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Whenever a research scholar starts working on some innovative ideas he/she searches for the domain specific technical research articles published as research papers in most of the international journals, conferences or workshops. The problems associated with these papers are similarity in contents and repeated relevant information. Reading these all relatedpapers completely one by one to get the latest research developments in the interested domain is time-consuming, unnecessary, irrelevant, cumbersome and impossible. These problems are solved by developing a innovative solution, which optimizes and summarizes these research papers as an aid for research scholars using various Data Mining strategies. This helps research scholar for getting short, condensed, accurate and most relevant summarized information i.e. overview of domain-specific topic-based contents from research papers. Data mining strategies such as extraction and clustering are used for identifying ‘Research Relevant Novel’ (RRN) terms. Extracting relevant sentences from multiple papers uses ‘Maximal Marginal Relevance’ (MMR) criteria containing RRN terms. In addition to optimized and summarized contents, this paperalso informs earlier and latest research developments, progress, and challenges and future scope in particular field of study through various research categories identified such as research methods/techniques/approaches used, comparisons with existing research and providing starting material for further innovation. [ABSTRACT FROM PUBLISHER]

In this paper, we compared several software defined radio platforms and proposed the general architecture of GPP (General Purpose Processor)-based soft base stations. Then, we studied on the scheme design of resource allocation and algorithm optimization in soft base station implementation. Finally, as an instance of our study above, a prototype of GPP-based soft base station referring to 3GPP LTE was realized and evaluated. With its evaluated performance, GPP's capability on processing high speed wireless signal flow was verified, which showed us a promising prospect for GPP-based soft base stations in the next generation wireless systems. [ABSTRACT FROM PUBLISHER]

Collects the abstracts for the constituents of the 2012 IEEE International Power Engineering and Optimization Conference (PEOCO2012) proceedings. [ABSTRACT FROM PUBLISHER]

Due to the increasing cost of energy and the demand of reducing the environmental footprints, energy saving is becoming an important subject in the industry operation. To realize the energy consumption optimization of papermaking, the energy model should be established while the product quality and process model also need to be constructed, which are taken as the constraints for optimization. This paper describes the identification of a forming section of paper machines with Multilayer Perception (MLP) Neural Networks. The process model, product quality model and energy consumption model are established for the energy saving in papermaking. The real industrial step tests are performed and the data are used to model training and validation. The models are validated by means of mean-squared error (MSE), fit measure and Akaike's Final Prediction Error (FPE). The results show the effectiveness of the established models, which are suitable for the next work of energy optimization. [ABSTRACT FROM PUBLISHER]

Service engineering is an emerging interdisciplinary subject which crosscuts business modeling, knowledge management and economic analysis. To better satisfy service providers' profiting goals, the service system modeling needs to take care of both the short and long run customer satisfaction. We believe that the ideology of value driven design fits well for this need. We propose to work towards value driven design by introducing a form of service design patterns, we call service value broker(SVB) patterns, with the aim to shorten the distance between economical analysis and IT implementation. SVB patterns allow us to not only study the value added in terms of functional and business aspects, but also reason about the need for brokerage across various domains. In this paper, we focus on modeling the basis of SVB. The analysis is provided with a formal development of SVB to be integrated across a variety of functional and business aspects of services. Placing particular emphasis on scenarios where these can be applied, an example of improvements provided by SVB is also included. [ABSTRACT FROM PUBLISHER]

The environmental impact of doing business becomes an increasingly relevant aspect for organizations, not only because of legal requirements but also because more customers care about. Most organizations, however, do not have comprehensive knowledge on how to restructure their business processes accordingly. In previous work we proposed green business process patterns that address the environmental impact explicitly as one possible solution. Beyond those patterns, we now provide a method to extract environmentally relevant patterns from existing patterns of different domains. Moreover, we present a set of such patterns related to automated business processes. The proposed approach as well as the identified patterns support stakeholders when analyzing their business processes with respect to the environmental impact and, therefore, supporting green business process reengineering. [ABSTRACT FROM PUBLISHER]

This paper accomplishes a real-time spectrum analyzer by the TMS320LF5509A DSP, and using the V search algorithm to get the optimal analysis. The different sampling rates will change the time scale, and also result in different spectral analysis. In the process of power parameter analysis, the characteristic of original signal is completely kept, and The V search algorithm applies the sum of the minimum amplitude read from the spectrum to find the optimized analysis. This paper accomplishes above theories in an analyzer. The analyzer is composed of a circuit for voltage conversing and current conversing, a keyboard, a LCM, and a DSP module. According to the difference of selection, the analyzer can display the amplitude and phase of voltage or current, and the real power, reactive power and apparent power of load. [ABSTRACT FROM PUBLISHER]

The problem of optimally adjusting the power spectral density level, referred as power spectrum optimization, is a well-known and difficult nonconvex optimization problem. This paper investigates a class of local optimization methods based on a technique called iterative function evaluation. This idea, first proposed in our previous work, is based on the manipulation of the first order condition of the optimization problem into an algorithm. This paper shows that these manipulations are not unique, and proposes a new iterative-function-evaluation-based method for power spectrum optimization. In addition, this paper proposes methods based on the average channel gains for an orthogonal frequency division multiple access network. Finally, the performance of the proposed methods is evaluated in a wireless backhaul application. [ABSTRACT FROM PUBLISHER]

FlexRay is a new communication protocol supported by a large group of car manufactures and automotive electronics suppliers. It's also accepted as the de-facto standard in the future. In this paper, we analyzed several message scheduling problems of FlexRay dynamic segment at first. Then we gave out a solution to improve the situations and also a detailed timing analysis. Finally, we simulated the system model stated in the paper and verified the solution with some experiments, and it's shown that our solution works efficiently. [ABSTRACT FROM PUBLISHER]

There is vigorous development in Healthcare terminals. It not only reduces much of medical resources, but also is more convenient for people to monitor their physical condition, so has met with a warm reception. However, all of the devices in the terminals are electronic. Some small factors have an impact on the measuring result, lead to more or less deviation even mistakes. The paper researches on the impact that physical posture acts on the precision and deduces the functional relations between postures and deviation. How to design the healthcare terminals and guide the user to measure in the comfort posture to get the more precise result is the topic of the paper. As the verification, a series of experiment based on the design from the paper is carried out. Experimental results show that 1) the user comfort can be gauged and evaluated by psycho-physiological (medical) measurement and 2) the comfort-gauged formulation works in the design methodology and 3) the design methodology is applicable in real designs. [ABSTRACT FROM PUBLISHER]

Efforts to realize video streaming over Mobile Ad hoc Networks (MANETs) meet many challenges, which are addressed by different techniques. In the highly dynamic and unpredictable environment of MANETs, cross-layer mechanisms seem to be the most suitable for optimising video streaming. This paper presents a survey of 44 studied papers on the area, comparing tools, parameters and metrics used for their evaluation. It also indicatively describes in more detail some of these proposals. [ABSTRACT FROM PUBLISHER]

Parallel Genetic Algorithm (PGA) is used in many practical global optimizations to achieve high speed in convergence. The Island Model Parallel Genetic Algorithm (IMPGA) is very useful. Genetic Algorithms are one of the most powerful search and optimization method when we must solvecomplex and time consuming problems. IMPGA are more flexible than other PGA methods. There are several variables in the IMPGA that determining them are effective to enhance performance of the IMPGA. In this paper, we proposed a Migration method (Max-Min method). In our proposed method, according to status of subpopulation and comparing subpopulation with other subpopulations, the individuals for migrationare selected. In addition to enhancing the performance of PGA, we propose another method that embedding Hill-Climbing Algorithm within the structure of the PGA. As we know, creating an optimized structure for a Neural Network is a time consuming problem and costly one. The problem was studied in this paper is to determine the structure of a Neural Network forforecasting next day air quality. In addition, we used real data which was received from the Meteorological Organization and Tehran's Air Pollution Company. Output of the neural network is the value of Ozone Gas (o3) for the next 24 hours. The results of our two proposed methods are compared with conventional methods in other papers. Our algorithm has better performance than other papers. [ABSTRACT FROM PUBLISHER]

In this paper, the reliability allocation issue of digital substation systems is analyzed and a new optimization allocation method for engineering applications is proposed. This paper uses the minimum cost allocation method and the feasibility-cost model to establish mathematic programming. The paper introduces the equivalent redundancy coefficient which is based on the optimal solution of the mathematic programming to measure the importance of the components. By reduplicating the most important component, the system reliability will increase in the most effective way. This paper takes a transformer bay in a typical 110kV digital substation as an example to further show the effectiveness of the method. [ABSTRACT FROM PUBLISHER]

Based on the improved genetic algorithm, the mathematical model of reactive power optimization for electric power distribution system integrating with distributed generation (DG) is proposed in this paper. The active power output of DG and the reactive power compensation position are added as control variable to analyze the influence to the reactive power optimization when DG connected to the system. The test system is a 33-bus electric power distribution system, and the simulation result shows that the method proposed in this paper is helpful in reducing power losses while improving the voltage profiles. [ABSTRACT FROM PUBLISHER]

To improve the user-perceived quality of service (QoS) performance of voice over Internet protocol (VoIP) services, a retransmission of a packet experienced an error is needed in broadband wireless access networks. This means that the number of wireless resources to successfully transmit a packet can be increased by the retransmitted packet. For this reason, there can be a trade-off between the QoS performance improvement and the wireless resource efficiency enhancement with respect to the maximum number of retransmissions. This paper has formulated the cross-layer optimization problem to maximize the wireless resource efficiency with a constraint of the user-perceived QoS performance. This paper has driven the R-value for the user-perceived QoS performance because it includes most of impairments that can be generated during transmitting a voice frame from mouth to ears. Due to this feature, we can directly assess the QoS performance of VoIP services from a viewpoint of users. In addition, we can clearly design the optimal maximum number of retransmissions that can provide the satisfied quality of a VoIP service. By the numerical results, the optimal maximum number of retransmissions to provide the fair quality of a VoIP service under given conditions for G.711, G.729 and G.723.1 are 1, 3 and 4, respectively. [ABSTRACT FROM PUBLISHER]

By taking advantage of their nonlinear dynamics Cellular Nonlinear Networks (CNN) are considered to be powerful tools for many image processing applications. In this paper we will try to investigate the feasibility of image representation by using CNN dynamics. [ABSTRACT FROM PUBLISHER]

Aimed at the characteristic of recognizing wheat seed, a method is proposed based on fuzzy theory. In this paper, Fuzzy C-means Clustering is introduced and remarked firstly. On the basis of systematic analysis of current algorithms, Tabu search is inducted into fuzzy clustering to solve the locality and the sensitivity of the initial condition of Fuzzy C-means Clustering. Then, this paper proposes the fuzzy discern method based on approach degree and the principle of closest. The deficiency of dose-approximation value is proposed. Finally, it provides the design method and the new algorithm. Simulation results show that this method has good performance regarding both the quality of obtained answer and efficiency. [ABSTRACT FROM PUBLISHER]

This paper gives a concept of filled function which is different from the that of traditional filled functions, and a class of generalized filled functions satisfying the new concept are presented. furthermore, the filled functions properties were discussed and point out the filled function in paper [6] is the special form of this generalized filled functions. [ABSTRACT FROM PUBLISHER]

The aim of this paper is to present modified genetic algorithms (GA) that are used in the design of a hybrid renewable energy system (HRES). Another aim is the presentation of the direct design control (DDC) concept for the HRES control. The main goal of this paper is to develop an efficient tool for the selection of the components of the energy system, with 2 major selection criteria (price and number), using modified GA. The modified GA for the selection module are used in order to decrease the computation time and generate the optimal solutions. This paper will present the modifications that have been made of to the GA in order to improve the quality of the generated solutions. The second goal of the paper is to present the DDC concept that allows the planning system to automatically generate the control and supervisory program for the designed HRES, thus, reducing the implementation time. The DDC concept will be introduced for the automatically generated control code, and the authors present a solution that uses data servers and command files that will provide the link between the design software and the control platform. [ABSTRACT FROM PUBLISHER]

The paper discusses economic performance design under nonlinear dynamic behavior and changing operating conditions. Two methods to control plants with input-induced nonlinearities in the presence of hard constraints are presented. A nonlinear predictive controller is designed based on a nonlinear dynamic parameter-dependent model of the system for tracking control. Next a decomposition of the model of the plant is made which allows nonlinear optimal static feedforward and linear dynamic feedback. Model predictive control (MPC) was selected to control the transients while satisfying all constraints without loss of performance. The control scheme has been applied on an industrial printing system. Simulation examples show the effectiveness of the proposed approaches in the presence of variation in the input print queue and constraints. [ABSTRACT FROM PUBLISHER]

As the demand to develop more green and cost efficient means of supplying power to customers grows, we need to look at the solution from another angle. From the customer viewpoint, this paper identifies an efficient manner in which to utilize available resources. These resources include traditional utility sources, renewable solar, and battery storage. This paper looks at how constraints set can affect the optimal solution. [ABSTRACT FROM PUBLISHER]

This paper presents the first steps toward going from human data to formal controller design to experimental realization in the context of underactuated bipedal robots. Specifically, by studying experimental human walking data, we find that specific outputs of the human, i.e., functions of the kinematics, appear to be canonical to walking and are all characterized by a single function of time, termed a human walking function. Using the human outputs and walking function, we design a human-inspired controller that drives the output of the robot to the output of the human as represented by the walking function. The main result of the paper is an optimization problem that determines the parameters of this controller so as to guarantee stable underactuated walking that is as “close” as possible to human walking. This result is demonstrated through the simulation of a physical underactuated 2D bipedal robot, AMBER. Experimentally implementing this control on AMBER through “feed-forward” control, i.e., trajectory tracking, repeatedly results in 5–10 steps. [ABSTRACT FROM PUBLISHER]

This paper proposes a multi-agent based control system for real-time and adaptive Volt/VAR Optimization (VVO) and Conservation Voltage Reduction (CVR) in Smart Substations. The design and implementation of the proposed distributed control system using agent technology is discussed in the paper. Furthermore, the architecture, tasks and limits of each Intelligent Agent (IA) as a component of a multi-agent system (MAS) have been explained. A number of control functions are simulated and the results are presented in the paper. The results obtained demonstrate the potential of MAS for improving the efficiency of the system. [ABSTRACT FROM PUBLISHER]

Genetic Algorithm (GA) is one of the effective methods in the application to optimization problems. Recently, Multi-Objective Genetic Algorithm (MOGA), which is the application of Genetic Algorithm to Multi-objective Optimization Problems, is focused on in the engineering design field. In this field, the analysis of design variables in the acquired Pareto solutions, which gives the designers useful knowledge in the applied problem, is important as well as the acquisition of advanced solutions. This paper proposes a visualization method using an idea of Isomap, that visualizes manifold embedded in the high dimensional space, which was originally proposed in the field of multiple classification analysis. The proposed method visualizes the geometric distance of solutions in the design variable space considering their distance in the objective space. This method enables a user to analyze the design variables of the acquired solutions considering their relationship in the objective space. This paper applies the proposed method to the conceptual design optimization problem of hybrid rocket engine and studies the effectiveness of the proposed method. We found interesting structure in the distribution of Pareto solutions by applying the proposed method to this problem. This paper shows that the visualized result gives some knowledge on the features between design variables and fitness values in the acquired Pareto solutions. [ABSTRACT FROM PUBLISHER]

This paper addresses the provision of personal soundfields (zones) to multiple listeners in a space for which there are several fixed, virtual sources. For such multizone systems, optimization of speaker positions and weightings is important to reduce the number of active speakers. In this paper a two stage pressure matching optimization is proposed for wideband sound sources (such as speech signals). In the first stage, the least-absolute shrinkage and selection operator (Lasso) is used to select the speakers' positions for all sources and frequencies. A second stage then optimizes reproduction using all selected speakers on the basis of regularized least-squares (LS) or Lasso algorithm. The performance of these new, two-stage approaches is investigated for different speaker numbers, frequency range and reproduction angles. Results show that a limited arc of speakers using a two-stage optimization can give up to 38dB improvement in zone normalized squared error over a single-stage LS optimization. [ABSTRACT FROM PUBLISHER]

Timing Optimization is one of the most important objectives of the designer in the Modern VLSI world. Memory elements play a vital role on Digital World. The basic memory elements of designer considerations are Latch and flip flop. In this paper, we analyze the design of Single-bit Flipflop (SBFF) and made performance comparison over the Multi-bit Flip-flop (MBFF). For improving Flip flop performance one of the promising way is to merge the clock pulse. The Multi-bit Flip-flop is designed by single clock pulse and achieves same functionality like two single-bit Flip-flop. A shift register is designed using both Single-Bit Flip-Flop (SBFF) and Multi-Bit Flip-Flop (MBFF). This paper analyzes the timing performance of both SBFF and MBFF in Xilinx Virtex-5 family (XC5VLX50). These results in favor of Multi-Bit Flip-Flop as reduction of Clock network such as clock buffer and gate delay. [ABSTRACT FROM PUBLISHER]

In recent years, data mining has become a global research area for acquiring interesting relationships hidden in large data sets. Data Mining has been used in various application domains such as market basket data, bioinformatics, medical diagnosis, web mining and scientific data analysis. In this paper, we have tried to optimize the rules generated by Association Rule Mining using Biogeography Based Optimization(BBO). BBO has a way of sharing information between solutions depending on the migration mechanisms. The motivation of this paper is to use the feature of BBO for finding more accurate results. [ABSTRACT FROM PUBLISHER]

This paper investigates low temperature in situ steam generation (ISSG) oxidation, the correlation between the thickness growth rate and temperature, pressure, hydrogen flow and oxidation time. For low temperature ISSG oxidation, the within wafer uniformity is improved by increasing the temperature. An optimum pressure is revealed for all the possible hydrogen concentrations studied in this paper. However, the hydrogen flow itself exhibits a much more complicated relationship with the uniformity than that of temperature and pressure. Good uniformity is achieved through process optimization. It is found that the low temperature ISSG process exhibits a more robust within wafer uniformity than typical high temperature ISSG process due to the fact that the former one has better resistance to pressure and gas flow disturbance. One of the advantages that low temperature ISSG can enable SSRW application in 20nm semiconductor devices is also discussed in this paper. [ABSTRACT FROM PUBLISHER]

Software as a service (SaaS) is the main service model in cloud computing and has been generally recognized. More and more traditional software turns to SaaS applications. For SaaS provider, it hopes that it can provide better service performance to tenants while attain more profit. But the two goals are contradictory. So in this paper, we model the SaaS application service provisioning problem as multi-objective optimization problem and propose a service provisioning strategy based on Strength Pareto Evolutionary Algorithm 2 (SPEA2) for SaaS applications in cloud. The experiments show that compared with random strategy and greedy strategy, the service provisioning strategy proposed in this paper can effectively improve the service performance and profit. [ABSTRACT FROM PUBLISHER]

In the vehicle routing problem (VRP), it is usually difficult to confederate the cargo and arrange vehicles path. Due to performance reasons, the traditional shortest path algorithm can not be applied to the large scale of VRP. On the basis of the VRP mathematical model, this paper constructs a mixed climbing particle swarm algorithms to solve the problem. First, through coding, the VRP problem is divided into two sub-problems: task allocation and single vehicle path optimization. Particle swarm algorithm is in charge of controlling the overall situation and allocating task, while hill-climbing algorithm is responsible for calculating the vehicle path optimization (fitness). Finally, by performing experiments in MATLAB programming and comparison of the operational results of the matrix method and genetic algorithm, the algorithm is shown to be feasible in solving VRP and have higher practicability. [ABSTRACT FROM PUBLISHER]

Mechanical engineers always expect to design a structure which could work properly in its whole lifetime. But there exist many random factors, such as dimension, material property and applied forces. Hence structures based on determinate design could fail with high probability. Reliability-based Topology Optimization (RBTO) is a computer-automated design method which combines reliability analysis and topology optimization method. Machines and equipments always have high reliabilities when they are new. But the structure working in corrosive environment will be gradually corroded, then the corroded structure may fail long before its expected lifetime in usual environment. If corrosive rate is also considered as a random factor in RBTO, the reliability constraint should be satisfied not at the beginning but at the end of the structure's expected lifetime. Unfortunately, most research about RBTO concern about the reliability of structure when it is new. In this paper, corrosion model fitting for RBTO is built. Since the structure's surfaces are corroded through the whole lifetime, new corrosion surfaces should be continuously updated. An algorithm is presented to find the finite elements on the surface of structure. Corrosion rate describes the corrosion depth in unit time, and it cannot be directly used to control the corrosion in a finite element. Hence corrosion coefficient α(t) is introduced to describe the fade of material volume density in finite element. The final corroded structure can be generated after simulating the corrosion phenomenon. Its reliability index is checked to see whether the corroded structure is safe enough during its whole lifetime. If it is not safe, then a stronger structure will be generated. If the reliability of the corroded structure is higher than the requirement, our method will generate a lighter optimal structure, which is our initial design goal. In this paper, first order reliability method (FORM) is used to find the Most Probable Point (MPP) on the curve of limited state function. Sequential Optimization and Reliability Assessment (SORA) is used to solve the RBTO problem. Three different cases of cantilever beam RBTO design considering different corrosion rate are presented, and the reliability analysis results based on Monte Carlo Method successfully prove the consistence between the reliability of optimum structure and the preset minimum reliability requirement. [ABSTRACT FROM PUBLISHER]

Coverage optimisation is an important self-organising capability that operators would like to have in LTE networks. This paper applies a Reinforcement Learning (RL) based Sparse Sampling algorithm for the self-optimisation of coverage through antenna tilting. This algorithm is better than supervised learning and Q-learning based algorithms as it has the ability to adapt to network environments without prior knowledge, handle large state spaces, perform self-healing and potentially focus on multiple coverage problems. [ABSTRACT FROM PUBLISHER]

This paper proposes three optimization solutions for hard cooperative sensing by taking into account different system constraints. Considering the global detection performance of the cooperative system, different methods for optimizing the detection are provided. These methods depend on both local and global false alarm probabilities but they also require the knowledge of individual local detection probabilities. A second part of this paper is therefore dedicated to a novel SNR prediction method, which is necessary for estimating the local detection probabilities used in the optimization process. This work clearly shows that depending on different local or global detection constraints, the result of the optimization is different. [ABSTRACT FROM PUBLISHER]

The QoS based route optimization is a key issue of the wireless network, which is a NPC-hard multi-objective discrete optimization problem. In this paper, an efficient multi-objective artificial bee colony optimization algorithm based on Pareto dominance called MOABC is proposed to tackle this problem. The algorithm was evaluated on a set of different scale test problems and compared with GA based multi-objective optimization algorithm for this problem. The experimental results reveal very encouraging results in terms of the quality of solution and the processing time required. [ABSTRACT FROM PUBLISHER]

To reliability prediction of products with high reliability and long life, the Step Stress Accelerated Degradation Test (SSADT) is commonly applied. With the motivation of predicting product reliability most precisely, this paper discusses degradation process of products using Birnbaum-Saunders model, and proposes an optimal design method of SSADT. In order to minimize the mean square error (MSE) of product operation reliability, the test plans of SSADT under specified total test cost by utilizing Monte Carlo simulation. The plans can determine the optimal sample size, parameter measurement interval and measurement times of SSADT. In the end of this paper, we present an example of permanent magnet used in satellite to validate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

To investigate the optimal policy of continuously deteriorating system with economical dependence, a kind of improved opportunistic maintenance policy is presented in this paper. This system is composed of two kinds of units, which are subjected to the deterioration failure described by Gamma process and the Poisson failure respectively. The maintenance mode and corresponding control threshold are determined by the analysis of failure rules of system units. Since the optimal policy for multi-unit system should not limit itself to a simple juxtaposition of the mono-unit models considering the economical dependence, the opportunistic policy is used to coordinate the maintenance of the two kinds of units and minimize the long-run maintenance cost of the system. Finally, a numerical example is put forward to illustrate the implementation of the model and iteration algorithm. [ABSTRACT FROM PUBLISHER]

Power consumption has become an important issue in embedded system. Reducing the total number of signal transitions during each bus cycle has great effect on power consumption. In this paper, we proposed an instruction scheduling method which is based on the Particle Swarm Optimization (PSO) Algorithm to reduce the signal transitions. We formulate the low-power instruction scheduling problem to the constrained discrete PSO problem. And then we modify the PSO solution to satisfy the path constrained and find the better instruction schedule with litter signal transitions. For more effectively, we also improve the velocity updating formula to get the better result. The main contribution of our paper is that we use the improved PSO algorithm to find the better instructions sequence for low power quickly. [ABSTRACT FROM PUBLISHER]

In this paper, online path optimization method for Unmanned Aerial Vehicles (UAV) by adjusting parameters of flight path is proposed. Especially, the energy efficient path for UAVs under the presence of steady wind is discussed. Although the relation between the energy consumption and the flight path parameters is hard to model explicitly in general, which induces the difficulty to adopt gradient based optimization techniques. On the other hand, actual energy consumption can be measured, e.g. by measuring fuel consumption rate, and it is natural to assume that the rate is a function of flight path. This paper proposes to perturb the flight path in order to estimate the gradient of the energy consumption rate that is used for the optimization, which is based on Simultaneous Perturbation Stochastic Approximation (SPSA) method. Numerical results are shown to evaluate the proposed approach, and the method succeeded to improve the energy efficiency. [ABSTRACT FROM PUBLISHER]

In this paper, a synthesis method of a reconfigurable fault-tolerant control system for a steer-by-wire vehicle is proposed. The proposed control law consists of a linear feedback control law and a control allocator based on online optimization. It is shown that the input-output property of the control allocator can be regarded as a sector bounded nonlinearity. Based on this fact, a design method of a controller that guarantees stability of the overall system is proposed. The effectiveness of the method is shown through numerical examples. [ABSTRACT FROM PUBLISHER]

The growing market for Digital Signal Processing (DSP), Computer graphics and embedded systems applications that can be modeled as polynomial computations in their datapath designs, requires improvements in high-level synthesis and optimization techniques for such systems. This paper concentrates on how to find common sub-expressions between s given polynomial functions over Z2n1 × Z2n2 × … × Z2nd to Z2m in order to optimize the area and delay as much as possible. Our main contributions in this paper is proposing an optimization method based on adding/deleting vanishing polynomials over Z2m, i.e., those polynomials that are equivalent to zero over Z2m, to/from given polynomial functions in the hope of achieving further common sub-expressions. After applying our optimization techniques, experimental comparisons with the state-of-the-art techniques show an average improvement in the area by 36.80% with an average delay decrease of 2.41%. Regarding the comparison with our previous works, the area and delay are improved by 21.4% and 8.7% respectively. [ABSTRACT FROM PUBLISHER]

This paper deals with Smart Grids including renewable generation plants and plug-in vehicle fleets managed by aggregators and connected to the grid through power electronic devices. A new multi-objective optimization model is proposed in order to obtain the optimal operation of the Smart Grids. The proposed model originates from the need of accomplishing numerous and sometime conflicting objectives in the Smart Grid operation and allows to perform several services, aimed at contemporaneously meeting needs internal to the SG and external to it. Among the possible optimization methods to solve the multi-objective model, two different approaches were used in this paper based on objective sum criterion and weighted sum criterion, respectively. The objective sum criterion does not require any articulation of preferences and seems particularly suitable when low CPU time is required. The weighted sum criterion could lead to better quality of decisions since it evaluates the relative importance of each objective. Numerical simulations applying the analyzed methods for the optimal operation of a low voltage test Smart Grid were performed and discussed. [ABSTRACT FROM PUBLISHER]

A special detection device, or an E-Pod is generally installed in a plane to perform the target detection and track mission. Aimed at designing a reliable E-Pod, This paper adopts the SolidWorks to build a physical model of E-Pod, and analyze its strength, stiffness and frequency to assess the feasibility for further improvement. Then this paper offers a way of optimization to ensure the reliability of the E-Pod. [ABSTRACT FROM PUBLISHER]

In this paper we introduce a mathematical model in the framework of long term evolution (LTE) to solve the problem of coverage and capacity optimization by employing multi-level random Taguchi's Method. The optimization process runs in a centralized manner with no human intervention required and interacts with environment situation automatically. Under the mathematical model which combines coverage and capacity optimization by a coefficient factor, conventional Taguchi's Method transcends traditional trial-and-error approach in convergence speed and simple implementation, to offer even more search capacity, Gaussian shrink coefficient and random optimization offset are applied to the level-to-tilts mapping function. Antenna tilt is an effective interference reduction technique, which has been adopted as the tuning parameter. The simulation results turn out to be better than traditional Taguchi's Method and trial-and-error approach. The system model presented and evaluated also gives an insight to the mathematical model especially the trade-off between coverage and capacity in homogeneous scenario. [ABSTRACT FROM PUBLISHER]

In this paper we present a systematic model based approach to state and parameter estimation for the induction machine. We use moving horizon estimation (MHE), an optimization based scheme that yields excellent performance and can be used with aggressive controllers such as model predictive controllers. The past measurements within a given horizon are combined with an a priori estimate based on the induction machine model. Under mild assumptions, this yields a maximum-likelihood estimate of the states and parameters over the horizon. The resulting optimization problem is solved using the Generalized Gauss-Newton method. A real-time iteration approach can be used to significantly reduce execution and response times. Simulation results indicate superior performance of MHE over established methods such as model reference adaptive system (MRAS) or Extended Kalman Filter (EKF). Real-time feasibility of the proposed approach up to 3.5 kHz sampling rate is demonstrated by experiments on a state-of-the-art embedded control platform. [ABSTRACT FROM PUBLISHER]

This paper presents a Genetic Algorithm (GA) based optimization approach for assisting circuit design. The GA is developed to optimize the parameter setting for circuit design in order to achieve the required specifications in terms of noise figure, power gain, power loss, current, and circuit stability factors. Two case studies are presented in this paper: 15.12 GHz single pole double throw (SPDT) switch design and 5 GHz MMIC monolithic microwave integrated circuit (MMIC) Low Noise Amplifier (LNA) design. The Agilent Advance Design System (ADS) is adopted to simulate the circuit performance of SPDT switch and MMIC LNA. The developed GA is compared to a number of built-in optimizer of ADS. Based on the results obtained, GA is shown to be capable in assisting circuit designs, solving the crucial circuit parameters for achieving the required specifications, preference and constraints. [ABSTRACT FROM PUBLISHER]

Optimising the locations of base stations (BSs) is very challenging in highly dynamic environments such as airports, shopping malls and train stations where both spatial and temporal traffic variations are considerably high. Due to the continuous growth in international air traffic and the dynamic behaviour of passengers in an airport environment, providing reliable and cost effective communication facilities to passengers and staff becomes even more difficult at different times and locations. Using real measurements from Heathrow Terminal 4 (T4), we, in this paper, develop T4 passenger flow models which take both the spatial and temporal variations into account and help us accurately determine the traffic demand (TD), coverage area and path loss and thus outage and energy consumption. In this paper, we develop a multi-objective genetic algorithm (GA) which serves traffic demand and minimises both outage and energy consumption of the whole network. This eventually minimises the number of BSs while optimising their locations. To validate GA's results, a multi-objective mixed integer linear programming (MILP) model has been developed and both are found to be in good agreement. The results also reveal that only a few more base stations are required when we consider all three parameters together compared to the TD only case. However multiparametric objective function, considering TD, outage and energy consumption, consumes 100 times less transmission energy compared to the case of TD only while serving the same amount of traffic in such a dynamic environment. [ABSTRACT FROM PUBLISHER]

Time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. Auto-Regressive Integrated Moving Average (ARIMA) models are one of the most important time series models used in financial market forecasting over the past three decades. Recent research activities in time series forecasting indicate that two basic limitations detract from their popularity for financial time series forecasting: (a) ARIMA models assume that future values of a time series have a linear relationship with current and past values as well as with white noise, so approximations by ARIMA models may not be adequate for complex nonlinear problems; and (b) ARIMA models require a large amount of historical data in order to produce accurate results. Both theoretical and empirical findings have suggested that integration of different models can be an effective method of improving upon their predictive performance, especially when the models in the ensemble are quite different. In this paper, ARIMA models are integrated with Artificial Neural Networks (ANNs) and Fuzzy logic in order to overcome the linear and data limitations of ARIMA models, thus obtaining more accurate results. Empirical results of forecasting model indicate that the hybrid models exhibit effectively improved forecasting accuracy so that the model proposed can be used as an alternative to financial market forecasting tools. In this paper, experiments were conducted to confirm these hypotheses by evaluating the predictive capability of the developed ensemble of models in the domain of emotion prediction. This work attempts to anticipate subsequent emotion given historical emotions recorded. [ABSTRACT FROM PUBLISHER]

Platooning of vehicles allows to saving energy and increasing safety provided that there are reliable wireless communication protocols. In this paper, the optimization of the medium access control (MAC) protocol based on IEEE 802.11e for the platoon joining is investigated. The exchange of prosperous dynamic information among vehicules through certain bounded and closed-fitting timeout windows is challenging. On the one side, safe and secure joining of vehicles to a platoon is time-consuming and in the actual speed of the vehicles may be very difficult. On the other side, the decrease in joining timeout windows results in rising of joining failure. The analytical characterization of the appropriate timeout windows, which is dependent on the rate of exchange messages to request and verify joining, is proposed. By using such a new characterization, the estimation of closed-fitting timeout windows for joining is achieved based on the rate of transferred joining messages. Numerical results show that regular joining timeout windows suffer unacceptable delay for platooning. By contrast, adaptive optimized timeout windows reduce delay of communication. It is concluded that the new optimization proposed in this paper can potentially reduce energy consumption of vehicles and increase safety. [ABSTRACT FROM PUBLISHER]

Increased penetration of distributed generators (DGs) is one of the characteristics of smart grids. Distribution grid reconfiguration is one of the methods of accommodating more DG into the electric grid, which is illustrated with the help of a 16 node test network in this paper. The reconfiguration of the distribution grid involves changing the grid topology thereby optimizing a few objectives. In addition to the inclusion of DGs, grid reconfiguration also helps in achieving minimal power loss, minimal voltage deviation etc. In this paper the grid reconfiguration problem is formulated as an optimization problem. Simple genetic algorithm (GA) and its variant NSGA-II are used for solving the optimization problem. For a simple test system like the 16 node system discussed in this paper, simple GA is efficient enough to find the global optimum for a single objective optimization. The paper also illustrates the advantage of NSGA-II compared to simple GA when multiple objectives are considered. [ABSTRACT FROM PUBLISHER]

Recently, flash memories have become a competitive solution for mass storage. The flash memories have rather different properties compared with the rotary hard drives. That is, the writing of flash memories is constrained, and flash memories can endure only limited numbers of erases. Therefore, the design goals for the flash memory systems are quite different from these for other memory systems. In this paper, we consider the problem of coding efficiency. We define the “coding-efficiency” as the amount of information that one flash memory cell can be used to record per cost. Because each flash memory cell can endure a roughly fixed number of erases, the cost of data recording can be well-defined. We define “payload” as the amount of information that one flash memory cell can represent at a particular moment. By using information-theoretic arguments, we prove a coding theorem for achievable coding rates. We prove an upper and lower bound for coding efficiency. We show in this paper that there exists a fundamental trade-off between “payload” and “coding efficiency”. The results in this paper may provide useful insights on the design of future flash memory systems. [ABSTRACT FROM PUBLISHER]