Automated GUI performance testing

A significant body of prior work has devised approaches for automating the functional testing of interactive applications. However, little work exists for automatically testing their performance. Performance testing imposes additional requirements upon GUI test automation tools: the tools have to be able to replay complex interactive sessions, and they have to avoid perturbing the application’s performance. We study the feasibility of using five Java GUI capture and replay tools for GUI performance test automation. Besides confirming the severity of the previously known GUI element identification problem, we also describe a related problem, the temporal synchronization problem, which is of increasing importance for GUI applications that use timer-driven activity. We find that most of the tools we study have severe limitations when used for recording and replaying realistic sessions of real-world Java applications and that all of them suffer from the temporal synchronization problem. However, we find that the most reliable tool, Pounder, causes only limited perturbation and thus can be used to automate performance testing. Based on an investigation of Pounder’s approach, we further improve its robustness and reduce its perturbation. Finally, we demonstrate in a set of case studies that the conclusions about perceptible performance drawn from manual tests still hold when using automated tests driven by Pounder. Besides the significance of our findings to GUI performance testing, the results are also relevant to capture and replay-based functional GUI test automation approaches.     

Decentralized fault detection and diagnosis via sparse PCA based decomposition and Maximum Entropy decision fusion

This paper proposes an approach for decentralized fault detection and diagnosis in process monitoring sensor networks. The sensor network is decomposed into multiple, potentially overlapping, blocks using the Sparse Principal Component Analysis algorithm. Local predictions are generated at each block using Support Vector Machine classifiers. The local predictions are then fused via a Maximum Entropy algorithm. Empirical studies on the benchmark Tennessee Eastman Process data demonstrated that the proposed decentralized approach achieves accuracy comparable to that of the fully centralized approach, while offering benefits in terms of fault tolerance, reusability, and scalability.     

Study of Silicon Cantilevers by the Photoacoustic Elastic Bending Method

Rectangular silicon cantilevers are studied by the photoacoustic (PA) elastic bending method. Experimental signals versus modulation frequency of the excitation optical beam are measured and analyzed in a frequency range from 20 Hz to 50 000 Hz. The procedure for experimental signal correction to eliminate the frequency characteristics of the measuring system is given. The corrected experimental signal shows a good correlation with theoretically calculated PA signal at frequencies below 32 000 Hz. The corrected experimental PA elastic bending signals for cantilevers with different thicknesses are analyzed. The experimental results allow identifying the resonant frequency (the first resonant mode) of the cantilever vibrations. These values are in good agreement with the theoretically computed values. A theoretical model of the optically excited Si cantilever is derived, taking into account plasmaelastic, thermoelastic, and thermodiffusion mechanisms. Dynamic relations for the amplitude and phase of electronic and thermal elastic vibrations in optically excited cantilevers are derived. The theoretical model is compared to the experimental results.     

Outage performance of dual‐hop relaying systems over extended generalized‐K fading channels

The outage performance of the amplify‐and‐forward relaying strategies over mutually uncorrelated extended generalized‐K fading channels is addressed in this paper. The attention is dedicated to the analyses of the noise‐limited and also interference‐limited environment. The new analytical expression for outage probability of observed relaying system in the presence of thermal noise is derived using the method for approximating equivalent signal‐to‐noise ratio. In addition, the outage performance is studied for the dual‐hop system when only the single dominant co‐channel interference is inherent at the relay and destination node. The correctness of the proposed mathematical derivations is verified by simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

Supervised clustering of label ranking data using label preference information

This paper studies supervised clustering in the context of label ranking data. The goal is to partition the feature space into K clusters, such that they are compact in both the feature and label ranking space. This type of clustering has many potential applications. For example, in target marketing we might want to come up with K different offers or marketing strategies for our target audience. Thus, we aim at clustering the customers’ feature space into K clusters by leveraging the revealed or stated, potentially incomplete customer preferences over products, such that the preferences of customers within one cluster are more similar to each other than to those of customers in other clusters. We establish several baseline algorithms and propose two principled algorithms for supervised clustering. In the first baseline, the clusters are created in an unsupervised manner, followed by assigning a representative label ranking to each cluster. In the second baseline, the label ranking space is clustered first, followed by partitioning the feature space based on the central rankings. In the third baseline, clustering is applied on a new feature space consisting of both features and label rankings, followed by mapping back to the original feature and ranking space. The RankTree principled approach is based on a Ranking Tree algorithm previously proposed for label ranking prediction. Our modification starts with K random label rankings and iteratively splits the feature space to minimize the ranking loss, followed by re-calculation of the K rankings based on cluster assignments. The MM-PL approach is a multi-prototype supervised clustering algorithm based on the Plackett-Luce (PL) probabilistic ranking model. It represents each cluster with a union of Voronoi cells that are defined by a set of prototypes, and assign each cluster with a set of PL label scores that determine the cluster central ranking. Cluster membership and ranking prediction for a new instance are determined by cluster membership of its nearest prototype. The unknown cluster PL parameters and prototype positions are learned by minimizing the ranking loss, based on two variants of the expectation-maximization algorithm. Evaluation of the proposed algorithms was conducted on synthetic and real-life label ranking data by considering several measures of cluster goodness: (1) cluster compactness in feature space, (2) cluster compactness in label ranking space and (3) label ranking prediction loss. Experimental results demonstrate that the proposed MM-PL and RankTree models are superior to the baseline models. Further, MM-PL is has shown to be much better than other algorithms at handling situations with significant fraction of missing label preferences.     

Konstruktion und experimentelle Untersuchung des Arbeitsdiagrammes einer Einphase-Ausgleichswelle

Übersicht Zunächst werden Formeln für den Motorstrom in Zusammenhang mit der Einphasen-Ausgleichswelle gegeben; weiter wird gezeigt, wie die Motor-Arbeitsdiagramme konstruiert werden können, d. h. entweder mit Hilfe der berechneten Parameter oder mit Hilfe der durch Experimente erhaltenen Angaben.Mit 10 Textabbildungen.     

The corrosion behavior of Ti3SiC2 in common acids and dilute NaOH

Hot isostatically processed bulk, fine (3-5 μm) grained samples of Ti₃SiC₂ were immersed in concentrated and dilute hydrochloric, HCl, sulphuric, H₂SO₄, nitric, HNO₃, dilute hydrofluoric, HF, acids and sodium hydroxide, NaOH, solutions at room temperature. Based on six-months weight changes the dissolution rates of Ti₃SiC₂ in concentrated and dilute HCl, H₂SO₄ and dilute NaOH were found to be negligible (<2 μm/yr). In dilute HF and concentrated HNO₃ the corrosion rates were, respectively, ≈5 μm/yr and 13 μm/yr respectively. In contrast to Ti metal, the weight losses of Ti₃SiC₂ in dilute HNO₃ were higher (≈250-320 μm/yr) and depended on concentration. Post-immersion scanning electron microscopic micrographs of samples immersed in HNO₃ indicated that an oxygen rich Si-based layer forms on the surface of the samples. This implies that the Ti atoms are leached out into the HNO₃ solution, leaving behind a Si-rich layer that is ultimately oxidized. Cyclic polarization and potentiostatic i-t transients in dilute HCl and H₂SO₄ acids, strongly suggest that a thin irreversible electrically insulating layer forms on the surface of Ti₃SiC₂. Exposing a sample to a constant current density of 0.6 mA/cm² for two days resulted in the formation of a 5 μm thick SiO₂-based layer on the surface. The presence of such a layer would explain the excellent corrosion resistance of Ti₃SiC₂ in these acids.     

Performance Analysis of System with Micro- and Macrodiversity Reception in Correlated Gamma Shadowed Rician Fading Channels

In this paper, the performance of wireless system employing microdiversity to mitigate the effects of short-term fading and macrodiversity to reduce long-term fading (shadowing) effects is studied. The system model assumes implementation of maximal-ratio combining (MRC) at the microlevel and selection combining (SC) at the macrolevel. The received signal envelope follows a Rician distribution and it also suffers gamma shadowing. Novel expressions for the probability density function (PDF), cumulative distribution function (CDF), and moment-generating function (MGF) of the output signal-to-noise ratio (SNR) are obtained. Several useful performance criteria, such as the moments of the output SNR and outage probability are analytically derived. Moreover, the average bit error probability (ABEP) for noncoherent binary differential phase-shift keying (BDPSK) is calculated using the MGF based approach while the ABEP for coherent binary phase-shift keying (BPSK) is studied by averaging the conditional bit error probability over the PDF. Numerical results are graphically presented to show the effects of various system parameters to the system performance, as well as the enhancement due to use of the combination of micro- and macrodiversity. Some of numerical results are complemented by equivalent computer simulated results which validate the accuracy of the proposed analysis. The agreement between the Rician-gamma and Rician-lognormal fading model is also established.     

Outage analysis of selection diversity over Rayleigh fading channels with multiple co-channel interferers

In this paper an approach to the performance analysis of signal-to-interference (SIR) based selection combining (SC) operating over the Rayleigh fading channels experiencing an arbitrary number of multiple, Rayleigh co-channel interferers is presented. We have presented a general analysis of multibranch SC where each branch experiences an arbitrary number of multiple equal power co-channel interferers. Useful closed form expressions are derived for the probability density function (PDF) and cumulative distribution function (CDF) at the output of the combiner. Also an outage analysis is performed in order to show the effects of the number of multiple interferers, diversity order and input SIR unbalance to the system performances.