Scheduling jobs with equal processing times subject to machine eligibility constraints

We consider the problem of nonpreemptively scheduling a set of n jobs with equal processing times on m parallel machines so as to minimize the makespan. Each job has a prespecified set of machines on which it can be processed, called its eligible set. We consider the most general case of machine eligibility constraints as well as special cases of nested and inclusive eligible sets. Both online and offline models are considered. For offline problems we develop optimal algorithms that run in polynomial time, while for online problems we focus on the development of optimal algorithms of a new and more elaborate structure as well as approximation algorithms with good competitive ratios.     

Rule acquisition and attribute reduction in real decision formal contexts

Formal Concept Analysis of real set formal contexts is a generalization of classical formal contexts. By dividing the attributes into condition attributes and decision attributes, the notion of real decision formal contexts is introduced. Based on an implication mapping, problems of rule acquisition and attribute reduction of real decision formal contexts are examined. The extraction of “if–then” rules from the real decision formal contexts, and the approach to attribute reduction of the real decision formal contexts are discussed. By the proposed approach, attributes which are non-essential to the maximal s rules or l rules (to be defined later in the text) can be removed. Furthermore, discernibility matrices and discernibility functions for computing the attribute reducts of the real decision formal contexts are constructed to determine all attribute reducts of the real set formal contexts without affecting the results of the acquired maximal s rules or l rules.     

Data race: tame the beast

Data races hamper parallel programming and threaten the reliability of future software. This paper proposes the data race prevention scheme View-Oriented Data race Prevention (VODAP), which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses views to bundle mutual exclusion with data access. We have implemented the data race prevention scheme with a memory protection mechanism. Experimental results show that the extra overhead of memory protection is trivial in our applications. The performance is evaluated and compared with modern programming models such as OpenMP and Cilk.     

Kernel Width Optimization for Faulty RBF Neural Networks with Multi-node Open Fault

Many researches have been devoted to select the kernel parameters, including the centers, kernel width and weights, for fault-free radial basis function (RBF) neural networks. However, most are concerned with the centers and weights identification, and fewer focus on the kernel width selection. Moreover, to our knowledge, almost no literature has proposed the effective and applied method to select the optimal kernel width for faulty RBF neural networks. As is known that the node faults inevitably take place in real applications, which results in a great many of faulty networks, it will take a lot of time to calculate the mean prediction error (MPE) for the traditional method, i.e., the test set method. Thus, the letter derives a formula to estimate the MPE of each candidate width value and then use it to select the optimal one with the lowest MPE value for faulty RBF neural networks with multi-node open fault. Simulation results show that the chosen optimal kernel width by our proposed MPE formula is very close to the actual one by the conventional method. Moreover, our proposed MPE formula outperforms other selection methods used for fault-free neural networks.     

A Monte Carlo Simulation approach for the modeling of free-molecule squeeze-film damping of flexible microresonators

Squeeze-film damping on microresonators is a significant damping source even when the surrounding gas is highly rarefied. This article presents a general modeling approach based on Monte Carlo (MC) simulations for the prediction of squeeze-film damping on resonators in the free-molecule regime. The generality of the approach is demonstrated in its capability of simulating resonators of any shape and with any accommodation coefficient. The approach is validated using both the analytical results of the free-space damping and the experimental data of the squeeze-film damping on a clamped–clamped plate resonator oscillating at its first flexure mode. The effect of oscillation modes on the quality factor of the resonator has also been studied and semi-analytical approximate models for the squeeze-film damping with diffuse collisions have been developed.     

On the security of a visual cryptography scheme for color images

Hou [Visual cryptography for color images, Pattern Recognition 36 (2003) 1619-1629] proposed a four-share visual cryptography scheme for color images. The scheme splits a dithered eight-color secret image into four shares: the black mask and other three shares. It was claimed that without knowing the black mask, no information about the secret image can be obtained even if all the other three shares are known. In this paper, we show that this may be true for a few specific two-color secret images only. In all other cases, however, security cannot be guaranteed. We show that an attacker can compromise a randomly chosen two-color secret image from any two of the other three shares with probability by completely recovering the shape and pattern of the secret image. The advantage will increase to if all the three shares are known. If the secret image has three or four colors, we show that the attacker can compromise it with probability and , respectively. Finally, we show that our technique can be extended to compromising secret images with more than four colors.     

Examining the Potentially Confounding Effect of Class Size on the Associations between Object-Oriented Metrics and Change-Proneness

Previous research shows that class size can influence the associations between object-oriented (OO) metrics and fault-proneness and therefore proposes that it should be controlled as a confounding variable when validating OO metrics on fault-proneness. Otherwise, their true associations may be distorted. However, it has not been determined whether this practice is equally applicable to other external quality attributes. In this paper, we use three size metrics, two of which are available during the high-level design phase, to examine the potentially confounding effect of class size on the associations between OO metrics and change-proneness. The OO metrics that are investigated include cohesion, coupling, and inheritance metrics. Our results, based on Eclipse, indicate that: 1) The confounding effect of class size on the associations between OO metrics and change-proneness, in general, exists, regardless of whichever size metric is used; 2) the confounding effect of class size generally leads to an overestimate of the associations between OO metrics and change-proneness; and 3) for many OO metrics, the confounding effect of class size completely accounts for their associations with change-proneness or results in a change of the direction of the associations. These results strongly suggest that studies validating OO metrics on change-proneness should also consider class size as a confounding variable.     

Task-Space Modular Dynamics for Dual-Arms Expressed through a Relative Jacobian

This paper presents modular dynamics for dual-arms, expressed in terms of the kinematics and dynamics of each of the stand-alone manipulators. The two arms are controlled as a single manipulator in the task space that is relative to the two end-effectors of the dual-arm robot. A modular relative Jacobian, derived from a previous work, is used which is expressed in terms of the stand-alone manipulator Jacobians. The task space inertia is expressed in terms of the Jacobians and dynamics of each of the stand-alone manipulators. When manipulators are combined and controlled as a single manipulator, as in the case of dual-arms, our proposed approach will not require an entirely new dynamics model for the resulting combined manipulator. But one will use the existing Jacobians and dynamics model for each of the stand-alone manipulators to come up with the dynamics model of the combined manipulator. A dual-arm KUKA is used in the experimental implementation.