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This paper describes the application of the continuous Newton's method to the power flow problem. This method basically consists in formulating the power flow problem as a set of autonomous ordinary differential equations. Based on this formal analogy, we propose an entire family of numerically efficient algorithms for solving ill-conditioned or badly-initialized power flow cases. The paper also shows that the classical Newton-Raphson's method and most robust power flow techniques proposed in the literature are particular cases of the proposed formulation. An example based on a 1254-bus model of the UCTE system is presented and discussed. [ABSTRACT FROM AUTHOR]

For the development of communications software com- posed of many modules, protocol validation is essential to detect errors in the interactions among the modules. A number of protocol validation techniques were proposed in the past, but the validation time required by these techniques is too long for many actual protocols. This paper proposes a new fast protocol validation technique to overcome this drawback. The proposed technique is to construct the minimum acyclic form of state transitions in individual processes of the protocol, and to detect protocol errors such as system deadlocks and channel overflows fast. This paper also presents a protocol validation system based on the proposed technique to confirm its feasibility and shows validation results for some actual protocols obtained with this system. As a result, the protocol validation system is expected to contribute to a great extent to the improvement of the productivity in development and maintenance of communications software. [ABSTRACT FROM AUTHOR]

This paper describes a method of developing wide-band multi-port system equivalents for use with real-time digital power system simulators. The proposed equivalent combines a frequency dependent network equivalent (FDNE) for the high frequency electromagnetic transients and a transient stability analysis (TSA) type simulation block for the electromechanical transients. The frequency dependent characteristic for FDNE is obtained by curve-fitting frequency domain admittance characteristics using the vector fitting method. The paper also introduces an approach for approximating the frequency dependent characteristic of large power networks from readily available typical power-flow data. The paper shows how the TSA algorithm can be adapted to a real-time platform. The validity of this method is confirmed with examples, including the study of a multi infeed HVDC system based network. [ABSTRACT FROM AUTHOR]

The power oscillation damping (POD) controllers implemented in the two thyristor controlled series compensators of the Brazilian North-South (NS) interconnection, in the year 1999, were solely intended to damp the low-frequency NS oscillation mode. These controllers are still under operation and are derived from the modulus of the active power flow in the NS line that is phase-lagged at the frequency of the NS mode and may experience relatively large excursions generated by exogenous disturbances. This paper utilizes the same 1999 data to compare the performance of a proposed robust POD controller design with those of two conventional designs. A recent robust control synthesis algorithm used in this work is based on a nonsmooth optimization technique and has the capability to handle various controller structures, including reduced-order, and to deal with time-domain constraints on both controlled and measured outputs. Moreover, the nonsmooth design technique encompasses multiple operating conditions subject to various test signals, hence building a truly time-domain multi-scenarios approach. According to the results discussed hereafter, this is a key advantage in the industrial context of increasing demand for performance and robustness. The described results relate to a large-scale system model used in the feasibility studies for that interconnection. [ABSTRACT FROM AUTHOR]

Traditional online security assessment determines whether the system is secure or not, but how secure or insecure is not explicitly indicated. This paper develops probabilistic indices, risk, to assess real-time power system security level. Risk captures not only event likelihood, but also consequence. System security level associated with low voltage and overload can be optimally controlled, using the NSGA multiobjective optimization method. A security diagram is used to visualize operating conditions in a way that enables both risk-based and traditional deterministic views. An index for cascading overloads is used to evaluate the Pareto optimal solutions. This paper shows that the multiobjective approach results in less risky and less costly operating conditions, and it provides a practical algorithm for implementation. The IEEE 24-bus RTS-1996 system is analyzed to show that risk-based system security control results in lower risk, lower cost, and less exposure to cascading outages. [ABSTRACT FROM AUTHOR]

This paper is concerned with the nonrepeatable runout (NRRO) compensation problem for hard disk drives. After standard servo control, several visible frequency components remain in the spectrum of nonrepeatable position error signal (NRPES). The dominant ones among these frequency components contribute a lot to the track mis-registration (TMR). In this paper, we propose an adaptive compensation scheme for the time-varying dominant frequency component of NRRO. The frequency of the dominant component is estimated online by the least mean squares (LMS) algorithm within a short time window. Based on the frequency estimate, the basis function algorithm is applied to adaptively identify the time-varying magnitude and phase of the dominant component. With the identified frequency, magnitude, and phase, an estimate of the dominant component is constructed and then canceled by the control signal. This scheme is further extended to compensating for multiple frequency components. The performance of this compensation scheme is demonstrated by simulation on a realistic hard disk drive model. [ABSTRACT FROM AUTHOR]

This paper investigates the features of a cellular geometry in code-division multiple-access (CDMA) systems with soft handoff and distinguishes controlling area of a cell from coverage area of a cell. Some important characteristics of the cellular configuration in soft handoff systems are used to propose a new design of efficient call admission control (CAC) in CDMA systems. Then, the paper constructs a continuous-time Markov chain (CTMC) model for CAC in CDMA with a soft handoff queue, obtains closed-form solutions, and thus develops loss formulas as performance indices such as the new blocking probability and the handoff dropping probability. In order to determine handoff traffic arrival rate, a fixed-point strategy is developed. Algorithms are also provided to stably compute loss probabilities and to determine the optimal number of guard channels. A new soft handoff scheme—eliminating pseudo handoff calls (EPHC)—is proposed to improve channel utilization efficiency based on mobility information. As an application of the loss formulas, the proposed modeling techniques are used to evaluate and compare the performance of conventional and proposed EPHC soft handoff schemes. Numerical results show the effectiveness of the proposed Markov chain models and the benefits of the new soft handoff scheme. [ABSTRACT FROM AUTHOR]

Parallel and distributed processing has been broadly applied to scientific and engineering computing, including various aspects of power system analysis. This paper first presents a distributed processing approach of reliability index assessment (RIA) for distribution systems. Then, this paper proposes a balanced task partition approach to achieve better efficiency. Next, the distributed processing of RIA is applied to reliability-based network reconfiguration (NR), which employs an algorithm combining local search and simulated annealing to optimize system reliability. Testing results are presented to demonstrate the speeded execution of RIA and NR with distributed processing. [ABSTRACT FROM AUTHOR]

This paper discusses a method for the construction of multiport broadband passive macromodels using frequency data obtained from an electromagnetic simulation or measurements. This data could represent the frequency response of a distributed interconnect system. The macromodels are generated using rational functions by solving an eigenvalue problem. For numerical computation, the macromodels are represented as a summation of rational functions consisting of low-pass, band-pass, high-pass, and all-pass filters. The stability and passivity of the macromodels are enforced through constraints on the poles and residues of rational functions. To enable the construction of broad- band macromodels, methods based on band division, selector, subband reordering, subband dilation, and pole replacement have been used. Two test cases that describe the performance of the proposed algorithm, and three test cases that are representative of distributed systems have been analyzed to verify the efficiency of the method. [ABSTRACT FROM AUTHOR]

Speed is a great concern in the recursive shortest spanning tree (RSST) algorithm as its applications are focused on image segmentation and video coding, in which a large amount of data is processed. Several efficient RSST algorithms have been proposed in the literature, but the linking properties are not properly addressed and used in these algorithms and they are intended to produce a truncated RSST. This paper categorizes the linking process into three classes based on link weights. These linking processes are defined as the linking process for link weight equal to zero (LPLW-Z), the linking process for link weight equal to one (LPLW-O), and the linking process for link weight equal to real number (LFLW-R). We study these linking properties and apply them to an efficient RSST algorithm. The proposed efficient RSST algorithm is novel, as it makes use of linking properties, and its resulting shortest spanning tree is truly identical to that produced by the conventional algorithm. Our experimental results show that the percentages of links for the three classes are 17%, 27%, and 58%, respectively. This paper proposes a prediction method for LPLW-O, as a result of which the vertex weight of the next region can be determined by comparing sizes of the merging regions. It is also demonstrated that the proposed LPLW-O with prediction approach is applicable to the multiple-stage merging. Our experimental results show that the proposed algorithm has a substantial improvement over the conventional RSST algorithm. [ABSTRACT FROM AUTHOR]

The MPEG-4 standard enables the representation of video as a collection of objects. This paper describes an automatic system that exploits such a representation. Our system consists of two parts: real-time content extraction algorithms and a real-time multi-object rate control method. We present two approaches to content extraction: foreground segmentation based on two cameras and face segmentation based on a single camera. The main contributions of this paper are: 1) under a stereo camera setup, we improve a disparity estimation algorithm to obtain crisp and smooth boundaries of foreground objects; 2) for a single camera scenario, we propose a novel algorithm for face detection and tracking, combining facial color and structure information; and 3) we develop a constant-quality variable bitrate (CQ-VBR) control algorithm that guarantees the quality specification for each object obtained from the two content extraction methods. Both segmentation algorithms run in real-time on a low-cost media processor and have been tested extensively in various indoor environments. The CQ-VBR control algorithm is a useful tool for the evaluation of object-based coding. For low-bit-rate applications, we can achieve significant reduction in the overall bitrate, while maintaining the same visual quality of the foreground/face object as compared to conventional frame-based coding. Based on tests conducted on several sequences of different complexity levels, the bit-rate savings can be up to 48%. The satisfactory foreground segmentation (results presented) permits porting a live foreground object into arbitrary scenes to create composite video. [ABSTRACT FROM AUTHOR]

The effect of repair of a complex system can usually be approximated by the following two types: minimal repair for which the system is restored to its functioning state with minimum effort, or perfect repair for which the system is replaced or repaired to a good-as-new state. When both types of repair are possible, an important problem is to determine the repair policy; that is, the type of repair which should be carried out after a failure. In this paper, an optimal allocation problem is studied for a monotonic failure rate repairable system under some resource constraints. In the first model, the numbers of minimal & perfect repairs are fixed, and the optimal repair policy maximizing the expected system lifetime is studied. In the second model, the total amount of repair resource is fixed, and the costs of each minimal & perfect repair are assumed to be known. The optimal allocation algorithm is derived in this case. Two numerical examples are shown to illustrate the procedures. [ABSTRACT FROM AUTHOR]

This paper discusses some of the difficulties in the paper: "A BDD-based algorithm for reliability analysis of phased-mission systems" by X. Zang, H. Sun, and K. S. Trivedi. [ABSTRACT FROM AUTHOR]

Current control in inverter-driven machine systems is the inner most component of the hierarchy of control loops. If the control of current in the machine is not fast and accurate then it is difficult, if not impossible, to build a high-performance drive system. Unfortunately, the implementation of current control in power electronic systems is not ideal. Practical effects can have a significant influence on its performance. This paper examines one of these effects, dead time, and considers the influence it has on the performance of predictive current controllers (PCCs). The paper presents analysis that shows that a PCC implicitly compensates for voltage loss due to dead time. Also, a modified PCC is introduced that reduces the zero-current-clamp problem caused by dead time. Simulation and experimental results are presented to verify the analysis and confirm the performance of the new algorithm. [ABSTRACT FROM AUTHOR]

In power distribution networks the load varies within any given time frame. It may, therefore, seem that a good approach to reduce losses would be the solving of a network reconfiguration problem to suit each of the significant load variations. However, frequent changes in configuration can trigger outages or cause transient problems; they are best avoided. A recent formulation of this problem explicitly considers load variations and proposes to restrain frequent reconfigurations by assuming that network topologies will remain unchanged for a given planning period. This formulation leads to a much larger optimization problem than that traditionally used for network reconfiguration; moreover, it requires a new approach to optimization which is capable of dealing with energy flows instead of only instantaneous power flows. Such an approach is proposed in this paper, which discusses the design of an adaptive hybrid genetic algorithm that fulfills these new requirements. Key concepts in evolutionary computation and analysis of distribution systems are explored to develop this new algorithm. Application to real case studies certifies its benefits. [ABSTRACT FROM AUTHOR]

In this paper, dead band control algorithms using a performance index of the load tap changing (LTC) tap position are proposed to reduce the tap changing operation times. The performance index is defined as the customer voltage quality with the tap position of LTC transformer. In addition, dead band control algorithms using the load diversity values of the feeders are proposed. The mathematical formulations of the proposed dead band control algorithms are introduced. A sample case study is shown to verify the effectiveness of the proposed dead band control algorithms. [ABSTRACT FROM AUTHOR]

In a competitive electricity market, price forecasts are important for market participants. However, electricity price is a complex signal due to its nonlinearity, nonstationarity, and time variant behavior. In spite of much research in this area, more accurate and robust price forecast methods are still required. In this paper, a combination of a feature selection technique and cascaded neuro-evolutionary algorithm (CNEA) is proposed for this purpose. The feature selection method is an improved version of the mutual information (MI) technique. The CNEA is composed of cascaded forecasters where each forecaster consists of a neural network (NN) and an evolutionary algorithm (EA). An iterative search procedure is also incorporated in our solution strategy to fine-tune the adjustable parameters of both the MI technique and CNEA. The price forecast accuracy of the proposed method is evaluated by means of real data from the Pennsylvania-New Jersey-Maryland (PJM) and Spanish electricity markets. The method is also compared with some of the most recent price forecast techniques. [ABSTRACT FROM AUTHOR]

As power systems becoming more closely interconnected and are being deregulated in energy markets, distributed simulations among different dispatch centers are highly required for online full system analysis and control applications. In this paper a new algorithm for distributed transient stability simulation of interconnected power systems is presented. Based on a Jacobian-free Newton-GMRES(m) method, this algorithm requires only exchanges of states of boundary buses among different regions. Therefore, it has strong scalability in distributed computing environments built on heterogeneous computing resources. Moreover, several accelerating methods are developed to enhance its efficiency, including continuous preconditioning with adaptive preconditioners, predicting boundary conditions and multistep coordination. The standard IEEE 39-bus system and a real power system with 1165 buses were used as test systems. The test results show that these accelerating methods greatly enhance the convergence rate of the proposed algorithm and reduce communication costs remarkably, which proves the novel algorithm is feasible and can be adopted in wide area networks with high-latency. [ABSTRACT FROM AUTHOR]

Many applications in modern distribution management systems (DMS) need the support of robust and reliable radial power flow analysis. In this connection, although radial power flow solution algorithms are widely proposed in the literature, their application is often complicated by the presence of uncertainties affecting the distribution network operation. The effect of these uncertainties could affect the power flow solution to a considerable extent. A comprehensive tolerance analysis is therefore required in order to incorporate the effect of data uncertainties into power flow analysis. To address this problem, in this paper the employment of interval constraint propagation (ICP) is proposed. ICP is an effective technique for refining enclosures to solutions of nonlinear systems of equations by merging interval mathematic and constraint propagation techniques. Several numerical results are presented and discussed in order to assess the effectiveness of the proposed methodology as an alternative to sampling-based technique, in radial power flow analysis. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of predicting hourly load demand using adaptive artificial neural networks (ANNs). A particle swarm optimization (PSO) algorithm is employed to adjust the network's weights in the training phase of the ANNs. The advantage of using a PSO algorithm over other conventional training algorithms such as the back-propagation (BP) is that potential solutions will be flown through the problem hyperspace with accelerated movement towards the best solution. Thus the training phase should result in obtaining the weights configuration associated with the minimum output error. Data are wavelet transformed during the preprocessing stage and then inserted into the neural network to extract redundant information from the load curve. This results in better load characterization which creates a more reliable forecasting model. The transformed data of historical load and weather information were trained and tested over various periods of time. The generalized error estimation is done by using the reverse part of the data as a "test" set. The results were compared with traditional BP algorithm and offered a high forecasting precision. [ABSTRACT FROM AUTHOR]

Understanding the business (interaction) protocol supported by a service is very important for both clients and service providers: It allows developers to know how to write clients that interact with a service, and it allows development tools and runtime middleware to deliver functionalities that simplifies the service development life cycle. It also greatly facilitates the monitoring, visualization, and aggregation of interaction data. This paper presents an approach for discovering protocol models from real-world service interaction logs. It presents a novel discovery algorithm, which is widely applicable, robust to different kinds of imperfections often present in real-world service logs, and able to derive protocols of small sizes targeted for human understanding. As interring the most precise and concise model is not always possible from imperfect service logs using purely automated method, the paper presents a novel method for user-driven refinement of the discovered protocol models. The proposed approach has been implemented and experimental results show its viability on both synthetic and real-world data sets. [ABSTRACT FROM AUTHOR]

This paper presents a new concept of removing impulse noise through primary implicant elimination (PIE) applied to a logical system representation of the data. Applicable to binary and grayscale images, errors are corrected efficiently, in terms of the number of computations and memory requirements, while the fine details of the image are mostly preserved. Three filtering algorithms are presented: a general form in addition to iterative and switching variations. Experimental results on salt-and-pepper impulse noise, as well as on random-valued impulse noise, are compared against the performance of traditional median-based filters (both regular and switching) and are shown to be most successful in the often difficult case of when the original image contains many detailed patterns. [ABSTRACT FROM AUTHOR]

The investment in an automated fabric defect detection system is more than economical when reduction in labor cost and associated benefits are considered. The development of a fully automated web inspection system requires robust and efficient fabric defect detection algorithms. The inspection of real fabric defects is particularly challenging due to the large number of fabric defect classes, which are characterized by their vagueness and ambiguity. Numerous techniques have been developed to detect fabric defects and the purpose of this paper is to categorize and/or describe these algorithms. This paper attempts to present the first survey on fabric defect detection techniques presented in about 160 references. Categorization of fabric defect detection techniques is useful in evaluating the qualities of identified features. The characterization of real fabric surfaces using their structure and primitive set has not yet been successful. Therefore, on the basis of the nature of features from the fabric surfaces, the pro- posed approaches have been characterized into three categories; statistical, spectral and model-based. In order to evaluate the state-of-the-art, the limitations of several promising techniques are identified and performances are analyzed in the context of their demonstrated results and intended application. The conclusions from this paper also suggest that the combination of statistical, spectral and model-based approaches can give better results than any single approach, and is suggested for further research. [ABSTRACT FROM AUTHOR]

Recently, there has been a dramatic increase in the use of XML data to deliver information over the Web. Personal Weblogs, news Web sites, and discussion forums are now publishing RSS feeds for their subscribers to retrieve new postings. As the popularity of personal Weblogs and RSS feeds grows rapidly, RSS aggregation services and blog search engines have appeared, which try to provide a central access point for simpler access and discovery of new content from a large number of diverse RSS sources. In this paper, we study how the RSS aggregation services should monitor the data sources to retrieve new content quickly using minimal resources and to provide its subscribers with fast news alerts. We believe that the change characteristics of RSS sources and the general user access behavior pose distinct requirements that make this task significantly different from the traditional index refresh problem for Web search engines. Our studies on a collection of 10,000 RSS feeds reveal some general characteristics of the RSS feeds and show that, with proper resource allocation and scheduling, the RSS aggregator provides news alerts significantly faster than the best existing approach. [ABSTRACT FROM AUTHOR]

Engineering change order changes are almost inevitable in the late stages of a design process. Based on an existing design, incremental change is favored since it can avoid considerable efforts of redoing the whole process and can minimize the disturbance on the existing converged design. The coupling-capacitance violation elimination (CVE) problem is addressed. Due to the changes in the multiple layer routing design, the total coupling capacitance on some signal wire segments on a layer may be larger than their allowable bounds after postlayout timing/noise analysis. The target is to find a new routing solution without coupling-capacitance violations under certain constraints, which helps to keep the new design close to the original one. This paper proposes a two-stage algorithm to solve CVE problems, and present optimization strategies to speed up the execution. Experimental results demonstrate the efficiency and effectiveness of this algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of two control parameters of the Universal Mobile Telecommunications System (UMTS) handoff algorithm on the total peak base station (BS) transmit power required per mobile station (MS) to satisfy a prescribed outage probability. Denoting the set of BSs supporting an MS in soft handoff (SH) as the active group, the first parameter n is the maximum allowed size of the active group. The second, denoted r, is the upper limit on the difference between the path loss of the dominant BS and that of any other member of the active group, where the term "dominant" refers to the BS with the lowest path loss to the MS. It was assumed that the MS is equipped with a Rake receiver capable of performing "maximal ratio combining" of the signals it receives from the transmitting BSs. General analytical derivations along with results derived for specific situations through numerical integration are presented. [ABSTRACT FROM AUTHOR]

In this paper, we present a unified approach for the computation of the outage probability, the level crossing rate (LCR), and the average outage duration (AOD) of selection combining (SC) in the presence of multiple cochannel interferences and under both minimum signal-to-interference ratio (SIR) and desired signal power constraints. We consider three selection algorithms, namely, 1) the best signal power algorithm; 2) the best SIR algorithm; and 3) the best total power (desired plus interference) algorithm. As a specific application example, we analyze the three algorithms for a low-complexity dual-branch SC receiver subject to multiple interferers over Rayleigh fading channels. When applicable, the new results are compared to those previously reported in the literature dealing with the outage probability, AOD, and LCR of 1) interference-limited systems and 2) power-limited systems. Numerical examples show that the minimum desired signal power constraint induces a floor to the outage probability, AOD, and LCR performance measures. They also show that the best SIR algorithm provides the best outage probability and AOD performance for low average SIR. On the other hand, the best signal power algorithm and the best S + I algorithm outperform the best SIR algorithm for high average SIR. It is also shown that the best SIR algorithm tends to have more outage level crossings. [ABSTRACT FROM AUTHOR]

Switching state-space models have been widely used in many applications arising from science, engineering, economic, and medical research. In this paper, we present a Monte Carlo Expectation Maximization (MCEM) algorithm for learning the parameters and classifying the states of a state-space model with a Markov switching. A stochastic implementation based on the Gibbs sampler is introduced in the expectation step of the MCEM algorithm. We study the asymptotic properties of the proposed algorithm, and we also describe how a nesting approach and the Rao-Blackwellized forms can be employed to accelerate the rate of convergence of the MCEM algorithm. Finally, the performance and the effectiveness of the proposed method are demonstrated by applications to simulated and physiological experimental data. [ABSTRACT FROM AUTHOR]

Divisible load applications occur in many fields of science and engineering and can be easily parallelized in a master-worker fashion, but pose several scheduling challenges. While a number of approaches have been proposed that allocate toad to workers in a single round, using multiple rounds improves overlap of computation with communication. Unfortunately, multiround algorithms are difficult to analyze and have thus received only limited attention. In this paper, we answer three open questions in the multiround divisible load scheduling area: 1) how to account for Iatencies, 2) how to account for heterogeneous platforms, and 3) how many rounds should be used. To answer 1), we derive the first closed-form optimal schedule for a homogeneous platform with both computation and communication latencies, for a given number of rounds. To answer 2) and 3), we present a novel algorithm, UMR. We evaluate UMR in a variety of realistic scenarios. [ABSTRACT FROM AUTHOR]

Many engineering problems that can be formulated as constrained optimization problems result in solutions given by a waterfilling structure; the classical example is the capacity-achieving solution for a frequency-selective channel. For simple waterfilling solutions with a single waterlevel and a single constraint (typically, a power constraint), some algorithms have been proposed in the literature to compute the solutions numerically. However, some other optimization problems result in significantly more complicated waterfilling solutions that include multiple waterlevels and multiple constraints. For such cases, it may still be possible to obtain practical algorithms to evaluate the solutions numerically but only after a painstaking inspection of the specific waterfilling structure. In addition, a unified view of the different types of waterfilling solutions and the corresponding practical algorithms is missing. The purpose of this paper is twofold. On the one hand, it overviews the waterfilling results existing in the literature from a unified viewpoint. On the other hand, it bridges the gap between a wide family of waterfilling solutions and their efficient implementation in practice; to be more precise, it provides a practical algorithm to evaluate numerically a general waterfilling solution, which includes the currently existing waterfilling solutions and others that may possibly appear in future problems. [ABSTRACT FROM AUTHOR]

This paper proposes a suite of approaches to solve the survivable routing problem with shared protection. We first define in mathematics the maximum extent of resource sharing for a protection path given the corresponding working path according to the current network link-state. Then the problem of solving the least-cost working & protection path-pair (in terms of the sum of the cost) is formulated into an Integer Linear Programming process. Due to the dependency of the protection path on its working path, however, the formulation is not scalable with the network size, and takes an extract effort to solve. Therefore, we introduce two heuristic algorithms, called Iterative Two-Step-Approach (ITSA) & Maximum Likelihood Relaxation (MLR), which aim to explore the approximating eptimal solutions with less computation time. We evaluate the performance of the proposed schemes, and make a comparison with some reported counterparts. The simulation results show that the ITSA scheme, with a properly defined tolerance to optimality, can achieve the best performance at the expense of more computation time. On the other hand, MLR delivers a compromise between computation efficiency & performance. [ABSTRACT FROM AUTHOR]

The transient behavior of a system with operational and repair times distributed following phase-type distributions is studied. These times are alternated in the evolution of the system, and they form 2 separate geometric processes. The stationary study of this system when the repair times form a renewal process has been made [3]. This paper also considers that operational times are partitioned into two well-distinguished classes successively accupied: good, and preventive. An algorithmic approach is performed to determine the transition probabilities for the Markov process which governs the system, and other performance measures beyond those in [3] are calculated in a well-structured form. The results are applied to a numerical example, and the transient quantities are compared with the ones obtained in the stationary case. The computational implementation of the mathematical expressions formulated are performed using the Matlab program. [ABSTRACT FROM AUTHOR]

The concept of miss distance--Euclidean, Mahalanobis, etc.--is a fundamental, far-reaching, and taken-for-granted element of the engineering theory and practice of single-target systems. In this paper we introduce a comprehensive Lp-type theory of distance metrics for multitarget (and, more generally, multiobject) systems. We show that this theory extends, and provides a rigorous theoretical basis for, an intuitively appealing optimal-assignment approach proposed by Drummond for evaluating the performance of multitarget tracking algorithms. We describe tractable computational approaches for computing such metrics based on standard optimal assignment or convex optimization techniques. We describe the potentially far-reaching implications of these metrics for applications such as performance evaluation and sensor management. In the former case, we demonstrate the application of multitarget miss-distance metrics as measures of effectiveness (MoEs) for multitarget tracking algorithms. [ABSTRACT FROM AUTHOR]

Trellis-coded space-time (TC-ST) coding for continuous-phase modulation (TC-ST-CPM) was recently proposed by Zhang and Fitz. In this paper, we propose an orthogonal space-time coding for CPM (OST-CPM) systems and two transmit antennas. In the proposed OST-CPM, signals from two transmit antennas at any time t are orthogonal while both of them have continuous phases. Similar to Alamouti's OST coding for phase-shift keying (PSK) and quadrature amplitude modulation (QAM) systems, the newly proposed OST-CPM has a fast decoding algorithm. [ABSTRACT FROM AUTHOR]

The ability of using dispersed generation (DG) in the distribution system restoration service in the context of smart networks is presented in this paper. The objectives are to reduce the consequences due to a major blackout in terms of the out-of-service load volume, and the duration of restoration process. Based on knapsack problem formulation and network represented graph modeling, a new restoration procedure for distribution network is proposed. An adapted branch-and-bound algorithm is then used to solve the problem. It maximizes the restored loads in distribution by using the DG availability. Simulation results on a study case will be shown to illustrate the proposed procedure and quantify the benefit of using DG in critical situations. [ABSTRACT FROM AUTHOR]

The problem of opportunistic access of parallel channels occupied by primary users is considered. Under a continuous-time Markov chain modeling of the channel occupancy by the primary users, a slotted transmission protocol for secondary users using a periodic sensing strategy with optimal dynamic access is proposed. To maximize channel utilization while limiting interference to primary users, a framework of constrained Markov decision processes is presented, and the optimal access policy is derived via a linear program. Simulations are used for performance evaluation. It is demonstrated that periodic sensing yields negligible loss of throughput when the constraint on interference is tight. [ABSTRACT FROM AUTHOR]

Software quality assurance is a vital component of software project development. A software quality estimation model is trained using software measurement and defect (software quality) data of a previously developed release or similar project. Such an approach assumes that the development organization has experience with systems similar to the current project and that defect data are available for all modules in the training data. In software engineering practice, however, various practical issues limit the availability of defect data for modules in the training data. In addition, the organization may not have experience developing a similar system. In such cases, the task of software quality estimation or labeling modules as fault prone or not fault prone falls on the expert. We propose a semisupervised clustering scheme for software quality analysis of program modules with no defect data or quality-based class labels. It is a constraint-based semisupervised clustering scheme that uses k-means as the underlying clustering algorithm. Software measurement data sets obtained from multiple National Aeronautics and Space Administration software projects are used in our empirical investigation. The proposed technique is shown to aid the expert in making better estimations as compared to predictions made when the expert labels the clusters formed by an unsupervised learning algorithm. In addition, the software quality knowledge learnt during the semisupervised process provided good generalization performance for multiple test data sets. An analysis of program modules that remain unlabeled subsequent to our semisupervised clustering scheme provided useful insight into the characteristics of their software attributes. [ABSTRACT FROM AUTHOR]

Random noise radar has recently been used in a variety of imaging and surveillance applications. These systems can be made phase coherent using the technique of heterodyne correlation. Phase coherence has been exploited to measure Doppler and thereby the velocity of moving targets. The Doppler visibility, i.e., the ability to extract Doppler information over the inherent clutter spectra, is constrained by system parameters, especially the phase noise generated by microwave components. Our paper proposes a new phase noise model for the heterodyne mixer as applicable for ultrawideband (UWB) random noise radar and for the local oscillator in the time domain. The Doppler spectra are simulated by including phase noise contamination effects and compared with our previous experimental results. A genetic algorithm (GA) optimization routine is applied to synthesize the effects of a variety of parameter combinations to derive a suitable empirical formula for estimating the Doppler visibility in dB. According to the phase noise analysis and the simulation results, the Doppler visibility of UWB random noise radar depends primarily on the following parameters: 1) the local oscillator (LO) drive level of the receiver heterodyne mixer, 2) the saturation current in the receiver heterodyne mixer, 3) the bandwidth of the transmit noise source, and 4) the target velocity. Other parameters such as the carrier frequency of the receiver LO and the loaded quality factor of the LO have a small effect over the range of applicability of the model and are therefore neglected in the model formulation. The Doppler visibility curves generated from this formula match the simulation results very well over the applicable parameter range within 1 dB. Our model may therefore be used to quickly estimate the Doppler visibility of random UWB noise radars for trade-off analysis. [ABSTRACT FROM AUTHOR]

Over the past several decades, there has been a considerable interest in investigating high-speed dynamic gaits for legged robots. While much research has been published, both in the biomechanics and engineering fields regarding the analysis of these gaits, no single study has adequately characterized the dynamics of high-speed running as can be achieved in a realistic, yet simple, robotic system. The goal of this paper is to find the most energy-efficient, natural, and unconstrained gallop that can be achieved using a simulated quadrupedal robot with articulated legs, asymmetric mass distribution, and compliant legs. For comparison purposes, we also implement the bound and canter. The model used here is planar, although we will show that it captures much of the predominant dynamic characteristics observed in animals. While it is not our goal to prove anything about biological locomotion, the dynamic similarities between the gaits we produce and those found in animals does indicate a similar underlying dynamic mechanism. Thus, we will show that achieving natural, efficient high-speed locomotion is possible even with a fairly simple robotic system. lb generate the high-speed gaits, we use an efficient evolutionary algorithm called set-based stochastic optimization. This algorithm finds open-loop control parameters to generate periodic trajectories for the body. Several alternative methods are tested to generate periodic trajectories for the legs. The combined solutions found by the evolutionary search and the periodic-leg methods, over a range of speeds up to 10.0 m/s, reveal "biological" characteristics that are emergent properties of the underlying gaits. [ABSTRACT FROM AUTHOR]

Three-dimensional (3-D) subband/wavelet coding with motion compensation has been demonstrated to be an efficient technique for video coding applications in some recent research works. When motion compensation is performed with half-pixel accuracy, images need to be interpolated in both temporal sub- band analysis and synthesis stages. The resulting subband filter banks developed in these former algorithms were not invertible due to image interpolation. In this paper, an invertible temporal analysis/synthesis system with half-pixel-accurate motion compensation is presented. We look at temporal decomposition of image sequences as a kind of down-conversion of the sampling lattices. The earlier motion-compensated (MC) interlaced/progressive scan conversion scheme is extended for temporal subband analysis/synthesis. The proposed subband/wavelet filter banks allow perfect reconstruction of the decomposed video signal while retaining high energy compaction of subband transforms. The invertible filter banks are then utilized in our 3-D subband video coder. This video coding system does not contain the temporal DPCM loop employed in the conventional hybrid coder and the earlier MC 3-D subband coders. The experimental results show a significant PSNR improvement by the proposed method. The generalization of our algorithm for MC temporal filtering at arbitrary subpixel accuracy is also discussed. [ABSTRACT FROM AUTHOR]

There are two main contributions of this paper. First, this paper introduces the concept of a processor working set (pws) as a single value parameter for characterizing the parallel program behavior. Through detailed experimental studies of different algorithms on a transputer-based multiprocessor machine, it is shown that the pws is indeed a robust measure for characterizing the workload of a multiprocessor system. Small deviations in the performance of algorithms arising due to communication overhead are captured in this parameter. The second contribution of this paper relates to the study of static processor allocation strategies. It is shown that processor allocation strategies based on the pws provide significantly better throughput-delay characteristics. The robustness of pws is further demonstrated by showing that allocation policies that allocate processors more than the pws are inferior in performance to those that never allocate more than the pws—even at a moderately low load. Based on the results, a simple static allocation policy that allocates the pws at low load and adaptively fragments at high load to one processor per job is proposed. This allocation strategy is shown to possess the best throughput-delay characteristic over a wide range of loads. [ABSTRACT FROM AUTHOR]

The concept of multiway rendezvous has been proposed to implement synchronous communication among an arbitrary number of concurrent, asynchronous processes. The synchronization and exclusion problems associated with implementing multiway rendezvous are expressed succinctly in the context of the committee coordination problem. A variety of techniques to solve the synchronization and exclusion problems may be combined to design algorithms for the committee coordination problem. This paper presents a simple solution for the problem and shows how it can be implemented to develop a family of algorithms. The algorithms use message counts to solve synchronization and solve the exclusion problem by using a circulating token, or by using auxiliary resources as in the solutions for the dining or drinking philosophers problems. The paper also presents the results of a simulation study on the performance of the algorithms. The experiments measured the response time and message complexity of each algorithm as a result of variations in different model parameters including network topology and level of conflict in the system. The results from the study show that the response time for algorithms proposed in this paper is significantly better than an existing algorithm, whereas the message complexity is considerably worse. [ABSTRACT FROM AUTHOR]

This study deals with simultaneous testing of two systems, one "basic" (subscript b), and the other "new" (n), both with an exponential distribution describing the times between failures. We test whether the mean TBFn/MTBFb ratio equals a given value, versus whether it is smaller than the given value. These tests yield a binomial pattern. A recursive algorithm calculates the probability of a given combination of failure numbers in the systems, permitting rapid, accurate determination of the test characteristics. The influence of truncation of Wald's Sequential Probability Ratio Test (SPRT) on its characteristics is analysed, and relationships are derived for calculating the coordinates of truncation apex (TA). A test planning methodology is presented for the most common cases. [ABSTRACT FROM AUTHOR]

We present a new algorithm for joint detection and decoding of iteratively decodable codes transmitted over channels affected by a time-varying phase noise (PN) and a constant frequency offset. The proposed algorithm is obtained as an application of the sum-product algorithm to the factor graph representing the joint a posteriori distribution of the information symbols and the channel parameters given the channel output. The resulting algorithm employs the soft-output information on the coded symbols provided by the decoder and performs forward- backward recursions, taking into account the joint probability distribution of phase and frequency offset. We present simulation results for high-order coded modulation schemes based on low-density parity-check codes and serially concatenated convolutional codes, showing that, despite its low complexity, the algorithm is able to cope with a strong PN and a significant uncompensated frequency offset, thus avoiding the use of complicated data-aided frequency-estimation schemes operating on a known preamble. The robustness of the algorithm in the presence of a time-varying frequency offset is also discussed. [ABSTRACT FROM AUTHOR]

The navigation state (position, velocity, and attitude) can be determined using optical measurements from an imaging sensor pointed toward the ground. Extracting navigation information from an image sequence depends on tracking the location of stationary objects in multiple images, which is generally termed the correspondence problem. This is an active area of research and many algorithms exist which attempt to solve this problem by identifying a unique feature in one image and then searching subsequent images for a feature match. In general, the correspondence problem is plagued by feature ambiguity, temporal feature changes, and occlusions which are difficult for a computer to address. Constraining the correspondence search to a subset of the image plane has the dual advantage of increasing robustness by limiting false matches and improving search speed. A number of ad hoc methods to constrain the correspondence search have been proposed in the literature. A rigorous stochastic projection method is developed here which constrains the correspondence search space by incorporating a priori knowledge of the aircraft navigation state using inertial measurements and a statistical terrain model. The stochastic projection algorithm is verified using Monte Carlo simulation and flight data. The constrained correspondence search area is shown to accurately predict the pixel location of a feature with an arbitrary level of confidence, thus promising improved speed and robustness of conventional algorithms. [ABSTRACT FROM AUTHOR]

This article studies the reliability bounds of arbitrary graphs under the NEF model. It finds good upper bound & lower bound expressions, and efficient algorithms for bounding the reliability R(G). These expressions are simple & easy to understand. The algorithms are highly accurate. In fact, this article demonstrates that the difference between the upper bounds & lower bounds gradually leads to zero. As an example application, we apply the bounding algorithms to the dependable distributed system which we developed for secure internet applications. The article used these algorithms to find the best-suitable subgraphs to host critical tasks.