Big data refer to the variety of the massive amount and the velocity of the data. The traditional databases are not suitable to store the big data because of huge volume. The cloud computing is a best and optimal choi...
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ISBN:
(纸本)9781538643495
Big data refer to the variety of the massive amount and the velocity of the data. The traditional databases are not suitable to store the big data because of huge volume. The cloud computing is a best and optimal choice to store and process the big data. However, there is an important issue to be addressed before storing the big data into the cloud that is maintaining the privacy and access control, in which the data must encrypt and restrict the unauthorized user access by providing effective access control. Ciphertext Policy-Attribute Based Encryption (CP-ABE) is a promising technique to provide both encryption and effective access control. The existing CP-ABE schemes are not apt for big data in cloud since it creates heavy computation overhead. In this paper, we propose an efficient ciphertext policy attribute based encryption scheme with less computation overhead in the encryption process by providing the short ciphertext and reducing the decryption time by minimizing the pairing operations required. Through the security analysis we demonstrate that our design is secure under chosen-plaintext attack and user collusion attack. The performance analysis proves that our scheme is efficient when compared with existing schemes.
Mushroom production is one of the biggest solid state fermentation industries in the world. The success in mushroom planting depends on how the control temperature, humidity and CO2 parameters. This paper presents a n...
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Mushroom production is one of the biggest solid state fermentation industries in the world. The success in mushroom planting depends on how the control temperature, humidity and CO2 parameters. This paper presents a novel method for modeling an environment of mushrooms growth to comparing the performance of two controlling methods (fuzzy logic and digital (ON/OFF) control) for controlling mentioned parameters on production rate. The controllers and other equipment were developed to data collection and analysis of these parameters was performed by using Simulink part of MATLAB software. Precise control of the parameters involved in the growth of mushrooms caused to improve product quality and reduced energy consumption. The results of tests and mean value obtained on two different methods showed that the fuzzy controlling with having least standard deviation, variance and error, is better than digital controlling. Fuzzy controlling system had the lowest fluctuation and lowest band pass. According to gradient of graph, maximum and minimum of results, can conclude that the fuzzy controlling has shown better response in controlling the process. Based on the number of actuators mode changing on both systems, it can be understood that in digital control system, downtime, and depreciation and energy consumption would be higher than the fuzzy control system. (C) 2016 Elsevier Ltd. All rights reserved.
As one of the most important structural and functional materials, rolled-product plays an irreplaceable role in national economy, people's lives and national development. Metallurgy industry is moving from traditi...
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As one of the most important structural and functional materials, rolled-product plays an irreplaceable role in national economy, people's lives and national development. Metallurgy industry is moving from traditional semi-automation to knowledge automation, process intelligence, and manufacturing information. Rolling exerts an essential impact on material properties and product quality as an important part of the production in steel industry. Rolling process is multi-scale, multi-variable, nonlinear and unbalanced with strong coupling and non-steady state. With an increasing rolling speed, more difficulties like process information monitoring, behavior characteristics modeling, and controlling of high speed operating are manifested in high-speed continuous rolling mills. The existing control system of rolling process is difficult to cope with the condition changes of high-speed rolling and the specification changes of complex products. The main reason lies in the fact that the prediction of force parameters is based on traditional mathematical models, and the procedure parameter setting depends on static optimization methods. In order to achieve precise control of large-scale and high-speed rolling, the analysis of rolling process rules based on industrial big data should be considered to establish the dynamic process model, and multi-objective real-time computational method of rolling schedules should also be introduced. Through a summary of steel industry and a review of the history of rolling optimization, the purpose is to explore the relationship between the optimization objectives of the rolling schedule and the process parameters of the rolling process, reveal the rules of how rolling conditions affecting rolling process in high speed rolling and provide theoretical basis and technical support to the production of steel industry.
The automatic pouring of molten metal from a ladle into a mold by a robot requires an high-precision tracking control of the flow rate. Due to the hydrodynamics of the liquid metal, the model of the pouring process is...
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ISBN:
(纸本)9781457710636
The automatic pouring of molten metal from a ladle into a mold by a robot requires an high-precision tracking control of the flow rate. Due to the hydrodynamics of the liquid metal, the model of the pouring process is highly nonlinear which has to be considered for the model-based design of the tracking control. The two design approaches studied in the paper combine a feedforward and a feedback control in order to obtain a precise and robust tracking performance. Thereby, the property of differential flatness is used for the design of the tracking control, and the unmeasured states are reconstructed for the feedback control by an unscented Kalman filter. Two proposed control schemes are compared by simulations of the automatic pouring robot together with the pouring process.
Equipment integrated logistics support (ILS) datamodeling is the foundation for equipment ILS design, analysis, and decision-making. At present, the ILS data resources have the characteristics of multi-source heterog...
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Activity of any enterprise represents set of the consecutive, directed to a definite purpose actions (business processes). The description and the analysis of business processes allow to estimate optimality of perform...
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ISBN:
(纸本)9781538667576
Activity of any enterprise represents set of the consecutive, directed to a definite purpose actions (business processes). The description and the analysis of business processes allow to estimate optimality of performance of process, to allocate excess operations, to define distribution of responsibility within process performance that in the subsequent, by means of reengineering to reconstruct activity of the organization in the best way.
Condition Based Maintenance(CBM) is a preventive maintenance strategy based on the actual running state of equipment. There are some deficiencies in the implementation of traditional CBM method. Firstly, how to acquir...
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ISBN:
(纸本)9781509057108
Condition Based Maintenance(CBM) is a preventive maintenance strategy based on the actual running state of equipment. There are some deficiencies in the implementation of traditional CBM method. Firstly, how to acquire data used by CBM reasonably and improve the data coverage of equipment information is a problem to be solved. Secondly, the CBM method is still a maintenance strategy, when facing the different types of data, how to manage these data with characteristics of multi-sources, heterogeneous and different time scales for convenient searching and dataprocessing also need to be studied. At the same time, how to choose a reasonable model to deal with this data, and then quickly give the maintenance strategy to the staff is another problem. Above all, this paper presents an CBM information system architecture based on multi-dimensional operation and maintenance data, including extensible data acquisition method;data management method based on Ontology modeling and dataprocessing method based on model selection. The architecture proposed sets data acquisition, data management and dataanalysis in one system, effectively integrating available information and making the whole analysisprocess becomes simple, and shortening the analysisprocess and improving the efficiency of dataanalysis through computer technology and information technology.
Today, a wide variety of computer systems are required to react automatically to various events generated by external processes and/or human operators. An important class of these processcontrol systems, called hard ...
Today, a wide variety of computer systems are required to react automatically to various events generated by external processes and/or human operators. An important class of these processcontrol systems, called hard real-time systems, need to respond to events under severe timing constraints expressed in terms of deadlines and earliest starting times. In general, missing deadlines is often as dangerous as producing incorrect results. Most of such real-time processcontrol systems are also required to deliver correct service even in the presence of hardware faults and software errors in their components. The fault-tolerant attribute is essential when system failures may cause economic disasters or loss of human lives. The main purpose of this dissertation is to report research results related to the mathematical state space modeling of the three major characteristics of a processcontrol system: timeliness, dependability, and external environment dependencies. Our results are presented in the context of Supervisory control and data Acquisition (SCADA) of power systems and Energy Management Systems (EMS). Particularly, SCADA systems are fault-tolerant, real-time processcontrol systems hosted in distributed architectures composed of heterogenous machines, with a technology of widespread utilization that pervades several industrial control applications. We show how Markov reward models can be applied in the availability analysis of EMS computer architectures before proposing and purchasing any equipment. We also characterize a distributed architecture with associated fault-tolerant strategies, representative of the latest generation of master stations deployed in utility industry applications. We study the effect of failure and repair dependencies in a data acquisition computer model developed using stochastic Petri nets and continuous-time Markov chains. Special attention is given to the representation of external influences and human errors. Additionally, we introdu
A fuzzy model predictive control strategy for active power filter is presented in this paper. In the strategy, T-S fuzzy model is employed to predict future harmonic compensating current. The fuzzy model is derived fr...
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ISBN:
(纸本)0780382374
A fuzzy model predictive control strategy for active power filter is presented in this paper. In the strategy, T-S fuzzy model is employed to predict future harmonic compensating current. The fuzzy model is derived from input-output data by means of product-space fuzzy clustering. In order to make the fuzzy model compact and accurate, similarity driven rule base simplification is applied to detect and merge compatible fuzzy sets in the model and a new validity measure is proposed to determine appropriate number of the clusters. Based on the model output, branch-and-bound optimization method is adopted to produce proper value of control vector, this value is adequately modulated by means of a space vector PWM modulator which generate proper gating patterns of the inverter switches to maintain tracking of reference current. The fuzzy model predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. The proposed control is applied to compensate the harmonic produced by the variable non-linear load. Simulation results show the fuzzy model based predictive controller is effective and feasible.
A control and dataprocessing system for HT-7, the first super-conducting tokamak in China, is developed in order to both control the experimental system and process the huge amount of experimental data (600 MB/shot)....
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A control and dataprocessing system for HT-7, the first super-conducting tokamak in China, is developed in order to both control the experimental system and process the huge amount of experimental data (600 MB/shot). A fully distributed structure is adopted. The distributed control system (DCS) includes several subsystems, such as those for the main control, synchronization, safety, interlock, data acquisition and dataanalysis, physical data management, remote control facility via networks, etc. The basic element of the DCS is the personal computer (PC) with a Fiber Distributed data Interface based on a fast network. The system uses multiple data-transfer paths in parallel and categorizes the entire computer functions into the servers. The subsystems for main control, communication, and data management are described in details.
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