An empirical evaluation of P system testing techniques

This paper presents the existing techniques for P system testing and performs an empirical evaluation of their fault-detection efficiency. The comparison is performed using mutation testing and, based on the results obtained, some improved testing methodologies are proposed.     

A review and critique on integrated production–distribution planning models and techniques

Optimisation modelling of integrated production–distribution (P–D) plans has raised significant interest among both researchers and practitioners over the past two decades. This paper provides the readers with a comprehensive review and critique on the current P–D planning and optimisation literature. We classify the published P–D planning models into seven categories based on their degree of complexity and hence capability in addressing real-life scenarios. Summary tables highlight the main characteristics of the selected models at each category. Next, the paper reclassifies and evaluates the proposed models based on the solution techniques used. Lastly, the unaddressed areas in the current literature are highlighted, important managerial implications are proposed and directions for future research in the area are suggested.     

Theoretical and Experimental Analysis of a Laser Textured Thrust Bearing

In this article, a laser partially textured thrust bearing is theoretically and experimentally analyzed. An adiabatic model is developed in order to theoretically investigate the performances of the bearing. The bearing sample is partially textured both in radial and circumferential direction using the laser texturing process. The performance of the bearing (fluid film thickness and friction torque) is evaluated on a specially adapted test rig and the experimental results are compared with the theoretical model. A good agreement is found between the theoretical model and the experimental data. Also a comparison between a laser textured bearing and a bearing textured using the photolithographic method is presented.     

Effect of hydrogen on room-temperature plasticity of B2 iron aluminides

Different sensitivities to hydrogen embrittlement for the disordered and ordered B2 FeAl alloys have been investigated. The plasticity of annealed alloys (before hydrogenating) has been found to decrease with increasing the long-range order parameter. An intrinsic weakness of FeAl phase grain boundaries revealed at a high degree of ordering. The results of bending tests on specimens annealed and cathodically charged with hydrogen have shown that the influence of hydrogen on the plasticity diminishes with the increase in the degree of FeAl phase ordering.     

The Impact of an Agile Methodology on the Well Being of Development Teams

This paper describes an empirical study, which addresses the aspect of well being amongst members of the software development teams. The question of interest is whether an agile methodology has any distinct effect on the well being of the software developers. Both quantitative and qualitative methods were utilised, including the participative observation, focus group interviews, close-ended questionnaires and simple statistical tests such as Spearman Correlation and Mann–Whitney test. Initial results showed that an agile methodology (XP) has a positive effect on the level of enthusiasm of the software developers in the most dynamic project. To understand why XP can increase enthusiasm, results are interpreted with references to cognitive, affective and managerial properties of the practices studied. This result needs further investigation on the individual effects of each practice on the wellbeing and attitudes of Software Engineering (SE) teams.     

Dynamic transitions from smooth to rough to twinning in dislocation motion

The motion of dislocations in response to stress dictates the mechanical behaviour of materials. However, it is not yet possible to directly observe dislocation motion experimentally at the atomic level. Here, we present the first observations of the long-hypothesized kink-pair mechanism in action using atomistic simulations of dislocation motion in iron. In a striking deviation from the classical picture, dislocation motion at high strain rates becomes rough, resulting in spontaneous self-pinning and production of large quantities of debris. Then, at still higher strain rates, the dislocation stops abruptly and emits a twin plate that immediately takes over as the dominant mode of plastic deformation. These observations challenge the applicability of the Peierls threshold concept to the three-dimensional motion of screw dislocations at high strain rates, and suggest a new interpretation of plastic strength and microstructure of shocked metals.     

Projective filtering of time-aligned ECG beats

A method of electrocardiographic (ECG) signal processing developed by introduction of time synchronization into the method of nonlinear state-space projections is presented. It can be regarded as an extension of time averaging but contrary to usual averaging it preserves variability of ECG beats morphology. For this purpose, after the respective beats time alignment, the synchronized intervals of the signal undergo processing according to the rules of principal component analysis (PCA). PCA allows for determination of orthogonal basis functions which can be employed for approximation of the respective intervals. The operation is aimed to retain the deviations from the mean which result from the desired component changes and to reject the deviations caused by noise. The method's capabilities are investigated and some of its applications are presented.     

Event-driven Video Awareness Providing Physical Security

The Video Event Awareness Workbench (VEAW) analyzes surveillance video from thousands of video cameras and automatically detects complex events in near-real-time-at pace with their input video streams. For events of interest to security personnel, VEAW generates and routes alerts and related video evidence to subscribing security personnel. Complex event processing in VEAW is driven by user-authored awareness specifications comprised of inter-connected spatio-temporal stream and statistical operators that consume and produce events described in VEAW’s surveillance ontology. In this paper we introduce VEAW’s event driven architecture and describe its solutions for automating video surveillance, including the orchestration of continuous and tasked video analysis algorithms (e.g., for entity tracking and identification), fusion of events from multiple sources in an installation-specific “world” model, and proactive information gathering to deal with missing or incomplete information (this is done by tasking video analysis algorithms and security personnel to provide it). We also discuss how VEAW deals with late arriving information (due to out-of-band video analysis tasks and overhead), as well as a related resource optimization aimed at minimizing computation costs. We illustrate the benefits of VEAW by illustrating its application on the automation of real-world security policies.     

The kernel common vector method: a novel nonlinear subspace classifier for pattern recognition.

The common vector (CV) method is a linear subspace classifier method which allows one to discriminate between classes of data sets, such as those arising in image and word recognition. This method utilizes subspaces that represent classes during classification. Each subspace is modeled such that common features of all samples in the corresponding class are extracted. To accomplish this goal, the method eliminates features that are in the direction of the eigenvectors corresponding to the nonzero eigenvalues of the covariance matrix of each class. In this paper, we introduce a variation of the CV method, which will be referred to as the modified CV (MCV) method. Then, a novel approach is proposed to apply the MCV method in a nonlinearly mapped higher dimensional feature space. In this approach, all samples are mapped into a higher dimensional feature space using a kernel mapping function, and then, the MCV method is applied in the mapped space. Under certain conditions, each class gives rise to a unique CV, and the method guarantees a 100% recognition rate with respect to the training set data. Moreover, experiments with several test cases also show that the generalization performance of the proposed kernel method is comparable to the generalization performances of other linear subspace classifier methods as well as the kernel-based nonlinear subspace method. While both the MCV method and its kernel counterpart did not outperform the support vector machine (SVM) classifier in most of the reported experiments, the application of our proposed methods is simpler than that of the multiclass SVM classifier. In addition, it is not necessary to adjust any parameters in our approach.