as the ultimate synthesis of all former ideas dealing with the development of ecological structure of cities, open landscapes and regions. In most European countries, apart from Great Britain, the concept of green infrastructure is currently in its implementation phase. Therefore, its true – not paper – history is about to begin and it will probably look diff erent in every country. It will be aff ected by various traditions of development planning, the already developed concepts, degree of involvement of the authorities and – probably above all – the will of those that expect quantifiable benefits from green infrastructure.
Utilization of drones is going to become predominated in cellular networks as aerial base stations in order to temporary cover areas where stationary base stations cannot serve the users. Detecting optimal location and efficient number of drone-Base Stations (DBSs) are the targets we tackle in this paper. Toward this goal, we first model the problem using mixed integer non-linear programming. The output of the proposed method is the number and the optimal location of DBSs in a two-dimension area, and the object is to maximize the number of covered users. In the second step, since the proposed method is not solvable using conventional methods, we use a proposed method to solve the optimization problem. Simulation results illustrate that the proposed method has achieved its goals.
The author’s aim was to present actual conditions of rural primary schools functioning and the spatial differentiation of their network reorganization with particular emphasis on the consequences of those schools liquidation change their a governing body other from the local government units (LGU) to local community organizators. The study was focused on rural areas of the Małopolskie Voivodship over 2000–2016 period. In the paper were presented the number of pupils and schools (open and closed) and the school governing bodies structure too. Those data, obtained by the author from the Local Data Banks and the Board of Education in Cracow and were presented for each statistical locality. A population and settlement concentration in many rural areas made costs of schools maintenance higher and higher. Thus school governing bodies faced a difficult decision – either to reorganize the actual school network or to spend more on education from the municipal budget. Most complicated structures is observed in the rural areas showing depopulation and dispersed settlement, the zones of traditional agricultural. In all rural areas of the Małopolskie Voivodship, the number of pupils in primary schools during the analysed period decreased nearly by 30%. Thus 118 small rural schools were closed i.e. in the county Miechów, of 43 schools remained only 21. The number of closed schools would be much higher without a activity of the local communities, which began to take over their schools from the LGU. Within rural areas the Małopolskie Voivodship in 2016, 123 schools were run by local organization i.e. over 11,5% of all the rural primary schools.
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
The aim of the studywas to find an effective method of ripple torque compensation for a direct drive with a permanent magnet synchronous motor (PMSM) without time-consuming drive identification. The main objective of the research on the development of a methodology for the proper teaching a neural network was achieved by the use of iterative learning control (ILC), correct estimation of torque and spline interpolation. The paper presents the structure of the drive system and the method of its tuning in order to reduce the torque ripple, which has a significant effect on the uneven speed of the servo drive. The proposed structure of the PMSM in the dq axis is equipped with a neural compensator. The introduced iterative learning control was based on the estimation of the ripple torque and spline interpolation. The structurewas analyzed and verified by simulation and experimental tests. The elaborated structure of the drive system and method of its tuning can be easily used by applying a microprocessor system available now on the market. The proposed control solution can be made without time-consuming drive identification, which can have a great practical advantage. The article presents a new approach to proper neural network training in cooperation with iterative learning for repetitive motion systems without time-consuming identification of the motor.
The loss of power and voltage can affect distribution networks that have a significant number of distributed power resources and electric vehicles. The present study focuses on a hybrid method to model multi-objective coordination optimisation problems for dis- tributed power generation and charging and discharging of electric vehicles in a distribution system. An improved simulated annealing based particle swarm optimisation (SAPSO) algorithm is employed to solve the proposed multi-objective optimisation problem with two objective functions including the minimal power loss index and minimal voltage deviation index. The proposed method is simulated on IEEE 33-node distribution systems and IEEE-118 nodes large scale distribution systems to demonstrate the performance and effectiveness of the technique. The simulation results indicate that the power loss and node voltage deviation are significantly reduced via the coordination optimisation of the power of distributed generations and charging and discharging power of electric vehicles.With the methodology supposed in this paper, thousands of EVs can be accessed to the distribution network in a slow charging mode.