Lightweight monitors for the Java virtual machine

Java supports the monitor construct for language‐level synchronization in the context of multi‐threading. This paper introduces the lightweight monitor, an efficient user‐level monitor implementation. The lightweight monitor is useful for single‐threaded Java programs as well as for multi‐threaded Java programs with little lock contention. A 32‐bit lock is embedded in each object for efficient lock access while other monitor data structures are managed using a hash table. We highly optimized the lock manipulation code, which is translated and inlined by a just‐in‐time (JIT) compiler. In the most probable cases, only nine SPARC instructions are spent for lock acquisition and five instructions are spent for lock release. Our experimental results indicate that the lightweight monitor is faster than the monitor implementation in the SUN JDK 1.2 RC1 by up to 21 times in the absence of lock contention and by up to seven times in the presence of lock contention. Copyright © 2004 John Wiley & Sons, Ltd.     

The Physico-chemical Hydrodynamics of Dyeing

Meetings of the Leeds Junior Section, held in the Department of Colour Chemistry and Dyeing, University of Leeds, on 11 November 1969, Mr K. R. F. Cockett in the chair; and of the Manchester Region, held at the Literary and Philosophical Society, Manchester, on 20 November 1969, Mr H. R. Hadfield in the chair Films of methoxymethylnylon 6.6 have been inserted into a stream of dye-liquor. The rates of dyeing of an acid dye at different points down the film were measured. Under some conditions of dyeing, the rate was shown to be controlled by the diffusion in the liquid phase. Values of the thickness of the diffusional boundary layer were calculated from the flux and shown to agree with theory. Modifications of the dyeing conditions, e.g. by increasing the pH or lowering thedyebath concentration, reduced the diffusion coefficient of the dye in the film, and the rate of dyeing became dependent on diffusion both in the film and in the liquid.     

Data weighting method on the basis of binary encoded output to solve multi-class pattern classification problems

Data weighting is of paramount importance with respect to classification performance in pattern recognition applications. In this paper, the output labels of datasets have been encoded using binary codes (numbers) and by this way provided a novel data weighting method called binary encoded output based data weighting (BEOBDW). In the proposed data weighting method, first of all, the output labels of datasets have been encoded with binary codes and then obtained two encoded output labels. Depending to these encoded outputs, the data points in datasets have been weighted using the relationships between features of datasets and two encoded output labels. To generalize the proposed data weighting method, five datasets have been used. These datasets are chain link (2 classes), two spiral (2 classes), iris (3 classes), wine (3 classes), and dermatology (6 classes). After applied BEOBDW to five datasets, the k-NN (nearest neighbor) classifier has been used to classify the weighted datasets. A set of experiments on used real world datasets demonstrated that the proposed data weighting method is a very efficient and has robust discrimination ability in the classification of datasets. BEOBDW method could be confidently used before many classification algorithms.     

Survey of multipath routing protocols for mobile ad hoc networks

This survey investigates multipath routing protocols for mobile ad hoc networks (MANETs). The main objectives of multipath routing protocols are to provide reliable communication and to ensure load balancing as well as to improve quality of service (QoS) of MANETs. These multipath protocols are broadly classified into five categories based on their major goals. The goals are to improve delay, provide reliability, reduce overhead, maximize network life and support hybrid routing. Multipath routing protocols address issues such as multiple paths discovery and maintaining these paths. Issues, objectives, performances, advantages and disadvantages of these protocols are investigated and summarized. A checklist is provided as a guideline so that a network designer can choose an appropriate multipath routing protocol to meet the network's application objectives.     

Distributed Learning for Planning Under Uncertainty Problems with Heterogeneous Teams

This paper considers the problem of multiagent sequential decision making under uncertainty and incomplete knowledge of the state transition model. A distributed learning framework, where each agent learns an individual model and shares the results with the team, is proposed. The challenges associated with this approach include choosing the model representation for each agent and how to effectively share these representations under limited communication. A decentralized extension of the model learning scheme based on the Incremental Feature Dependency Discovery (Dec-iFDD) is presented to address the distributed learning problem. The representation selection problem is solved by leveraging iFDD’s property of adjusting the model complexity based on the observed data. The model sharing problem is addressed by having each agent rank the features of their representation based on the model reduction error and broadcast the most relevant features to their teammates. The algorithm is tested on the multi-agent block building and the persistent search and track missions. The results show that the proposed distributed learning scheme is particularly useful in heterogeneous learning setting, where each agent learns significantly different models. We show through large-scale planning under uncertainty simulations and flight experiments with state-dependent actuator and fuel-burn- rate uncertainty that our planning approach can outperform planners that do not account for heterogeneity between agents.     

Automatic recognition of vigilance state by using a wavelet-based artificial neural network

In this study, 5-s long sequences of full-spectrum electroencephalogram (EEG) recordings were used for classifying alert versus drowsy states in an arbitrary subject. EEG signals were obtained from 30 healthy subjects and the results were classified using a wavelet-based neural network. The wavelet-based neural network model, employing the multilayer perceptron (MLP), was used for the classification of EEG signals. A multilayer perceptron neural network (MLPNN) trained with the Levenberg–Marquardt algorithm was used to discriminate the alertness level of the subject. In order to determine the MLPNN inputs, spectral analysis of EEG signals was performed using the discrete wavelet transform (DWT) technique. The MLPNN was trained, cross-validated, and tested with training, cross-validation, and testing sets, respectively. The correct classification rate was 93.3% alert, 96.6% drowsy, and 90% sleep. The classification results showed that the MLPNN trained with the Levenberg–Marquardt algorithm was effective for discriminating the vigilance state of the subject.     

Effect of high temperature heat treatment on intergranular corrosion of AlMgSi(Cu) model alloy

Copper containing 6000-series aluminium alloys may become susceptible to intergranular corrosion (IGC) as a result of improper thermomechanical processing. Effect of cooling rate after solution heat treatment on the corrosion behaviour of a model AlMgSi(Cu) alloy of nominal composition (wt%) 0.6 Mg, 0.6 Si, 0.2 Fe, 0.2 Mn and 0.1 Cu was investigated. Slow cooling rates were simulated by isothermal treatment for predetermined times in lower temperature baths immediately after solution heat treatment. Treatment for 10-100 s at temperatures below 400 °C introduced susceptibility to IGC. Longer heat treatment at the same temperatures introduced susceptibility to pitting. A corrosion resistant time zone was found between the zones of IGC and pitting at temperatures lower than 350 °C. Quenching in water after solution heat treatment prevented IGC. IGC was related to microgalvanic coupling between the noble Q-phase (Al₄Mg₈Si₇Cu₂) grain boundary precipitates and the adjacent depleted zone. Pitting was attributed to coarse particles in the matrix. Possible mechanisms causing the corrosion resistant intermediate zone are discussed. The results indicate possible methods for obtaining increased corrosion resistance of similar alloys by proper thermal processing.     

Voronoi diagrams with barriers and on polyhedra for minimal path planning

Two generalizations of the Voronoi diagram in two dimensions (E²) are presented in this paper. The first allows impenetrable barriers that the shortest path must go around. The barriers are straight line segments that may be combined into polygons and even mazes. Each region of the diagram delimits a set of points that have not only the same closest existing point, but have the same topology of shortest path. The edges of this diagram, which has linear complexity in the number of input points and barrier lines, may be hyperbolic sections as well as straight lines. The second construction considers the Voronoi diagram on the surface of a convex polyhedron, given a set of fixed source points on it. Each face is partitioned into regions, such that the shortest path to any goal point in a given region from the closest fixed source point travels over the same sequence of faces to the same closest point.     

Determination of Coal Rank by Fuzzy Logic: A Case Study of Coal from Central Anatolia,Turkey

Koyunagili coalfield in the Beypazari basin of the Central Anatolia was investigated and coal ranks were determined using fuzzy Mamdani model based on ASTM coal rank classification. This is a pilot study to investigate the applicability of the fuzzy model to determine the ranking of any coal seam. The Koyunagili coalfield, which is located at the southern part of the Beypazari basin, consists of the late Miocene coal seam within the tuffaceous rocks. The mineable coal seam is split by a 0.5–0.55 m thick clayey limestone into the upper (1.2–1.3 m thick) and lower (0.4 m thick) benches. A total of 28 profile coal samples from underground mines were collected. The samples have an average of 30.9% moisture (as-received), 23% ash yield, and 2.9% total sulphur and 4167 kcal/kg gross calorific value on an air-dried basis. Mean random reflectance values of huminite have an average of 0.34%, and show no differences across the coalfield. Coal ranking has been determined by the fuzzy Mamdani model. During processing, fixed carbon content (FCC), volatile matter values (VMV), calorific value (CV), and vitrinite/huminite reflectance (Ro %) parameters are inputs, and a total of 10 rules are used for the model. Modeling results are consistent with the previous studies.