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Software rejuvenation is a policy to counter the phenomenon of software ageing. However, how to implement software rejuvenation is still an important issue. In this paper, periodic impulse control is proposed as an effective tool to perform software rejuvenation and improve the availability of software system. First, we formulate the software rejuvenation system with periodic impulse by a group of coupled differential equations with impulsive action. Then the well-posedness of the system is demonstrated by using operator semigroup theory. At the end of the paper, numerical examples are shown to illustrate the dynamic behaviour of the system and the relationship between the system instantaneous availability and the impulsive indexes, including impulse interval and impulse strength, which yields that the system availability can be improved by adjusting the impulsive indexes. [ABSTRACT FROM AUTHOR]

This paper explores the presence and consideration of economics in sociology, specifically its classical version. It identifies certain original and independent economic theories, concepts and approaches in classical sociological theory as central and its derivations, implications and extensions of economics as peripheral. The paper argues and demonstrates that classical sociology is far from being the science of noneconomic or irrational phenomena, as often sociologists conceive it and economists perceive it in counter-distinction from economics defined as the science of rational behavior, and indeed encompasses virtually all economic activities and processes, and thus prefigures New Economic Sociology adopting the same approach. [ABSTRACT FROM AUTHOR]

The accurate characterization of carbonate rocks is crucial for determining the potential for exploring outcrops in the oil industry. Modern remote sensing instruments have played an important role in estimating mineral characteristics in the most varied scales. However, mathematical expressions suggested for converting radiance values to mineral information are often designed to work in only one particular territory. At the same time, the few general solutions existing tend to achieve overall poor results. In this paper, we propose an adaptive approach to estimate subpixel amounts of carbonate rocks using OLI-Landsat 8 image data. The main formulation is derived from exhaustive analysis of the spectral behavior of several carbonate materials. The formulation is subsequently adapted through the use of a genetic algorithm to work on diverse situations. Experiments have demonstrated the adaptability of the method for different environments, as well as its higher performance when compared with existing carbonate indices. [ABSTRACT FROM AUTHOR]

Different types of research have been done on video data using Artificial Intelligence (AI) deep learning techniques. Most of them are behavior analysis, scene understanding, scene labeling, human activity recognition (HAR), object localization, and event recognition. Among all these, HAR is one of the challenging tasks and thrust areas of video data processing research. HAR is applicable in different areas, such as video surveillance systems, human-computer interaction, human behavior characterization, and robotics. This paper aims to present a comparative review of vision-based human activity recognition with the main focus on deep learning techniques on various benchmark video datasets comprehensively. We propose a new taxonomy for categorizing the literature as CNN and RNN-based approaches. We further divide these approaches into four sub-categories and present various methodologies with their experimental datasets and efficiency. A short comparison is also made with the handcrafted feature-based approach and its fusion with deep learning to show the evolution of HAR methods. Finally, we discuss future research directions and some open challenges on human activity recognition. The objective of this survey is to give the current progress of vision-based deep learning HAR methods with the up-to-date study of literature. [ABSTRACT FROM AUTHOR]

Applied behavior analysis (ABA) is a common treatment for individuals with autism spectrum disorder (ASD). In a recent volume of this journal, Sanvodal-Norton and Shkedy (2019) published a criticism of behavior analysis including the professionals and entire field as a discipline—of demonstrating unethical behavior, creating prompt dependency in the learners, destroying internal motivation, and refusing to collaborate with new and other treatment philosophies. The current paper is a response to the these claims by providing several examples of peer-reviewed studies that contradicts the authors' arguments, and summarizing the information of the included study's findings by and other objective. The primary purpose of this paper is to demonstrate that, contrary to the perspectives of Sanvodal-Norton and Shkedy (2019), ABA is scientific approach that identifies environmental variables that influence socially significant behaviors and develop strategies to cause behavior change that is practical and applicable, improve educational outcomes, and provide real-life support for parents and families who are seeking treatment for their loved one with ASD. In doing so, this paper will demonstrate that ABA is an efficacious approach that is supported by numerous scientific studies in the peer-reviewed literature [ABSTRACT FROM AUTHOR]

Computing the moments in RC structures after the yield by linear elastic analysis can lead to an inaccurate assessment of the behaviour due to the nonlinear behaviour. Therefore, it can become necessary to use more advanced methodologies to achieve a higher degree of performance optimisation of structures than those resulting from the simplified approaches adopted by existing design codes based on linear elastic analysis with redistribution of internal forces. The moment redistribution is supposed to start after occurring the cracks of concrete, but with small ratio. In this study, the moment redistribution before the yielding will be neglected, and the redistribution is focused after the yield. This paper suggests a mathematical model to investigate the moment redistribution in RC beams after yielding analytically. In the suggested mathematical model, the beam after forming the plastic hinges is converted into a virtual beam that can be analysed by structural linear analysis. The plastic hinges in the virtual beam will be represented as rotational springs having a linear rotational stiffness against the induced moment. The actual moments can be found through derived relationships in the mathematical model between it and the virtual moment. The mathematical model was verified and it gave values of moment matching experimental results. Also, a comparison for degree of moment redistribution among the suggested mathematical model and several design codes was performed. The analytical results indicate that the proposed mathematical model can be used for analysis of moment redistribution of RC beams. [ABSTRACT FROM AUTHOR]

The paper reports a new mathematical model for understanding the mechanism delivery from drug release systems. To do this, two drug release systems based on chitosan and diclofenac sodium salt as a drug model, were prepared by in situ hydrogelation in the presence of salicylaldehyde. The morphology of the systems was analyzed by scanning electron microscopy and polarized light microscopy and the drug release was in vitro investigated into a medium mimicking the in vivo environment. The drug release mechanism was firstly assessed by fitting the in vitro release data on five traditional mathematical model. In the context of pharmacokinetics behavioral analysis, a new mathematical procedure for describing drug release dynamics in polymer-drug complex systems was proposed. Assuming that the dynamics of polymer-drug system's structural units take place on continuous and nondifferentiable curves (multifractal curves), it was showed that in a one-dimensional hydrodynamic formalism of multifractal variables the drug release mechanism is given through synchronous dynamics at a differentiable and non-differentiable scale resolutions. [ABSTRACT FROM AUTHOR]

Numerous reports indicate that the incidence of posttraumatic stress disorder (PTSD) in Operation Enduring Freedom/Operation Iraqi Freedom/Operation New Dawn (OEF/OIF/OND) military personnel has created a significant behavioural healthcare challenge. These findings have served to motivate research on how to better develop and disseminate evidence-based treatments for PTSD. The current article presents the use of Virtual Reality (VR) as a clinical tool to address the assessment, prevention, and treatment of PTSD, based on the VR projects that were evolved at the University of Southern California Institute for Creative Technologies since 2004. A brief discussion of the definition and rationale for the clinical use of VR is followed by a description of a VR application designed for the delivery of prolonged exposure (PE) for treating Service Members (SMs) and Veterans with combat- and sexual assault-related PTSD. The expansion of the virtual treatment simulations of Iraq and Afghanistan for PTSD assessment and prevention is then presented. This is followed by a forward-looking discussion that details early efforts to develop virtual human agent systems that serve the role of virtual patients for training the next generation of clinical providers, as healthcare guides that can be used to support anonymous access to trauma-relevant behavioural healthcare information, and as clinical interviewers capable of automated behaviour analysis of users to infer psychological state. The paper will conclude with a discussion of VR as a tool for breaking down barriers to care in addition to its direct application in assessment and intervention. [ABSTRACT FROM AUTHOR]