Incremental learning with respect to new incoming input attributes

Neural networks are generally exposed to a dynamic environment where the training patterns or the input attributes (features) will likely be introduced into the current domain incrementally. This paper considers the situation where a new set of input attributes must be considered and added into the existing neural network. The conventional method is to discard the existing network and redesign one from scratch. This approach wastes the old knowledge and the previous effort. In order to reduce computational time, improve generalization accuracy, and enhance intelligence of the learned models, we present ILIA algorithms (namely ILIA1, ILIA2, ILIA3, ILIA4 and ILIA5) capable of Incremental Learning in terms of Input Attributes. Using the ILIA algorithms, when new input attributes are introduced into the original problem, the existing neural network can be retained and a new sub-network is constructed and trained incrementally. The new sub-network and the old one are merged later to form a new network for the changed problem. In addition, ILIA algorithms have the ability to decide whether the new incoming input attributes are relevant to the output and consistent with the existing input attributes or not and suggest to accept or reject them. Experimental results show that the ILIA algorithms are efficient and effective both for the classification and regression problems

Parallel growing and training of neural networks using output parallelism

In order to find an appropriate architecture for a large-scale real-world application automatically and efficiently, a natural method is to divide the original problem into a set of sub-problems. In this paper, we propose a simple neural network task decomposition method based on output parallelism. By using this method, a problem can be divided flexibly into several sub-problems as chosen, each of which is composed of the whole input vector and a fraction of the output vector. Each module (for one sub-problem) is responsible for producing a fraction of the output vector of the original problem. The hidden structure for the original problem’s output units are decoupled. These modules can be grown and trained in parallel on parallel processing elements. Incorporated with a constructive learning algorithm, our method does not require excessive computation and any prior knowledge concerning decomposition. The feasibility of output parallelism is analyzed and proved. Some benchmarks are implemented to test the validity of this method. Their results show that this method can reduce computational time, increase learning speed and improve generalization accuracy for both classification and regression problems

Regulation of vacuolar H+-ATPase activity by the Cdc42 effector Ste20 in Saccharomyces cerevisiae

In the budding yeast Saccharomyces cerevisiae, the Cdc42 effector Ste20 plays a crucial role in the regulation of filamentous growth, a response to nutrient limitation. Using the split-ubiquitin technique, we found that Ste20 forms a complex with Vma13, an important regulatory subunit of vacuolar H(+)-ATPase (V-ATPase). This protein-protein interaction was confirmed by a pulldown assay and coimmunoprecipitation. We also demonstrate that Ste20 associates with vacuolar membranes and that Ste20 stimulates V-ATPase activity in isolated vacuolar membranes. This activation requires Ste20 kinase activity and does not depend on increased assembly of the V1 and V0 sectors of the V-ATPase, which is a major regulatory mechanism. Furthermore, loss of V-ATPase activity leads to a strong increase in invasive growth, possibly because these cells fail to store and mobilize nutrients efficiently in the vacuole in the absence of the vacuolar proton gradient. In contrast to the wild type, which grows in rather small, isolated colonies on solid medium during filamentation, hyperinvasive vma mutants form much bigger aggregates in which a large number of cells are tightly clustered together. Genetic data suggest that Ste20 and the protein kinase A catalytic subunit Tpk2 are both activated in the vma13Δ strain. We propose that during filamentous growth, Ste20 stimulates V-ATPase activity. This would sustain nutrient mobilization from vacuolar stores, which is beneficial for filamentous growth.The project was supported by Deutsche Forschungsgemeinschaft grant HO 2098/3 to T.H. and NIH grant R01 GM50322 to P.M.K

Integration of an Active Filter and a Single-Phase AC/DC Converter with Reduced Capacitance Requirement and Component Count

Existing methods of incorporating an active filter into an AC/DC converter for eliminating electrolytic capacitors usually require extra power switches. This inevitably leads to an increased system cost and degraded energy efficiency. In this paper, a concept of active-filter integration for single-phase AC/DC converters is reported. The resultant converters can provide simultaneous functions of power factor correction, DC voltage regulation, and active power decoupling for mitigating the low-frequency DC voltage ripple, without an electrolytic capacitor and extra power switch. To complement the operation, two closed-loop voltage-ripple-based reference generation methods are developed for controlling the energy storage components to achieve active power decoupling. Both simulation and experiment have confirmed the eligibility of the proposed concept and control methods in a 210-W rectification system comprising an H-bridge converter with a half-bridge active filter. Interestingly, the end converters (Type I and Type II) can be readily available using a conventional H-bridge converter with minor hardware modification. A stable DC output with merely 1.1% ripple is realized with two 50-μF film capacitors. For the same ripple performance, a 900-μF capacitor is required in conventional converters without an active filter. Moreover, it is found out that the active-filter integration concept might even improve the efficiency performance of the end converters as compared with the original AC/DC converter without integration

Multispace and Multilevel BDDC

BDDC method is the most advanced method from the Balancing family of iterative substructuring methods for the solution of large systems of linear algebraic equations arising from discretization of elliptic boundary value problems. In the case of many substructures, solving the coarse problem exactly becomes a bottleneck. Since the coarse problem in BDDC has the same structure as the original problem, it is straightforward to apply the BDDC method recursively to solve the coarse problem only approximately. In this paper, we formulate a new family of abstract Multispace BDDC methods and give condition number bounds from the abstract additive Schwarz preconditioning theory. The Multilevel BDDC is then treated as a special case of the Multispace BDDC and abstract multilevel condition number bounds are given. The abstract bounds yield polylogarithmic condition number bounds for an arbitrary fixed number of levels and scalar elliptic problems discretized by finite elements in two and three spatial dimensions. Numerical experiments confirm the theory.Comment: 26 pages, 3 figures, 2 tables, 20 references. Formal changes onl

Clustered-loss retransmission protocol over wireless TCP

Transmission Control Protocol (TCP) performs well in traditional wired networks where the packet loss rate is low. However, in heterogeneous wired/wireless networks, the high packet loss rate over wireless links may result in excessive invocation of the congestion control algorithm, thus deteriorating the performance of TCP. In this paper, a novel localized link layer retransmission protocol, called Clustered-loss Retransmission Protocol (CLRP), is proposed. CLRP consists of three protocol components, namely, TCP-FH deployed on a fixed host, TCP-MH deployed on a mobile host and CLRP-BS deployed on a base station. CLRP can provide not only explicit distinction between congestion and packet corruption losses, and effective multiple wireless loss information for retransmissions, but also better retransmission control for wireless losses. Thus it is well suited to wireless networks, in which packet loss and bursty packet corruption is a serious problem. Moreover, CLRP does not require any modifications to TCP deployed on fixed hosts. © 2005 IEEE.published_or_final_versio

Conservation form of Helbing's fluid dynamic traffic flow model

A standard conservation form is derived in this paper. The hyperbolicity of Helbing's fluid dynamic traffic flow model is proved, which is essential to the general analytical and numerical study of this model. On the basis of this conservation form, a local discontinuous Galerkin scheme is designed to solve the resulting system efficiently. The evolution of an unstable equilibrium traffic state leading to a stable stop-and-go traveling wave is simulated. This simulation also verifies that the model is truly improved by the introduction of the modified diffusion coefficients, and thus helps to protect vehicles from collisions and avoide the appearance of the extremely large density. © 2011 Shanghai University and Springer-Verlag Berlin Heidelberg.postprin

Optimization of Number of Operators and Allocation of New Lines in an Oligopolistic Transit Market

This paper proposes a novel model for determining the optimal number of transit operators and the allocation of new lines in an oligopolistic transit market. The proposed model consists of three interrelated sub-models that are associated with three types of players; namely, transit authority, transit operators, and transit passengers. In practice, the operating cost per unit of transit line of each operator is decreasing in the number of lines that it operates. These effects which are referred to as the scale economies of transit operations are explicitly incorporated in the proposed model. On the basis of a logit-type transit passenger travel choice sub-model with elastic demand, the fares and frequencies of transit services are determined by an oligopolistic competitive equilibrium model (i. e. transit operator sub-model). The transit authority sub-model for optimization of the number of operators and the allocation of new lines is expressed as a 0-1 integer programming problem. It can be solved by an implicit enumeration heuristic solution algorithm. Numerical results show that both the scale economies and the market demand level have significant impacts on the optimal number of operators and the allocation schemes of new lines. Ignoring the effects of scale economies on transit operations may lead transit authorities to make biased decisions. © 2010 Springer Science+Business Media, LLC.postprin

Bottleneck model revisited: An activity-based perspective

The timing of commuting trips made during morning and evening peaks has typically been investigated using Vickrey’s bottleneck model. However, in the conventional trip-based approach, the decisions that commuters make during the day about their activity schedules and time use are not explicitly considered. This study extends the bottleneck model to address the scheduling problem of commuters’ morning home-to-work and evening work-to-home journeys by using an activity-based approach. A day-long activity-travel scheduling model is proposed for the simultaneous determination of departure times for morning and evening commutes, together with allocations of time during the day among travel and activities undertaken at home or at the workplace. The proposed model maximizes the total net utility of the home-based tour, which is the difference between the benefits derived from participating in activities and the disutility incurred by travel between activity locations. The properties of the model solution are analytically explored and compared with the conventional bottleneck model for a special case with constant marginal-activity utility. For the case with linear marginal-activity utility, we develop a heuristic procedure to seek the equilibrium scheduling solution. We also explore the effects of marginal-work utility (or the employees’ average wage level) and of flexible work-hour schemes on the scheduling problem in relation to the morning and evening commuting tours.postprin

Real-time estimation of lane-based queue lengths at isolated signalized junctions

In this study, we develop a real-time estimation approach for lane-based queue lengths. Our aim is to determine the numbers of queued vehicles in each lane, based on detector information at isolated signalized junctions. The challenges involved in this task are to identify whether there is a residual queue at the start time of each cycle and to determine the proportions of lane-to-lane traffic volumes in each lane. Discriminant models are developed based on time occupancy rates and impulse memories, as calculated by the detector and signal information from a set of upstream and downstream detectors. To determine the proportions of total traffic volume in each lane, the downstream arrivals for each cycle are estimated by using the Kalman filter, which is based on upstream arrivals and downstream discharges collected during the previous cycle. Both the computer simulations and the case study of real-world traffic show that the proposed method is robust and accurate for the estimation of lane-based queue lengths in real time under a wide range of traffic conditions. Calibrated discriminant models play a significant role in determining whether there are residual queued vehicles in each lane at the start time of each cycle. In addition, downstream arrivals estimated by the Kalman filter enhance the accuracy of the estimates by minimizing any error terms caused by lane-changing behavior.postprin