Determination of Autotransformer-Capacitor Phase Converter Parameters

An analytical approach is described for determining the parameters for an autotransformer-capacitor phase converter that allows matching of the converter to a specific motor for a given load. Equations are developed for the capacitor size and autotransformer turns ratio that will give balanced operation of a three-phase motor. Predicted values are compared with the experimental results.     

Accurately Measuring Denial of Service in Simulation and Testbed Experiments

Researchers in the denial-of-service (DoS) field lack accurate, quantitative, and versatile metrics to measure service denial in simulation and testbed experiments. Without such metrics, it is impossible to measure severity of various attacks, quantify success of proposed defenses, and compare their performance. Existing DoS metrics equate service denial with slow communication, low throughput, high resource utilization, and high loss rate. These metrics are not versatile because they fail to monitor all traffic parameters that signal service degradation. They are not quantitative because they fail to specify exact ranges of parameter values that correspond to good or poor service quality. Finally, they are not accurate since they were not proven to correspond to human perception of service denial. We propose several DoS impact metrics that measure the quality of service experienced by users during an attack. Our metrics are quantitative: they map QoS requirements for several applications into measurable traffic parameters with acceptable, scientifically determined thresholds. They are versatile: they apply to a wide range of attack scenarios, which we demonstrate via testbed experiments and simulations. We also prove metrics' accuracy through testing with human users.     

Sequential Exploration of Complex Surfaces Using Minimum Energy Designs

A new space-filling design, called minimum energy design (MED), is proposed to explore unknown regions of the design space of particular interest to an experimenter. The key ideas involved in constructing the MED are the visualization of each design point as a charged particle inside a box, and minimization of the total potential energy of these particles. It is shown through theoretical arguments and simulations that with a proper choice of the charge function, the MED can asymptotically generate any arbitrary probability density function. A version of the MED, which adaptively updates the design by “learning” about the unknown response surface sequentially, is proposed and implemented. Two potential applications of MED in simulation of complex probability densities and optimization of complex response surfaces are discussed and demonstrated with examples. This article has supplementary material online.     

Last Planner System and Scrum: Comparative analysis and suggestions for adjustments

This study provides a critical review of the concepts of Agile, Lean, Scrum, and Last Planner^® System (LPS). A comparative analysis is conducted between LPS and Scrum to expand LPS by considering Scrum’s best practices. Eight dimensions, namely, 1) origins, 2) main purpose, 3) overall system/framework process, 4) tools or artifacts maintained by the team, 5) team composition and main roles, 6) regular events or team meetings, 7) metrics/dashboards, and 8) approach to learning, are evaluated. After analyzing side by side the eight dimensions, it was found that many aspects from Scrum already exist in LPS in the same or similar form. However, the authors identify four main elements from Scrum that can be leveraged to improve the LPS benchmark, such as considering the Scrum “Increment” concept into LPS, having a clear definition of roles and responsibilities, or adding an equivalent to a Scrum Master to have a designated “rule keeper” in LPS. These opportunities to be considered in new LPS benchmarks need to be tested and validated with real applications. To the best of the authors’ knowledge, this work is the first to comprehensively compare Scrum (Agile) and LPS (Lean) and could be seen as a contribution toward the evolution of the Last Planner System for the academic and industrial environments.     

A heuristic technique to detect phishing websites using TWSVM classifier

Neural Computing and Applications - Phishing websites are on the rise and are hosted on compromised domains such that legitimate behavior is embedded into the designed phishing site to overcome the...     

Detection of phishing websites using an efficient feature-based machine learning framework

Neural Computing and Applications - Phishing is a cyber-attack which targets naive online users tricking into revealing sensitive information such as username, password, social security number or...     

RETRACTED ARTICLE: Determination of dopant of ceria system by density functional theory

Oxides with the cubic fluorite structure, e.g., ceria (CeO₂), are known to be good solid electrolytes when they are doped with cations of lower valence than the host cations. The high ionic conductivity of doped ceria makes it an attractive electrolyte for solid oxide fuel cells, whose prospects as an environmentally friendly power source are very promising. In these electrolytes, the current is carried by oxygen ions that are transported by oxygen vacancies, present to compensate for the lower charge of the dopant cations. Ionic conductivity in ceria is closely related to oxygen-vacancy formation and migration properties. A clear physical picture of the connection between the choice of a dopant and the improvement of ionic conductivity in ceria is still lacking. Here we present quantum-mechanical first-principles study of the influence of different trivalent impurities on these properties. Our results reveal a remarkable correspondence between vacancy properties at the atomic level and the macroscopic ionic conductivity. The key parameters comprise migration barriers for bulk diffusion and vacancy–dopant interactions, represented by association (binding) energies of vacancy–dopant clusters. The interactions can be divided into repulsive elastic and attractive electronic parts. In the optimal electrolyte, these parts should balance. This finding offers a simple and clear way to narrow the search for superior dopants and combinations of dopants. The ideal dopant should have an effective atomic number between 61 (Pm) and 62 (Sm), and we elaborate that combinations of Nd/Sm and Pr/Gd show enhanced ionic conductivity, as compared with that for each element separately. An erratum to this article can be found at     

Neural network approach for estimating the residual tensile strength after drilling in uni-directional glass fiber reinforced plastic laminates

The drilling of fiber reinforced plastics (FRP) often results in damage around the drilled hole. The drilling induced damage often serves to impair the long-term performance of the composite products with drilled holes. The present research investigation focuses on developing a predictive model for the residual tensile strength of uni-directional glass fiber reinforced plastic (UD-GFRP) laminates with drilled hole which has not been developed worldwide till now. Artificial neural network (ANN) predictive approach has been used. The drill point geometry, the feed rate and the spindle speed have been used as the input variables and the residual tensile strength as the output. The results of the predictive model are in close agreement with the training and the testing data.