Quantitative Evaluation Of Systems Research Articles

An Efficient Multifeature Model for Improving the Performance of Critical Energy Infrastructure

Energy infrastructure is well thought-out to be one of the complex infrastructures due to its convoluted configuration and automatic control among all of the systems. With such systems, various connections are made for the purpose of configurations. The energy system infrastructure aims to analytically evaluate each element of the system based on fundamental energy branches according to the customer demand. Developing a novel critical evaluation approach for complex energy infrastructure is pertinent to the evaluation of mixed energy system infrastructure. Considering the functional relationships between elements and their infrastructures, a system is needed to overcome the limitations of the current systems. By doing the efficient modeling of enhancing the performance infrastructure of critical energy infrastructure enable better quantitative evaluation of system. The purpose of the proposed study is to develop an evaluation approach for enhancing the performance of critical energy infrastructure. With the help of the proposed approach, efficient multifeature model for enhancing the performance of critical energy infrastructure was experimentally calculated. The experimental setup of the proposed study was done in the Super Decision tool for an efficient multifeature model for enhancing the performance. Results of the experiments reveal the effectiveness of the proposed research.

Introduction to the Special Section on Quantitative Evaluation of Systems (QEST 2018)

Introduction to the Special Section on Quantitative Evaluation of Systems (QEST 2018)

Preventive Replacement Decisions for Dragline Components Using Reliability Analysis

Reliability-based maintenance policies allow qualitative and quantitative evaluation of system downtimes via revealing main causes of breakdowns and discussing required preventive activities against failures. Application of preventive maintenance is especially important for mining machineries since production is highly affected from machinery breakdowns. Overburden stripping operations are one of the integral parts in surface coal mine productions. Draglines are extensively utilized in overburden stripping operations and they achieve earthmoving activities with bucket capacities up to 168 m3. The massive structure and operational severity of these machines increase the importance of performance awareness for individual working components. Research on draglines is rarely observed in the literature and maintenance studies for these earthmovers have been generally ignored. On this basis, this paper offered a comprehensive reliability assessment for two draglines currently operating in the Tunçbilek coal mine and discussed preventive replacement for wear-out components of the draglines considering cost factors.

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

Digital breast tomosynthesis (DBT) is a promising breast cancer screening tool that has already begun making inroads into clinical practice. However, there is ongoing debate over how to quantitatively evaluate and optimize these systems, because different definitions of image quality can lead to different optimal design strategies. Powerful and accurate tools are desired to extend our understanding of DBT system optimization and validate published design principles. The authors developed a virtual trial framework for task-specific DBT assessment that uses digital phantoms, open-source x-ray transport codes, and a projection-space, spatial-domain observer model for quantitative system evaluation. The authors considered evaluation of reconstruction algorithms as a separate problem and focused on the information content in the raw, unfiltered projection images. Specifically, the authors investigated the effects of scan angle and number of angular projections on detectability of a small (3 mm diameter) signal embedded in randomly-varying anatomical backgrounds. Detectability was measured by the area under the receiver-operating characteristic curve (AUC). Experiments were repeated for three test cases where the detectability-limiting factor was anatomical variability, quantum noise, or electronic noise. The authors also juxtaposed the virtual trial framework with other published studies to illustrate its advantages and disadvantages. The large number of variables in a virtual DBT study make it difficult to directly compare different authors' results, so each result must be interpreted within the context of the specific virtual trial framework. The following results apply to 25% density phantoms with 5.15 cm compressed thickness and 500 μm(3) voxels (larger 500 μm(2) detector pixels were used to avoid voxel-edge artifacts): 1. For raw, unfiltered projection images in the anatomical-variability-limited regime, AUC appeared to remain constant or increase slightly with scan angle. 2. In the same regime, when the authors fixed the scan angle, AUC increased asymptotically with the number of projections. The threshold number of projections for asymptotic AUC performance depended on the scan angle. In the quantum- and electronic-noise dominant regimes, AUC behaviors as a function of scan angle and number of projections sometimes differed from the anatomy-limited regime. For example, with a fixed scan angle, AUC generally decreased with the number of projections in the electronic-noise dominant regime. These results are intended to demonstrate the capabilities of the virtual trial framework, not to be used as optimization rules for DBT. The authors have demonstrated a novel simulation framework and tools for evaluating DBT systems in an objective, task-specific manner. This framework facilitates further investigation of image quality tradeoffs in DBT.

Guest Editors' Introduction to the Special Issue on Quantitative Evaluation of Computer Systems

OFTWARE systems are expected to meet a multitude of quantitative constraints, such as timely response, performability, and efficient use of energy and other resources. Quantitative evaluation of systems refers to a set of techniques which can be applied to analyze such systems and obtain a range of quantitative characteristics of their performance, for example, the probability of satisfying a request within a given time or the appropriate number of replicas in a quorum air traffic control system. In this special issue, we publish a diverse range of novel research work which contributes to the development of quantitative evaluation of computer systems from a number of perspectives. These include theoretical foundations, models and modeling languages, analysis methods, simulation, verification, and software tools. Queueing networks have long been used for performance analysis of computer systems. This issue includes two papers related to queueing networks. In the first, “Enhanced Modeling and Solution of Layered Queueing Networks,” the layered queueing networks modeling formalism is presented. This modeling language allows a structured, hierarchical queueing network to be built up representing the resource usage and contention within a system. Analysis techniques which make use of the hierarchical structure allow complex models to be analyzed to address questions about the performance and dependability of the system. The second queueing paper, “CoMoM: Efficient Class-Oriented Evaluation of Multiclass Performance Models,” describes an improved solution technique for multiclass queueing network models. For more than 25 years, mean value analysis (MVA) has been one of the most frequently applied analysis methods of these models. This paper proposes an efficient rearrangement of recursive computational steps (referred to as the CoMoM method) such that it minimizes the number of recursive steps needed to solve the model. The CoMoM method makes possible the approximate analysis of much larger queueing network models, with tens of classes and thousands of nodes. Another well-established quantitative modeling technique is based on timed and stochastic extensions of Petri nets. In “State-Density Functions over DBM Domains in the Analysis of Non-Markovian Models,” a solution technique for such a Petri net extension is considered. The analysis of stochastic Petri nets with exponentially distributed firing times is well-developed and widely applied in software systemsmodeling.Incontrast,thecaseofstochasticPetrinets

Evaluation of automatic guided vehicle systems

This paper presents a methodology for detailed evaluation of autonomous automated guided vehicles systems (AGVS) used for material handling. The methodology includes: stand-alone sub-module evaluation, including comprehensive simulations and statistical analysis of the system's sub-modules, along with hardware validation; quantitative system evaluation for integrated system performance investigation; and structured qualitative analyses for identifying strengths and weaknesses not readily apparent. The defined performance measures include aspects from both multi-robot and AGV fields. The developed methodology provides a systematic way to model, experiment with, analyze, and compare different AGVS control methods. To demonstrate the methodology, it was applied to evaluate a recently developed decentralized AGVS control method.

Performance of Biometric Quality Measures

We document methods for the quantitative evaluation of systems that produce a scalar summary of a biometric sample's quality. We are motivated by a need to test claims that quality measures are predictive of matching performance. We regard a quality measurement algorithm as a black box that converts an input sample to an output scalar. We evaluate it by quantifying the association between those values and observed matching results. We advance detection error trade-off and error versus reject characteristics as metrics for the comparative evaluation of sample quality measurement algorithms. We proceed this with a definition of sample quality, a description of the operational use of quality measures. We emphasize the performance goal by including a procedure for annotating the samples of a reference corpus with quality values derived from empirical recognition scores.

Guest Editors' Introduction to the Special Section on the First International Conference on the Quantitative Evaluation of SysTems (QEST)

Guest Editors' Introduction to the Special Section on the First International Conference on the Quantitative Evaluation of SysTems (QEST)

Approximation of a Metric on a Dominating Cone

A theorem on the representation of a pseudoball of a dominating cone is proven. This theorem is an analog of the Caratheodory theorem on the representation of convex sets. The theorem allows to develop numerical methods for quantitative evaluation of systems in many indicators.