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By increase in smart phone penetration rate, mobile social networks (MSNs) become more popular. In such networks, users can exchange and share information via peer‐to‐peer opportunistic wireless connections. Wireless connections are prone to failures, devices are battery‐powered, and the buffer space is limited. These lead to uncertainty in connections and selfish behaviours in dissemination processes. Hence, information dissemination in MSNs becomes a challenge. In this study, the authors analyse the information dissemination in MSNs with selfish users from different communities. They develop an analytical model through ordinary differential equations to analyse the dissemination process in MSNs. Then, they propose an optimisation problem to find the optimal forwarding probabilities of users. They employ the branch and bound‐outer approximation algorithm to analytically solve the optimisation problem. The analytical results represent that the optimal forwarding probability of users diminished by increasing the number of relay users, which accelerate the dissemination in the network. Also, these results represent that the proposed algorithm to find the optimal selfishness vector can improve the network performance by decreasing the dissemination delay. [ABSTRACT FROM AUTHOR]

This study addresses two algorithms for set stabilisation of Boolean control networks (BCNs). Based on the semi‐tensor product tool, the dynamics of BCNs can be characterised by its labelled digraph, which derived an graphical expression for the set stabilisation of BCNs. Then, two tree‐search algorithms, namely, generalised breadth‐first search and generalised depth‐first search, are proposed for the first time to decide the controllers for the set stabilisation of BCNs. In addition, some properties concerning the tree search algorithm are proposed. Finally, an example is employed to show the application of the presented algorithms. [ABSTRACT FROM AUTHOR]

The DC distribution technology brings challenges and opportunities to the penetration of large‐scale distributed renewable energy sources. In a medium‐voltage DC (MVDC) distribution network, operation mode switch occurs owing to some large disturbances. To manage these disturbances and achieve seamless switch of the operation mode, a hierarchical control strategy with two layers, namely local and global layers, is proposed in this work. The novel local layer controller called P–U–I controller is designed to enhance the voltage stability, improve system controllability and suppress overcurrent under large disturbances. This controller only needs local information and does not rely on fast communication. Furthermore, as the scale of the DC distribution network expands continuously, the number of system operation mode increases in geometric progression. Therefore, a global layer controller based on breadth‐first search algorithm is proposed. This controller can automatically identify the system topology and adjust the control mode of converters to optimise the system operating characteristics. Thus, this hierarchical control strategy can accurately control the system power in steady state, suppress overcurrent under large disturbances and suit large‐scale DC distribution networks. Finally, a three‐terminal MVDC distribution network simulation model established on power systems computer‐aided design and RT‐LAB validates the proposed strategy. [ABSTRACT FROM AUTHOR]

Complete orders, also called chains, are transitive acyclic digraphs which can be employed as a topological unit to model, abstract and exploit the Internet's path diversity. The main objective behind this work is to demonstrate why complete orders are well suited in abstracting routing information at the interdomain level. In order to abstract a network's topological information, it becomes necessary to introduce another mathematical structure called virtual arc, which allows to define complete orders where these cannot be formed directly. An algorithm, called chain routing, that employs virtual arcs to define chains in a network is described and tested. Further analysis of the chain routing algorithm leads to the conclusion that this is an NP‐complete problem; however, by limiting the size of the complete orders to be used, it is possible to provide an upper bound to the computational task needed to discover these structures in the Internet. [ABSTRACT FROM AUTHOR]

Simulation‐based sequential test generation procedures address the high computational complexity of sequential test generation by replacing the deterministic branch‐and‐bound process with lower‐complexity processes. These processes introduce new primary input patterns into a functional test sequence in order to increase its fault coverage. This study observes that, even without introducing new primary input patterns, it is possible to increase the fault coverage of a functional test sequence by applying the same primary input patterns in different orders. This is referred to as reconstruction of the sequence. It provides a new low‐complexity option for increasing the fault coverage, and thus addressing the high computational complexity of sequential test generation. This study describes a reconstruction procedure that is based on repeating short subsequences of primary input patterns from the sequence. Experimental results demonstrate the effectiveness of the reconstruction procedure in increasing the fault coverage as part of a simulation‐based sequential test generation procedure. [ABSTRACT FROM AUTHOR]

Finding the best phylogenetic tree under the maximum parsimony optimality criterion is computationally difficult. We quantify the occurrence of such optima for well-behaved sets of data. When nearest neighbor interchange operations are used, multiple local optima can occur even for 'perfect' sequence data, which results in hill-climbing searches that never reach a global optimum. In contrast, we show that when neighbors are defined via the subtree prune and regraft metric, there is a single local optimum for perfect sequence data, and thus, every such search finds a global optimum quickly. We further characterize conditions for which sequences simulated under the Cavender-Farris-Neyman and Jukes-Cantor models of evolution yield well-behaved search spaces. [ABSTRACT FROM AUTHOR]

In this study, the authors propose a modelling algorithm of inductors that provides a powerful tool for solving a variety of engineering optimisation problems. The algorithm has been developed in accordance with desire to consolidate cost benefit, losses minimisation and inductance maximisation, and finding the best manufacturing solution. A non‐linear mathematical model for optimisation of three‐phase, dry type double‐E iron‐core inductor has been presented in this study. Its purpose is to show that design of three‐phase, air‐cooled, network frequency inductors can be obtained using of new, adopted non‐linear modelling algorithm‐MISP (mixed‐integer signomial programming), for minimising cost of materials (or inductor's mass) while ensuring the satisfaction of inductance value together with constraints imposed by overall measures, copper fill factor, maximum allowed induction, current density and temperature rise. The MISP is solved using branch‐and‐bound approach, specially implemented to inductor design problems. To confirm the result obtains by optimisation, inductor has been constructed according to the minimum loss criterion. The application is industry acceptable in cases if there are restrictions on the inductor weight. Also, where core dimensions are known, this approach can be used to design inductor by either maximising the inductance value or minimising total losses. [ABSTRACT FROM AUTHOR]

Combining the best‐first tree search and orthogonal matching pursuit (OMP), A*OMP has been introduced that aims at solving the compressed sensing problem. The theoretical analysis of A*OMP is mainly presented and an improved condition for exact recovery of sparse signals via the A*OMP algorithm is proposed. [ABSTRACT FROM AUTHOR]

After a major outage happens, the independent system operator, transmission owners (TOs), generation owners (GOs), and distribution owners (DOs) should coordinate control actions to restore the power system timely and reliably. This study proposes a methodology to establish load restoration plans for the coordination among these participants. This methodology models the load restoration as a multi‐stage decision‐making process. At each stage, a mixed‐integer nonlinear load restoration model (MINLR) is formulated to maximise load pickup subject to AC power flow and reserve constraints. Comprehensive load characteristics are considered in this model. The solution of the MINLR model provides power set points for GOs/TOs and load pickup amount for DOs. A complete load restoration plan is obtained by solving a series of MINLR models. To solve MINLR models efficiently, a branch‐and‐cut solver is constructed by identifying efficient cutting planes and a reliable problem‐specific branching method. The applicability of cutting planes is proven. This methodology is tested using a 24‐bus system with 170 interrupted load increments, and a 118‐bus system with 637 interrupted load increments. The simulation results show that the proposed methodology can be efficiently applied to aid restoration participants pickup load increments within the TO's islands, while maintaining adequate reserve margins. [ABSTRACT FROM AUTHOR]

In this paper, we propose a low-complexity multiple-input multiple-output (MIMO) detection algorithm with lattice-reduction-aided fixed-complexity tree searching which is motivated by the fixed-complexity sphere decoder (FSD). As the proposed scheme generates a fixed tree whose size is much smaller than that of the full expansion in the FSD, the computational complexity is reduced considerably. Nevertheless, the proposed scheme achieves a near-maximum-likelihood (ML) performance with a large number of transmit antennas and a high-order modulation. The experimental results demonstrate that the performance degradation of the proposed scheme is less than 0.5 dB at the bit error rate (BER) of 10^-5 for a 8 $\times$ 8 MIMO system with 256 QAM. Also, the proposed method reduces the complexity to about 1.23% of the corresponding FSD complexity. [ABSTRACT FROM PUBLISHER]

Local binary pattern (LBP) and its variants have shown promising results in visual recognition applications. However, most existing approaches rely on a pre-defined structure to extract LBP features. We argue that the optimal LBP structure should be task-dependent and propose a new method to learn discriminative LBP structures. We formulate it as a point selection problem: Given a set of point candidates, the goal is to select an optimal subset to compose the LBP structure. In view of the problems of current feature selection algorithms, we propose a novel Maximal Joint Mutual Information criterion. Then, the point selection is converted into a binary quadratic programming problem and solved efficiently via the branch and bound algorithm. The proposed LBP structures demonstrate superior performance to the state-of-the-art approaches on classifying both spatial patterns in scene recognition and spatial-temporal patterns in dynamic texture recognition. [ABSTRACT FROM AUTHOR]

It is well known that broadband wireless communications (BWC) are necessary for high speed vehicles since passengers need many broadband wireless multimedia services. However, one design challenge is to identify sufficient spectrum resource to support BWC in high speed vehicles. Recently, cognitive radios (CRs) are being considered as a promising technology to solve scarcity problem of spectrum resource. Therefore, we investigate the spectrum resource allocation problem in the CR based high speed vehicle network (CR-HSVN) in this paper. Specifically, we propose a spectrum resource allocation framework, where high speed vehicles could effectively utilize the TV white spaces. Subsequently, we formulate the allocation of spectrum resource as an optimization problem to maximize the available spectrum resources (i.e., TV white spaces) utilized by the CR-HSVN, and investigate the property of the CR-HSVN to reduce the complexity by separation computing method without loss of optimality. Furthermore, we analyze the optimal solution based on branch and bound method, the suboptimal solutions based on single channel and linear programming, respectively. Simulation results show that the proposed framework could offer excellent performances of the spectrum utilization and fairness for the CR-HSVN. Meanwhile, the aggregated interference from vehicles to primary users is constrained. [ABSTRACT FROM PUBLISHER]

In this paper we present a decoding algorithm for multiple-input multiple-output (MIMO) communications. The algorithm is based on the QRD-QLD algorithm (see, e.g., Radosavljevic et al. 2012), proposes an improved path metric computation, and achieves a low probability of error which is close to the single tree search sphere decoder, at low implementation complexity. The proposed improved path metric computation increases the reliability of combining the results of the partial searches into sequences representing the maximum likelihood (ML) and the counter ML hypotheses in soft input MIMO decoding. The excellent performance of the improved algorithm are demonstrated via numerical simulations. [ABSTRACT FROM PUBLISHER]

Sum-rate maximization in two-way amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying belongs to the class of difference-of-convex functions (DC) programming problems. DC programming problems occur also in other signal processing applications and are typically solved using different modifications of the branch-and-bound method which, however, does not have any polynomial time complexity guarantees. In this paper, we develop two efficient polynomial time algorithms for the sum-rate maximization in two-way AF MIMO relaying. The first algorithm guarantees to find at least a Karush-Kuhn-Tucker (KKT) solution. There is a strong evidence, however, that such a solution is actually globally optimal. The second algorithm that is based on the generalized eigenvectors shows the same performance as the first one with reduced computational complexity. The objective function of the problem is represented as a product of quadratic fractional ratios and parameterized so that its convex part (versus the concave part) contains only one (or two) optimization variables. One of the algorithms is called POlynomial Time DC (POTDC) and is based on semi-definite programming (SDP) relaxation, linearization, and an iterative Newton-type search over a single parameter. The other algorithm is called RAte-maximization via Generalized EigenvectorS (RAGES) and is based on the generalized eigenvectors method and an iterative search over two (or one, in its approximate version) optimization variables. We derive an upper-bound for the optimal value of the corresponding optimization problem and show by simulations that this upper-bound is achieved by both algorithms. It provides an evidence that the algorithms find a global optimum. The proposed methods are also superior to other state-of-the-art algorithms. [ABSTRACT FROM PUBLISHER]

In branch-and-bound (B&B) schemes for solving a minimization problem, a better lower bound could prune many meaningless branches which do not lead to an optimum solution. In this paper, we propose several techniques to refine the lower bound on the makespan in the multiprocessor scheduling problem (MSP). The key idea of our proposed method is to combine an efficient quadratic-time algorithm for calculating the Fernández's bound, which is known as the best lower bounding technique proposed in the literature with two improvements based on the notions of binary search and recursion. The proposed method was implemented as a part of a B&B algorithm for solving MSP, and was evaluated experimentally. The result of experiments indicates that the proposed method certainly improves the performance of the underlying B&B scheme. In particular, we found that it improves solutions generated by conventional heuristic schemes for more than 20 percent of randomly generated instances, and for more than 80 percent of instances, it could provide a certification of optimality of the resulting solutions, even when the execution time of the B&B scheme is limited by one minute. [ABSTRACT FROM AUTHOR]

Bidirectional reflectance distribution function (BRDF) estimation is one of the fundamental problems in computer graphics, computer vision and related fields, yet most work relies on conventional local minimisation. Two global optimisation methods for estimating the anisotropic Ward BRDF model and its variants under an L2‐cost function are introduced. The presented algorithms are based on branch‐and‐bound search which guarantees to provide globally optimal solutions. In contrast to the traditional local optimisation, the methods mentioned here are not affected by the setting of initial BRDF parameter values. Experiments have been carried out to validate the presented methods using anisotropic materials from the UTIA BRDF database. [ABSTRACT FROM AUTHOR]

This paper presents a security analysis for data-hiding methods based on nested lattice codes, extending the analysis provided by previous works to a more general scenario. The security is quantified as the difficulty of estimating the secret key used in the embedding process, assuming that the attacker has several signals watermarked available with the same secret key. The theoretical analysis accomplished in the first part of this paper quantifies security in an information-theoretic sense by means of the mutual information between the watermarked signals and the secret key, addressing important issues, such as the possibility of achieving perfect secrecy and the impact of the embedding rate in the security level. In the second part, a practical algorithm for estimating the secret key is proposed, and the information extracted is used for implementing a reversibility attack on real images. [ABSTRACT FROM PUBLISHER]

Sparse signal representations and approximations from overcomplete dictionaries have become an invaluable tool recently. In this paper, we develop a new, heuristic, graph-structured, sparse signal representation algorithm for overcomplete dictionaries that can be decomposed into subdictionaries and whose dictionary elements can be arranged in a hierarchy. Around this algorithm, we construct a methodology for advanced image formation in wide-angle synthetic aperture radar (SAR), defining an approach for joint anisotropy characterization and image formation. Additionally, we develop a coordinate descent method for jointly optimizing a parameterized dictionary and recovering a sparse representation using that dictionary. The motivation is to characterize a phenomenon in wide-angle SAR that has not been given much attention before: migratory scattering centers, i.e., scatterers whose apparent spatial location depends on aspect angle. Finally, we address the topic of recovering solutions that are sparse in more than one objective domain by introducing a suitable sparsifying cost function. We encode geometric objectives into SAR image formation through sparsity in two domains, including the normal parameter space of the Hough transform. [ABSTRACT FROM AUTHOR]

We explore the performance and hardware complexity tradeoffs associated with performing iterative multiple-input multiple-output (MIMO) detection using a sphere decoder and a low-density parity-check (LDPC) decoder. Iterations are performed both within the LDPC decoder as well as via an outer iteration loop through which refined soft information is fed back from the LDPC decoder to a MIMO detector. A hardware architecture and associated implementation results on Xilinx Virtex-5 field programmable gate array for a 4x4 QPSK MIMO system are presented. The system offers a performance improvement of approximately 1 dB over systems without the outer iteration loop, and provides an information bit throughput that ranges from 60 to 300 megabits per second when a length 1944 rate 1/2 LDPC code is used. [ABSTRACT FROM AUTHOR]

Previously, an optical code-division multiplexing (OCDM)-based network architecture was proposed to improve the wavelength utilization and to provide finer bandwidth granularities to users. By this technology, different channels using distinct optical codes (OCs) can be multiplexed onto the same wavelength, in which an OC is considered as the basic unit in lightpath provisioning. In the ideal case, multiaccess interference (MAI) inherent to the OCDM technology is assumed to be removed completely at intermediate nodes and cannot be propagated or accumulated along the lightpath. However, since no optical-electrical (O/E) or electrical-optical (E/O) conversion is allowed in transparent OCDM-based optical networks, the MAI cannot be removed completely at intermediate nodes with current all-optical regeneration techniques. As a result, the residual MAI may be propagated and accumulated along the lightpath and affect other active lightpaths carried by the same wavelength in the network. The affected active lightpaths may build unintended cycles along which the MAI is accumulated. Furthermore, this MAI keeps increasing when the lightpaths traversed by the cycle are active, which deteriorates the lightpath signal quality. Since this deterioration may eventually result in unacceptable signal quality and service disruption, the phenomenon caused by the MAI is termed as cycle attack in this paper. The explanations of the MAI propagation mechanism and the cycle attack problem are given. A depth-first search (DFS)-based algorithm is proposed to diagnose such cycle attacks under dynamic traffic conditions. The numerical results show that our DFS-based cycle attack diagnostic algorithm enables one to detect cycle attacks effectively, and the two-way resource reservation method associated with heuristic wavelength assignment is shown to mitigate the blocking performance degradation due to cycle attacks greatly with some proper wavelength and OC configuration. [ABSTRACT FROM PUBLISHER]

In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multiagent system in which the IP and the TSP are represented by separate software agents. One of the tasks of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between the timetables that were attained from the proposed methods and those that were derived by the scheduling principles adopted in practice. [ABSTRACT FROM PUBLISHER]

We introduce a new family of detectors for multiple-input multiple-output (MIMO) channels. These detectors are called Chase detectors because they can be interpreted as a translation of the Chase error-control decoding algorithm from time to space. The Chase detector is parameterized by only four parameters; nevertheless, it reduces to a wide range of previously reported MIMO detectors as special cases, including the maximum-likelihood and decision-feedback detectors. The Chase detector defines a simple framework for not only comparing existing MIMO detection algorithms but also proposing new ones. For example, based on the Chase framework, we propose a new detector called B-Chase that performs well on fading channels. Specifically, on a four-input four-output Rayleigh-fading channel with uncoded 16-QAM inputs, one instance of the B-Chase detector falls only 0.4 dB short of the performance of the maximum-likelihood sphere detector while reducing complexity by 68%. Another instance of the B-Chase detector outperforms the BLAST-ordered decision-feedback detector by 4.4 dB while increasing complexity by only 17%. [ABSTRACT FROM AUTHOR]

We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller's classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZF-DFD). Extensive computer simulation results are also provided. [ABSTRACT FROM PUBLISHER]

A fast optimal algorithm for solving radio resource allocation (RRA) problems in orthogonal frequency division multiple access (OFDMA) systems is proposed based on branch- and-bound (BnB) approach. The proposed algorithm offers the same performance as that achieved by some other existing optimal algorithms but with much reduced average computational complexity. As an effort in providing trade-off between performance and computational complexity, two suboptimal algorithms are also developed. Simulation results are shown to compare the performance and complexity of the proposed suboptimal algorithms with several existing algorithms. [ABSTRACT FROM PUBLISHER]

We consider the planted (I, d) motif search problem, which consists of finding a substring of length I that occurs in a set of input sequences si,. ..,sn with up to d errors, a problem that arises from the need to find transcription factor-binding sites in genomic information. We propose a sequence of practical algorithms, which start based on the ideas considered in PMS1. These algorithms are exact, have little space requirements, and are able to tackle challenging instances with bigger d, taking less time in the instances reported solved by exact algorithms. In particular, one of the proposed algorithms, PMSprune, is able to solve the challenging instances, such as (17, 6) and (19, 7), which were not previously reported as solved in the literature. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under network bandwidth and playback delay constraints. The streaming policy consists in a joint selection of the network path and of the video packets to be transmitted, along with their sending time. A simple streaming model is introduced, which takes into account the video packet importance, and the dependencies between packets. A careful timing analysis allows to compute the quality perceived by the receiver for a constrained playback delay, as a function of the streaming policy. We derive an optimization problem based on a video abstraction model, under the assumption that the server knows, or can predict accurately the state of the network. A detailed analysis of constrained multipath streaming systems provides helpful insights to design an efficient branch and bound algorithm that finds the optimal streaming strategy. This solution allows to bound the performance of any scheduling strategy, but the complexity of the algorithm becomes rapidly intractable. We therefore propose a fast heuristic-based algorithm, built on load-balancing principles. It allows to reach close to optimal performance with a polynomial time complexity. The algorithm is then adapted to live streaming scenarios, where the server has only a partial knowledge of the packet stream, and the channel bandwidth. Extensive simulations show that the proposed algorithm only induces a negligible distortion penalty compared to the optimal strategy, even when the optimization horizon is limited, or the rate estimation is not perfect. Simulation results also demonstrate that the proposed scheduling solution performs better than common scheduling algorithms, and therefore represents a very efficient low-complexity multipath streaming algorithm, for both stored and live video services [ABSTRACT FROM PUBLISHER]

In recent publications, we have presented a data-driven approach to representing the nonlinear structure of hyperspectral imagery using manifold coordinates. The approach relies on graph methods to derive geodesic distances on the high-dimensional hyperspectral data manifold. From these distances, a set of intrinsic manifold coordinates that parameterizes the data manifold is derived. Scaling the solution relied on divide-conquer-and-merge strategies for the manifold coordinates because of the computational and memory scaling of the geodesic coordinate calculations. In this paper, we improve the scaling performance of isometric mapping (ISOMAP) and achieve full-scene global manifold coordinates while removing artifacts generated by the original methods. The CPU time of the enhanced ISOMAP approach scales as O(N log²(N)), where N is the number of samples, while the memory requirement is bounded by O(N log(N)). Full hyperspectral scenes of 0(106) samples or greater are obtained via a reconstruction algorithm, which allows insertion of large numbers of samples into a representative ‘backbone’ manifold obtained for a smaller but representative set of O(105) samples. We provide a classification example using a coastal hyperspectral scene to illustrate the approach. [ABSTRACT FROM AUTHOR]

We consider the problem of rate-distortion optimized streaming of packetized multimedia data over a single quality-of-service network using feedback and retransmissions. For a single data unit, we prove that the problem is NP-hard and provide efficient branch and bound algorithms that are much faster than the previously best solution based on dynamic programming. For a group of interdependent data units, we show how to compute optimal solutions with branch and bound algorithms. The branch and bound algorithms for a group of data units are much slower than the current state of the art, a heuristic technique known as sensitivity adaptation. However, in many real-world situations, they provide a significantly better rate-distortion performance. [ABSTRACT FROM PUBLISHER]

The use of multiple transmit/receive antennas forming a multiple-input multiple-output (MIMO) system can significantly enhance channel capacity. This paper considers a V-BLAST-type combination of orthogonal frequency-division multiplexing (OFDM) with MIMO (MIMO-OFDM) for enhanced spectral efficiency and multiuser downlink throughput. A new joint data detection and channel estimation algorithm for MIMO-OFDM is proposed which combines the QRD-M algorithm and Kalman filter. The individual channels between antenna elements are tracked using a Kalman filter, and the QRD-M algorithm uses a limited tree search to approximate the maximum-likelihood detector. A closed-form symbol-error rate, conditioned on a static channel realization, is presented for the M=1 case with QPSK modulation. An adaptive complexity QRD-M algorithm (AC-QRD-M) is also considered which assigns different values of M to each subcarrier according to its estimated received power. A rule for choosing M using subcarrier powers is obtained using a kernel density estimate combined with the Lloyd-Max algorithm. [ABSTRACT FROM PUBLISHER]

An acquisition method of long pseudo-noise (PN) sequences in direct-sequence spread spectrum (DS/SS) systems is presented. The concurrent cross correlation of locally generated auxiliary signals with the incoming PN sequence produces binary search estimates leading to an initial approximation of the input signal's PN offset. The PN receiver then uses a closed-loop subsystem to determine the true offset of the incoming PN signal. New phase estimates are generated from successive corrections of likely errors in the binary search. The acquisition scheme's average acquisition time and its variance are analytically determined. Simulation results show that the proposed acquisition scheme is faster than the conventional serial receiver. A hybrid serial/parallel PN acquisition receiver is used for comparing the acquisition performance given similar hardware complexity. The hybrid receiver used the same number of parallel correlators as used in the proposed receiver's input phase estimator. Simulation results show that the proposed system provides an improved performance under normal operating conditions. [ABSTRACT FROM PUBLISHER]

This paper addresses a difficult problem that often arises in printed circuit card assembly systems: how should circuit cards be grouped into families to decrease total assembly time? Traditional approaches to this problem focus on setup time, without considering the possible impacts on processing time. A new approach for selecting card families to be processed on an assembly machine is developed to minimize total assembly time through the joint consideration of setup time and processing time. The overall approach for addressing the card grouping problem involves capturing the lower level machine configuration decisions through an empirical estimator function and incorporating this function with the higher level card grouping problem. The card grouping problem is solved using a branch-and-bound algorithm supplemented by techniques to improve the solution time. An industrial case study is conducted for a turret style placement machine, a Panasonic MV150 machine. The results demonstrate the positive impact of including the lower level decisions on the total assembly time and system throughput for certain types of assembly machines. In addition, this research provides insight on other process planning problems, such as line assignment and card sequencing, by demonstrating the importance of incorporating the related lower level decision problems. [ABSTRACT FROM PUBLISHER]

A low‐complexity method for symbol detection in multiple‐input multiple‐output communication systems with spatial modulation is proposed. The proposed method finds a solution by performing beam search, where the beam search algorithm is modified to apply an additional branch‐and‐bound technique in order to reduce the search space. Simulation results show that the proposed method achieves a near‐optimal bit error rate, and its complexity is much lower than that of previous methods. [ABSTRACT FROM AUTHOR]

C++ gives programmers the tools to create reusable object classes. While the language is not complete in this respect, a programmers can create generic classes that can solve more than […]

A model of a cyclic manufacturing system representable as a deterministic timed event graph is considered in this paper. It is possible to apply analytical techniques for performance evaluation of such systems. On this basis, a two-level optimization problem is considered. The higher level refers to the maximization of the system productivity with respect to the assignment of operations to machines, the lot sizes, and the service sequences at the various machines, assuming that unlimited work-in-progress and buffers of finite dimension are available. The lower level deals with the minimization of an aggregate cost taking into account the work-in-progress and the buffer dimensions. [ABSTRACT FROM PUBLISHER]

An important functional component of every file organization is the set of search mechanisms which are used to locate individually identified records during the process of either update of retrieval. There have been a large number of computer-related search techniques developed in the past 20 years. The objectives of this article is to synthesize many of these techniques into one parametrically techniques into two categries: addressing techniques, and tree searching techniques into two categories via a genralized model. The model has proven to be a peadgogic convenience in explaining the relation between alternative search techniques. It has also been used in a practical application as a schema for alternative search strategies which are automatically evaluated during the process of a file organization design. [ABSTRACT FROM AUTHOR]

In order to provide value-added services such as policy-based routing and the quality of services in next generation network, the Internet routers need to classify packets into flows for different treatments. Since packet classification should be performed in wire-speed for every packet incoming in several hundred gigabits per second, it becomes a major challenge in the Internet routers. In this letter, we propose a new packet classification scheme based on hierarchical binary search tree. The proposed scheme hierarchically connects binary search trees without empty internal nodes, and hence the proposed architecture significantly improves the search performance as well as greatly reduces the memory requirement compared with trie-based schemes. [ABSTRACT FROM PUBLISHER]