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Vulnerabilities need to be detected and removed from software. Although previous studies demonstrated the usefulness of employing prediction techniques in deciding about vulnerabilities of software components, the improvement of effectiveness of these prediction techniques is still a grand challenging research question. This paper employed a technique based on a deep neural network with rectifier linear units trained with stochastic gradient descent method and batch normalization, for predicting vulnerable software components. The features are defined as continuous sequences of tokens in source code files. Besides, a statistical feature selection algorithm is then employed to reduce the feature and search space. We evaluated the proposed technique based on some Java Android applications, and the results demonstrated that the proposed technique could predict vulnerable classes, i.e., software components, with high precision, accuracy and recall.
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Although research on substance use disorders (SUDs) largely focuses on the developed world, treatment programs from the developing world seldom get international attention. Focusing on India, this study was designed (1) to describe India’s treatment programs, and (2) to report Indian perspectives on critical factors related to treating SUDs. An online survey instrument was created, based on mixed-methods approach with concurrent strategies, to collect data. Participants were India’s clinicians (N = 112). Indian treatment approach suggests that SUDs must be treated by a multidisciplinary treatment team with a comprehensive plan that must include systemically focused clinical interventions in patients’/clients’ relevant relational systems. Findings may have relevance to clinicians, researchers, and policy makers globally. © 2017 Taylor & Francis.
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Parenting literature often focuses on parental strategies that promote positive behavioral outcomes for children, but ignores key aspects of parents’ own growth process. This article presents a critical review of current literature on parenting and highlights the importance of focusing on parents’ growth in therapy. A clinical framework to define parents’ growth is offered along with case vignettes and practical guidelines for clinicians in order to assess parents’ growth. © 2017 Taylor & Francis Group, LLC.
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The balancing act of living between two cultures can have a significant impact on the development of adolescent Latinas living in the United States. Many adolescent Latinas, particularly second generation, live with two sets of cultural values that are often in conflict with one another. This case study illustrates the importance of understanding the impact of acculturation on the individual and the family. Issues of identity, biculturalism, and bilingualismspecifically the phenomenon of language switchingare dismantled in this case study to gain deeper insight into the unique experience that second-generation Latinas undergo when negotiating two cultural orientations. These findings are important to consider when working with the Latino population as they represent one of the largest immigrant groups and the most rapidly growing group in the United States.
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Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community. © 2017 Open Society Foundation.
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Mechanistic accounts of explanation have recently found popularity within philosophy of science. Presently, we introduce the idea of an extended mechanistic explanation, which makes explicit room for the role of environment in explanation. After delineating Craver and Bechtel’s (2007) account, we argue this suggestion is not sufficiently robust when we take seriously the mechanistic environment and modeling practices involved in studying contemporary complex biological systems. Our goal is to extend the already profitable mechanistic picture by pointing out the importance of the mechanistic environment. It is our belief that extended mechanistic explanations, or mechanisms that take into consideration the temporal sequencing of the interplay between the mechanism and the environment, allow for mechanistic explanations regarding a broader group of scientific phenomena. © 2016, Springer Science+Business Media Dordrecht.
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Community Arts have a long history within art and education, yet its practices continue to evolve. The issue of nomenclature when discussing such socially engaged practices raises the deeper questions of whether work in this area suggests the formalization of yet another new genre of art, or does it entail a more profound re-ordering of the discursive system that underlies most existing modes of artistic production? This chapter attends to individual differences and similarities in perception and practice through a careful consideration for how the field of art education might nurture new and diverse articulations of community-based practices that emphasize relational aesthetics, participatory pedagogy, and socially engaged artistic practices. This chapter will (re)frame the discourse as Socially Engaged Art Education (SEAE) to emphasize a new terrain of consciousness that is socially responsible and ethically sound, and goes beyond mere promotion of aesthetic quality to contribute to improved quality of life.
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In this article, we derive the joint Laplace transform of the sequential probability ratio test (SPRT) and the resulting stopped random walk process for the negative exponential model. The Laplace transform is derived by solving a related difference equation. This technique is novel because it only takes advantage of the Markov structure and does not rely on the typical martingale methods used for deriving the Laplace transform of other SPRTs. The joint Laplace transform provides the joint distribution of the SPRT and the associated stopped process, which is a new result. Even the marginal distributions were hitherto unknown. © 2017 Taylor & Francis.
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