Andrey V. Masloboev
Full Text Available Subject of research. The research goal and scope are development of methods and software for mathematical and computer modeling of the regional security information support systems as multilevel hierarchical systems. Such systems are characterized by loosely formalization, multiple-aspect of descendent system processes and their interconnectivity, high level dynamics and uncertainty. The research methodology is based on functional-target approach and principles of multilevel hierarchical system theory. The work considers analysis and structural-algorithmic synthesis problem-solving of the multilevel computer-aided systems intended for management and decision-making information support in the field of regional security. Main results. A hierarchical control multilevel model of regional socio-economic system complex security has been developed. The model is based on functional-target approach and provides both formal statement and solving, and practical implementation of the automated information system structure and control algorithms synthesis problems of regional security management optimal in terms of specified criteria. An approach for intralevel and interlevel coordination problem-solving in the multilevel hierarchical systems has been proposed on the basis of model application. The coordination is provided at the expense of interconnection requirements satisfaction between the functioning quality indexes (objective functions, which are optimized by the different elements of multilevel systems. That gives the possibility for sufficient coherence reaching of the local decisions, being made on the different control levels, under decentralized decision-making and external environment high dynamics. Recurrent model application provides security control mathematical models formation of regional socioeconomic systems, functioning under uncertainty. Practical relevance. The model implementation makes it possible to automate synthesis realization of
A. V. Masloboev
Full Text Available The paper deals with development of methods and tools for mathematical and computer modeling of the multilevel network-centric control systems of regional security. This research is carried out under development strategy implementation of the Arctic zone of the Russian Federation and national safeguarding for the period before 2020 in the Murmansk region territory. Creation of unified interdepartmental multilevel computer-aided system is proposed intended for decision-making information support and socio-economic security monitoring of the Arctic regions of Russia. The distinctive features of the investigated system class are openness, self-organization, decentralization of management functions and decision-making, weak hierarchy in the decision-making circuit and goal generation capability inside itself. Research techniques include functional-target approach, mathematical apparatus of multilevel hierarchical system theory and principles of network-centric control of distributed systems with pro-active components and variable structure. The work considers network-centric management local decisions coordination problem-solving within the multilevel distributed systems intended for information support of regional security. The coordination problem-solving approach and problem formalization in the multilevel network-centric control systems of regional security have been proposed based on developed multilevel recurrent hierarchical model of regional socio-economic system complex security. The model provides coordination of regional security indexes, optimized by the different elements of multilevel control systems, subject to decentralized decision-making. The model specificity consists in application of functional-target technology and mathematical apparatus of multilevel hierarchical system theory for coordination procedures implementation of the network-centric management local decisions. The work-out and research results can find further
Finch, W Holmes; Kelley, Ken
A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software environment.After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models fo
This book provides a clear introduction to this important area of statistics. The author provides a wide of coverage of different kinds of multilevel models, and how to interpret different statistical methodologies and algorithms applied to such models. This 4th edition reflects the growth and interest in this area and is updated to include new chapters on multilevel models with mixed response types, smoothing and multilevel data, models with correlated random effects and modeling with variance.
Kang, Myong H; Froscher, Judith N; Sheth, Amit P; Kochut, Krys J; Miller, John A
The Department of Defense (DoD) needs multilevel secure (MLS) workflow management systems to enable globally distributed users and applications to cooperate across classification levels to achieve mission critical goals...
Levin, Timothy, E.; Irvine, Cynthia E.; Weissman, Clark; Nguyen, Thuy D.
Proceedings of the Computer Security Architecture Workshop, ACM. November 2, 2007, Fairfax, Virginia, USA. pp. 37-46 Various system architectures have been proposed for high assurance enforcement of multilevel security. This paper provides an analysis of the relative merits of three architectural types, one based on a security kernel, another based on a traditional separation kernel, and a third based on a least-privilege separation kernel. We introduce the Least Privilege architecture, w...
Full Text Available Multi-level security mechanism has been widely applied in the military, government, defense and other domains in which information is required to be divided by security-level. Through this type of security mechanism, users at different security levels are provided with information at corresponding security levels. Traditional multi-level security mechanism which depends on the safety of operating system finally proved to be not practical. We propose a container-based trusted multi-level security mechanism in this paper to improve the applicability of the multi-level mechanism. It guarantees multi-level security of the system through a set of multi-level security policy rules and trusted techniques. The technical feasibility and application scenarios are also discussed. The ease of realization, strong practical significance and low cost of our method will largely expand the application of multi-level security mechanism in real life.
Syed Asad Hussain
Full Text Available Threats jeopardize some basic security requirements in a cloud. These threats generally constitute privacy breach, data leakage and unauthorized data access at different cloud layers. This paper presents a novel multilevel classification model of different security attacks across different cloud services at each layer. It also identifies attack types and risk levels associated with different cloud services at these layers. The risks are ranked as low, medium and high. The intensity of these risk levels depends upon the position of cloud layers. The attacks get more severe for lower layers where infrastructure and platform are involved. The intensity of these risk levels is also associated with security requirements of data encryption, multi-tenancy, data privacy, authentication and authorization for different cloud services. The multilevel classification model leads to the provision of dynamic security contract for each cloud layer that dynamically decides about security requirements for cloud consumer and provider.
Wang, Jichuan; Fisher, James F
This book covers a broad range of topics about multilevel modeling. The goal is to help readers to understand the basic concepts, theoretical frameworks, and application methods of multilevel modeling. It is at a level also accessible to non-mathematicians, focusing on the methods and applications of various multilevel models and using the widely used statistical software SAS®. Examples are drawn from analysis of real-world research data.
Leckie, George; Pillinger, Rebecca; Jones, Kelvyn; Goldstein, Harvey
The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…
Ong, Kar L
The Monterey Security Architecture (MYSEA) provides a distributed multilevel secure networking environment where authenticated users can securely access data and services at different security classification levels...
This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...
Min, Suqin; He, Xiaoqun
The traditional multilevel model assumed independence between groups. However, the datasets grouped by geographical units often has spatial dependence. The individual is influenced not only by its region but also by the adjacent regions, and level-2 residual distribution assumption of traditional multilevel model is violated. In order to deal with such spatial multilevel data, we introduce spatial statistics and spatial econometric models into multilevel model, and apply spatial parameters and adjacency matrix in traditional level-2 model to reflect the spatial autocorrelation. Spatial lag model express spatial effects. We build spatial multilevel model which consider both multilevel thinking and spatial correlation.
Schotanus, H.A.; Hartog, T.; Verkoelen, C.A.A.
Multi-Level Security (MLS) is often viewed as the holy grail of information security, especially in those environments where information of different classifications is being processed. In this paper we argue that MLS cannot facilitate the right balance between need-to-protect and duty-to-share as
Karunarathna, G. H. S.; Sooriyarachchi, M. R.
Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).
feed items. Some software presents feed items in the form of a news ticker, showing summaries of syndicated content as feed updates are detected . 1.4.2...motivates designs capable of addressing the gazillions problem, which is endemic to those multiuser MLS systems in which security compartments are commonplace...the cache. This is, of course, merely to avoid logging errors and not for policy enforcement. Similar logic is used to detect when image and favicon
Dickson. 1996. "Teams in Organizations: Recent Research on Performance and Effectiveness". Annual Review of Psychology , 47:307-338.  Hall, D.L... Psychology , 94, 2, 535-546.  Moore, J.A. (2002). JView: an information visualization paradigm. Proc. SPIE, Vol. 4716, 367-374. In Enabling...date. Multilevel security solutions like the Multi-Layer Access Solution were developed by Gestalt and MAXIM Systems before these companies became
Curran, Patrick J.; Bauer, Daniel J.
Multilevel models have come to play an increasingly important role in many areas of social science research. However, in contrast to other modeling strategies, there is currently no widely used approach for graphically diagramming multilevel models. Ideally, such diagrams would serve two functions: to provide a formal structure for deriving the…
Lynch, Martin F.
This article reports a test of a multilevel model investigating how attachment security and autonomy contribute to emotional reliance, or the willingness to seek interpersonal support. Participants ("N" = 247) completed online measures of attachment, autonomy, emotional reliance, and vitality with respect to several everyday…
Wright, Daniel B; London, Kamala
Over the last 30 years statistical algorithms have been developed to analyse datasets that have a hierarchical/multilevel structure. Particularly within developmental and educational psychology these techniques have become common where the sample has an obvious hierarchical structure, like pupils nested within a classroom. We describe two areas beyond the basic applications of multilevel modelling that are important to psychology: modelling the covariance structure in longitudinal designs and using generalized linear multilevel modelling as an alternative to methods from signal detection theory (SDT). Detailed code for all analyses is described using packages for the freeware R.
Paassen, M.M. van; Wieringa, Peter A.
Complex heterogeneous systems, such as power plants or petro-chemical process plants, nowadays contain complex automation for start-up and shut-down control and support systems for the operators. Often, however, the operator support and automation suffers from a lack of flexibility, and only functions for a number of well defined operating modes and pre-defined paths for the transition between these modes. This paper proposes an alternative and more flexible method for developing and describing intentional mode transitions, and for developing diagnostic systems, using Multilevel Flow Modeling (MFM). MFM models a system by expressing it in terms of its goals and in terms of elementary functions that describe the mass, energy and information flows in the system. This paper describes the use of MFM models as a basis for reasoning about the actions that are necessary to achieve the goals of a system or to obtain an intentional change in the system's mode. For this, data measured from the system must be used to update the state of the MFM model so that the state of the model reflects the state of the system. The outcome of the reasoning can be used as support for an operator or for automated control of complex systems. This paper defines the relevant states for goals and flow functions and presents a set of rules for determining these states on the basis of measurements from a process. The relations between goals and functions, and among functions themselves, are discussed. A mechanism is introduced to produce a change in the desired mode of a process, and expressed in rules to implement this change. The approach is explained at the hand of a simple example system. An MFM model of this example system is presented, and used to illustrate how measured variables can be used to calculate the states of the elements in the MFM model. At the hand of the same model the rules for inferring the states of goals and functions, and for determining the required actions will be
Skrondal, Anders; Rabe-Hesketh, Sophia
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.
Peterson, M.F.; Arregle, J-L.; Martin, Xavier
Multiple-level (or mixed linear) modeling (MLM) can simultaneously test hypotheses at several levels of analysis (usually two or three), or control for confounding effects at one level while testing hypotheses at others. Advances in multi-level modeling allow increased precision in quantitative
Multilevel Flow Modeling (MFM) is a methodology for functional modeling of industrial processes on several interconnected levels of means-end and part-whole abstractions. The basic idea of MFM is to represent an industrial plant as a system which provides the means required to serve purposes in i...... in detail by a water mill example. The overall reasoning capabilities of MFM and its basis in cause-effect relations are also explained. The appendix contains an overview of MFM concepts and their definitions....
Park, W.; Belova, E.V.; Fu, G.Y.
The question of how to proceed toward ever more realistic plasma simulation studies using ever increasing computing power is addressed. The answer presented here is the M3D (Multilevel 3D) project, which has developed a code package with a hierarchy of physics levels that resolve increasingly complete subsets of phase-spaces and are thus increasingly more realistic. The rationale for the multilevel physics models is given. Each physics level is described and examples of its application are given. The existing physics levels are fluid models (3D configuration space), namely magnetohydrodynamic (MHD) and two-fluids; and hybrid models, namely gyrokinetic-energetic-particle/MHD (5D energetic particle phase-space), gyrokinetic-particle-ion/fluid-electron (5D ion phase-space), and full-kinetic-particle-ion/fluid-electron level (6D ion phase-space). Resolving electron phase-space (5D or 6D) remains a future project. Phase-space-fluid models are not used in favor of delta f particle models. A practical and accurate nonlinear fluid closure for noncollisional plasmas seems not likely in the near future
Park, W.; Belova, E.V.; Fu, G.Y. [and others
The question of how to proceed toward ever more realistic plasma simulation studies using ever increasing computing power is addressed. The answer presented here is the M3D (Multilevel 3D) project, which has developed a code package with a hierarchy of physics levels that resolve increasingly complete subsets of phase-spaces and are thus increasingly more realistic. The rationale for the multilevel physics models is given. Each physics level is described and examples of its application are given. The existing physics levels are fluid models (3D configuration space), namely magnetohydrodynamic (MHD) and two-fluids; and hybrid models, namely gyrokinetic-energetic-particle/MHD (5D energetic particle phase-space), gyrokinetic-particle-ion/fluid-electron (5D ion phase-space), and full-kinetic-particle-ion/fluid-electron level (6D ion phase-space). Resolving electron phase-space (5D or 6D) remains a future project. Phase-space-fluid models are not used in favor of delta f particle models. A practical and accurate nonlinear fluid closure for noncollisional plasmas seems not likely in the near future.
Kim, Eun Sook; Cao, Chunhua
Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.
Zhang, Xinxin; Lind, Morten; Ravn, Ole
Consequence reasoning is a major element for operation support system to assess the plant situations. The purpose of this paper is to elaborate how Multilevel Flow Models can be used to reason about consequences of disturbances in complex engineering systems. MFM is a modelling methodology...... for representing process knowledge for complex systems. It represents the system by using means-end and part-whole decompositions, and describes not only the purposes and functions of the system but also the causal relations between them. Thus MFM is a tool for causal reasoning. The paper introduces MFM modelling...... syntax and gives detailed reasoning formulas for consequence reasoning. The reasoning formulas offers basis for developing rule-based system to perform consequence reasoning based on MFM, which can be used for alarm design, risk monitoring, and supervision and operation support system design....
Implementation of multilevel model is becoming a common analytic technique over a wide range of disciplines including social and economic sciences. In this paper, an attempt has been made to assess the application of multilevel logistic model for the purpose of identifying the effect of household characteristics on poverty ...
A. V. Chernov
Full Text Available Security monitoring and incident management systems have become the main research focus in the area of intelligent railway control systems. In this work, we discuss a system architecture of multilevel intelligent control system in Russian Railway transport and security incident classification and the handling of theprocess. We make a detailed explanation of problems and tasks of security information and event management system as an important part of a multilevel intelligent control system. We use a rough sets theory to detect an abnormal activity in the considered system. Our main result consists in the development of simple and fast detection techniques that are based on rough sets theory and allow investigating a new type of incidents.
Huang, Hung-Yu; Wang, Wen-Chung
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Tanenbaum, A.S.; Popescu, B.C.; Crispo, B.; Hempelmann, C.F.; Raskin, V.
Digital rights management systems allow copyrighted content to be commercialized in digital format without the risk of revenue loss due to piracy. Making such systems secure is no easy task, given that content needs to be protected while accessed through electronic devices in the hands of
Pang, James Christopher S.; Monterola, Christopher P.
Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.
Scott, Marc A; Marx, Brian D
Leading contributors combine practical pieces with overviews of the state of the art in the field, making this handbook essential reading for any student or researcher looking to apply multilevel techniques in their own research
Krull, J L; MacKinnon, D P
This article combines procedures for single-level mediational analysis with multilevel modeling techniques in order to appropriately test mediational effects in clustered data. A simulation study compared the performance of these multilevel mediational models with that of single-level mediational models in clustered data with individual- or group-level initial independent variables, individual- or group-level mediators, and individual level outcomes. The standard errors of mediated effects from the multilevel solution were generally accurate, while those from the single-level procedure were downwardly biased, often by 20% or more. The multilevel advantage was greatest in those situations involving group-level variables, larger group sizes, and higher intraclass correlations in mediator and outcome variables. Multilevel mediational modeling methods were also applied to data from a preventive intervention designed to reduce intentions to use steroids among players on high school football teams. This example illustrates differences between single-level and multilevel mediational modeling in real-world clustered data and shows how the multilevel technique may lead to more accurate results.
Dorairaj, Sudha Devi; Kaliannan, Thilagavathy
Cloud computing is renowned for delivering information technology services based on internet. Nowadays, organizations are interested in moving their massive data and computations into cloud to reap their significant benefits of on demand service, resource pooling, and rapid elasticity that helps to satisfy the dynamically changing infrastructure demand without the burden of owning, managing, and maintaining it. Since the data needs to be secured throughout its life cycle, security of the data in cloud is a major challenge to be concentrated on because the data is in third party's premises. Any uniform simple or high level security method for all the data either compromises the sensitive data or proves to be too costly with increased overhead. Any common multiple method for all data becomes vulnerable when the common security pattern is identified at the event of successful attack on any information and also encourages more attacks on all other data. This paper suggests an adaptive multilevel security framework based on cryptography techniques that provide adequate security for the classified data stored in cloud. The proposed security system acclimates well for cloud environment and is also customizable and more reliant to meet the required level of security of data with different sensitivity that changes with business needs and commercial conditions.
Sudha Devi Dorairaj
Full Text Available Cloud computing is renowned for delivering information technology services based on internet. Nowadays, organizations are interested in moving their massive data and computations into cloud to reap their significant benefits of on demand service, resource pooling, and rapid elasticity that helps to satisfy the dynamically changing infrastructure demand without the burden of owning, managing, and maintaining it. Since the data needs to be secured throughout its life cycle, security of the data in cloud is a major challenge to be concentrated on because the data is in third party’s premises. Any uniform simple or high level security method for all the data either compromises the sensitive data or proves to be too costly with increased overhead. Any common multiple method for all data becomes vulnerable when the common security pattern is identified at the event of successful attack on any information and also encourages more attacks on all other data. This paper suggests an adaptive multilevel security framework based on cryptography techniques that provide adequate security for the classified data stored in cloud. The proposed security system acclimates well for cloud environment and is also customizable and more reliant to meet the required level of security of data with different sensitivity that changes with business needs and commercial conditions.
Matsueda, Ross L.; Drakulich, Kevin M.
This article specifies a multilevel measurement model for survey response when data are nested. The model includes a test-retest model of reliability, a confirmatory factor model of inter-item reliability with item-specific bias effects, an individual-level model of the biasing effects due to respondent characteristics, and a neighborhood-level…
Brykalov, S. M.; Kryanev, A. V.
The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.
Vis, Daniel J; Bombardelli, Lorenzo; Lightfoot, Howard; Iorio, Francesco; Garnett, Mathew J; Wessels, Lodewyk Fa
Experimental variation in dose-response data of drugs tested on cell lines result in inaccuracies in the estimate of a key drug sensitivity characteristic: the IC50. We aim to improve the precision of the half-limiting dose (IC50) estimates by simultaneously employing all dose-responses across all cell lines and drugs, rather than using a single drug-cell line response. We propose a multilevel mixed effects model that takes advantage of all available dose-response data. The new estimates are highly concordant with the currently used Bayesian model when the data are well behaved. Otherwise, the multilevel model is clearly superior. The multilevel model yields a significant reduction of extreme IC50 estimates, an increase in precision and it runs orders of magnitude faster.
Díaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Mukkerikar, Amol
The aim of this work is to present the development of a computer aided multilevel modeling network for the systematic design and analysis of processes employing lipid technologies. This is achieved by decomposing the problem into four levels of modeling: i) pure component property modeling...
Fox, Gerardus J.A.; Glas, Cornelis A.W.
In this article, a two-level regression model is imposed on the ability parameters in an item response theory (IRT) model. The advantage of using latent rather than observed scores as dependent variables of a multilevel model is that it offers the possibility of separating the influence of item
O'Connell, Ann A.; Reed, Sandra J.
Multilevel modeling (MLM), also referred to as hierarchical linear modeling (HLM) or mixed models, provides a powerful analytical framework through which to study colleges and universities and their impact on students. Due to the natural hierarchical structure of data obtained from students or faculty in colleges and universities, MLM offers many…
Garcia-Gabin, Winston; Jacobsen, Elling W
Diabetes is a disease that involves alterations at multiple biological levels, ranging from intracellular signalling to organ processes. Since glucose homeostasis is the consequence of complex interactions that involve a number of factors, the control of diabetes should be based on a multilevel analysis. In this paper, a novel approach to design of closed-loop glucose controllers based on multilevel models is presented. A control scheme is proposed based on combining a pharmacokinetic/pharmacodynamic model with an insulin signal transduction model for type 1 diabetes mellitus patients. Based on this, an insulin feedback control schemes is designed. Two main advantages of explicitly utilizing information at the intracellular level were obtained. First, significant reduction of hypoglycaemic risk by reducing the undershoot in glucose levels in response to added insulin. Second, robust performance for inter-patient changes, demonstrated through application of the multilevel control strategy to a well established in silico population of diabetic patients.
Cho, Sun-Joo; Cohen, Allan S.
Mixture item response theory models have been suggested as a potentially useful methodology for identifying latent groups formed along secondary, possibly nuisance dimensions. In this article, we describe a multilevel mixture item response theory (IRT) model (MMixIRTM) that allows for the possibility that this nuisance dimensionality may function…
Kahn, Jeffrey H.
Multilevel modeling (MLM) is rapidly becoming the standard method of analyzing nested data, for example, data from students within multiple schools, data on multiple clients seen by a smaller number of therapists, and even longitudinal data. Although MLM analyses are likely to increase in frequency in counseling psychology research, many readers…
Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael
Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.
Lind, Morten; Yoshikawa, Hidekazu; Jørgensen, Sten Bay
functions and structure. The paper will describe how MFM can be used to represent the goals and functions of the Japanese Monju Nuclear Power Plant. A detailed explanation will be given of the model describing the relations between levels of goal, function and structural. Furthermore, it will be explained......Multilevel Flow Modeling is a method for modeling complex processes on multiple levels of means-end and part-whole abstraction. The modeling method has been applied on a wide range of processes including power plants, chemical engineering plants and power systems. The modeling method is supported...
Lee, Woo-yeol; Cho, Sun-Joo
Cross-level invariance in a multilevel item response model can be investigated by testing whether the within-level item discriminations are equal to the between-level item discriminations. Testing the cross-level invariance assumption is important to understand constructs in multilevel data. However, in most multilevel item response model…
The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure...... operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as a basis for design of control strategies and for the allocation of control tasks to the computer and the plant operator....
Rusá, Šárka; Komárek, Arnošt; Lesaffre, Emmanuel; Bruyneel, Luk
Although increasingly complex models have been proposed in mediation literature, there is no model nor software that incorporates the multiple possible generalizations of the simple mediation model jointly. We propose a flexible moderated mediation model allowing for (1) a hierarchical structure of clustered data, (2) more and possibly correlated mediators, and (3) an ordinal outcome. The motivating data set is obtained from a European study in nursing research. Patients' willingness to recommend their treating hospital was recorded in an ordinal way. The research question is whether such recommendation directly depends on system-level features in the organization of nursing care, or whether these associations are mediated by 2 measurements of nursing care left undone and possibly moderated by nurse education. We have developed a Bayesian approach and accompanying program that takes all the above generalizations into account. Copyright © 2018 John Wiley & Sons, Ltd.
Zhang, Guangquan; Gao, Ya
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.
Díaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Mukkerikar, Amol
of a master parameter table; iii) development of a model library consisting of new and adopted process models of unit operations involved in lipid processing technologies, validation of the developed models using operating data collected from existing process plants, and application of validated models......The aim of this work is to present the development of a computer aided multilevel modeling network for the systematic design and analysis of processes employing lipid technologies. This is achieved by decomposing the problem into four levels of modeling: i) pure component property modeling...... and a lipid-database of collected experimental data from industry and generated data from validated predictive property models, as well as modeling tools for fast adoption-analysis of property prediction models; ii) modeling of phase behavior of relevant lipid mixtures using the UNIFACCI model, development...
El-Khatib, Walid Ziad; Holbøll, Joachim; Rasmussen, Tonny Wederberg
Looking at the near future, we see that offshore wind penetration into the electrical grid will continue increasing rapidly. Until very recently, the trend has been to place the offshore wind farms close to shore within the reach for transmission using HVAC cables but for larger distances HVDC...... are calculated for the converter. Time-domain simulations on a MMC HVDC test system are performed in the PSCAD/EMTDC software environment based on the new model. The results demonstrate that the modeled MMC-HVDC system with or without converter transformer is able to operate under specific fault conditions....
Full Text Available In this article we propose to study occupational careers with historical data by using multilevel growth models. Historical career data are often characterized by a lack of information on the timing of occupational changes and by different numbers of observations of occupations per individual. Growth models can handle these specificities, whereas standard methods, such as event history analyses can't. We illustrate the use of growth models by studying career success of men and women, using data from the Historical Sample of the Netherlands. The results show that the method is applicable to male careers, but causes trouble when analyzing female careers.
Hu, Junjie; Lind, Morten; You, Shi
of complementing this reasoning methodology. Domestic heating systems, as the main resource to meet the thermal requirements of end-users, have different implementations in Europe in order to achieve various degrees of controllability and heating efficiencies. As all the heating systems serve the same basic needs...... i.e. supplying and transferring thermal energy, it is off interest to use MFM to investigate similarities and differences between different implementations. In this paper, three typical domestic European heating systems, which differ from each other in the number of temperature sensors and auxiliary...... components e.g. storage tanks, are modeled using the MFM methodology. Both the goals and functions of material and energy processes and the control functions of the heating systems are represented in the MFM models. It is found that varying the physical system setup results in only little differences among...
Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P
Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.
n an article that first appeared in US magazine, Medical Construction & Design, Mark Howell, senior vice-president of Skanska USA Building, based in Seattle, describes the design and construction of a new nine-storey, 350,000 ft2 extension to the Good Samaritan Hospital in Puyallup, Washington state. He explains how the use of an Integrated Project Delivery (IPD) approach by the key players, and extensive use of building information modelling (BIM), combined to deliver a healthcare facility that he believes should meet the needs of patients, families, and the clinical care team, 'well into the future'.
This research paper presentation will feature current frameworks to addressing risk and security modeling and metrics. The paper will analyze technical level risk and security metrics of Common Criteria/ISO15408, Centre for Internet Security guidelines, NSA configuration guidelines and metrics used at this level. Information IT operational standards view on security metrics such as GMITS/ISO13335, ITIL/ITMS and architectural guidelines such as ISO7498-2 will be explained. Business process level standards such as ISO17799, COSO and CobiT will be presented with their control approach to security metrics. Top level, the maturity standards such as SSE-CMM/ISO21827, NSA Infosec Assessment and CobiT will be explored and reviewed. For each defined level of security metrics the research presentation will explore the appropriate usage of these standards. The paper will discuss standards approaches to conducting the risk and security metrics. The research findings will demonstrate the need for common baseline for both risk and security metrics. This paper will show the relation between the attribute based common baseline and corporate assets and controls for risk and security metrics. IT will be shown that such approach spans over all mentioned standards. The proposed approach 3D visual presentation and development of the Information Security Model will be analyzed and postulated. Presentation will clearly demonstrate the benefits of proposed attributes based approach and defined risk and security space for modeling and measuring.
Gola, G; Lind, Morten; Thunem, Harald P-J
As complexity and safety requirements of current and future nuclear power plants increase, innovative methods are being investigated to perform accurate and reliable system diagnoses. Detecting malfunctions, identifying their causes and possibly predicting their consequences are major challenges......-scale monitoring systems is hard to handle manually. In this paper, the use of an innovative function-oriented modeling approach, called Multilevel Flow Modeling, is proposed for performing an automatic analysis of the outcomes of the monitoring systems with the aim of identifying the root causes of the possibly...
When SOA-based business processes are to be enhanced with security properties, the model-driven business process development approach enables an easier and more reliable security definition compared to manually crafting the security realizations afterwards. In this paper, we outline an appropriate...... security model definition and transformation approach, targeting the WS-SecurityPolicy and WS-BPEL specifications, in order to enable a Web-Service-based secure business process development....
Witt, Michael; Krefting, Dagmar
Human sample data is stored in biobanks with software managing digital derived sample data. When these stand-alone components are connected and a search infrastructure is employed users become able to collect required research data from different data sources. Data protection, patient rights, data heterogeneity and access control are major challenges for such an infrastructure. This dissertation will investigate concepts for a multi-level security architecture to comply with these requirements.
Full Text Available Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.
George Leckie; Chris Charlton
Multilevel analysis is the statistical modeling of hierarchical and nonhierarchical clustered data. These data structures are common in social and medical sciences. Stata provides the xtmixed, xtmelogit, and xtmepoisson commands for fitting multilevel models, but these are only relevant for univariate continuous, binary, and count response variables, respectively. A much wider range of multilevel models can be fit using the user-written gllamm command, but gllamm can be computationally slow f...
Zhang, Yong-ku; Song, Li-ren
Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.
Adam Shostack is responsible for security development lifecycle threat modeling at Microsoft and is one of a handful of threat modeling experts in the world. Now, he is sharing his considerable expertise into this unique book. With pages of specific actionable advice, he details how to build better security into the design of systems, software, or services from the outset. You'll explore various threat modeling approaches, find out how to test your designs against threats, and learn effective ways to address threats that have been validated at Microsoft and other top companies. Systems secur
Fox, Gerardus J.A.
An item response theory (IRT) model is used as a measurement error model for the dependent variable of a multilevel model. The dependent variable is latent but can be measured indirectly by using tests or questionnaires. The advantage of using latent scores as dependent variables of a multilevel
Natesan, Prathiba; Limbers, Christine; Varni, James W.
The present study presents the formulation of graded response models in the multilevel framework (as nonlinear mixed models) and demonstrates their use in estimating item parameters and investigating the group-level effects for specific covariates using Bayesian estimation. The graded response multilevel model (GRMM) combines the formulation of…
The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation
Full Text Available This paper presents a model for an integrated security system, which can be implemented in any organization. It is based on security-specific standards and taxonomies as ISO 7498-2 and Common Criteria. The functionalities are derived from the classes proposed in the Common Criteria document. In the paper we present the process model for each functionality and also we focus on the specific components.
Full Text Available It seems plausible that a person's demographic behaviour may be influenced by that among other people in the community, for example because of an inclination to imitate. When estimating multilevel models from clustered individual data, some investigators might perhaps feel tempted to try to capture this effect by simply including on the right-hand side the average of the dependent variable, constructed by aggregation within the clusters. However, such modelling must be avoided. According to simulation experiments based on real fertility data from India, the estimated effect of this obviously endogenous variable can be very different from the true effect. Also the other community effect estimates can be strongly biased. An "imitation effect" can only be estimated under very special assumptions that in practice will be hard to defend.
Full Text Available To estimate a time series model for multiple individuals, a multilevel model may be used.In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1 models, namely Maximum Likelihood Estimation (MLE and Bayesian Markov Chain Monte Carlo.Furthermore, we examine the difference between modeling fixed and random individual parameters.To this end, we perform a simulation study with a fully crossed design, in which we vary the length of the time series (10 or 25, the number of individuals per sample (10 or 25, the mean of the autocorrelation (-0.6 to 0.6 inclusive, in steps of 0.3 and the standard deviation of the autocorrelation (0.25 or 0.40.We found that the random estimators of the population autocorrelation show less bias and higher power, compared to the fixed estimators. As expected, the random estimators profit strongly from a higher number of individuals, while this effect is small for the fixed estimators.The fixed estimators profit slightly more from a higher number of time points than the random estimators.When possible, random estimation is preferred to fixed estimation.The difference between MLE and Bayesian estimation is nearly negligible. The Bayesian estimation shows a smaller bias, but MLE shows a smaller variability (i.e., standard deviation of the parameter estimates.Finally, better results are found for a higher number of individuals and time points, and for a lower individual variability of the autocorrelation. The effect of the size of the autocorrelation differs between outcome measures.
Park, Jungkyu; Yu, Hsiu-Ting
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Bauer, Daniel J.; Sterba, Sonya K.
Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ…
Schoeneberger, Jason A.
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Full Text Available In today's world, the key to meeting the demand for improved security is to implement repeatable processes that reliably deliver measurably improved security. While many organizations have announced efforts to institutionalize a secure software development process, there is little or no industry acceptance for a common process improvement framework for secure software development. Motorola has taken the initiative to develop such a framework, and plans to share this with the Software Engineering Institute for possible inclusion into its Capability Maturity Model Integration (CMMI®. This paper will go into the details of how Motorola is addressing this issue. The model that is being developed is designed as an extension of the existing CMMI structure. The assumption is that the audience will have a basic understanding of the SEI CMM® / CMMI® process framework. The paper will not describe implementation details of a security process model or improvement framework, but will address WHAT security practices are required for a company with many organizations operating at different maturity levels. It is left to the implementing organization to answer the HOW, WHEN, WHO and WHERE aspects. The paper will discuss how the model is being implemented in the Motorola Software Group.
Full Text Available The growing popularity of wireless sensor networks increases the risk of security attacks. One of the most common and dangerous types of attack that takes place these days in any electronic society is a distributed denial of service attack. Due to the resource constraint nature of mobile sensors, DDoS attacks have become a major threat to its stability. In this paper, we established a model of a structural health monitoring network, being disturbed by one of the most common types of DDoS attacks, the flooding attack. Through a set of simulations, we explore the scope of flood-based DDoS attack problem, assessing the performance and the lifetime of the network under the attack condition. To conduct our research, we utilized the Quality of Protection Modeling Language. With the proposed approach, it was possible to examine numerous network configurations, parameters, attack options, and scenarios. The results of the carefully performed multilevel analysis allowed us to identify a new kind of DDoS attack, the delayed distributed denial of service, by the authors, referred to as DDDoS attack. Multilevel approach to DDoS attack analysis confirmed that, examining endangered environments, it is significant to take into account many characteristics at once, just to not overlook any important aspect.
Jiun-Yu Wu; Yuan-Hsuan Lee; John J. H. Lin
To construct CFA, MCFA, and maximum MCFA with LISREL v.8 and below, we provide iMCFA (integrated Multilevel Confirmatory Analysis) to examine the potential multilevel factorial structure in the complex survey data. Modeling multilevel structure for complex survey data is complicated because building a multilevel model is not an infallible statistical strategy unless the hypothesized model is close to the real data structure. Methodologists have suggested using different modeling techniques to...
Cho, Sun-Joo; Cohen, Allan S.; Bottge, Brian
A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students' response to instructional intervention as well as a methodology for…
Safro, I. M. (Mathematics and Computer Science)
researchers. We propose to develop multilevel methods to model complex networks. The key point of the proposed strategy is that it will help to preserve part of the unknown structural attributes by guaranteeing the similar behavior of the real and artificial model on different scales.
Full Text Available Traditional Rasch estimation of the item and student parameters via marginal maximum likelihood, joint maximum likelihood or conditional maximum likelihood, assume individuals in clustered settings are uncorrelated and items within a test that share a grouping structure are also uncorrelated. These assumptions are often violated, particularly in educational testing situations, in which students are grouped into classrooms and many test items share a common grouping structure, such as a content strand or a reading passage. Consequently, one possible approach is to explicitly recognize the clustered nature of the data and directly incorporate random effects to account for the various dependencies. This article demonstrates how the multilevel Rasch model can be estimated using the functions in R for mixed-effects models with crossed or partially crossed random effects. We demonstrate how to model the following hierarchical data structures: a individuals clustered in similar settings (e.g., classrooms, schools, b items nested within a particular group (such as a content strand or a reading passage, and c how to estimate a teacher × content strand interaction.
Lappenschaar, M.; Hommersom, A.; Lucas, P.J.; Lagro, J.; Visscher, S.; Korevaar, J.C.; Schellevis, F.G.
Objectives Although the course of single diseases can be studied using traditional epidemiologic techniques, these methods cannot capture the complex joint evolutionary course of multiple disorders. In this study, multilevel temporal Bayesian networks were adopted to study the course of
Lenzini, Gabriele; Gnesi, S.; Latella, D.
This paper presents SpyDer, a model checking environment for security protocols. In SpyDer a protocol is described as a term of a process algebra (called spy-calculus) consisting in a parallel composition of a finite number of communicating and finite-behaviored processes. Each process represents an
Zhang, Qian; Wang, Lijuan; Bergeman, C S
In the current study, extending from the cross-lagged panel models (CLPMs) in Cole and Maxwell (2003), we proposed the multilevel autoregressive mediation models (MAMMs) by allowing the coefficients to differ across individuals. In addition, Level-2 covariates can be included to explain the interindividual differences of mediation effects. Given the complexity of the proposed models, Bayesian estimation was used. Both a CLPM and an unconditional MAMM were fitted to daily diary data. The 2 models yielded different statistical conclusions regarding the average mediation effect. A simulation study was conducted to examine the estimation accuracy of Bayesian estimation for MAMMs and consequences of model mis-specifications. Factors considered included the sample size (N), number of time points (T), fixed indirect and direct effect sizes, and Level-2 variances and covariances. Results indicated that the fixed effect estimates for the indirect effect components (a and b) and the fixed effects of Level-2 covariates were accurate when N ≥ 50 and T ≥ 5. For estimating Level-2 variances and covariances, they were accurate provided a sufficiently large N and T (e.g., N ≥ 500 and T ≥ 50). Estimates of the average mediation effect were generally accurate when N ≥ 100 and T ≥ 10, or N ≥ 50 and T ≥ 20. Furthermore, we found that when Level-2 variances were zero, MAMMs yielded valid inferences about the fixed effects, whereas when random effects existed, CLPMs had low coverage rates for fixed effects. DIC can be used for model selection. Limitations and future directions were discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
and uncertain environments. It is a hierarchy of self-regulating holons ability to model and control very complex systems , high resilience to internal...14th ICCRTS: C2 and Agility Multi-level operational C2 holonic reference architecture modeling for MHQ with MOC C2 Approaches and...SUBTITLE Multi-level operational C2 holonic reference architecture modeling for MHQ with MOC 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM
Nielsen, Emil Krabbe; Bram, Mads Valentin; Frutiger, Jerome
Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions, and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Model...... plant experiments are used for validation of simple Multilevel Flow Modelling models of a hydrocyclone unit for oil removal from produced water....
Nielsen, Emil Krabbe; Bram, Mads Valentin; Frutiger, Jerome
Decision support systems are a key focus in research on developing control rooms to aidoperators in making reliable decisions, and reducing incidents caused by human errors. For thispurpose, models of complex systems can be developed to diagnose causes or consequences forspecific alarms. Models a...... experiments are used for validation of two simpleMultilevel Flow Modeling models of a deoiling hydrocyclone, used for water and oil separation....
Carvalho Humberto M.
Full Text Available The aim of this paper was to outline a multilevel modeling approach to fit individual angle-specific torque curves describing concentric knee extension and flexion isokinetic muscular actions in Master athletes. The potential of the analytical approach to examine between individual differences across the angle-specific torque curves was illustrated including between-individuals variation due to gender differences at a higher level. Torques in concentric muscular actions of knee extension and knee extension at 60°·s-1 were considered within a range of motion between 5°and 85° (only torques “truly” isokinetic. Multilevel time series models with autoregressive covariance structures with standard multilevel models were superior fits compared with standard multilevel models for repeated measures to fit anglespecific torque curves. Third and fourth order polynomial models were the best fits to describe angle-specific torque curves of isokinetic knee flexion and extension concentric actions, respectively. The fixed exponents allow interpretations for initial acceleration, the angle at peak torque and the decrement of torque after peak torque. Also, the multilevel models were flexible to illustrate the influence of gender differences on the shape of torque throughout the range of motion and in the shape of the curves. The presented multilevel regression models may afford a general framework to examine angle-specific moment curves by isokinetic dynamometry, and add to the understanding mechanisms of strength development, particularly the force-length relationship, both related to performance and injury prevention.
Enders, Craig K; Mistler, Stephen A; Keller, Brian T
Although missing data methods have advanced in recent years, methodologists have devoted less attention to multilevel data structures where observations at level-1 are nested within higher-order organizational units at level-2 (e.g., individuals within neighborhoods; repeated measures nested within individuals; students nested within classrooms). Joint modeling and chained equations imputation are the principal imputation frameworks for single-level data, and both have multilevel counterparts. These approaches differ algorithmically and in their functionality; both are appropriate for simple random intercept analyses with normally distributed data, but they differ beyond that. The purpose of this paper is to describe multilevel imputation strategies and evaluate their performance in a variety of common analysis models. Using multiple imputation theory and computer simulations, we derive 4 major conclusions: (a) joint modeling and chained equations imputation are appropriate for random intercept analyses; (b) the joint model is superior for analyses that posit different within- and between-cluster associations (e.g., a multilevel regression model that includes a level-1 predictor and its cluster means, a multilevel structural equation model with different path values at level-1 and level-2); (c) chained equations imputation provides a dramatic improvement over joint modeling in random slope analyses; and (d) a latent variable formulation for categorical variables is quite effective. We use a real data analysis to demonstrate multilevel imputation, and we suggest a number of avenues for future research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Carvalho, Humberto M
The aim of this paper was to outline a multilevel modeling approach to fit individual angle-specific torque curves describing concentric knee extension and flexion isokinetic muscular actions in Master athletes. The potential of the analytical approach to examine between individual differences across the angle-specific torque curves was illustrated including between-individuals variation due to gender differences at a higher level. Torques in concentric muscular actions of knee extension and knee extension at 60º·s−1 were considered within a range of motion between 5º and 85º (only torques “truly” isokinetic). Multilevel time series models with autoregressive covariance structures with standard multilevel models were superior fits compared with standard multilevel models for repeated measures to fit angle-specific torque curves. Third and fourth order polynomial models were the best fits to describe angle-specific torque curves of isokinetic knee flexion and extension concentric actions, respectively. The fixed exponents allow interpretations for initial acceleration, the angle at peak torque and the decrement of torque after peak torque. Also, the multilevel models were flexible to illustrate the influence of gender differences on the shape of torque throughout the range of motion and in the shape of the curves. The presented multilevel regression models may afford a general framework to examine angle-specific moment curves by isokinetic dynamometry, and add to the understanding mechanisms of strength development, particularly the force-length relationship, both related to performance and injury prevention. PMID:26839603
Rolland, Joran; Simonnet, Eric
Adaptive multilevel splitting algorithms have been introduced rather recently for estimating tail distributions in a fast and efficient way. In particular, they can be used for computing the so-called reactive trajectories corresponding to direct transitions from one metastable state to another. The algorithm is based on successive selection–mutation steps performed on the system in a controlled way. It has two intrinsic parameters, the number of particles/trajectories and the reaction coordinate used for discriminating good or bad trajectories. We investigate first the convergence in law of the algorithm as a function of the timestep for several simple stochastic models. Second, we consider the average duration of reactive trajectories for which no theoretical predictions exist. The most important aspect of this work concerns some systems with two degrees of freedom. They are studied in detail as a function of the reaction coordinate in the asymptotic regime where the number of trajectories goes to infinity. We show that during phase transitions, the statistics of the algorithm deviate significatively from known theoretical results when using non-optimal reaction coordinates. In this case, the variance of the algorithm is peaking at the transition and the convergence of the algorithm can be much slower than the usual expected central limit behaviour. The duration of trajectories is affected as well. Moreover, reactive trajectories do not correspond to the most probable ones. Such behaviour disappears when using the optimal reaction coordinate called committor as predicted by the theory. We finally investigate a three-state Markov chain which reproduces this phenomenon and show logarithmic convergence of the trajectory durations
Full Text Available A model-theoretic approach can establish security theorems for cryptographic protocols. Formulas expressing authentication and non-disclosure properties of protocols have a special form. They are quantified implications for all xs . (phi implies for some ys . psi. Models (interpretations for these formulas are *skeletons*, partially ordered structures consisting of a number of local protocol behaviors. *Realized* skeletons contain enough local sessions to explain all the behavior, when combined with some possible adversary behaviors. We show two results. (1 If phi is the antecedent of a security goal, then there is a skeleton A_phi such that, for every skeleton B, phi is satisfied in B iff there is a homomorphism from A_phi to B. (2 A protocol enforces for all xs . (phi implies for some ys . psi iff every realized homomorphic image of A_phi satisfies psi. Hence, to verify a security goal, one can use the Cryptographic Protocol Shapes Analyzer CPSA (TACAS, 2007 to identify minimal realized skeletons, or "shapes," that are homomorphic images of A_phi. If psi holds in each of these shapes, then the goal holds.
This article critiques traditional single-level statistical approaches (e.g., multiple regression analysis) to examining relationships between language test scores and variables in the assessment setting. It highlights the conceptual, methodological, and statistical problems associated with these techniques in dealing with multilevel or nested…
Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.
Guillen, Edward Paul; Quintero, Rulfo
Information security has a wide variety of solutions including security policies, network architectures and technological applications, they are usually designed and implemented by security architects, but in its own complexity this solutions are difficult to understand by company managers and they are who finally fund the security project. The main goal of the functional security model is to achieve a solid security platform reliable and understandable in the whole company without leaving of side the rigor of the recommendations and the laws compliance in a single frame. This paper shows a general scheme of the model with the use of important standards and tries to give an integrated solution.
Full Text Available Morphometric data usually have a hierarchical structure (i.e., cells are nested within patients, which should be taken into consideration in the analysis. In the recent years, special methods of handling hierarchical data, called multilevel models (MM, as well as corresponding software have received considerable development. However, there has been no application of these methods to morphometric data yet. In this paper we report our first experience of analyzing karyometric data by means of MLwiN – a dedicated program for multilevel modeling. Our data were obtained from 34 follicular adenomas and 44 follicular carcinomas of the thyroid. We show examples of fitting and interpreting MM of different complexity, and draw a number of interesting conclusions about the differences in nuclear morphology between follicular thyroid adenomas and carcinomas. We also demonstrate substantial advantages of multilevel models over conventional, single‐level statistics, which have been adopted previously to analyze karyometric data. In addition, some theoretical issues related to MM as well as major statistical software for MM are briefly reviewed.
Beretvas, S. Natasha; Walker, Cindy M.
This study extends the multilevel measurement model to handle testlet-based dependencies. A flexible two-level testlet response model (the MMMT-2 model) for dichotomous items is introduced that permits assessment of differential testlet functioning (DTLF). A distinction is made between this study's conceptualization of DTLF and that of…
Schuurman, N. K.; Grasman, R. P P P; Hamaker, E. L.
Multilevel autoregressive models are especially suited for modeling between-person differences in within-person processes. Fitting these models with Bayesian techniques requires the specification of prior distributions for all parameters. Often it is desirable to specify prior distributions that
Cheung, Mike W.-L.; Au, Kevin
Multilevel structural equation modeling (MSEM) has been proposed as an extension to structural equation modeling for analyzing data with nested structure. We have begun to see a few applications in cross-cultural research in which MSEM fits well as the statistical model. However, given that cross-cultural studies can only afford collecting data…
Jiao, Hong; Zhang, Yuan
Applications of standard item response theory models assume local independence of items and persons. This paper presents polytomous multilevel testlet models for dual dependence due to item and person clustering in testlet-based assessments with clustered samples. Simulation and survey data were analysed with a multilevel partial credit testlet model. This model was compared with three alternative models - a testlet partial credit model (PCM), multilevel PCM, and PCM - in terms of model parameter estimation. The results indicated that the deviance information criterion was the fit index that always correctly identified the true multilevel testlet model based on the quantified evidence in model selection, while the Akaike and Bayesian information criteria could not identify the true model. In general, the estimation model and the magnitude of item and person clustering impacted the estimation accuracy of ability parameters, while only the estimation model and the magnitude of item clustering affected the item parameter estimation accuracy. Furthermore, ignoring item clustering effects produced higher total errors in item parameter estimates but did not have much impact on the accuracy of ability parameter estimates, while ignoring person clustering effects yielded higher total errors in ability parameter estimates but did not have much effect on the accuracy of item parameter estimates. When both clustering effects were ignored in the PCM, item and ability parameter estimation accuracy was reduced. © 2014 The British Psychological Society.
Fox, Gerardus J.A.
An item response theory (IRT) model is used as a measurement error model for the dependent variable of a multilevel model where tests or questionnaires consisting of separate items are used to perform a measurement error analysis. The advantage of using latent scores as dependent variables of a
Fulmer, Gavin W.; Lee, Iris C. H.; Tan, Kelvin H. K.
We present a multi-level model of contextual factors that may influence teachers' assessment practices, and use this model in a selected review of existing literature on teachers' assessment knowledge, views and conceptions with respect to these contextual factors. Adapting Kozma's model, we distinguish three levels of influence on teachers'…
Full Text Available The main purpose of the paper is the proposal of multi-level simulation, suited for the evaluation of the lifetime of critical electronic devices (electrolytic capacitors. The aim of this issue is to imagine about the expected operation of complex and expensive power electronic systems, when the failure of the most critical component occurs. For that reason, various operational conditions and various physical influences must be considered (e.g. mechanical, humidity, electrical, heat stress, where nonlinearities are naturally introduced. Verification of the proposal is given, whereby the life-time estimation of an electrolytic capacitor operated in a DC-DC converter during various operational conditions is shown. At this point electrical and heat stress is considered for lifetime influence. First, the current state in the field of mathematical modeling of the lifetime for electrolytic capacitors, considering main phenomena is introduced. Next, individual sub-models for multi-level simulation purposes are developed, including a thermal simulation model and electrical simulation model. Several complexities of individual models are mutually compared in order to evaluate their accuracy and suitability for further use. Proper simulation tools have been mutually linked and data transfer was secured, in order to have the possibility of investigation of a lifetime depend on the changes of various variables.
Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey
The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey.
Konishi, Chiaki; Miyazaki, Yasuo; Hymel, Shelley; Waterhouse, Terry
This study examined how student reports of bullying were related to different dimensions of school climate, at both the school and the student levels, using a contextual effects model in a two-level multilevel modeling framework. Participants included 48,874 secondary students (grades 8 to 12; 24,244 girls) from 76 schools in Western Canada.…
Beretvas, S. Natasha; Cawthon, Stephanie W.; Lockhart, L. Leland; Kaye, Alyssa D.
This pedagogical article is intended to explain the similarities and differences between the parameterizations of two multilevel measurement model (MMM) frameworks. The conventional two-level MMM that includes item indicators and models item scores (Level 1) clustered within examinees (Level 2) and the two-level cross-classified MMM (in which item…
Lu, Xingjiang; Yao, Chen; Zheng, Jianmin
This paper focuses on the training of undergraduate students' innovation ability. On top of the theoretical framework of the Quality Function Deployment (QFD), we propose a teaching quality management model. Based on this model, we establish a multilevel decomposition indicator system, which integrates innovation ability characterized by four…
de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.
We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…
Liu, Feng; Ritzhaupt, Albert D.; Dawson, Kara; Barron, Ann E.
The purpose of this research was to design and test a model of classroom technology integration in the context of K-12 schools. The proposed multilevel path analysis model includes teacher, contextual, and school related variables on a teacher's use of technology and confidence and comfort using technology as mediators of classroom technology…
Michelle M. Jackson; Monica G. Turner; Scott M. Pearson; Anthony R. Ives
Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-...
Duvvuri, Sri Devi; Gruca, Thomas S.
Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…
Han, Xue; Bindner, Henrik W.; You, Shi
The paper summarises several modelling applications of distributed energy resources (DERs) for various purposes, and describes the related operational issues regarding the complexity of the future distribution grid. Furthermore, a multi-level functioning interface framework is proposed for DER mo....... The information mapping for photovoltaic panel (PV) modelling is also provided as an example....
Sulis, Isabella; Toland, Michael D.
Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…
Choi, In-Hee; Wilson, Mark
Multilevel data often cannot be represented by the strict form of hierarchy typically assumed in multilevel modeling. A common example is the case in which subjects change their group membership in longitudinal studies (e.g., students transfer schools; employees transition between different departments). In this study, cross-classified and multiple membership models for multilevel and longitudinal item response data (CCMM-MLIRD) are developed to incorporate such mobility, focusing on students' school change in large-scale longitudinal studies. Furthermore, we investigate the effect of incorrectly modeling school membership in the analysis of multilevel and longitudinal item response data. Two types of school mobility are described, and corresponding models are specified. Results of the simulation studies suggested that appropriate modeling of the two types of school mobility using the CCMM-MLIRD yielded good recovery of the parameters and improvement over models that did not incorporate mobility properly. In addition, the consequences of incorrectly modeling the school effects on the variance estimates of the random effects and the standard errors of the fixed effects depended upon mobility patterns and model specifications. Two sets of large-scale longitudinal data are analyzed to illustrate applications of the CCMM-MLIRD for each type of school mobility.
Battauz, Michela; Bellio, Ruggero; Gori, Enrico
This article proposes a multilevel model for the assessment of school effectiveness where the intake achievement is a predictor and the response variable is the achievement in the subsequent periods. The achievement is a latent variable that can be estimated on the basis of an item response theory model and hence subject to measurement error.…
Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi
Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.
Smith, John A.; Biswas, Gautam
This paper discusses a knowledge-based system for diagnostic problem solving based on a multi-level representational structure and associated reasoning methods. The motivation behind this approach is to combine shallow evidential models for fault diagnosis with deep qualitative models that derive behavior from structural descriptions. In addition, the reasoning scheme utilizes historical data based on past experience for diagnosis. Using this integrated framework, we concentrate on the following issues: (i) Multi-level knowledge based system design, and (ii) Reasoning systems that exploit the multi-level representational structure for diagnostic problem solving. This system is applied to the diagnosis of a complex electro-mechanical system, specifically, the upper cargo door of the DC-10 aircraft in use at Federal Express Corporation.
The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.
Rights, Jason D; Sterba, Sonya K
Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.
Dmitry Sergeevich Chernyavskiy
Full Text Available Policy management for network security systems (NSSs is one of the most topical issues of network security management. Incorrect configurations of NSSs lead to system outages and appearance of vulnerabilities. Moreover, policy management process is a time-consuming task, which includes significant amount of manual work. These factors reduce efficiency of NSSs’ utilization. The paper discusses peculiarities of policy management process and existing approaches to policy modeling, presents a model aimed to formalize policies for NSSs independently on NSSs’ platforms and select the most effective NSSs for implementation of the policies.
I. V. Khomyackov
Full Text Available A stochastic model of critically important object security system element has been developed. The model includes mathematical description of the security system element properties and external influences. The state evolution of the security system element is described by the semi-Markov process with finite states number, the semi-Markov matrix and the initial semi-Markov process states probabilities distribution. External influences are set with the intensity of the Poisson thread.
Li, Wei; Cen, Li-Xiang
We investigate the solvability of multi-level extensions of the Allen-Eberly model and the population transfer yielded by the corresponding dynamical evolution. We demonstrate that, under a matching condition of the frequency, the driven two-level system and its multi-level extensions possess a stationary-state solution in a canonical representation associated with a unitary transformation. As a consequence, we show that the resulting protocol is able to realize complete population transfer in a nonadiabatic manner. Moreover, we explore the imperfect pulsing process with truncation and display that the nonadiabatic effect in the evolution can lead to suppression to the cutoff error of the protocol.
Full Text Available This paper presents a three-cell converter DC / AC. Multilevel topologies are attracting attention in the industry, obtained as a ripple on the state variables much smaller, and reduces stress on the switching devices. The topology used in this work is known in the technical literature as floating capacitor multilevel inverter, which imposes the challenge of balancing the voltage across each cell switching using floating capacitors, besides obtaining a sinusoidal signal regulated. The paper presents the averaged model of the inverter, and results obtained through simulation.
Park, Guihyun; DeShon, Richard P.
The consideration of minority opinions when making team decisions is an important factor that contributes to team effectiveness. A multilevel model of minority opinion influence in decision-making teams is developed to address the conditions that relate to adequate consideration of minority opinions. Using a sample of 57 teams working on a…
Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…
Multilevel models (MLMs) have proven themselves to be very useful in social science research, as data from a variety of sources is sampled such that individuals at level-1 are nested within clusters such as schools, hospitals, counseling centers, and business entities at level-2. MLMs using restricted maximum likelihood estimation (REML) provide…
Li, Ci-Rong; Lin, Chen-Ju; Tien, Yun-Hsiang; Chen, Chien-Ming
We developed a multi-level model to test how team cultural diversity may relate to team- and individual-level creativity, integrating team diversity research and information-exchange perspective. We proposed that the team climate for inclusion would moderate both the relationship between cultural diversity and team information sharing and between…
Bauer, Daniel J.; Preacher, Kristopher J.; Gil, Karen M.
The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects.…
Jones, Leah; Totsika, Vasiliki; Hastings, Richard P.; Petalas, Michael A.
Parenting a child with autism may differentially affect mothers and fathers. Existing studies of mother-father differences often ignore the interdependence of data within families. We investigated gender differences within-families using multilevel linear modeling. Mothers and fathers of children with autism (161 couples) reported on their own…
Wang, Chee Keng John; Pyun, Do Young; Liu, Woon Chia; Lim, Boon San Coral; Li, Fuzhong
Using a multilevel latent growth curve modeling (LGCM) approach, this study examined longitudinal change in levels of physical fitness performance over time (i.e. four years) in young adolescents aged from 12-13 years. The sample consisted of 6622 students from 138 secondary schools in Singapore. Initial analyses found between-school variation on…
Bennink, M.; Croon, M.A.; Kroon, B.; Vermunt, J.K.
An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the
Kanaparti, Venkataramana; Naveen K., R.; Rajani, S.; Padmvathamma, M.; Anitha, C.
Cloud computing is a new approach emerged to meet ever-increasing demand for computing resources and to reduce operational costs and Capital Expenditure for IT services. As this new way of computation allows data and applications to be stored away from own corporate server, it brings more issues in security such as virtualization security, distributed computing, application security, identity management, access control and authentication. Even though Virtualization forms the basis for cloud computing it poses many threats in securing cloud. As most of Security threats lies at Virtualization layer in cloud we proposed this new Security Model for Virtual Machine in Cloud (SMVC) in which every process is authenticated by Trusted-Agent (TA) in Hypervisor as well as in VM. Our proposed model is designed to with-stand attacks by unauthorized process that pose threat to applications related to Data Mining, OLAP systems, Image processing which requires huge resources in cloud deployed on one or more VM's.
Sæther, Sandra; Kjærgaard, Thomas; Koch, Henrik; Høyvik, Ida-Marie
We introduce a density-based multilevel Hartree-Fock (HF) method where the electronic density is optimized in a given region of the molecule (the active region). Active molecular orbitals (MOs) are generated by a decomposition of a starting guess atomic orbital (AO) density, whereas the inactive MOs (which constitute the remainder of the density) are never generated or referenced. The MO formulation allows for a significant dimension reduction by transforming from the AO basis to the active MO basis. All interactions between the inactive and active regions of the molecule are retained, and an exponential parametrization of orbital rotations ensures that the active and inactive density matrices separately, and in sum, satisfy the symmetry, trace, and idempotency requirements. Thus, the orbital spaces stay orthogonal, and furthermore, the total density matrix represents a single Slater determinant. In each iteration, the (level-shifted) Newton equations in the active MO basis are solved to obtain the orbital transformation matrix. The approach is equivalent to variationally optimizing only a subset of the MOs of the total system. In this orbital space partitioning, no bonds are broken and no a priori orbital assignments are carried out. In the limit of including all orbitals in the active space, we obtain an MO density-based formulation of full HF.
Control Policies.” IEEE International Conference on System of Systems Engineering 2009, n.p.  C. R. McDaniel, and M. L . Tardy, Role-Based...read O (Object) if and only if lo ls ( l represents the security clearance) and S has discretionary read access to O . The *-Property (Star...Fun 1546 uri=“dc:author”> 1547 <Ind>Randy Arvay</Ind> 1548 </Fun> 1549 </Expr> 1550
Fragoso, Tiago M; de Andrade, Mariza; Pereira, Alexandre C; Rosa, Guilherme J M; Soler, Júlia M P
The goal of this paper is to present an implementation of stochastic search variable selection (SSVS) to multilevel model from item response theory (IRT). As experimental settings get more complex and models are required to integrate multiple (and sometimes massive) sources of information, a model that can jointly summarize and select the most relevant characteristics can provide better interpretation and a deeper insight into the problem. A multilevel IRT model recently proposed in the literature for modeling multifactorial diseases is extended to perform variable selection in the presence of thousands of covariates using SSVS. We derive conditional distributions required for such a task as well as an acceptance-rejection step that allows for the SSVS in high dimensional settings using a Markov Chain Monte Carlo algorithm. We validate the variable selection procedure through simulation studies, and illustrate its application on a study with genetic markers associated with the metabolic syndrome. © 2016 WILEY PERIODICALS, INC.
Groothuis-Oudshoorn, Catharina Gerarda Maria; Miedema, Henk M.E.
A method for modeling the relationship of polychotomous health ratings with predictors such as area characteristics, the distance to a source of environmental contamination, or exposure to environmental pollutants is presented. The model combines elements of grouped regression and multilevel
Anitha, R; Lekshmi, R; Kumar, M; Bonato, Anthony; Graña, Manuel
This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19–21, 2013. The materials in the book include theory and applications for design, analysis, and modeling of computational intelligence and security. The book will be useful material for students, researchers, professionals, and academicians. It will help in understanding current research trends and findings and future scope of research in computational intelligence, cyber security, and computational models.
Wan, Chi Pui; Leung, W Keung; Wong, May C M; Wong, Ruby M S; Wan, Peng; Lo, Edward C M; Corbet, Esmonde F
To investigate the factors predicting non-surgical periodontal treatment responses using multilevel multiple regression. Forty men (mean 45.6 years) were recruited; 20 were smokers. A 12-month reduction in probing pocket depth (PPD) and gain in probing attachment level (PAL) of 5814 sites were analysed, with 594 being initially diseased sites (initial PPD> or =5 mm). Variance Component models showed that site-level variations contributed about 70-90% of the total variance. About a 10% reduction of the total variations of PPD reduction in initially diseased sites was achieved with the inclusion of the 10 predictors in the multilevel multiple regression. Multilevel multiple regression showed that three predictors, subject level: non-smokers; tooth-level: anterior teeth; and site level: sites without plaque at baseline, were significantly associated with a greater reduction in PPD in initially diseased sites over the 12-month study period (pMultilevel analysis was applied on periodontal treatment response data. Smokers showed less favourable PPD reduction at deep sites after non-surgical periodontal therapy.
Nagel-Alne, G E; Krontveit, R; Bohlin, J; Valle, P S; Skjerve, E; Sølverød, L S
In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield. Copyright © 2014
Mustaffa, Azizul Azri; Díaz Tovar, Carlos Axel; Hukkerikar, Amol
and a lipid-database of collected experimental data from industry and generated data from validated predictive property models, as well as modeling tools for fast adoption-analysis of property prediction models; ii) modeling of phase behavior of relevant lipid mixtures using the UNIFAC-CI model, development...
Full Text Available For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML method is better than Penalized Quasilikelihood (PQL method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method.
Yang, Yongli; Fu, Pengyu; Xie, Jing; Zhang, Weidong; Zhang, Meixi; Wang, Chongjian; Ping, Zhiguang; Hu, Dongsheng
To explore the application of multivariate response model with multilevel in the influencing factors of blood pressure. Two response model with three-level was fitted under MLwin 2.02 software. The correlation coefficient between systolic blood pressure (SBP) and diastolic blood pressure (DBP) was 0.949 at region level, and 0.701 at individual level. SBP and DBP level increased with age, while the regression coefficient of age on SBP was significantly higher than on DBP, beta was 0.720 (SBP) and 0.118 (DBP) individually (chi2 = 4284.56, P response model with multilevel can be used to analyze the hierarchy structure data, and it is also a good tool to analyze the influencing factors of blood pressure.
Ali, Sabz; Ali, Amjad; Khan, Sajjad Ahmad; Hussain, Sundas
For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML) method is better than Penalized Quasilikelihood (PQL) method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method.
Chung, Hyewon; Beretvas, S Natasha
This study compared the use of the conventional multilevel model (MM) with that of the multiple membership multilevel model (MMMM) for handling multiple membership data structures. Multiple membership data structures are commonly encountered in longitudinal educational data sets in which, for example, mobile students are members of more than one higher-level unit (e.g., school). While the conventional MM requires the user either to delete mobile students' data or to ignore prior schools attended, MMMM permits inclusion of mobile students' data and models the effect of all schools attended on student outcomes. The simulation study identified underestimation of the school-level predictor coefficient, as well as underestimation of the level-two variance component with corresponding overestimation of the level-one variance when multiple membership data structures were ignored. Results are discussed along with limitations and ideas for future MMMM methodological research as well as implications for applied researchers. ©2011 The British Psychological Society.
Rom-Jensen, Byron Zachary
of Scandinavian achievements were variable in their ideological outlook and sometimes deliberately challenged the existence and goals of New Deal policies. Moreover, this essay explores the usage of Scandinavia in New Deal social legislation by examining the policymaking rhetoric of the Social Security Act...... and its 1939 amendments. The surprising plasticity of the Scandinavian image amongst policymakers ultimately reveals the fluid nature of both New Deal-era politics and the Scandinavian images it appropriated....
the premier Cryptography conferences (CRYPTO, EuroCrypt, TCC ); 5 of these papers were selected for special issues on best papers. 15. SUBJECT TERMS...prestigious Cryptography conferences (CRYPTO, EuroCrypt, TCC ); 5 of these papers were selected for special issues on best papers. 2 Concurrent Security...sequence of works appearing in STOC 2013, FOCS 2013 (2 on this topic), and TCC 2014, we resolved some of central outstanding open questions in this
Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael
An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.
Full Text Available This paper develops a methodology for extending multilevel modelling to incorporate spatial interaction effects. The motivation is that classic multilevel models are not specifically spatial. Lower level units may be nested into higher level ones based on a geographical hierarchy (or a membership structure--for example, census zones into regions but the actual locations of the units and the distances between them are not directly considered: what matters is the groupings but not how close together any two units are within those groupings. As a consequence, spatial interaction effects are neither modelled nor measured, confounding group effects (understood as some sort of contextual effect that acts 'top down' upon members of a group with proximity effects (some sort of joint dependency that emerges between neighbours. To deal with this, we incorporate spatial simultaneous autoregressive processes into both the outcome variable and the higher level residuals. To assess the performance of the proposed method and the classic multilevel model, a series of Monte Carlo simulations are conducted. The results show that the proposed method performs well in retrieving the true model parameters whereas the classic multilevel model provides biased and inefficient parameter estimation in the presence of spatial interactions. An important implication of the study is to be cautious of an apparent neighbourhood effect in terms of both its magnitude and statistical significance if spatial interaction effects at a lower level are suspected. Applying the new approach to a two-level land price data set for Beijing, China, we find significant spatial interactions at both the land parcel and district levels.
Geiser, Christian; Bishop, Jacob; Lockhart, Ginger; Shiffman, Saul; Grenard, Jerry L.
Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear modeling) frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demons...
Susana Fernández-Pérez de la Lastra
Full Text Available Purpose: This paper proposes an alternative theoretical model to describe, from a multilevel perspective, the way in which ambidexterity is built across different organizational levels, through specific combinations of the facets of intellectual capital—human, social and organizational capital. Design/methodology/approach: In this study, main arguments from intellectual capital, strategic human resource management (SHRM and multilevel literature are integrated. The intellectual capital literature provides our model with the input (human capital, mechanisms (social capital and the infrastructure (organizational capital required to create ambidextrous capabilities; the multilevel perspective reveals the context in which ambidexterity is reached, and the strategic human resource management literature provides the model with the specific mechanisms (policies and practices and conditions required by ambidexterity (HRM flexibility and horizontal fit. Findings: Although the literature widely recognizes ambidexterity as a potential source of sustainable competitive advantage, the processes by which organizations complement exploration and exploitation activities still remain unclear. This study sheds some light on the analysis of these complex dynamics, explaining how ambidextrous capabilities can arise from different alternative combinations of human, social and organizational capital. Originality/value: The paper expands the extant literature in the field, describing different paths to achieving organizational ambidexterity. The configurational approach adopted adds value to the proposed model, as it helps to explaining alternative synergistic mixes of ambidextrous intellectual capital at different organizational levels.
Javdani, Shabnam; Allen, Nicole E; Todd, Nathan R; Anderson, Carolyn J
Facilitating systems change in the response to domestic violence has been touted as a central goal in the effort to hold systems accountable and create a coordinated response for survivors. However, examination of systems change and whether particular social change efforts (e.g., coordinating councils) contribute to such change is a notoriously difficult research endeavor due in large part to methodological barriers, including those that stem from nonexperimental designs and complex data that are characterized as nested and measured in proportions. This article describes important methodological challenges and proposes innovative techniques to address these challenges. Specifically, multilevel modeling is applied to examine two key systems markers, including protection order and domestic violence program referral rates over time in one state. For each marker, the methodological approach is highlighted and innovations in employing multilevel modeling are discussed. © The Author(s) 2011.
Full Text Available Video surveillance system senses and trails out all the threatening issues in the real time environment. It prevents from security threats with the help of visual devices which gather the information related to videos like CCTV’S and IP (Internet Protocol cameras. Video surveillance system has become a key for addressing problems in the public security. They are mostly deployed on the IP based network. So, all the possible security threats exist in the IP based application might also be the threats available for the reliable application which is available for video surveillance. In result, it may increase cybercrime, illegal video access, mishandling videos and so on. Hence, in this paper an intelligent model is used to propose security for video surveillance system which ensures safety and it provides secured access on video.
Zhang, Xinxin; Lind, Morten; Ravn, Ole
For complex engineering systems, there is an increasing demand for safety and reliability. Decision support system (DSS) is designed to offer su-pervision and analysis about operational situations. A proper model representa-tion is required for DSS to understand the process knowledge. Multilevel ...... techniques of MFM reasoning and less mature yet relevant MFM concepts are considered. It also offers an architecture design of task organization for MFM software tools by using the concept of agent and technology of multiagent software system....
Min, Ari; Park, Chang Gi; Scott, Linda D
Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org, a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states. © The Author(s) 2016.
Full Text Available Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.
In addition to random effects, various time series correlation structures were evaluated to account for residual autocorrelation, and the AR(1) and ARMA(1,1) structures were selected for the branch diameter and length growth models, respectively. Model validation results using an independent data set confirmed that ...
The question of how to analyze unbalanced hierarchical data generated from structural equation models has been a common problem for researchers and analysts. Among difficulties plaguing statistical modeling are estimation bias due to measurement error and the estimation of the effects of the individual's hierarchical social milieu. This paper…
Fox, Gerardus J.A.
Variance component models are generally accepted for the analysis of hierarchical structured data. A shortcoming is that outcome variables are still treated as measured without an error. Unreliable variables produce biases in the estimates of the other model parameters. The variability of the
Full Text Available In this Paper the problem of removing Power dissipation from single phase Induction Motor with DC sources is considered by the speed control of Induction Motor with highly advanced 9-Level multi-level Inverter which having approximate zero Harmonics. As the demand of power is increasing day by day. So that we must introduced very advanced Electrical Instruments which having high efficiency and less dissipation of power. The requirement of very advanced Inverter is necessary. Here we are designing a Multi-level Inverter up to the 9-level using IGBT Insulated-gate bipolar transistor by Mat lab which having negligible total harmonic distortion THD thats why it will control the speed of single phase Induction motor which is presently widely used in our daily needs. Also several informative Simulation results verify the authority and truthiness of the proposed Model.
O’Connell, Heather A.
I contribute to understandings of how context is related to individual outcomes by assessing the added value of combining multilevel and spatial modeling techniques. This methodological approach leads to substantive contributions to the smoking literature, including improved clarity on the central contextual factors and the examination of one manifestation of the social acceptability hypothesis. For this analysis I use restricted-use natality data from the Vital Statistics, and county-level data from the 2005–9 ACS. Critically, the results suggest that spatial considerations are still relevant in a multilevel framework. In addition, I argue that spatial processes help explain the relationships linking racial/ethnic minority concentration to lower overall odds of smoking. PMID:26188587
O'Connell, Heather A
I contribute to understandings of how context is related to individual outcomes by assessing the added value of combining multilevel and spatial modeling techniques. This methodological approach leads to substantive contributions to the smoking literature, including improved clarity on the central contextual factors and the examination of one manifestation of the social acceptability hypothesis. For this analysis I use restricted-use natality data from the Vital Statistics, and county-level data from the 2005-9 ACS. Critically, the results suggest that spatial considerations are still relevant in a multilevel framework. In addition, I argue that spatial processes help explain the relationships linking racial/ethnic minority concentration to lower overall odds of smoking. Copyright © 2015 Elsevier Ltd. All rights reserved.
Yoshimura, Seiichi; Takano, Kenichi; Sasou, Kunihide
It is necessary to analyze an operator's thinking process and a operator team's intension forming process for preventing human errors in a highly advanced huge system like a nuclear power plant. Central Research Institute of Electric Power Industry is promoting a research project to establish human error prevention countermeasures by modeling the thinking and intension forming process. The important is the future prediction and the cause identification when abnormal situations occur in a nuclear power plant. The concept of Multilevel Flow Modeling (MFM) seems to be effective as an operator's mental model which performs the future prediction and the cause identification. MFM is a concept which qualitatively describes the plant functions by energy and mass flows and also describes the plant status by breaking down the targets in a hierarchical manner which a plant should achieve. In this paper, an operator's mental model using the concept of MFM was proposed and a nuclear power plant diagnosis support system using MFM was developed. The system evaluation test by personnel who have operational experience in nuclear power plants revealed that MFM was superior in the future prediction and the cause identification to a traditional nuclear power plant status display system which used mimics and trends. MFM proved to be useful as an operator's mental model by the test. (author)
Ellen L. Hamaker
Full Text Available Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion, cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship. This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction, cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.
Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani
Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.
Kurmoiartseva, K. A.; Trusov, P. V.; Kotelnikova, N. V.
To predict the behavior of components and constructions it is necessary to develop the methods and mathematical models which take into account the self-organization of microstructural processes and the strain localization. The damage accumulation processes and the evolution of material properties during deformation are important to take into account. The heterogeneity of the process of damage accumulation is due to the appropriate physical mechanisms at the scale levels, which are lower than the macro-level. The purpose of this work is to develop a mathematical model for analyzing the behavior of polycrystalline materials that allows describing the damage accumulation processes. Fracture is the multistage and multiscale process of the build-up of micro- and mesodefects over the wide range of loading rates. The formation of microcracks by mechanisms is caused by the interactions of the dislocations of different slip systems, barriers, boundaries and the inclusions of the secondary phase. This paper provides the description of some of the most well-known models of crack nucleation and also suggests the structure of a mathematical model based on crystal plasticity and dislocation models of crack nucleation.
Sharifullina, E.; Shveykin, A.; Trusov, P.
Material behavior description in a wide range of thermomechanical effects is one of the topical areas in mathematical modeling. Inclusion of grain boundary sliding as an important mechanism of polycrystalline material deformation at elevated temperatures and predominant deformation mechanism of metals and alloys in structural superplasticity allows to simulate various deformation regimes and their transitions (including superplasticity regime with switch-on and switch-off regimes). The paper is devoted to description of grain boundary sliding in structure of two-level model, based on crystal plasticity, and relations for determination the contribution of this mechanism to inelastic deformation. Some results are presented concerning computational experiments of polycrystalline representative volume deformation using developed model.
The models were applied to data obtained from a phase-III clinical trial on a new meningococcal vaccine. The goal is to investigate whether children injected by the candidate vaccine have a lower or higher risk for the occurrence of specific adverse events than children injected with licensed vaccine, and if so, to quantify the ...
Ouyang, Jun; Yoshikawa, Hidekazu; Zhou, Yangping; Yang Ming
The paper describes the application of Multilevel Flow Modeling (MFM) - a modeling method in means-end and part-whole way, in interface design of supervisory control of Pressurized Water Reactor (PWR) plant, and automatic real-time fault diagnosis of PWR accident. The MFM decomposes the complex plant process from the main goal to each component at multiple levels to represent the contribution of each component to the whole system to make clear how the main goal of the system is achieved. The plant process is described abstractly in function level by mass, energy and information flows, which represent the interaction between different components and enable the causal reasoning between functions according to the flow properties. Thus, in the abnormal status, a goal-function-component oriented fault diagnosis can be performed with the model at a very quick speed and abnormal alarms can be fully explained by the reasoning relationship of the model. In this paper, an interface design of the PWR plant is built by the conception of means-end nad part-whole by using MFM, and several simulation cases are used for evaluating the fault diagnosis performance. The results show that the system has a good ability to detect and diagnose accidents timely before reactor trip. (author)
Koch, Tobias; Schultze, Martin; Eid, Michael; Geiser, Christian
One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed. PMID:24860515
Koch, Tobias; Schultze, Martin; Eid, Michael; Geiser, Christian
One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed.
Yang Ming; Zhang Zhijian
Multilevel Flow Models (MFM) is a goal-oriented system modeling method. MFM explicitly describes how a system performs the required functions under stated conditions for a stated period of time. This paper presents a novel system reliability analysis method based on MFM (MRA). The proposed method allows describing the system knowledge at different levels of abstraction which makes the reliability model easy for understanding, establishing, modifying and extending. The success probabilities of all main goals and sub-goals can be available by only one-time quantitative analysis. The proposed method is suitable for the system analysis and scheme comparison for complex industrial systems such as nuclear power plants. (authors)
Hajizadeh, Amin; Shahirinia, Amir
Investigation of an advanced control structure for integration of Photovoltaic Power Systems through Grid Connected-Modular Multilevel Converter (GC-MMC) is proposed in this paper. To achieve this goal, a non-linear model of MMC regarding considering of negative and positive sequence components has...... been presented. Then, due to existence of unbalance voltage faults in distribution grid, non-linarites and uncertainties in model, model predictive controller which is developed for GC-MMC. They are implemented based upon positive and negative components of voltage and current to mitigate the power...
Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.
Martinez-Moyano, I. J.; Conrad, S. H.; Andersen, D. F. (Decision and Information Sciences); (SNL); (Univ. at Albany)
The authors present experimental and simulation results of an outcome-based learning model for the identification of threats to security systems. This model integrates judgment, decision-making, and learning theories to provide a unified framework for the behavioral study of upcoming threats.
Full Text Available Tujuan umum penelitian ini untuk mengkaji bagaimana berbagai variabel mempengaruhi pertumbuhan anak usia 0-24 bulan di kabupaten Sleman. Penelitian noneksperimen desain korelasional ini dilakukan pada 272 anak usia 0-24 bulan yang diambil secara acak stratifikasi dari dua kecamatan (Sleman dan Moyudan yang ditentukan secara purposif. Analisis multilevel pertumbuhan anak dilakukan dengan program Stata-10 dan analisis jalur dilakukan dengan program Amos-8. Hasil penelitian menunjukkan bahwa ada hubungan variabel berat badan lahir, jenis kelamin dan strata usia anak dan status gizi ibu dengan pertumbuhan anak pada level-1 dan ada hubungan variabel hasil penimbangan pada level-2, sedangkan pada level 3 ada hubungan yang tidak signifikan hasil penimbangan dan pencapaian program. Hasil analisis jalur yang mempengaruhi pertumbuhan anak 0-24 bulan, yakni variabel endogenous terdiri dari status gizi ibu, pengetahuan ibu tentang gizi seimbang, pertumbuhan anak indeks BB/U, hasil penimbangan tingkat dusun dan hasil program tingkat desa. Sedangkan variabel exogenous terdiri dari sikap ibu terhadap posyandu, berat badan lahir, jenis kelamin dan stratifikasi usia anak. Kata kunci: Model multilevel, Pertumbuhan anak 0-24 bulan ______________________________________________________________ A MULTILEVEL MODEL FOR THE GROWTH OF CHILDREN AGED 0-24 MONTHS AND THE VARIABLES AFFECTING IT Abstract The main objective of this study is to investigate how various variables contribute to the growth of children between 0-24 months old in Sleman Regency. This study was a non-experimental correlational design which was conducted on 272 children aged 0-24 months, selected using the purposive stratified random sampling technique from 21 hamlets in two districts (Sleman and Moyudan. The multilevel analysis of children’s growth of was carried out using the Stata-10 program and the path analysis using the Amos-8 program. The results show that there is a significant
Mackaronis, Julia E; Strassberg, Donald S; Cundiff, Jeanne M; Cann, Deanna J
When individuals (observers) assess how appealing they find sexual stimuli (targets), which factors matter and to whom? The present study examined how observer and target characteristics interact and impact perceived sexual appeal. Participants were 302 men (206 heterosexual, 96 gay) and 289 women (196 heterosexual, 93 lesbian) between the ages of 18 and 67 years, who viewed 34 photographs of targets of their preferred gender and rated each target for sexual appeal, masculinity-femininity, and estimated age. Participants also rated their own masculinity-femininity. A baseline model indicated that roughly 30 % of the variance in sexual appeal ratings was at the observer level (between observers) and 70 % of the variance was at the target level (within observers). In the final model, five characteristics of the participant observers (gender, sexual orientation, age, race/ethnicity, and self-described masculinity-femininity) and six characteristics of the target photographs (gender, whether the photographs were taken from heterosexual versus gay/lesbian media, race/ethnicity, perceived masculinity-femininity, and estimated age) were independently and interactively related to observer ratings of target sexual appeal. Observers displayed preferences for similar targets in terms of race/ethnicity and masculinity-femininity, while also displaying a general preference for target youth. Variation in the strength of these preferences occurred according to observers' own gender, race/ethnicity, masculinity-femininity, and sexual orientation.
Tae-Hyoung Tommy Gim
Full Text Available Interests in weekend trips are increasing, but few have studied how they are affected by land use. In this study, we analyze the relationship between compact land use characteristics and trip time in Seoul, Korea by comparing two research models, each of which uses the weekday and weekend data of the same travelers. To secure sufficient numbers of subjects and groups, full random coefficients multilevel models define the trip as level one and the neighborhood as level two, and find that level-two land use characteristics account for less variation in trip time than level-one individual characteristics. At level one, weekday trip time is found to be reduced by the choice of the automobile as a travel mode, but not by its ownership per se. In addition, it becomes reduced if made by high income travelers and extended to travel to quality jobs. Among four land use characteristics at level two, population density, road connectivity, and subway availability are shown to be significant in the weekday model. Only subway availability has a positive relationship with trip time and this finding is consistent with the level-one result that the choice of automobile alternatives increases trip time. The other land use characteristic, land use balance, turns out to be a single significant land use variable in the weekend model, implying that it is concerned mainly with non-work, non-mandatory travel.
Zhang, Yi; Wang, Huai; Wang, Zhongxu
One of the future challenges in Modular Multilevel Converters (MMCs) is how to size key components with compromised costs and design margins while fulfilling specific reliability targets. It demands better thermal modeling compared to the state-of-the-art in terms of both accuracy and simplicity....... Different from two-level power converters, MMCs have inherent dc-bias in arm currents and the power device conduction time is affected by operational parameters. A time-wise thermal modeling for the power devices in MMCs is, therefore, an iteration process and time-consuming. This paper thus proposes...
Businaro, T.; Di Lorenzo, A.; Meo, G.B.; Rabbani, M.I.; Rubino, E.
With the advent of advanced digital techniques it has been rendered possible, necessity of which has long since been recognised, to develop a computer based man-machine interface and hance an expert system based on knowledge based decision making for operator support in the control rooms of nuclear plants. The Multilevel Flow Modelling method developed at RISO Laboratories, Denmark, has been applied in the present experiment to model Italian PEC reactor and to verify applicability of this method in plant state identification. In MFM method functional structure of a process plant is described in terms of a set of interrelated mass and energy flow structures on different levels of physical aggregation
Strathe, Anders Bjerring; Danfær, Allan Christian; Sørensen, H.
Growth functions have been used to predict market weight of pigs and maximize return over feed costs. This study was undertaken to compare 4 growth functions and methods of analyzing data, particularly one that considers nonlinear repeated measures. Data were collected from an experiment with 40...... pigs maintained from birth to maturity and their BW measured weekly or every 2 wk up to 1,007 d. Gompertz, logistic, Bridges, and Lopez functions were fitted to the data and compared using information criteria. For each function, a multilevel nonlinear mixed effects model was employed because....... Furthermore, studies should consider adding continuous autoregressive process when analyzing nonlinear mixed models with repeated measures....
Pigot, Corentin; Gilibert, Fabien; Reyboz, Marina; Bocquet, Marc; Zuliani, Paola; Portal, Jean-Michel
Phase-change memory (PCM) compact modeling of the threshold switching based on a thermal runaway in Poole–Frenkel conduction is proposed. Although this approach is often used in physical models, this is the first time it is implemented in a compact model. The model accuracy is validated by a good correlation between simulations and experimental data collected on a PCM cell embedded in a 90 nm technology. A wide range of intermediate states is measured and accurately modeled with a single set of parameters, allowing multilevel programing. A good convergence is exhibited even in snapback simulation owing to this fully continuous approach. Moreover, threshold properties extraction indicates a thermally enhanced switching, which validates the basic hypothesis of the model. Finally, it is shown that this model is compliant with a new drift-resilient cell-state metric. Once enriched with a phase transition module, this compact model is ready to be implemented in circuit simulators.
The main goal of this project is to develop a multilevel converter topology to be useful in power system applications. Although many topologies are introduced rapidly using a bunch of switches and isolated dc sources, having a single-dc-source multilevel inverter is still a matter of controversy. In fact, each isolated dc source means a bulky transformer and a rectifier that have their own losses and costs forcing the industries to avoid entering in this topic conveniently. On the other hand, multilevel inverters topologies with single-dc-source require associated controllers to regulate the dc capacitors voltages in order to have multilevel voltage waveform at the output. Thus, a complex controller would not interest investors properly. Consequently, developing a single-dc-source multilevel inverter topology along with a light and reliable voltage control is still a challenging topic to replace the 2-level inverters in the market effectively. The first effort in this project was devoted to the PUC7 inverter to design a simple and yet efficient controller. A new modelling is performed on the PUC7 inverter and it has been simplified to first order system. Afterwards, a nonlinear cascaded controller is designed and applied to regulate the capacitor voltage at 1/3 of the DC source amplitude and to generate 7 identical voltage levels at the output supplying different type of loads such as RL or rectifier harmonic ones. In next work, the PUC5 topology is proposed as a remedy to the PUC7 that requires a complicated controller to operate properly. The capacitor voltage is regulated at half of dc source amplitude to generate 5 voltage levels at the output. Although the 7-level voltage waveform is replaced by a 5-level one in PUC5 topology, it is shown that the PUC5 needs a very simple and reliable voltage balancing technique due to having some redundant switching states. Moreover, a sensor-less voltage balancing technique is designed and implemented on the PUC5 inverter
Using the framework described in my book "Software Security: Building Security In" I will discuss and describe the state of the practice in software security. This talk is peppered with real data from the field, based on my work with several large companies as a Cigital consultant. As a discipline, software security has made great progress over the last decade. Of the sixty large-scale software security initiatives we are aware of, thirty-two---all household names---are currently included in the BSIMM study. Those companies among the thirty-two who graciously agreed to be identified include: Adobe, Aon, Bank of America, Capital One, The Depository Trust & Clearing Corporation (DTCC), EMC, Google, Intel, Intuit, McKesson, Microsoft, Nokia, QUALCOMM, Sallie Mae, Standard Life, SWIFT, Symantec, Telecom Italia, Thomson Reuters, VMware, and Wells Fargo. The BSIMM was created by observing and analyzing real-world data from thirty-two leading software security initiatives. The BSIMM can...
Hartel, Pieter H.; van Eck, Pascal; Etalle, Sandro; Wieringa, Roelf J.
Security policies are rules that constrain the behaviour of a system. Different, largely unrelated sets of rules typically govern the physical and logical worlds. However, increased hardware and software mobility forces us to consider those rules in an integrated fashion. We present SPIN models of
Kordy, Barbara; Pouly, Marc; Schweitzer, Patrick
This work provides a computational framework for meaningful probabilistic evaluation of attack–defense scenarios involving dependent actions. We combine the graphical security modeling technique of attack–defense trees with probabilistic information expressed in terms of Bayesian networks. In order
Corin, R.J.; Etalle, Sandro; Hartel, Pieter H.; Mader, Angelika H.
We propose a method for engineering security protocols that are aware of timing aspects. We study a simplified version of the well-known Needham Schroeder protocol and the complete Yahalom protocol. Timing information allows the study of different attack scenarios. We illustrate the attacks by model
Vellekoop, M.H.; Nieuwenhuis, J.W.
We propose a generalized framework for the modeling of tradeable securities with dividends which are not necessarily cash dividends at fixed times or continuously paid dividends. In our setup the dividend processes are only required to be semi-martingales. We give a definition of self-financing
Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour
Francavilla, Francesca; Giannelli, Gianna Claudia; Grilli, Leonardo
This paper investigates the determinants of school attendance of children and their mother´s working status when the mother decides how to allocate her time and that of her children. A multilevel random effects model is applied to study the mother´s participation and the schooling status of her children in a joint framework. Using the second National Family Health Survey (NFHS-2) for India, we find that, controlling for many covariates among which wealth is the most powerful predictor, childr...
Full Text Available Technologies of precision agriculture, digital soil maps, and meteorological stations provide a minimum data set to guide precision farming operations. However, determining optimal nutrient requirements for potato (Solanum tuberosum L. crops at subfield scale remains a challenge given specific climatic, edaphic, and managerial conditions. Multilevel modeling can generalize yield response to fertilizer additions using data easily accessible to growers. Our objective was to elaborate a multilevel N fertilizer response model for potato crops using the Mitscherlich equation and a core data set of 93 N fertilizer trials conducted in Québec, Canada. Daily climatic data were collected at 10 × 10 km resolution. Soils were characterized by organic matter content, pH, and texture in the arable layer, and by texture and tools of pedometrics across a gleization-podzolization continuum in subsoil layers. There were five categories of preceding crops and five cultivar maturity orders. The three Mitscherlich parameters (Asymptote, Rate, and Environment were most often site-specific. Sensitivity analysis showed that optimum N dosage increased with non-leguminous high-residue preceding crops, coarser soils, podzolization, drier climatic condition, and late cultivar maturity. The inferential model could guide site-specific N fertilization using an accessible minimum data set to support fertilization decisions. As decision-support system, the model could also provide a range of optimum N doses across a large spectrum of site-specific conditions including climate change.
Liu Jingquan; Yoshikawa, H.; Zhou Yangping
Complex energy and environment system, especially nuclear fuel cycle system recently raised social concerns about the issues of economic competitiveness, environmental effect and nuclear proliferation. Only under the condition that those conflicting issues are gotten a consensus between stakeholders with different knowledge background, can nuclear power industry be continuingly developed. In this paper, a new analysis platform has been developed to help stakeholders to recognize and analyze various socio-technical issues in the nuclear fuel cycle sys- tem based on the functional modeling method named Multilevel Flow Models (MFM) according to the cognition theory of human being, Its character is that MFM models define a set of mass, energy and information flow structures on multiple levels of abstraction to describe the functional structure of a process system and its graphical symbol representation and the means-end and part-whole hierarchical flow structure to make the represented process easy to be understood. Based upon this methodology, a micro-process and a macro-process of nuclear fuel cycle system were selected to be simulated and some analysis processes such as economics analysis, environmental analysis and energy balance analysis related to those flows were also integrated to help stakeholders to understand the process of decision-making with the introduction of some new functions for the improved Multilevel Flow Models Studio, and finally the simple simulation such as spent fuel management process simulation and money flow of nuclear fuel cycle and its levelised cost analysis will be represented as feasible examples. (authors)
Hastings, Paul D; Helm, Jonathan; Mills, Rosemary S L; Serbin, Lisa A; Stack, Dale M; Schwartzman, Alex E
This investigation evaluated a multilevel model of dispositional and environmental factors contributing to the development of internalizing problems from preschool-age to school-age. In a sample of 375 families (185 daughters, 190 sons) drawn from three independent samples, preschoolers' behavioral inhibition, cortisol and gender were examined as moderators of the links between mothers' negative parenting behavior, negative emotional characteristics, and socioeconomic status when children were 3.95 years, and their internalizing problems when they were 8.34 years. Children's dispositional characteristics moderated all associations between these environmental factors and mother-reported internalizing problems in patterns that were consistent with either diathesis-stress or differential-susceptibility models of individual-environment interaction, and with gender models of developmental psychopathology. Greater inhibition and lower socioeconomic status were directly predictive of more teacher reported internalizing problems. These findings highlight the importance of using multilevel models within a bioecological framework to understand the complex pathways through which internalizing difficulties develop.
Full Text Available In order to reflect the situation of network security assessment performance fully and accurately, a new network security situation awareness model based on information fusion was proposed. Network security situation is the result of fusion three aspects evaluation. In terms of attack, to improve the accuracy of evaluation, a situation assessment method of DDoS attack based on the information of data packet was proposed. In terms of vulnerability, a improved Common Vulnerability Scoring System (CVSS was raised and maked the assessment more comprehensive. In terms of node weights, the method of calculating the combined weights and optimizing the result by Sequence Quadratic Program (SQP algorithm which reduced the uncertainty of fusion was raised. To verify the validity and necessity of the method, a testing platform was built and used to test through evaluating 2000 DAPRA data sets. Experiments show that the method can improve the accuracy of evaluation results.
Full Text Available Abstract Background Many studies conducted in health and social sciences collect individual level data as outcome measures. Usually, such data have a hierarchical structure, with patients clustered within physicians, and physicians clustered within practices. Large survey data, including national surveys, have a hierarchical or clustered structure; respondents are naturally clustered in geographical units (e.g., health regions and may be grouped into smaller units. Outcomes of interest in many fields not only reflect continuous measures, but also binary outcomes such as depression, presence or absence of a disease, and self-reported general health. In the framework of multilevel studies an important problem is calculating an adequate sample size that generates unbiased and accurate estimates. Methods In this paper simulation studies are used to assess the effect of varying sample size at both the individual and group level on the accuracy of the estimates of the parameters and variance components of multilevel logistic regression models. In addition, the influence of prevalence of the outcome and the intra-class correlation coefficient (ICC is examined. Results The results show that the estimates of the fixed effect parameters are unbiased for 100 groups with group size of 50 or higher. The estimates of the variance covariance components are slightly biased even with 100 groups and group size of 50. The biases for both fixed and random effects are severe for group size of 5. The standard errors for fixed effect parameters are unbiased while for variance covariance components are underestimated. Results suggest that low prevalent events require larger sample sizes with at least a minimum of 100 groups and 50 individuals per group. Conclusion We recommend using a minimum group size of 50 with at least 50 groups to produce valid estimates for multi-level logistic regression models. Group size should be adjusted under conditions where the prevalence
Lin, Yea-Wen; Lin, Yueh-Ysen
Organizational health culture is a health-oriented core characteristic of the organization that is shared by all members. It is effective in regulating health-related behavior for employees and could therefore influence the effectiveness of health promotion efforts among organizations and employees. This study applied a multilevel analysis to verify the effects of organizational health culture on the organizational and individual effectiveness of health promotion. At the organizational level, we investigated the effect of organizational health culture on the organizational effectiveness of health promotion. At the individual level, we adopted a cross-level analysis to determine if organizational health culture affects employee effectiveness through the mediating effect of employee health behavior. The study setting consisted of the workplaces of various enterprises. We selected 54 enterprises in Taiwan and surveyed 20 full-time employees from each organization, for a total sample of 1011 employees. We developed the Organizational Health Culture Scale to measure employee perceptions and aggregated the individual data to formulate organization-level data. Organizational effectiveness of health promotion included four dimensions: planning effectiveness, production, outcome, and quality, which were measured by scale or objective indicators. The Health Promotion Lifestyle Scale was adopted for the measurement of health behavior. Employee effectiveness was measured subjectively in three dimensions: self-evaluated performance, altruism, and happiness. Following the calculation of descriptive statistics, hierarchical linear modeling (HLM) was used to test the multilevel hypotheses. Organizational health culture had a significant effect on the planning effectiveness (β = .356, p organizational health culture on three dimensions of employee effectiveness were completely mediated by health behavior. The construct connections established in this multilevel model will help in
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Zhang, Yue; Berhane, Kiros
Questionnaire-based health status outcomes are often prone to misclassification. When studying the effect of risk factors on such outcomes, ignoring any potential misclassification may lead to biased effect estimates. Analytical challenges posed by these misclassified outcomes are further complicated when simultaneously exploring factors for both the misclassification and health processes in a multi-level setting. To address these challenges, we propose a fully Bayesian Mixed Hidden Markov Model (BMHMM) for handling differential misclassification in categorical outcomes in a multi-level setting. The BMHMM generalizes the traditional Hidden Markov Model (HMM) by introducing random effects into three sets of HMM parameters for joint estimation of the prevalence, transition and misclassification probabilities. This formulation not only allows joint estimation of all three sets of parameters, but also accounts for cluster level heterogeneity based on a multi-level model structure. Using this novel approach, both the true health status prevalence and the transition probabilities between the health states during follow-up are modeled as functions of covariates. The observed, possibly misclassified, health states are related to the true, but unobserved, health states and covariates. Results from simulation studies are presented to validate the estimation procedure, to show the computational efficiency due to the Bayesian approach and also to illustrate the gains from the proposed method compared to existing methods that ignore outcome misclassification and cluster level heterogeneity. We apply the proposed method to examine the risk factors for both asthma transition and misclassification in the Southern California Children's Health Study (CHS). PMID:24254432
Chen, Jun-Jie; Tan, Lei; Zheng, Bo
In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.
It briefly describes the impact of large data era on China’s network policy, but also brings more opportunities and challenges to the network information security. This paper reviews for the internationally accepted basic model and characteristics of network information security, and analyses the characteristics of network information security and their relationship. On the basis of the NIST security model, this paper describes three security control schemes in safety management model and the...
Hirschfeld, Gerrit; Blankenburg, Markus R; Süß, Moritz; Zernikow, Boris
The assessment of somatosensory function is a cornerstone of research and clinical practice in neurology. Recent initiatives have developed novel protocols for quantitative sensory testing (QST). Application of these methods led to intriguing findings, such as the presence lower pain-thresholds in healthy children compared to healthy adolescents. In this article, we (re-) introduce the basic concepts of signal detection theory (SDT) as a method to investigate such differences in somatosensory function in detail. SDT describes participants' responses according to two parameters, sensitivity and response-bias. Sensitivity refers to individuals' ability to discriminate between painful and non-painful stimulations. Response-bias refers to individuals' criterion for giving a "painful" response. We describe how multilevel models can be used to estimate these parameters and to overcome central critiques of these methods. To provide an example we apply these methods to data from the mechanical pain sensitivity test of the QST protocol. The results show that adolescents are more sensitive to mechanical pain and contradict the idea that younger children simply use more lenient criteria to report pain. Overall, we hope that the wider use of multilevel modeling to describe somatosensory functioning may advance neurology research and practice.
Hung, Peter W.; Johnson, Stephen B.; Kaufman, David R.; Mendonça, Eneida A.
Objective: Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. Design: The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. Results: A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. Conclusion: The described multi-level model provides a framework for future research and the foundation for development of an
The increasing usage of computer-based systems in almost every aspects of our daily life makes more and more dangerous the threat posed by potential attackers, and more and more rewarding a successful attack. Moreover, the complexity of these systems is also increasing, including physical devices......, software components and human actors interacting with each other to form so-called socio-technical systems. The importance of socio-technical systems to modern societies requires verifying their security properties formally, while their inherent complexity makes manual analyses impracticable. Graphical...... models for security offer an unrivalled opportunity to describe socio-technical systems, for they allow to represent different aspects like human behaviour, computation and physical phenomena in an abstract yet uniform manner. Moreover, these models can be assigned a formal semantics, thereby allowing...
Full Text Available There are many CPU scheduling algorithms inliterature like FIFO, Round Robin, Shortest-Job-First and so on.The Multilevel-Queue-Scheduling is superior to these due to itsbetter management of a variety of processes. In this paper, aMarkov chain model is used for a general setup of Multilevelqueue-scheduling and the scheduler is assumed to performrandom movement on queue over the quantum of time.Performance of scheduling is examined through a rowdependent data model. It is found that with increasing value of αand d, the chance of system going over the waiting state reduces.At some of the interesting combinations of α and d, it diminishesto zero, thereby, provides us some clue regarding better choice ofqueues over others for high priority jobs. It is found that ifqueue priorities are added in the scheduling intelligently thenbetter performance could be obtained. Data model helpschoosing appropriate preferences.
de validation pour les modèles informatisées des facteurs humains . DRDC CSS CR 2012-026 2 Executive summary Modelling Public Security ...Modelling Public Security Operations Evaluation of the Holistic Security Ecosystem (HSE) Proof-of-Concept Alexis Morris William Ross Mihaela...Centre for Security Science The scientific or technical validity of this Contract Report is entirely the responsibility of the Contractor and
WANG, Jiahai; HAN, Fangxi; Tang, Zheng; TAMURA, Hiroki; Ishii, Masahiro
The security of information is a key problem in the development of network technology. The basic requirements of security of information clearly include confidentiality, integrity, authentication and non-repudiation. This paper proposes a network security model that is composed of security system, security connection and communication, and key management. The model carries out encrypting, decrypting, signature and ensures confidentiality, integrity, authentication and non-repudiation. Finally...
Andreh, Angga Muhamad; Subiyanto, Sunardiyo, Said
Development of non-linear loading in the application of industry and distribution system and also harmonic compensation becomes important. Harmonic pollution is an urgent problem in increasing power quality. The main contribution of the study is the modeling approach used to design a shunt active filter and the application of the cascade multilevel inverter topology to improve the power quality of electrical energy. In this study, shunt active filter was aimed to eliminate dominant harmonic component by injecting opposite currents with the harmonic component system. The active filter was designed by shunt configuration with cascaded multilevel inverter method controlled by PID controller and SPWM. With this shunt active filter, the harmonic current can be reduced so that the current wave pattern of the source is approximately sinusoidal. Design and simulation were conducted by using Power Simulator (PSIM) software. Shunt active filter performance experiment was conducted on the IEEE four bus test system. The result of shunt active filter installation on the system (IEEE four bus) could reduce THD current from 28.68% to 3.09%. With this result, the active filter can be applied as an effective method to reduce harmonics.
Mum, Ng C
.... This research developed a scenario definition file for the CyberCIEGE game engine to illustrate and train players on matters related to information protection using compartmentalized Mutlilevel Secure (MLS) systems...
Grilli, Leonardo; Innocenti, Francesco
Fitting cross-classified multilevel models with binary response is challenging. In this setting a promising method is Bayesian inference through Integrated Nested Laplace Approximations (INLA), which performs well in several latent variable models. We devise a systematic simulation study to assess
Frei, Stefan; Schatzmann, Dominik; Plattner, Bernhard; Trammell, Brian
The security of information technology and computer networks is effected by a wide variety of actors and processes which together make up a security ecosystem; here we examine this ecosystem, consolidating many aspects of security that have hitherto been discussed only separately. First, we analyze the roles of the major actors within this ecosystem and the processes they participate in, and the the paths vulnerability data take through the ecosystem and the impact of each of these on security risk. Then, based on a quantitative examination of 27,000 vulnerabilities disclosed over the past decade and taken from publicly available data sources, we quantify the systematic gap between exploit and patch availability. We provide the first examination of the impact and the risks associated with this gap on the ecosystem as a whole. Our analysis provides a metric for the success of the “responsible disclosure” process. We measure the prevalence of the commercial markets for vulnerability information and highlight the role of security information providers (SIP), which function as the “free press” of the ecosystem.
Halatchliyski, Iassen; Cress, Ulrike
Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base. PMID:25365319
This work presents an equivalent model and simulation architecture for real-time electromagnetic transient analysis of either half-bridge or full-bridge modular multilevel converter (MMC) with 400 sub-modules (SMs) per arm. The proposed CPU/FPGA-based architecture is optimized for the parallel implementation of the presented MMC model on the FPGA and is beneficiary of a high-throughput floating-point computational engine. The developed real-time simulation architecture is capable of simulating MMCs with 400 SMs per arm at 825 nanoseconds. To address the difficulties of the sorting process implementation, a modified Odd-Even Bubble sorting is presented in this work. The comparison of the results under various test scenarios reveals that the proposed real-time simulator is representing the system responses in the same way of its corresponding off-line counterpart obtained from the PSCAD/EMTDC program.
Complex Nuclear Fuel Cycle (NFC) system faces many socio-technical issues that need to obtain the consensus between stake holders of different knowledge background. In this paper, a visualized analysis platform based on graphical functional modeling method, Multilevel Flow Model (MFM), was proposed to help those stake holders to recognize and analyze various socio-technical issues in NFC system. There are some new functions, such as 'Reaction Function', 'Switch Function' and 'Conversion Function', introduced to adapt new simulation tasks for NFC system. Based upon this methodology, a micro-process and a macro-process of NFC system were simulated and meanwhile some key analysis variables required by some analysis methods were deducted and displayed in the platform. And finally a simple simulation analysis was conducted based on the proposed MFM application. (author)
Full Text Available Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base.
In recent years, Bayesian model updating techniques based on measured data have been applied to many engineering and applied science problems. At the same time, parallel computational platforms are becoming increasingly more powerful and are being used more frequently by the engineering and scientific communities. Bayesian techniques usually require the evaluation of multi-dimensional integrals related to the posterior probability density function (PDF) of uncertain model parameters. The fact that such integrals cannot be computed analytically motivates the research of stochastic simulation methods for sampling posterior PDFs. One such algorithm is the adaptive multilevel stochastic simulation algorithm (AMSSA). In this paper we discuss the parallelization of AMSSA, formulating the necessary load balancing step as a binary integer programming problem. We present a variety of results showing the effectiveness of load balancing on the overall performance of AMSSA in a parallel computational environment.
Chen Qiang; Yang Ming
Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)
Gustavsson, R.; Mellstrand, P.; Tornqvist, B.
The deliverable D1.6 includes background material and specifications of a CRISP Framework on protection of information assets related to power net management and management of business operations related to energy services. During the project it was discovered by the CRISP consortium that the original description of WP 1.6 was not adequate for the project as such. The main insight was that the original emphasis on cost-benefit analysis of security protection measures was to early to address in the project. This issue is of course crucial in itself but requires new models of consequence analysis that still remains to be developed, especially for the new business models we are investigated in the CRISP project. The updated and approved version of the WP1.6 description, together with the also updated WP2.4 focus on Dependable ICT support of Power Grid Operations constitutes an integrated approach towards dependable and secure future utilities and their business processes. This document (D1.6) is a background to deliverable D2.4. Together they provide a dependability and security framework to the three CRISP experiments in WP3
Full Text Available Instead of paying by cash, check, or credit cards, customers can now also use their mobile devices to pay for a wide range of services and both digital and physical goods. However, customers’ security concerns are a major barrier to the broad adoption and use of mobile payments. In this paper we present the design of a secure operational model for mobile payments in which access control is based on a service-oriented architecture. A customer uses his/her mobile device to get authorization from a remote server and generate a two-dimensional barcode as the payment certificate. This payment certificate has a time limit and can be used once only. The system also provides the ability to remotely lock and disable the mobile payment service.
Instead of paying by cash, check, or credit cards, customers can now also use their mobile devices to pay for a wide range of services and both digital and physical goods. However, customers' security concerns are a major barrier to the broad adoption and use of mobile payments. In this paper we present the design of a secure operational model for mobile payments in which access control is based on a service-oriented architecture. A customer uses his/her mobile device to get authorization from a remote server and generate a two-dimensional barcode as the payment certificate. This payment certificate has a time limit and can be used once only. The system also provides the ability to remotely lock and disable the mobile payment service.
Instead of paying by cash, check, or credit cards, customers can now also use their mobile devices to pay for a wide range of services and both digital and physical goods. However, customers' security concerns are a major barrier to the broad adoption and use of mobile payments. In this paper we present the design of a secure operational model for mobile payments in which access control is based on a service-oriented architecture. A customer uses his/her mobile device to get authorization from a remote server and generate a two-dimensional barcode as the payment certificate. This payment certificate has a time limit and can be used once only. The system also provides the ability to remotely lock and disable the mobile payment service. PMID:25386607
Shin, Jinsoo; Son, Hanseong; Khalil ur, Rahman; Heo, Gyunyoung
Cyber security is an emerging safety issue in the nuclear industry, especially in the instrumentation and control (I and C) field. To address the cyber security issue systematically, a model that can be used for cyber security evaluation is required. In this work, a cyber security risk model based on a Bayesian network is suggested for evaluating cyber security for nuclear facilities in an integrated manner. The suggested model enables the evaluation of both the procedural and technical aspects of cyber security, which are related to compliance with regulatory guides and system architectures, respectively. The activity-quality analysis model was developed to evaluate how well people and/or organizations comply with the regulatory guidance associated with cyber security. The architecture analysis model was created to evaluate vulnerabilities and mitigation measures with respect to their effect on cyber security. The two models are integrated into a single model, which is called the cyber security risk model, so that cyber security can be evaluated from procedural and technical viewpoints at the same time. The model was applied to evaluate the cyber security risk of the reactor protection system (RPS) of a research reactor and to demonstrate its usefulness and feasibility. - Highlights: • We developed the cyber security risk model can be find the weak point of cyber security integrated two cyber analysis models by using Bayesian Network. • One is the activity-quality model signifies how people and/or organization comply with the cyber security regulatory guide. • Other is the architecture model represents the probability of cyber-attack on RPS architecture. • The cyber security risk model can provide evidence that is able to determine the key element for cyber security for RPS of a research reactor
van Cleeff, A.
Consumer mobile phone security requires more attention, now that their data storage capacity is increasing. At the same time, much effort is spent on data-centric security for large enterprises. In this article we try to apply data-centric security to consumer mobile phones. We show a maturity model
Austin, Peter C
Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public health, epidemiological, and educational research. Procedures for estimating the parameters of such models are available in many statistical software packages. There is currently little evidence on the minimum number of clusters necessary to reliably fit multilevel regression models. We conducted a Monte Carlo study to compare the performance of different statistical software procedures for estimating multilevel logistic regression models when the number of clusters was low. We examined procedures available in BUGS, HLM, R, SAS, and Stata. We found that there were qualitative differences in the performance of different software procedures for estimating multilevel logistic models when the number of clusters was low. Among the likelihood-based procedures, estimation methods based on adaptive Gauss-Hermite approximations to the likelihood (glmer in R and xtlogit in Stata) or adaptive Gaussian quadrature (Proc NLMIXED in SAS) tended to have superior performance for estimating variance components when the number of clusters was small, compared to software procedures based on penalized quasi-likelihood. However, only Bayesian estimation with BUGS allowed for accurate estimation of variance components when there were fewer than 10 clusters. For all statistical software procedures, estimation of variance components tended to be poor when there were only five subjects per cluster, regardless of the number of clusters.
Eduardo B. Fernandez
Full Text Available Clouds do not work in isolation but interact with other clouds and with a variety of systems either developed by the same provider or by external entities with the purpose to interact with them; forming then an ecosystem. A software ecosystem is a collection of software systems that have been developed to coexist and evolve together. The stakeholders of such a system need a variety of models to give them a perspective of the possibilities of the system, to evaluate specific quality attributes, and to extend the system. A powerful representation when building or using software ecosystems is the use of architectural models, which describe the structural aspects of such a system. These models have value for security and compliance, are useful to build new systems, can be used to define service contracts, find where quality factors can be monitored, and to plan further expansion. We have described a cloud ecosystem in the form of a pattern diagram where its components are patterns and reference architectures. A pattern is an encapsulated solution to a recurrent problem. We have recently expanded these models to cover fog systems and containers. Fog Computing is a highly-virtualized platform that provides compute, storage, and networking services between end devices and Cloud Computing Data Centers; a Software Container provides an execution environment for applications sharing a host operating system, binaries, and libraries with other containers. We intend to use this architecture to answer a variety of questions about the security of this system as well as a reference to design interacting combinations of heterogeneous components. We defined a metamodel to relate security concepts which is being expanded.
Hong, Ying; Liao, Hui; Raub, Steffen; Han, Joo Hun
Building upon and extending Parker, Bindl, and Strauss's (2010) theory of proactive motivation, we develop an integrated, multilevel model to examine how contextual factors shape employees' proactive motivational states and, through these proactive motivational states, influence their personal initiative behavior. Using data from a sample of hotels collected from 3 sources and over 2 time periods, we show that establishment-level initiative-enhancing human resource management (HRM) systems were positively related to departmental initiative climate, which was positively related to employee personal initiative through employee role-breadth self-efficacy. Further, department-level empowering leadership was positively related to initiative climate only when initiative-enhancing HRM systems were low. These findings offer interesting implications for research on personal initiative and for the management of employee proactivity in organizations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Full Text Available The purpose of this study was to examine individual- and classroom-level differences in the longitudinal change in motivational regulations during physical education students’ transition from elementary (Grade 6 across middle school (Grades 7 to 9. A sample of 757 Finnish adolescents (M = 12.71, SD = 0.23 participated in this study. Participants of the study responded to questionnaires collected six times. A multilevel latent growth modelling approach was used to analyze the data. Results showed that motivational regulations in physical education developed at different rates during middle school. More specifically, students’: (a identified regulation increased across Grades 6 to 9; (b amotivation increased during middle school transition from Grade 6 to 7; and (c introjected regulation declined from Grade 8 to 9. Other motivational regulations remained stable across time. The changes in amotivation and introjected regulation were largely due to individual factors, whereas the changes in identified regulation were due to environmental factors.
Chichester, F. D.
An approach to the application of multilevel control techniques for large space structures is presented. Gauss-Seidel second level controls and an extension of standard linear quadratic regulator techniques are applied to a model consisting of a flexible space vehicle comprising three rigid bodies rotating about a common axis. The method incorporates second order derivatives with respect to time, entailing the use of a two level hierarchy of subsystems. Gauss-Seidel second level control formulations were chosen to avoid the necessity of having as many controls as constraints or using gradient techniques in the choice of the Hamiltonian. The modular nature of the resulting control system allows applications for spacecraft with larger numbers of modules.
Keene, David J; Moe-Nilssen, Rolf; Lamb, Sarah E
Differences in gait performance can be explained by variations in walking speed, which is a major analytical problem. Some investigators have standardised speed during testing, but this can result in an unnatural control of gait characteristics. Other investigators have developed test procedures where participants walking at their self-selected slow, preferred and fast speeds, with computation of gait characteristics at a standardised speed. However, this analysis is dependent upon an overlap in the ranges of gait speed observed within and between participants, and this is difficult to achieve under self-selected conditions. In this report a statistical analysis procedure is introduced that utilises multilevel modelling to analyse data from walking tests at self-selected speeds, without requiring an overlap in the range of speeds observed or the routine use of data transformations. Copyright © 2015 Elsevier B.V. All rights reserved.
Dettmers, Swantje; Trautwein, Ulrich; Ludtke, Oliver; Kunter, Mareike; Baumert, Jurgen
The present study examined the associations of 2 indicators of homework quality (homework selection and homework challenge) with homework motivation, homework behavior, and mathematics achievement. Multilevel modeling was used to analyze longitudinal data from a representative national sample of 3,483 students in Grades 9 and 10; homework effects…
Yang, Ji Seung; Cai, Li
The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…
Wang, Ya-Ling; Tsai, Chin-Chung
This study aimed to investigate the factors accounting for science learning self-efficacy (the specific beliefs that people have in their ability to complete tasks in science learning) from both the teacher and the student levels. We thus propose a multilevel model to delineate its relationships with teacher and student science hardiness (i.e.,…
Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.
Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…
Televantou, Ioulia; Marsh, Herbert W.; Kyriakides, Leonidas; Nagengast, Benjamin; Fletcher, John; Malmberg, Lars-Erik
The main objective of this study was to quantify the impact of failing to account for measurement error on school compositional effects. Multilevel structural equation models were incorporated to control for measurement error and/or sampling error. Study 1, a large sample of English primary students in Years 1 and 4, revealed a significantly…
Schmidt, Susanne; Zlatkin-Troitschanskaia, Olga; Fox, Gerardus J.A.
Longitudinal research in higher education faces several challenges. Appropriate methods of analyzing competence growth of students are needed to deal with those challenges and thereby obtain valid results. In this article, a pretest-posttest-posttest multivariate multilevel IRT model for repeated
Dudaniec, Rachael Y; Rhodes, Jonathan R; Worthington Wilmer, Jessica; Lyons, Mitchell; Lee, Kristen E; McAlpine, Clive A; Carrick, Frank N
Landscape genetics offers a powerful approach to understanding species' dispersal patterns. However, a central obstacle is to account for ecological processes operating at multiple spatial scales, while keeping research outcomes applicable to conservation management. We address this challenge by applying a novel multilevel regression approach to model landscape drivers of genetic structure at both the resolution of individuals and at a spatial resolution relevant to management (i.e. local government management areas: LGAs) for the koala (Phascolartos cinereus) in Australia. Our approach allows for the simultaneous incorporation of drivers of landscape-genetic relationships operating at multiple spatial resolutions. Using microsatellite data for 1106 koalas, we show that, at the individual resolution, foliage projective cover (FPC) facilitates high gene flow (i.e. low resistance) until it falls below approximately 30%. Out of six additional land-cover variables, only highways and freeways further explained genetic distance after accounting for the effect of FPC. At the LGA resolution, there was significant variation in isolation-by-resistance (IBR) relationships in terms of their slopes and intercepts. This was predominantly explained by the average resistance distance among LGAs, with a weaker effect of historical forest cover. Rates of recent landscape change did not further explain variation in IBR relationships among LGAs. By using a novel multilevel model, we disentangle the effect of landscape resistance on gene flow at the fine resolution (i.e. among individuals) from effects occurring at coarser resolutions (i.e. among LGAs). This has important implications for our ability to identify appropriate scale-dependent management actions. © 2013 John Wiley & Sons Ltd.
Telwatte, Apsara; Anglim, Jeromy; Wynton, Sarah K A; Moulding, Richard
Existing research suggests that the decision to grant or deny workplace accommodations for people with disabilities is influenced by a range of legal and nonlegal factors. However, less is known about how these factors operate at the within-person level. Thus, we proposed and tested a multilevel model of the accommodation decision-making process, which we applied to better understand why people with psychological disabilities often experience greater challenges in obtaining accommodations. A sample of 159 Australian adults, composed mostly of managers and HR professionals, read 12 vignettes involving requests for accommodations from existing employees. The requests differed in whether they were for psychological or physical disabilities. For each vignette, participants rated their empathy with the employee, the legitimacy of the employee's disability, the necessity for productivity, the perceived cost, and the reasonableness, and indicated whether they would grant the accommodation. Multilevel modeling indicated that greater empathy, legitimacy, and necessity, and lower perceived cost predicted perceptions of greater reasonableness and greater granting. Accommodation requests from employees with psychological disabilities were seen as less reasonable and were less likely to be granted; much of this effect seemed to be driven by perceptions that such accommodations were less necessary for productivity. Ratings on accommodations were influenced both by general between-person tendencies and within-person appraisals of particular scenarios. The study points to a need for organizations to more clearly establish guidelines for how decision-makers should fairly evaluate accommodation requests for employees with psychological disabilities and disability more broadly. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Liu, Dong; Zhang, Shu; Wang, Lei; Lee, Thomas W.
Extending research on voluntary turnover in the team setting, this study adopts a multilevel self-determination theoretical approach to examine the unique roles of individual and social-contextual motivational precursors, autonomy orientation and autonomy support, in reducing team member voluntary turnover. Analysis of multilevel time-lagged data…
Terpstra, Niels; Willems, Rens; Frerks, Georg; Chang Pico, Tomás
This scoping study analyses the experiences with the implementation of the Human Security Approach in practice as elucidated in the literature, and aims at highlighting lessons that are of relevance to the successful design and implementation of the New Deal. The first chapter of this report
Moody, A T; Bronevetsky, G; Mohror, K M; de Supinski, B R
High-performance computing (HPC) systems are growing more powerful by utilizing more hardware components. As the system mean-time-before-failure correspondingly drops, applications must checkpoint more frequently to make progress. However, as the system memory sizes grow faster than the bandwidth to the parallel file system, the cost of checkpointing begins to dominate application run times. A potential solution to this problem is to use multi-level checkpointing, which employs multiple types of checkpoints with different costs and different levels of resiliency in a single run. The goal is to design light-weight checkpoints to handle the most common failure modes and rely on more expensive checkpoints for less common, but more severe failures. While this approach is theoretically promising, it has not been fully evaluated in a large-scale, production system context. To this end we have designed a system, called the Scalable Checkpoint/Restart (SCR) library, that writes checkpoints to storage on the compute nodes utilizing RAM, Flash, or disk, in addition to the parallel file system. We present the performance and reliability properties of SCR as well as a probabilistic Markov model that predicts its performance on current and future systems. We show that multi-level checkpointing improves efficiency on existing large-scale systems and that this benefit increases as the system size grows. In particular, we developed low-cost checkpoint schemes that are 100x-1000x faster than the parallel file system and effective against 85% of our system failures. This leads to a gain in machine efficiency of up to 35%, and it reduces the the load on the parallel file system by a factor of two on current and future systems.
Cuffney, T.F.; Kashuba, R.; Qian, S.S.; Alameddine, I.; Cha, Y.K.; Lee, B.; Coles, J.F.; McMahon, G.
Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development). ?? 2011 by The North American
Larochelle, David; Rosasco, Nicholas
We present a simple information security model to determine why, historically, the level of security has not increased despite numerous technical advances. In our model, the software design process involves trade-offs between security and functionality. Developers choose points in the design space corresponding to certain levels of security and functionality. If development resources, such as number of developers, time for completion, etc., are fixed, there is an implicit trade-off between se...
Katsiolides, Grigoris; Müller, Eike H.; Scheichl, Robert; Shardlow, Tony; Giles, Michael B.; Thomson, David J.
A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an efficient numerical method is particularly important in operational emergency-response applications, such as tracking radioactive clouds from nuclear accidents or predicting the impact of volcanic ash clouds on international aviation, where accurate and timely predictions are essential. In this paper, we investigate the application of the Multilevel Monte Carlo (MLMC) method to simulate the propagation of particles in a representative one-dimensional dispersion scenario in the atmospheric boundary layer. MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling. To reduce the absolute cost of the method also in the non-asymptotic regime, it is equally important to choose the best possible numerical timestepping method on each level. To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.
Slides for the opening panel on "Issues in the Security of Wireless Network systems" at ICETE 2008.......Slides for the opening panel on "Issues in the Security of Wireless Network systems" at ICETE 2008....
Full Text Available To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC design have been explored. The existing modeling tools, however, cover only a few memory technologies, technology nodes and fabrication approaches. We present DESTINY, a tool for modeling 2D/3D memories designed using SRAM, resistive RAM (ReRAM, spin transfer torque RAM (STT-RAM, phase change RAM (PCM and embedded DRAM (eDRAM and 2D memories designed using spin orbit torque RAM (SOT-RAM, domain wall memory (DWM and Flash memory. In addition to single-level cell (SLC designs for all of these memories, DESTINY also supports modeling MLC designs for NVMs. We have extensively validated DESTINY against commercial and research prototypes of these memories. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g., latency, area or energy-delay product for a given memory technology, choosing the suitable memory technology or fabrication method (i.e., 2D v/s 3D for a given optimization target, etc. We believe that DESTINY will boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers. The latest source-code of DESTINY is available from the following git repository: https://bitbucket.org/sparshmittal/destinyv2.
Culpepper, Steven Andrew
Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops distribution-appropriate methods for studying individual differences in predictability for settings in psychological research. Specifically, 3 different approaches are discussed for modeling predictability. The 1st is a bivariate measure of predictability discussed previously in the psychology literature, the squared or absolute valued difference between criterion and predictor, which is shown to follow the gamma distribution. The 2nd method extended limitations of previous research and involved understanding predictability in regression models. The 3rd method used nonlinear multilevel models to study predictability in settings where participants are nested within clusters. An application was presented using SAS NLMIXED to understand the predictability of college grade point average by student demographic characteristics. The findings from the application suggest that the 1st-year college performance of English as a second language students were, on average, less predictable whereas females and Whites tended to demonstrate more predictable academic performance than their male or racial/ethnic minority counterparts.
Klöckner, Christian; Oppedal, Inger Olin
This paper reports the results of a multilevel structure equation model predicting general and fraction specific self-reported recycling behaviour. The model was tested on a sample of 697 undergraduate students from four Norwegian universities who each reported their degree of participation in the local recycling schemes for paper/cardboard, glass, metal, and plastic. It was demonstrated that variance in recycling behaviour can be divided into a smaller general part that is relatively stable ...
Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.
Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization
Ensuring energy security has been at the centre of the IEA mission since its inception, following the oil crises of the early 1970s. While the security of oil supplies remains important, contemporary energy security policies must address all energy sources and cover a comprehensive range of natural, economic and political risks that affect energy sources, infrastructures and services. In response to this challenge, the IEA is currently developing a Model Of Short-term Energy Security (MOSES) to evaluate the energy security risks and resilience capacities of its member countries. The current version of MOSES covers short-term security of supply for primary energy sources and secondary fuels among IEA countries. It also lays the foundation for analysis of vulnerabilities of electricity and end-use energy sectors. MOSES contains a novel approach to analysing energy security, which can be used to identify energy security priorities, as a starting point for national energy security assessments and to track the evolution of a country's energy security profile. By grouping together countries with similar 'energy security profiles', MOSES depicts the energy security landscape of IEA countries. By extending the MOSES methodology to electricity security and energy services in the future, the IEA aims to develop a comprehensive policy-relevant perspective on global energy security. This Working Paper is intended for readers who wish to explore the MOSES methodology in depth; there is also a brochure which provides an overview of the analysis and results.
Security is today considered as a basic foundation in software development and therefore, the modelling and implementation of security requirements is an essential part of the production of secure software systems. Information technology organisations are moving towards agile development methods in order to satisfy customers' changing requirements in light of accelerated evolution and time restrictions with their competitors in software production. Security engineering is considered difficult...
Dong-Young Yoo; Jong-Whoi Shin; Jin-Young Choi
Social interest and demand on Home-Network has been increasing greatly. Although various services are being introduced to respond to such demands, they can cause serious security problems when linked to the open network such as Internet. This paper reviews the security requirements to protect the service users with assumption that the Home-Network environment is connected to Internet and then proposes the security model based on the requirement. The proposed security mode...
Yu Long Fu
Full Text Available The security of protocol implementation is important and hard to be verified. Since the penetration testing is usually based on the experience of the security tester and the specific protocol specifications, a formal and automatic verification method is always required. In this paper, we propose an extended model of IOLTS to describe the legal roles and intruders of security protocol implementations, and then combine them together to generate the suitable test cases to verify the security of protocol implementation.
Chelgren, Nathan; Adams, Michael J.; Bailey, Larissa L.; Bury, R. Bruce
Studies of the distribution of elusive forest wildlife have suffered from the confounding of true presence with the uncertainty of detection. Occupancy modeling, which incorporates probabilities of species detection conditional on presence, is an emerging approach for reducing observation bias. However, the current likelihood modeling framework is restrictive for handling unexplained sources of variation in the response that may occur when there are dependence structures such as smaller sampling units that are nested within larger sampling units. We used multilevel Bayesian occupancy modeling to handle dependence structures and to partition sources of variation in occupancy of sites by terrestrial salamanders (family Plethodontidae) within and surrounding an earlier wildfire in western Oregon, USA. Comparison of model fit favored a spatial N-mixture model that accounted for variation in salamander abundance over models that were based on binary detection/non-detection data. Though catch per unit effort was higher in burned areas than unburned, there was strong support that this pattern was due to a higher probability of capture for individuals in burned plots. Within the burn, the odds of capturing an individual given it was present were 2.06 times the odds outside the burn, reflecting reduced complexity of ground cover in the burn. There was weak support that true occupancy was lower within the burned area. While the odds of occupancy in the burn were 0.49 times the odds outside the burn among the five species, the magnitude of variation attributed to the burn was small in comparison to variation attributed to other landscape variables and to unexplained, spatially autocorrelated random variation. While ordinary occupancy models may separate the biological pattern of interest from variation in detection probability when all sources of variation are known, the addition of random effects structures for unexplained sources of variation in occupancy and detection
Damman, Olga C.; Stubbe, Janine H.; Hendriks, Michelle; Arah, Onyebuchi A.; Spreeuwenberg, Peter; Delnoij, Diana M. J.; Groenewegen, Peter P.
Background: Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for
Agarwal, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Lorch, Markus [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Thompson, Mary [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Perry, Marcia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Prevalent authentication and authorization models for distributed systems provide for the protection of computer systems and resources from unauthorized use. The rules and policies that drive the access decisions in such systems are typically configured up front and require trust establishment before the systems can be used. This approach does not work well for computer software that moderates human-to-human interaction. This work proposes a new model for trust establishment and management in computer systems supporting collaborative work. The model supports the dynamic addition of new users to a collaboration with very little initial trust placed into their identity and supports the incremental building of trust relationships through endorsements from established collaborators. It also recognizes the strength of a users authentication when making trust decisions. By mimicking the way humans build trust naturally the model can support a wide variety of usage scenarios. Its particular strength lies in the support for ad-hoc and dynamic collaborations and the ubiquitous access to a Computer Supported Collaboration Workspace (CSCW) system from locations with varying levels of trust and security.
Hald, Sara Ligaard; Pedersen, Jens Myrup; Prasad, Neeli R.
With the increasing focus on security in information systems, it is becoming necessary to be able to describe and compare security attributes for different technologies. Existing are well-described and comprehensive, but expensive and resource demanding to apply. The Security Evaluation...... for Compliance (SEC) model offers a lightweight alternative for use by decision makers to get a quick overview of the security attributes of different technologies for easy comparison and requirement compliance evaluation. The scientific contribution is this new approach to security modelling as well...
Valente, Maria I B; Vettore, Mario V
To investigate the relationship of contextual and individual factors with periodontal disease in dentate adults and older people using the Andersen's behavioural model. Secondary individual data from 6011 adults and 2369 older people from the Brazilian Oral Health Survey (2010) were combined with contextual data for 27 cities. Attachment loss (AL) categories for each sextant were coded and summed to obtain the periodontal disease measure. The association of predisposing, enabling and need characteristics at city and individual level with periodontal disease was assessed using an adapted version of the Andersen's behavioural model. Multilevel Poisson regression was used to estimate rate ratios (RR) and 95% CIs. Periodontal disease was associated with contextual predisposing (RR 0.93; 95% CI = 0.87-0.99) and enabling factors (RR 0.99; 95% CI = 0.98-0.99) in adults. Contextual predisposing was also associated with periodontal disease in older people (RR 0.82; 95% CI = 0.73-0.92). Individual predisposing (age, sex and schooling) and need characteristics (perceived treatment need) were common predictors of periodontal disease in adults and older people. Periodontal disease was also associated with behaviours in the latter age group. Contextual predisposing factors and individual characteristics influenced periodontal disease experience in adults and older people. Contextual enabling factors were also meaningful determinants of periodontal disease in the former age group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
V. S. Oladko
Full Text Available The article deals with the problem assessment of information security risks in the ERP-system. ERP-system functions and architecture are studied. The model malicious impacts on levels of ERP-system architecture are composed. Model-based risk assessment, which is the quantitative and qualitative approach to risk assessment, built on the partial unification 3 methods for studying the risks of information security - security models with full overlapping technique CRAMM and FRAP techniques developed.
Prajapati, Sanjay; Verma, Shivam; Kulkarni, Anant Aravind; Kaushik, Brajesh Kumar
Spin-transfer torque (STT) and spin-orbit torque (SOT) based magnetic tunnel junction (MTJ) devices are emerging as strong contenders for the next generation memories. Conventional STT magneto-resistive random access memory (MRAM) offers lower power, non-volatility and CMOS process compatibility. However, higher current requirement during the write operation leads to tunnel barrier reliability issues and larger access devices. SOT-MRAM eliminates the reliability issues with strong spin polarized current (100%) and separate read/write current paths; however, the additional two access transistors in SOT-MRAM results into increased cell area. Multilevel cell (MLC) structure paves a way to circumvent the problems related to the conventional STT/SOT based MTJ devices and provides enhanced integration density at reduced cost per bit. Conventional STT/SOT-MRAM requires a unit cell area of 10-60 F2 and reported simulations have been based on available single-level MTJ compact models. However, till date no compact model exists that can capture the device physics of MLC-MTJ accurately. Hence, a novel compact model is proposed in this paper to capture the accurate device physics and behaviour of the MLC-MTJs. It is designed for MLCs with different MTJ configurations demonstrated so far, such as series and parallel free layer based MLC-MTJs. The proposed model is coded in Verilog-A, which is compatible with SPICE for circuit level simulations. The model is in close agreement with the experimental results exhibiting an average error of less than 15%.
Full Text Available Ordinal logistic regression models are used to predict the dependent variable, when dependent variable is of ordinal type in both the situation for single level and multilevel. The most used model for ordinal regression is the Proportional Odd (PO model which assumes that the effect of the each predictor remains same for each category of the response variable. To estimate the wealth index of household in the province Punjab the proportional odds model is used. The wealth index is an order categorical dependent variable having five categories. The data MICS (2014, a multiple indicator cluster survey conduct by Punjab bureau of statistics was used in this article. The data was recorded at different level such as individual level (household level, district level and division level. The secondary data MICS contains a sample of 41413 household collected from both rural and urban areas of the province Punjab. In the present study analysis were made for single level (household level and two levels (division level. After fitting the proportional odds model for the single level the proportionality assumption is tested by the brand test whose results suggest that all the predictors fulfill assumption of proportional odds. The significance value suggests that all the predictors have significant effect on the wealth index. The variation due to division level was estimated by two level ordinal logistic regression equal to 5.842, and the Intra Class Correlation ICC is equal to 0.6397 which show that 63.97% of total variation is due to division level.
Sabeur, Zoheir; Chakravarthy, Ajay; Bashevoy, Maxim; Modafferi, Stefano
The rapid increase in environmental observations which are conducted by Small to Medium Enterprise communities and volunteers using affordable in situ sensors at various scales, in addition to the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing speeds. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached paramount importance. Specifically, it has become highly critical now to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources. The early stage aggregation of data will enable the pre-processing of data from multiple sources while reconciling the temporal gaps in measurement time series, and aligning their respective a-synchronicities. This low level type of data fusion process needs to be automated and chained to more advanced level of data fusion services specialising in observation forecasts at spaces where sensing is not deployed; or at time slices where sensing has not taken place yet. As a result, multi-level fusion services are required among the families of specific enablers for monitoring environments and spaces in the Future Internet. These have been intially deployed and piloted in the ongoing ENVIROFI project of the FI-PPP programme . Automated fusion and modelling of in situ and remote sensing data has been set up and the experimentation successfully conducted using RBF networks for the spatial fusion of water quality parameters measurements from satellite and stationary buoys in the Irish Sea. The RBF networks method scales for the spatial data fusion of multiple types of observation sources. This
Wagaman, M. Alex; Geiger, Jennifer Mullins; Bermudez-Parsai, Monica; Hedberg, E. C.
Although schools have been trying to address bulling by utilizing different approaches that stop or reduce the incidence of bullying, little remains known about what specific intervention strategies are most successful in reducing bullying in the school setting. Using the social-ecological framework, this paper examines school-based disciplinary interventions often used to deliver consequences to deter the reoccurrence of bullying and aggressive behaviors among school-aged children. Data for this study are drawn from the School-Wide Information System (SWIS) with the final analytic sample consisting of 1,221 students in grades K – 12 who received an office disciplinary referral for bullying during the first semester. Using Kaplan-Meier Failure Functions and Multi-level discrete time hazard models, determinants of the probability of a student receiving a second referral over time were examined. Of the seven interventions tested, only Parent-Teacher Conference (AOR=0.65, pbullying and aggressive behaviors. By using a social-ecological framework, schools can develop strategies that deter the reoccurrence of bullying by identifying key factors that enhance a sense of connection between the students’ mesosystems as well as utilizing disciplinary strategies that take into consideration student’s microsystem roles. PMID:22878779
Jung, Minsoo; Choi, Mankyu
There has been little conceptual understanding as to how community capacity works, although it allows for an important, population-based health promotional strategy. In this study, the mechanism of community capacity was studied through literature reviews to suggest a comprehensive conceptual model. The research results found that the key to community capacity prevailed in how actively the capacities of individuals and their communities are able to interact with one another. Under active interactions, community-based organizations, which are a type of voluntary association, were created within the community, and cohesion among residents was enhanced. In addition, people were more willing to address community issues. During the process, many services were initiated to meet the people's health needs and strengthen their social and psychological ties. The characteristics of community capacity were named as the contextual multilevel effects. Because an increase in community capacity contributes to a boosted health status, encourages health behaviors, and eventually leads to the overall prosperity of the community, more public health-related attention is required.
Peeters, Geert; Debbaut, Charlotte; Laleman, Wim; Monbaliu, Diethard; Vander Elst, Ingrid; Detrez, Jan R; Vandecasteele, Tim; De Schryver, Thomas; Van Hoorebeke, Luc; Favere, Kasper; Verbeke, Jonas; Segers, Patrick; Cornillie, Pieter; De Vos, Winnok H
The intricate (micro)vascular architecture of the liver has not yet been fully unravelled. Although current models are often idealized simplifications of the complex anatomical reality, correct morphological information is instrumental for scientific and clinical purposes. Previously, both vascular corrosion casting (VCC) and immunohistochemistry (IHC) have been separately used to study the hepatic vasculature. Nevertheless, these techniques still face a number of challenges such as dual casting in VCC and limited imaging depths for IHC. We have optimized both techniques and combined their complementary strengths to develop a framework for multilevel reconstruction of the hepatic circulation in the rat. The VCC and micro-CT scanning protocol was improved by enabling dual casting, optimizing the contrast agent concentration, and adjusting the viscosity of the resin (PU4ii). IHC was improved with an optimized clearing technique (CUBIC) that extended the imaging depth for confocal microscopy more than five-fold. Using in-house developed software (DeLiver), the vascular network - in both VCC and IHC datasets - was automatically segmented and/or morphologically analysed. Our methodological framework allows 3D reconstruction and quantification of the hepatic circulation, ranging from the major blood vessels down to the intertwined and interconnected sinusoids. We believe that the presented framework will have value beyond studies of the liver, and will facilitate a better understanding of various parenchymal organs in general, in physiological and pathological circumstances. © 2016 Anatomical Society.
Del Piccolo, Lidia; Mazzi, Maria Angela; Dunn, Graham; Sandri, Marco; Zimmermann, Christa
The aims of the study were to explore the importance of macro (patient, physician, consultation) and micro (doctor-patient speech sequences) variables in promoting patient cues (unsolicited new information or expressions of feelings), and to describe the methodological implications related to the study of speech sequences. Patient characteristics, a consultation index of partnership and doctor-patient speech sequences were recorded for 246 primary care consultations in six primary care surgeries in Verona, Italy. Homogeneity and stationarity conditions of speech sequences allowed the creation of a hierarchy of multilevel logit models including micro and macro level variables, with the presence/absence of cues as the dependent variable. We found that emotional distress of the patient increased cues and that cues appeared among other patient expressions and were preceded by physicians' facilitations and handling of emotion. Partnership, in terms of open-ended inquiry, active listening skills and handling of emotion by the physician and active participation by the patient throughout the consultation, reduced cue frequency.
The majority of research on sibling relationships has investigated only one or two siblings in a family, but there are many theoretical and methodological limitations to this single dyadic perspective. This study uses multiple siblings (541 adults) in 184 families, where 96 of these families had all siblings complete the study, to demonstrate the value in including full sibling groups when conducting research on sibling relationships. Two scales, positivity and willingness to sacrifice, are evaluated with a multilevel model to account for the nested nature of family relationships. The distribution of variance across three levels: relationship, individual, and family are computed, and results indicate that the relationship level explains the most variance in positivity, whereas the individual level explains the majority of variance in willingness to sacrifice. These distributions are affected by gender composition and family size. The results of this study highlight an important and often overlooked element of family research: The meaning of a scale changes based on its distribution of variance at these three levels. Researchers are encouraged to be cognizant of the variance distribution of their scales when studying sibling relationships and to incorporate more full sibling groups into their research methods and study design. © 2015 Family Process Institute.
Raab, Melinda; Dunst, Carl J; Hamby, Deborah W
The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Igor Gomes Menezes
Full Text Available Large-scale educational assessment has been established as source of descriptive, evaluative and interpretative information that influence educational policies worldwide throughout the last third of the 20th century. In the 1990s the Brazilian Ministry of Education developed the National Basic Education Assessment System (SAEB that regularly measures management, resource and contextual school features and academic achievement in public and private institutions. In 2005, after significant piloting and review of the SAEB, a new sampling strategy was taken and Prova Brasil became the new instrument used by the Ministry to assess skills in Portuguese (reading comprehension and Mathematics (problem solving, as well as collecting contextual information concerning the school, principal, teacher, and the students. This study aims to identify which variables are predictors of academic achievement of fifth grade students on Prova Brasil. Across a large sample of students, multilevel models tested a large number of variables relevant to student achievement. This approach uncovered critical variables not commonly seen as significant in light of other achievement determinants, including student habits, teacher ethnicity, and school technological resources. As such, this approach demonstrates the value of MLM to appropriately nuanced educational policies that reflect critical influences on student achievement. Its implications for wider application for psychology studies that may have relevant impacts for policy are also discussed.
Mario Arturo Ruiz Estrada
This paper proposes the construction of the Minimum Food Security Quota (MFSQuota)using mathematical economic modelling in real time. The MFS-Quota fixes a certain amount of annual food storage to prepare a country for any natural or social disasters. Any country can construct its own MFS-Quota for “food security policy”.
Liu, Y. R.; Li, Y. P.; Huang, G. H.; Zhang, J. L.; Fan, Y. R.
In this study, a Bayesian-based multilevel factorial analysis (BMFA) method is developed to assess parameter uncertainties and their effects on hydrological model responses. In BMFA, Differential Evolution Adaptive Metropolis (DREAM) algorithm is employed to approximate the posterior distributions of model parameters with Bayesian inference; factorial analysis (FA) technique is used for measuring the specific variations of hydrological responses in terms of posterior distributions to investigate the individual and interactive effects of parameters on model outputs. BMFA is then applied to a case study of the Jinghe River watershed in the Loess Plateau of China to display its validity and applicability. The uncertainties of four sensitive parameters, including soil conservation service runoff curve number to moisture condition II (CN2), soil hydraulic conductivity (SOL_K), plant available water capacity (SOL_AWC), and soil depth (SOL_Z), are investigated. Results reveal that (i) CN2 has positive effect on peak flow, implying that the concentrated rainfall during rainy season can cause infiltration-excess surface flow, which is an considerable contributor to peak flow in this watershed; (ii) SOL_K has positive effect on average flow, implying that the widely distributed cambisols can lead to medium percolation capacity; (iii) the interaction between SOL_AWC and SOL_Z has noticeable effect on the peak flow and their effects are dependent upon each other, which discloses that soil depth can significant influence the processes of plant uptake of soil water in this watershed. Based on the above findings, the significant parameters and the relationship among uncertain parameters can be specified, such that hydrological model's capability for simulating/predicting water resources of the Jinghe River watershed can be improved.
Full Text Available Abstract Background Using routinely collected patient data we explore the utility of multilevel latent class (MLLC models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs. Methods Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640. Patient age, sex, stage-at-diagnosis (Dukes, and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. Results Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years, and one with better prognosis (39.3% died within 3 years. In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. Conclusions A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments and factors associated with the processes of healthcare delivery (e.g. delays. Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.
Moroz Maxim O.
Full Text Available The article explores approaches to modelling the system of ensuring the investment security. Necessity of observance of investment security of Ukraine has been substantiated. The author’s own vision of the modelling essentials has been provided. The eligibility for consideration of the system of ensuring the investment security of Ukraine in the functional, structural, process, formative, and factor aspects has been proved. The target setting and tasks of a functional model of the system of ensuring the investment security have been defined. The functions, subjects, organizational-economic mechanisms of the system of ensuring the investment security of Ukraine have been characterized. A structural model of the system of ensuring the investment security has been presented. Special attention has been given to the definition of objects of direct and indirect influence, control and controlled subsystems, aggregate of indicators, safe levels, principles of formation of the investment security system. The process and formative models of the system of ensuring the investment security, as well as the algorithm of the complex assessment of the level of investment security, were analyzed in detail. Measures to ensure the investment security of Ukraine have been defined.
Ma Jie; Guo Lifeng; Zhang Yusheng; Peng Qiao; Ruan Minzhi
In order to improve the ability of condition monitoring and fault diagnostic system, a hybrid intelligent diagnostic system based on multilevel flow model (MFM) and information fusion was proposed. This method utilized information fusion technique to improve the rapidness and veracity of fault diagnosis, and made use of MFM to explain the alarm propagation path, which could enhance the comprehension of diagnostic result. The emulation test proves that the hybrid intelligent diagnostic system can identify fault and propose the alarm analysis quickly. (authors)
Maxwell, Sophie; Reynolds, Katherine J.; Lee, Eunro; Subasic, Emina; Bromhead, David
School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add “value” to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic d...
Cho, Sun-Joo; Goodwin, Amanda P
When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.
Fabian C.C. Uzoh; William W. Oliver
A diameter increment model is developed and evaluated for individual trees of ponderosa pine throughout the species range in the United States using a multilevel linear mixed model. Stochastic variability is broken down among period, locale, plot, tree and within-tree components. Covariates acting at tree and stand level, as breast height diameter, density, site index...
Title: Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Panel Data, Multilevel, and Spatial Econometric Models with Case Studies. The title used at the start of this project was Transportation and Soc...
Almohri, Hussain M. J.
Despite the recent advances in systems and network security, attacks on large enterprise networks consistently impose serious challenges to maintaining data privacy and software service integrity. We identify two main problems that contribute to increasing the security risk in a networked environment: (i) vulnerable servers, workstations, and…
Mouheb, Djedjiga; Pourzandi, Makan; Wang, Lingyu; Nouh, Mariam; Ziarati, Raha; Alhadidi, Dima; Talhi, Chamseddine; Lima, Vitor
This book comprehensively presents a novel approach to the systematic security hardening of software design models expressed in the standard UML language. It combines model-driven engineering and the aspect-oriented paradigm to integrate security practices into the early phases of the software development process. To this end, a UML profile has been developed for the specification of security hardening aspects on UML diagrams. In addition, a weaving framework, with the underlying theoretical foundations, has been designed for the systematic injection of security aspects into UML models. The
This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors have assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed.
Nielsen, Jesper Buus
the channels by which they communicate. A general solution to the secure multiparty computation problem is a compiler which given any feasible function describes an efficient protocol which allows the parties to compute the function securely on their local inputs over an open network. Over the past twenty...... previous approaches to the problem. Starting from an open point-to-point network there is a long way to general secure multiparty computation. The dissertation contains contributions at several points along the way. In particular we investigate how to realize secure channels. We also show how threshold...... you as possible. This is the general problem of secure multiparty computation. The usual way of formalizing the problem is to say that a number of parties who do not trust each other wish to compute some function of their local inputs, while keeping their inputs as secret as possible and guaranteeing...
Ntoumanis, N; Stenling, A; Thøgersen-Ntoumani, C; Vlachopoulos, S; Lindwall, M; Gucciardi, D F; Tsakonitis, C
Past work linking exercise identity and exercise motivation has been cross-sectional. This is the first study to model the relations between different types of exercise identity and exercise motivation longitudinally. Understanding the dynamic associations between these sets of variables has implications for theory development and applied research. This was a longitudinal survey study. Participants were 180 exercisers (79 men, 101 women) from Greece, who were recruited from fitness centers and were asked to complete questionnaires assessing exercise identity (exercise beliefs and role-identity) and exercise motivation (intrinsic, identified, introjected, external motivation, and amotivation) three times within a 6 month period. Multilevel growth curve modeling examined the role of motivational regulations as within- and between-level predictors of exercise identity, and a model in which exercise identity predicted exercise motivation at the within- and between-person levels. Results showed that within-person changes in intrinsic motivation, introjected, and identified regulations were positively and reciprocally related to within-person changes in exercise beliefs; intrinsic motivation was also a positive predictor of within-person changes in role-identity but not vice versa. Between-person differences in the means of predictor variables were predictive of initial levels and average rates of change in the outcome variables. The findings show support to the proposition that a strong exercise identity (particularly exercise beliefs) can foster motivation for behaviors that reinforce this identity. We also demonstrate that such relations can be reciprocal overtime and can depend on the type of motivation in question as well as between-person differences in absolute levels of these variables. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.
The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in
Huang, C.-H. [Fermilab; Wildish, T. [Princeton U.; Zhang, X. [Beijing, Inst. High Energy Phys.
PhEDEx, the data-placement tool used by the CMS experiment at the LHC, was conceived in a more trusting time. The security model provided a safe environment for site agents and operators, but offerred little more protection than that. Data was not sufficiently protected against loss caused by operator error or software bugs or by deliberate manipulation of the database. Operators were given high levels of access to the database, beyond what was actually needed to accomplish their tasks. This exposed them to the risk of suspicion should an incident occur. Multiple implementations of the security model led to difficulties maintaining code, which can lead to degredation of security over time. In order to meet the simultaneous goals of protecting CMS data, protecting the operators from undue exposure to risk, increasing monitoring capabilities and improving maintainability of the security model, the PhEDEx security model was redesigned and re-implemented. Security was moved from the application layer into the database itself, fine-grained access roles were established, and tools and procedures created to control the evolution of the security model over time. In this paper we describe this work, we describe the deployment of the new security model, and we show how these enhancements improve security on several fronts simultaneously.
Leeuw, Jan de; Meijer, Erik
... appropriate and eﬃcient model-based methods have become available to deal with this issue, that we have come to appreciate the power that more complex models provide for describing the world and providing new insights. This book sets out to present some of the most recent developments in what has come to be known as multilevel modelling. An...
Karassin, Orr; Bar-Haim, Aviad
The multilevel empirical study of the antecedents of corporate social responsibility (CSR) has been identified as "the first knowledge gap" in CSR research. Based on an extensive literature review, the present study outlines a conceptual multilevel model of CSR, then designs and empirically validates an operational multilevel model of the principal driving factors affecting corporate environmental responsibility (CER), as a measure of CSR. Both conceptual and operational models incorporate three levels of analysis: institutional, organizational, and individual. The multilevel nature of the design allows for the assessment of the relative importance of the levels and of their components in the achievement of CER. Unweighted least squares (ULS) regression analysis reveals that the institutional-level variables have medium relationships with CER, some variables having a negative effect. The organizational level is revealed as having strong and positive significant relationships with CER, with organizational culture and managers' attitudes and behaviors as significant driving forces. The study demonstrates the importance of multilevel analysis in improving the understanding of CSR drivers, relative to single level models, even if the significance of specific drivers and levels may vary by context. Copyright © 2016 Elsevier Ltd. All rights reserved.
Chockalingam, S.; Pieters, W.; Herdeiro Teixeira, A.M.; van Gelder, P.H.A.J.M.; Lipmaa, Helger; Mitrokotsa, Aikaterini; Matulevicius, Raimundas
Bayesian Networks (BNs) are an increasingly popular modelling technique in cyber security especially due to their capability to overcome data limitations. This is also instantiated by the growth of BN models development in cyber security. However, a comprehensive comparison and analysis of these
Full Text Available Multilevel analyses are ideally suited to assess the effects of ecological (higher level and individual (lower level exposure variables simultaneously. In applying such analyses to measures of ecologies in epidemiological studies, individual variables are usually aggregated into the higher level unit. Typically, the aggregated measure includes responses of every individual belonging to that group (i.e. it constitutes a self-included measure. More recently, researchers have developed an aggregate measure which excludes the response of the individual to whom the aggregate measure is linked (i.e. a self-excluded measure. In this study, we clarify the substantive and technical properties of these two measures when they are used as exposures in multilevel models.Although the differences between the two aggregated measures are mathematically subtle, distinguishing between them is important in terms of the specific scientific questions to be addressed. We then show how these measures can be used in two distinct types of multilevel models-self-included model and self-excluded model-and interpret the parameters in each model by imposing hypothetical interventions. The concept is tested on empirical data of workplace social capital and employees' systolic blood pressure.Researchers assume group-level interventions when using a self-included model, and individual-level interventions when using a self-excluded model. Analytical re-parameterizations of these two models highlight their differences in parameter interpretation. Cluster-mean centered self-included models enable researchers to decompose the collective effect into its within- and between-group components. The benefit of cluster-mean centering procedure is further discussed in terms of hypothetical interventions.When investigating the potential roles of aggregated variables, researchers should carefully explore which type of model-self-included or self-excluded-is suitable for a given situation
Suzuki, Etsuji; Yamamoto, Eiji; Takao, Soshi; Kawachi, Ichiro; Subramanian, S V
Multilevel analyses are ideally suited to assess the effects of ecological (higher level) and individual (lower level) exposure variables simultaneously. In applying such analyses to measures of ecologies in epidemiological studies, individual variables are usually aggregated into the higher level unit. Typically, the aggregated measure includes responses of every individual belonging to that group (i.e. it constitutes a self-included measure). More recently, researchers have developed an aggregate measure which excludes the response of the individual to whom the aggregate measure is linked (i.e. a self-excluded measure). In this study, we clarify the substantive and technical properties of these two measures when they are used as exposures in multilevel models. Although the differences between the two aggregated measures are mathematically subtle, distinguishing between them is important in terms of the specific scientific questions to be addressed. We then show how these measures can be used in two distinct types of multilevel models-self-included model and self-excluded model-and interpret the parameters in each model by imposing hypothetical interventions. The concept is tested on empirical data of workplace social capital and employees' systolic blood pressure. Researchers assume group-level interventions when using a self-included model, and individual-level interventions when using a self-excluded model. Analytical re-parameterizations of these two models highlight their differences in parameter interpretation. Cluster-mean centered self-included models enable researchers to decompose the collective effect into its within- and between-group components. The benefit of cluster-mean centering procedure is further discussed in terms of hypothetical interventions. When investigating the potential roles of aggregated variables, researchers should carefully explore which type of model-self-included or self-excluded-is suitable for a given situation, particularly
Yang, Zheng; Becerik-Gerber, Burcin
consistently well for both ECMs. Specific contributions of the study presented in this paper are the introduction of a novel calibration framework for multi-level simulation calibration, and improvements to the robustness of the calibrated model for different ECMs
Sanchez, R.; Mondot, J.
A new model for multigroup transport calculations based on a group-dependent spatial representation has been developed. The multilevel method takes advantage of the orthogonality of the energy and space operators, inherent to the structure of the linear transport equation, to decompose the energy domain into subdomains or levels, i.e., fast, epithermal and thermal, where suitable spatial approximations are used. The aim of the method is to allow for the use of larger mesh spacings at high neutron energies and, therefore, to cut down the computational cost while preserving the overall accuracy. The method can be easily implemented in today's standard transport codes by introducing small modifications in the computation of the multigroup external source. The multilevel model is of special interest for the calculation of media containing high thermal absorbers. A variant of this method, based on a nested, multilevel approximation, has been implemented in the APOLLO-II assembly transport code. Comparisons between the multilevel model and the usual multigroup approximation have been made for a PWR poisoned cell and for a thermal neutron barrier used to feed a molten FBR fuel sample. The results show that significant savings in computational times are obtained with the multilevel approximation. 10 refs
Abbas, R.; Farooq, A.
Cloud computing is a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. It has many service modes like Software as-a-Service (SaaS), Platform-as-a-Service (PaaS), Infrastructure-as-a-Service (IaaS). In SaaS model, service providers install and activate the applications in cloud and cloud customers access the software from cloud. So, the user does not have the need to purchase and install a particular software on his/her machine. While using SaaS model, there are multiple security issues and problems like Data security, Data breaches, Network security, Authentication and authorization, Data integrity, Availability, Web application security and Backup which are faced by users. Many researchers minimize these security problems by putting in hard work. A large work has been done to resolve these problems but there are a lot of issues that persist and need to overcome. In this research work, we have developed a security model that improves the security of data according to the desire of the End-user. The proposed model for different data security options can be helpful to increase the data security through which trade-off between functionalities can be optimized for private and public data. (author)
Ahmed, Naveed; Jensen, Christian D.
Most methods for protocol analysis classify protocols as “broken” if they are vulnerable to attacks from a strong attacker, e.g., assuming the Dolev-Yao attacker model. In many cases, however, exploitation of existing vulnerabilities may not be practical and, moreover, not all applications may......; for each fine level authentication goal, we determine the “least strongest-attacker” for which the authentication goal can be satisfied. We demonstrate that this model can be used to reason about the security of supposedly insecure protocols. Such adaptability is particularly useful in those applications...
Cao, Bo-Ling; Shi, Xiu-Quan; Qi, Yong-Hong; Hui, Ya; Yang, Hua-Jun; Shi, Shang-Peng; Luo, Li-Rong; Zhang, Hong; Wang, Xin; Yang, Ying-Ping
To explore the effect of a school-family-individual (SFI) multi-level education intervention model on knowledge and attitudes about accidental injuries among school-aged children to improve injury prevention strategies and reduce the incidence of pediatric injuries. The random sample of rural school-aged children were recruited by using a multistage, stratified, cluster sampling method in Zunyi, Southwest China from 2012 to 2014, and 2342 children were randomly divided into intervention and control groups. Then children answered a baseline survey to collect knowledge and attitude scores (KAS) of accidental injuries. In the intervention group, children, their parents/guardians and the school received a SFI multi-level education intervention, which included a children's injury-prevention poster at schools, an open letter about security instruction for parents/guardians and multiple-media health education (Microsoft PowerPoint lectures, videos, handbooks, etc.) to children. Children in the control group were given only handbook education. After 16 months, children answered a follow-up survey to collect data on accidental injury types and accidental injury-related KAS for comparing the intervention and control groups and baseline and follow-up data. The distribution of gender was not significantly different while age was different between the baseline and follow-up survey. At baseline, the mean KAS was lower for the intervention than control group (15.37 ± 3.40 and 18.35 ± 5.01; p children's injury-related KAS improved in the intervention group. Moreover, the KAS between the groups differed for most subtypes of incidental injuries (based on International Classification of Diseases 10, ICD-10) (p children had reported their accident injury episodes, while after intervention 237 children had reported their accidental injury episodes in the follow-up survey. SFI multi-level education intervention could significantly increase KAS for accidental injuries, which should
Maulana, Ridwan; Opdenakker, Marie-Christine; Bosker, Roel
Research has shown that the teacher-student interpersonal relationship (TSIR) is important for student motivation. Although TSIR has received a growing interest, there are only few studies that focus on changes and links between TSIR and student academic motivation in a longitudinal fashion in non-Western contexts. This study investigated changes in TSIR and links with academic motivation as perceived by first-grade secondary school students in Indonesia. TSIR was studied from the perspective of interpersonal behaviour in terms of Influence and Proximity. Students' academic motivation was studied from the perspective of self-determination theory. A total of 504 first-grade secondary school students of 16 mathematics and English classes participated in the study. Surveys were administered in five waves throughout the school year. Multilevel growth curve modelling was applied. Contrary to the (limited) general research findings from Western contexts, we found that the quality of TSIR (student perceptions) increased over time. The increase was slightly more pronounced for Proximity than for Influence. In accordance with the findings for the Western countries, the level of students' controlled motivation increased, while that of autonomous motivation decreased over time. However, the negative change in autonomous motivation was less pronounced. As in Western countries, TSIR was longitudinally linked with academic motivation, in particular, with autonomous motivation. Evidence is found that TSIR can change in a favourable way, and this positively affects student motivation. Future research could benefit from unravelling the influences of cultures on changes in TSIR in broader contexts. © 2013 The British Psychological Society.
Damman, O.C.; Stubbe, J.H.; Hendriks, M.; Arah, O.A.; Spreeuwenberg, P.; Delnoij, D.M.J.; Groenewegen, P.P.
Background: Ratings on the quality of healthcare from the consumer’s perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for
Damman, O.C.; Stubbe, J.H.; Hendriks, M.; Arah, O.A.; Spreeuwenberg, P.; Delnoij, D.M.J.; Groenewegen, P.P.
Background: Ratings on the quality of healthcare from the consumer’s perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for
Ramsey, Jase R.; Barakat, Livia L.; Aad, Amine Abi
Adopting a multilevel theoretical framework, we examined how metacognitive and motivational cultural intelligence influence an individual's commitment to the study of international business (IB). Data from 292 undergraduate and graduate business students nested in 12 U.S. business school classes demonstrated that individuals' metacognitive and…
Song, J; Zhao, H; Pan, C; Li, C; Liu, J; Pan, Y
Chronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting. Fifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters. Compared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P < 0.001), thus establishing that MLM data analysis was necessary. Site-level had effects on PD and CAL reduction; those variables could explain 77-78% of PD reduction and 70-80% of CAL reduction at 3, 6, and 12 months. Other levels only
Correia, Anacleto; Gonçalves, António; Teodoro, M. Filomena
The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.
Wu, Jing; Zhang, Laibin; Lind, Morten
HAZOP studies are widely accepted in chemical and petroleum industries as the method for conducting process hazard analysis related to design, maintenance and operation of the systems. Different tools have been developed to automate HAZOP studies. In this paper, a HAZOP reasoning method based...... on function-oriented modeling, Multilevel Flow Modeling (MFM), is extended with function roles. A graphical MFM editor, which is combined with the reasoning capabilities of the MFM Workbench developed by DTU is applied to automate HAZOP studies. The method is proposed to support the “brain-storming” sessions...
Liu, Kai; Wang, Jiangbo; Yamamoto, Toshiyuki; Morikawa, Takayuki
Highlights: • The impacts of driving heterogeneity on EVs’ energy efficiency are examined. • Several multilevel mixed-effects regression models are proposed and compared. • The most reasonable nested structure is extracted from the long term GPS data. • Proposed model improves the energy estimation accuracy by 7.5%. - Abstract: To improve the accuracy of estimation of the energy consumption of electric vehicles (EVs) and to enable the alleviation of range anxiety through the introduction of EV charging stations at suitable locations for the near future, multilevel mixed-effects linear regression models were used in this study to estimate the actual energy efficiency of EVs. The impacts of the heterogeneity in driving behaviour among various road environments and traffic conditions on EV energy efficiency were extracted from long-term daily trip-based energy consumption data, which were collected over 12 months from 68 in-use EVs in Aichi Prefecture in Japan. Considering the variations in energy efficiency associated with different types of EV ownership, different external environments, and different driving habits, a two-level random intercept model, three two-level mixed-effects models, and two three-level mixed-effects models were developed and compared. The most reasonable nesting structure was determined by comparing the models, which were designed with different nesting structures and different random variance component specifications, thereby revealing the potential correlations and non-constant variability of the energy consumption per kilometre (ECPK) and improving the estimation accuracy by 7.5%.
Full text: Nuclear security culture found its way into professional parlance several years ago, but still lacks an agreed-upon definition and description. The February 2005 U.S.-Russian Joint Statement, issued at the presidential summit meeting in Bratislava, referred specifically to security culture, focusing renewed attention on the concept. Numerous speakers at the March 2005 International Atomic Energy Agency's (IAEA) international conference on nuclear security referred to security culture, but their visions and interpretations were often at odds with one another. Clearly, there is a need for a generic model of nuclear security culture with universal applicability. Internationally acceptable standards in this area would be invaluable for evaluation, comparison, cooperation, and assistance. They would also help international bodies better manage their relations with the nuclear sectors in various countries. This paper will develop such a model. It will use the IAEA definition of nuclear security, and then apply Edgar Schein's model of organizational culture to security culture at a generic nuclear facility. A cultural approach to physical protection involves determining what attitudes and beliefs need to be established in an organization, how these attitudes and beliefs manifest themselves in the behavior of assigned personnel, and how desirable attitudes and beliefs can be transcribed into formal working methods to produce good outcomes, i.e., effective protection. The security-culture mechanism I will propose is broken into four major units: facility leadership, proactive policies and procedures, personnel performance, and learning and professional improvement. The paper will amplify on the specific traits characteristic of each of these units. Security culture is not a panacea. In a time of mounting terrorist threats, it should nonetheless be looked upon as a necessary organizational tool that enhances the skills of nuclear personnel and ensures that
Alexander Panteleevich Batsula
Full Text Available The article, paper addresses problem of increasing the level of information security. As a result, a method of increasing the level of information security is developed through its modeling of strategic planning SWOT-analysis using expert assessments.
L. A. Zaporozhtseva
Full Text Available Article explains the necessity the application of the ontological approach to modeling the strategic economic security in the formalization of the basic categories of domain company recognized its benefits. Among the advantages of the model distinguishes its versatility and ability to describe various aspects of strategic security - the system strategies and goals of the organization and business processes; possibility of its use at different levels of detail - from the top-level description of the basic categories of management, to design-level analytic applications; as well as the adaptability of the model, with depth on particular aspects determined by practical necessity and not regulated methodology. The model integrates various aspects of the concept of enterprise architecture and organizes conceptual apparatus. Ontological model easy to understand and adjust as business architects and specialists in designing systems of economic security and offers many categories of verbal representation of the domain of the enterprise. Proved the feasibility of using process-functional approach in providing strategic economic security, according to which the components of such a security company proposed as business processes, finance, staff and contractors. The article presents the author's ontological model of strategic economic security, including endangered sites, the presence of factors that threaten the security of the object and the subject of providing security. Further, it is proved that in the subjects of security impact on the object using the tools, measures and activities within the strategy formed the mechanism is implemented managerial decisions to strengthen the strategic economic security. The process of diagnosis, detection, identification of threats of economic security, and the development of enterprise development strategies, taking into account its level of economic security must be under the constant supervision of the process of
Mihail N. Dudin
Full Text Available The leading countries of the world consider food security the important condition of internal political and social-economic stability of the state and its external independence. The topic of the article is crucial due to the fact that the problem of food security is rather complicated and multilevel and should be considered at different interrelated hierarchical levels. In this context the efficient model of food security is the result of the permanent dialogue between the representatives of the state government, business entities, social organizations and scientific institutions. The article justifies the fact that the model of innovation development, known as ‘the triple helix model’ should be applied at the modern stage of economic development as an efficient tool for the food security provision, which can be implemented in the activity of regional economic entities and the whole economic system of the Russian Federation.
.... The CyberCIEGE game introduces a new method of training in computer and network security. The player engages in a simulation-based network security game, that reflects real-world security principles...
Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong
Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.
Baek, Eun Kyeng; Ferron, John M
Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.
Troelsen, Jens; Klinker, Charlotte Demant; Breum, Lars
specifies that factors at multiple levels can influence PA behavior, and emphasizes the importance of behavior-specific models. On this theoretical basis the three mentioned multi-level interventions were planned and implemented. Based on the empirical studies we argue that site-specific factors have......Settings for Physical Activity – Developing a Site-specific Physical Activity Behavior Model based on Multi-level Intervention Studies Introduction: Ecological models of health behavior have potential as theoretical framework to comprehend the multiple levels of factors influencing physical...... activity (PA). The potential is shown by the fact that there has been a dramatic increase in application of ecological models in research and practice. One proposed core principle is that an ecological model is most powerful if the model is behavior-specific. However, based on multi-level interventions...
van Nispen, Ruth M A; Knol, Dirk L; Neve, Han J; van Rens, Ger H M B
To investigate how a multilevel item response theory (IRT) model for longitudinal dependent data could provide average and individual quality-of-life outcomes of low-vision rehabilitation. In a nonrandomized longitudinal design, visually impaired older patients (n=296) were referred to multidisciplinary rehabilitation or to an optometric service. The five-dimensional Low Vision Quality of Life Questionnaire was administered at four time points. The IRT model was characterized by the graded response model for rating scales. Covariates were added to the model, mainly to correct for missing data. The invariance assumption across time points was investigated. Average and individual rehabilitation effects were estimated. For multidisciplinary rehabilitation, significant average deterioration was seen on three dimensions after 4.4 years. Many individuals in the optometric service group significantly improved on the "reading small print" dimension (18.5%); in both groups, many individuals significantly deteriorated on "visual (motor) skills" (22.2-30.0%). Invariance across time points could be assumed for all dimensions, except for "adjustment." Gender, education, visual acuity, and health status were significantly associated with the outcome. We present how a multilevel IRT model can be applied to describe longitudinal dependent vision-related quality-of-life data, while focusing on average and individual effects.
Full Text Available In reality, some computers have specific security classification. For the sake of safety and cost, the security level of computers will be upgraded with increasing of threats in networks. Here we assume that there exists a threshold value which determines when countermeasures should be taken to level up the security of a fraction of computers with low security level. And in some specific realistic environments the propagation network can be regarded as fully interconnected. Inspired by these facts, this paper presents a novel computer virus dynamics model considering the impact brought by security classification in full interconnection network. By using the theory of dynamic stability, the existence of equilibria and stability conditions is analysed and proved. And the above optimal threshold value is given analytically. Then, some numerical experiments are made to justify the model. Besides, some discussions and antivirus measures are given.
Zhang, Xinxin; Lind, Morten; Ravn, Ole
For complex engineering systems, there is an increasing demand forsafety and reliability. Decision support system (DSS) is designed to offersupervision and analysis about operational situations. A proper modelrepresentation is required for DSS to understand the process knowledge.Multilevel flow m...... available techniques of MFM reasoning and less matureyet relevant MFM concepts are considered. It also offers an architecture designof task organisation for MFM software tools by using the concept of agent andtechnology of multiagent software system...
This working paper contributes to a collective discussion in a workshop occurring in January 2011 at the International Institute of Social Studies, bringing scholars from Europe and Brazil and aiming inter-university research collaboration on linking policies on social responsibility to development and equity. The paper serves as an introductory discussion for reframing the concept of corporate social responsibility into a broader umbrella concept of multi-actor and multilevel social responsi...
Cho, Sun-Joo; Gilbert, Jennifer K; Goodwin, Amanda P
This paper presents an explanatory multidimensional multilevel random item response model and its application to reading data with multilevel item structure. The model includes multilevel random item parameters that allow consideration of variability in item parameters at both item and item group levels. Item-level random item parameters were included to model unexplained variance remaining when item related covariates were used to explain variation in item difficulties. Item group-level random item parameters were included to model dependency in item responses among items having the same item stem. Using the model, this study examined the dimensionality of a person's word knowledge, termed lexical representation, and how aspects of morphological knowledge contributed to lexical representations for different persons, items, and item groups.
Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming
ZigBee is a fairly new but promising wireless sensor network standard that offers the advantages of simple and low resource communication. Nevertheless, security is of great concern to ZigBee, and enhancements are prescribed in the latest ZigBee specication: ZigBee-2007. In this technical report......, we identify an important gap in the specification on key updates, and present a methodology for determining optimal key update policies and security parameters. We exploit the stochastic model checking approach using the probabilistic model checker PRISM, and assess the security needs for realistic...
previously proposed certificateless signature schemes were insecure under a considerably strong security model in the sense that they suffered from outsiders’ key replacement attacks or the attacks from the key generation center (KGC. In this paper, we propose a certificateless signature scheme without random oracles. Moreover, our scheme is secure under the strong security model and provides a public revocation mechanism, called revocable certificateless signature (RCLS. Under the standard computational Diffie-Hellman assumption, we formally demonstrate that our scheme possesses existential unforgeability against adaptive chosen-message attacks.
Hank, Karsten; Erlinghagen, Marcel
Using data from the 2004 Survey of Health, Ageing and Retirement in Europe, this paper investigates older workers' perceptions of job security in eleven countries. We describe cross-national patterns and estimate multilevel models to analyse individual and societal determinants of self-perceived job security in the older labour force. While there…
Mutsvari, Timothy; Bandyopadhyay, Dipankar; Declerck, Dominique; Lesaffre, Emmanuel
Dental caries is a highly prevalent disease affecting the tooth's hard tissues by acid-forming bacteria. The past and present caries status of a tooth is characterized by a response called caries experience (CE). Several epidemiological studies have explored risk factors for CE. However, the detection of CE is prone to misclassification because some cases are neither clearly carious nor noncarious, and this needs to be incorporated into the epidemiological models for CE data. From a dentist's point of view, it is most appealing to analyze CE on the tooth's surface, implying that the multilevel structure of the data (surface-tooth-mouth) needs to be taken into account. In addition, CE data are spatially referenced, that is, an active lesion on one surface may impact the decay process of the neighboring surfaces, and that might also influence the process of scoring CE. In this paper, we investigate two hypotheses: that is, (i) CE outcomes recorded at surface level are spatially associated; and (ii) the dental examiners exhibit some spatial behavior while scoring CE at surface level, by using a spatially referenced multilevel autologistic model, corrected for misclassification. These hypotheses were tested on the well-known Signal Tandmobiel® study on dental caries, and simulation studies were conducted to assess the effect of misclassification and strength of spatial dependence on the autologistic model parameters. Our results indicate a substantial spatial dependency in the examiners' scoring behavior and also in the prevalence of CE at surface level. Copyright © 2013 John Wiley & Sons, Ltd.
Full Text Available Software Defined Networking (SDN has brought many changes in terms of the interaction processes between systems and humans. It has become the key enabler of software defined architecture, which allows enterprises to build a highly agile Information Technology (IT infrastructure. For Future Sustainability Computing (FSC, SDN needs to deliver on many information technology commitments—more automation, simplified design, increased agility, policy-based management, and network management bond to more liberal IT workflow systems. To address the sustainability problems, SDN needs to provide greater collaboration and tighter integration with networks, servers, and security teams that will have an impact on how enterprises design, plan, deploy and manage networks. In this paper, we propose FS-OpenSecurity, which is a new and pragmatic security architecture model. It consists of two novel methodologies, Software Defined Orchestrator (SDO and SQUEAK, which offer a robust and secure architecture. The secure architecture is required for protection from diverse threats. Usually, security administrators need to handle each threat individually. However, handling threats automatically by adapting to the threat landscape is a critical demand. Therefore, the architecture must handle defensive processes automatically that are collaboratively based on intelligent external and internal information.
Patricia A.H. Williams
Full Text Available Information governance is becoming an important aspect of organisational accountability. In consideration that information is an integral asset of most organisations, the protection of this asset will increasingly rely on organisational capabilities in security. In the medical arena this information is primarily sensitive patient-based information. Previous research has shown that application of security measures is a low priority for primary care medical practice and that awareness of the risks are seriously underestimated. Consequently, information security governance will be a key issue for medical practice in the future. Information security governance is a relatively new term and there is little existing research into how to meet governance requirements. The limited research that exists describes information security governance frameworks at a strategic level. However, since medical practice is already lagging in the implementation of appropriate security, such definition may not be practical although it is obviously desirable. This paper describes an on-going action research project undertaken in the area of medical information security, and presents a tactical approach model aimed at addressing information security governance and the protection of medical data.
Biological realism (Revonsuo, 2001, 2006) states that dreaming is a biological phenomenon and therefore explainable in naturalistic terms, similar to the explanation of other biological phenomena. In the biological sciences, the structure of explanations can be described with the help of a framework called 'multilevel explanation'. The multilevel model provides a context that assists to clarify what needs to be explained and how, and how to place different theories into the same model. Here, I will argue that the multilevel framework would be useful when we try to construct scientific explanations of dreaming. Copyright © 2011 Elsevier Inc. All rights reserved.
Zhang, Yi; Wang, Huai; Wang, Zhongxu
The reliability aspect study of Modular Multilevel Converter (MMC) is of great interest in industry applications, such as offshore wind. Lifetime prediction of key components is an important tool to design MMC with fulfilled reliability specifications. While many efforts have been made to the lif......The reliability aspect study of Modular Multilevel Converter (MMC) is of great interest in industry applications, such as offshore wind. Lifetime prediction of key components is an important tool to design MMC with fulfilled reliability specifications. While many efforts have been made...... and electrical power modeling methods on the estimated lifetime of IGBT modules in an MMC for offshore wind power application. In a 30 MW MMC case study, an annual wind speed profile with a resolution of 1 s/data, 10 minute/data, and 1 hour/data are considered, respectively. A method to re-generate higher...... used in the MMC, resulting in significant differences. The study serves as a first step to quantify the impact of mission profile modeling on lifetime prediction, and to provide a guideline on mission profile collection for the presented application....
Scholz, Eberhard P; Kehrle, Florian; Vossel, Stephan; Hess, Alexander; Zitron, Edgar; Katus, Hugo A; Sager, Sebastian
The discrimination between atrial flutter (AFlu) and atrial fibrillation (AFib) can be made difficult by an irregular ventricular response owing to complex conduction phenomena within the atrioventricular (AV) node, known as multilevel AV block. We tested the hypothesis that a mathematical algorithm might be suitable to discriminate both arrhythmias. To discriminate AFlu with irregular ventricular response from AFib based on the sequence of R-R intervals. Intracardiac recordings of 100 patients (50 patients with AFib and 50 patients with AFlu) were analyzed. On the basis of a numerical simulation of variable flutter frequencies followed by 2 levels of AV block in series, a given sequence of R-R intervals was analyzed. Although the ventricular response displays absolute irregularity in AFib, the sequences of R-R intervals follow certain rules in AFlu. We find that using a mathematical simulation of multilevel AV block, based on the R-R sequence of 16 ventricular beats, a stability of atrial activation could be predicted with a sensitivity of 84% and a specificity of 74%. When limiting the ventricular rate to 125 beats/min, discrimination could be performed with a sensitivity of even 89% and a specificity of 80%. In cases of AFlu, the atrial cycle length could be predicted with high accuracy. On the basis of the electrophysiological mechanism of multilevel AV block, we developed a computer algorithm to discriminate between AFlu and Afib. This algorithm is able to predict the stability and cycle length of atrial activation for short R-R sequences with high accuracy. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.
Liu Yachun; Zou Shuliang; Yang Xiaohua; Ouyang Zigen; Dai Jianyong
In the field of nuclear safety, traditional work places extra emphasis on risk assessment related to technical skills, production operations, accident consequences through deterministic or probabilistic analysis, and on the basis of which risk management and control are implemented. However, high quality of product does not necessarily mean good safety quality, which implies a predictable degree of uniformity and dependability suited to the specific security needs. In this paper, we make use of the system security engineering - capability maturity model (SSE-CMM) in the field of spent fuel reprocessing, establish a spent fuel reprocessing systems security engineering capability maturity model (SFR-SSE-CMM). The base practices in the model are collected from the materials of the practice of the nuclear safety engineering, which represent the best security implementation activities, reflect the regular and basic work of the implementation of the security engineering in the spent fuel reprocessing plant, the general practices reveal the management, measurement and institutional characteristics of all process activities. The basic principles that should be followed in the course of implementation of safety engineering activities are indicated from 'what' and 'how' aspects. The model provides a standardized framework and evaluation system for the safety engineering of the spent fuel reprocessing system. As a supplement to traditional methods, this new assessment technique with property of repeatability and predictability with respect to cost, procedure and quality control, can make or improve the activities of security engineering to become a serial of mature, measurable and standard activities. (author)
I. A. Zikratov
Full Text Available This paper focuses on aspects of information security for group of mobile robotic systems with swarm intellect. The ways for hidden attacks realization by the opposing party on swarm algorithm are discussed. We have fulfilled numerical modeling of potentially destructive information influence on the ant shortest path algorithm. We have demonstrated the consequences of attacks on the ant algorithm with different concentration in a swarm of subversive robots. Approaches are suggested for information security mechanisms in swarm robotic systems, based on the principles of centralized security management for mobile agents. We have developed the method of forming a self-organizing information security management system for robotic agents in swarm groups implementing POM (Police Office Model – a security model based on police offices, to provide information security in multi-agent systems. The method is based on the usage of police station network in the graph nodes, which have functions of identification and authentication of agents, identifying subversive robots by both their formal characteristics and their behavior in the swarm. We have suggested a list of software and hardware components for police stations, consisting of: communication channels between the robots in police office, nodes register, a database of robotic agents, a database of encryption and decryption module. We have suggested the variants of logic for the mechanism of information security in swarm systems with different temporary diagrams of data communication between police stations. We present comparative analysis of implementation of protected swarm systems depending on the functioning logic of police offices, integrated in swarm system. It is shown that the security model saves the ability to operate in noisy environments, when the duration of the interference is comparable to the time necessary for the agent to overcome the path between police stations.
The Space Station contains safety critical computer software components in systems that can affect life and vital property. These components require a multilevel secure system that provides dynamic access control of the data and processes involved. A study is under way to define requirements for a security model providing access control through level B3 of the Orange Book. The model will be prototyped at NASA-Johnson Space Center.
Cheng, Cecilia; Cheung, Mike W-L; Montasem, Alex
This multinational study simultaneously tested three prominent hypotheses--universal disposition, cultural relativity, and livability--that explained differences in subjective well-being across nations. We performed multilevel structural equation modeling to examine the hypothesized relationships at both individual and cultural levels in 33 nations. Participants were 6,753 university students (2,215 men; 4,403 women; 135 did not specify), and the average age of the entire sample was 20.97 years (SD = 2.39). Both individual- and cultural-level analyses supported the universal disposition and cultural relativity hypotheses by revealing significant associations of subjective well-being with Extraversion, Neuroticism, and independent self-construal. In addition, interdependent self-construal was positively related to life satisfaction at the individual level only, whereas aggregated negative affect was positively linked with aggregate levels of Extraversion and interdependent self-construal at the cultural level only. Consistent with the livability hypothesis, gross national income (GNI) was related to aggregate levels of negative affect and life satisfaction. There was also a quadratic relationship between GNI and aggregated positive affect. Our findings reveal that universal disposition, cultural self-construal, and national income can elucidate differences in subjective well-being, but the multilevel analyses advance the literature by yielding new findings that cannot be identified in studies using individual-level analyses alone. © 2014 Wiley Periodicals, Inc.
Multilevel modeling techniques facilitated examination of relationships between fidelity indicators and outcomes associated with a summer literacy intervention. Three-level growth models were specified to capture the extent to which students experienced instruction and to demonstrate the ways in which dosage-response relationships manifest in…
Martin, Jean-Charles; Berton, Amélie; Ginies, Christian; Bott, Romain; Scheercousse, Pierre; Saddi, Alessandra; Gripois, Daniel; Landrier, Jean-François; Dalemans, Daniel; Alessi, Marie-Christine; Delplanque, Bernadette
We assessed the atheroprotective efficiency of modified dairy fats in hyperlipidemic hamsters. A systems biology approach was implemented to reveal and quantify the dietary fat-related components of the disease. Three modified dairy fats (40% energy) were prepared from regular butter by mixing with a plant oil mixture, by removing cholesterol alone, or by removing cholesterol in combination with reducing saturated fatty acids. A plant oil mixture and a regular butter were used as control diets. The atherosclerosis severity (aortic cholesteryl-ester level) was higher in the regular butter-fed hamsters than in the other four groups (P metabolism" appeared central to atherogenic development relative to diets. The "vitamin E metabolism" cluster was the main driver of atheroprotection with the best performing transformed dairy fat. Under conditions that promote atherosclerosis, the impact of dairy fats on atherogenesis could be greatly ameliorated by technological modifications. Our modeling approach allowed for identifying and quantifying the contribution of complex factors to atherogenic development in each dietary setup. Copyright © 2015 the American Physiological Society.
Sang Hoon Kim
Full Text Available The authors found the behavioral factors that influence the organization members’ compliance with the information security policy in organizations on the basis of neutralization theory, Theory of planned behavior, and protection motivation theory. Depending on the theory of planned behavior, members’ attitudes towards compliance, as well as normative belief and self-efficacy, were believed to determine the intention to comply with the information security policy. Neutralization theory, a prominent theory in criminology, could be expected to provide the explanation for information system security policy violations. Based on the protection motivation theory, it was inferred that the expected efficacy could have an impact on intentions of compliance. By the above logical reasoning, the integrative behavioral model and eight hypotheses could be derived. Data were collected by conducting a survey; 194 out of 207 questionnaires were available. The test of the causal model was conducted by PLS. The reliability, validity, and model fit were found to be statistically significant. The results of the hypotheses tests showed that seven of the eight hypotheses were acceptable. The theoretical implications of this study are as follows: (1 the study is expected to play a role of the baseline for future research about organization members’ compliance with the information security policy, (2 the study attempted an interdisciplinary approach by combining psychology and information system security research, and (3 the study suggested concrete operational definitions of influencing factors for information security policy compliance through a comprehensive theoretical review. Also, the study has some practical implications. First, it can provide the guideline to support the successful execution of the strategic establishment for the implement of information system security policies in organizations. Second, it proves that the need of education and training
Kim, Sang Hoon; Yang, Kyung Hoon; Park, Sunyoung
The authors found the behavioral factors that influence the organization members' compliance with the information security policy in organizations on the basis of neutralization theory, Theory of planned behavior, and protection motivation theory. Depending on the theory of planned behavior, members' attitudes towards compliance, as well as normative belief and self-efficacy, were believed to determine the intention to comply with the information security policy. Neutralization theory, a prominent theory in criminology, could be expected to provide the explanation for information system security policy violations. Based on the protection motivation theory, it was inferred that the expected efficacy could have an impact on intentions of compliance. By the above logical reasoning, the integrative behavioral model and eight hypotheses could be derived. Data were collected by conducting a survey; 194 out of 207 questionnaires were available. The test of the causal model was conducted by PLS. The reliability, validity, and model fit were found to be statistically significant. The results of the hypotheses tests showed that seven of the eight hypotheses were acceptable. The theoretical implications of this study are as follows: (1) the study is expected to play a role of the baseline for future research about organization members' compliance with the information security policy, (2) the study attempted an interdisciplinary approach by combining psychology and information system security research, and (3) the study suggested concrete operational definitions of influencing factors for information security policy compliance through a comprehensive theoretical review. Also, the study has some practical implications. First, it can provide the guideline to support the successful execution of the strategic establishment for the implement of information system security policies in organizations. Second, it proves that the need of education and training programs suppressing
Lindberg, Kasper; Jensen, Christian D.
, but this also means that anyone can introduce errors into documents, either by accident or on purpose. A security model for wiki-style authoring systems, called the Secure Wiki Model, has previously been proposed to address this problem. This model is designed to prevent corruption of good quality documents......Wiki systems form a subclass of the more general Open Collaborative Authoring Systems, where content is created by a user community. The ability of anyone to edit the content is, at the same time, their strength and their weakness. Anyone can write documents that improve the value of the wiki-system......, by limiting updates, to such documents, to users who have demonstrated their ability to produce documents of similar or better quality. While this security model prevents all user from editing all documents, it does respect the wiki philosophy by allowing any author who has produced documents of a certain...
Wei, Huaqiang; Alves-Foss, James; Soule, Terry; Pforsich, Hugh; Zhang, Du; Frincke, Deborah A.
System security involves decisions in at least three areas: identification of well-defined security policies, selection of cost-effective defence strategies, and implementation of real-time defence tactics. Although choices made in each of these areas affect the others, existing decision models typically handle these three decision areas in isolation. There is no comprehensive tool that can integrate them to provide a single efficient model for safeguarding a network. In addition, there is no clear way to determine which particular combinations of defence decisions result in cost-effective solutions. To address these problems, this paper introduces a Layered Decision Model (LDM) for use in deciding how to address defence decisions based on their cost-effectiveness. To validate the LDM and illustrate how it is used, we used simulation to test model rationality and applied the LDM to the design of system security for an e-commercial business case.
Ramasamy, Vijayalakshmi; Sheen, Shina; Veeramani, C; Bonato, Anthony; Batten, Lynn
This book aims at promoting high-quality research by researchers and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security, and Computational Models ICC3 2015 organized by PSG College of Technology, Coimbatore, India during December 17 – 19, 2015. This book enriches with innovations in broad areas of research like computational modeling, computational intelligence and cyber security. These emerging inter disciplinary research areas have helped to solve multifaceted problems and gained lot of attention in recent years. This encompasses theory and applications, to provide design, analysis and modeling of the aforementioned key areas.
Harding, D B; Gac, R J; Reynolds, C T; Romlein, J; Chacko, A K
The modern information revolution has facilitated a metamorphosis of health care delivery wrought with the challenges of securing patient sensitive data. To accommodate this reality, Congress passed the Health Insurance Portability and Accountability Act (HIPAA). While final guidance has not fully been resolved at this time, it is up to the health care community to develop and implement comprehensive security strategies founded on procedural, hardware and software solutions in preparation for future controls. The Virtual Radiology Environment (VRE) Project, a landmark US Army picture archiving and communications system (PACS) implemented across 10 geographically dispersed medical facilities, has addressed that challenge by planning for the secure transmission of medical images and reports over their local (LAN) and wide area network (WAN) infrastructure. Their model, which is transferable to general PACS implementations, encompasses a strategy of application risk and dataflow identification, data auditing, security policy definition, and procedural controls. When combined with hardware and software solutions that are both non-performance limiting and scalable, the comprehensive approach will not only sufficiently address the current security requirements, but also accommodate the natural evolution of the enterprise security model.
Cederquist, J.G.; Dashti, Muhammad Torabi
We present a process algebraic intruder model for verifying a class of liveness properties of security protocols. For this class, the proposed intruder model is proved to be equivalent to a Dolev-Yao intruder that does not delay indefinitely the delivery of messages. In order to prove the
PhEDEx. the data-placement tool used by the CMS experiment at the LHC, was conceived in a more trusting time. The security model was designed to provide a safe working environment for site agents and operators, but provided little more protection than that. CMS data was not sufficiently protected against accidental loss caused by operator error or software bugs or from loss of data caused by deliberate manipulation of the database. Operations staff were given high levels of access to the database, beyond what should have been needed to accomplish their tasks. This exposed them to the risk of suspicion should an incident occur. Multiple implementations of the security model led to difficulties maintaining code, which can lead to degredation of security over time.In order to meet the simultaneous goals of protecting CMS data, protecting the operators from undue exposure to risk, increasing monitoring capabilities and improving maintainability of the security model, the PhEDEx security model was redesigned and r...
Herrero Olaizola, Juan; Rodríguez Díaz, Francisco Javier; Musitu Ochoa, Gonzalo
The literature has rarely paid attention to the differential influence of intergroup contact on subtle and blatant prejudice. In this study, we hypothesized that the influence of intergroup contact on subtle prejudice will be smaller than its influence on blatant prejudice. This hypothesis was tested with data from a cross-sectional design on 1,655 school-aged native Spanish adolescents. Prejudice was measured with a shortened version of the Meertens and Pettigrew scale of blatant and subtle prejudice adapted to Spanish adolescent population. Results from multivariate multilevel analyses for correlated outcome variables supported the hypothesis. Students tended to score higher on the subtle prejudice scale; contact with the outgroup was statistically related both to levels of blatant and subtle prejudice; and, the negative relationship of contact with the outgroup and prejudice is greater for blatant prejudice as compared to subtle prejudice. Overall, results provide statistical evidence supporting the greater resistance to change of subtle forms of prejudice.
Jaganathan, Venkatesh; Cherurveettil, Priyesh; Muthu Sivashanmugam, Premapriya
Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization.
Full Text Available Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization.
Ruff, Ryan Richard; Akhund, Ali; Adjoian, Tamar
Local food environments can influence the diet and health of individuals through food availability, proximity to retail stores, pricing, and promotion. This study focused on how small convenience stores, known in New York City as bodegas, influence resident shopping behavior and the food environment. Using a cross-sectional design, 171 bodegas and 2118 shoppers were sampled. Small convenience stores in New York City. Any bodega shopper aged 18+ who purchased food or beverage from a participating store. Data collection consisted of a store assessment, a health and behavior survey given to exiting customers, and a bag check that recorded product information for all customer purchases. Descriptive statistics were generated for bodega store characteristics, shopper demographics, and purchase behavior. Multilevel models were used to assess the influence of product availability, placement, and advertising on consumer purchases of sugar-sweetened beverages (SSBs), water, and fruits and vegetables. Seventy-one percent of participants reported shopping at bodegas five or more times per week, and 35% reported purchasing all or most of their monthly food allotment at bodegas. Model results indicated that lower amounts of available fresh produce were significantly and independently associated with a higher likelihood of SSB purchases. A second, stratified multilevel model showed that the likelihood of purchasing an SSB increased with decreasing varieties of produce when produce was located at the front of the store. No significant effects were found for water placement and beverage advertising. Small convenience stores in New York City are an easily accessible source of foods and beverages. Bodegas may be suitable for interventions designed to improve food choice and diet.
Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.
Lang, Ulrich; Schreiner, Rudolf
Compliance with regulatory and governance standards is rapidly becoming one of the hot topics of information security today. This is because, especially with regulatory compliance, both business and government have to expect large financial and reputational losses if compliance cannot be ensured and demonstrated. One major difficulty of implementing such regulations is caused the fact that they are captured at a high level of abstraction that is business-centric and not IT centric. This means that the abstract intent needs to be translated in a trustworthy, traceable way into compliance and security policies that the IT security infrastructure can enforce. Carrying out this mapping process manually is time consuming, maintenance-intensive, costly, and error-prone. Compliance monitoring is also critical in order to be able to demonstrate compliance at any given point in time. The problem is further complicated because of the need for business-driven IT agility, where IT policies and enforcement can change frequently, e.g. Business Process Modelling (BPM) driven Service Oriented Architecture (SOA). Model Driven Security (MDS) is an innovative technology approach that can solve these problems as an extension of identity and access management (IAM) and authorization management (also called entitlement management). In this paper we will illustrate the theory behind Model Driven Security for compliance, provide an improved and extended architecture, as well as a case study in the healthcare industry using our OpenPMF 2.0 technology.
Li, Wenjuan; Ping, Lingdi
Trust is one of the most important means to improve security and enable interoperability of current heterogeneous independent cloud platforms. This paper first analyzed several trust models used in large and distributed environment and then introduced a novel cloud trust model to solve security issues in cross-clouds environment in which cloud customer can choose different providers' services and resources in heterogeneous domains can cooperate. The model is domain-based. It divides one cloud provider's resource nodes into the same domain and sets trust agent. It distinguishes two different roles cloud customer and cloud server and designs different strategies for them. In our model, trust recommendation is treated as one type of cloud services just like computation or storage. The model achieves both identity authentication and behavior authentication. The results of emulation experiments show that the proposed model can efficiently and safely construct trust relationship in cross-clouds environment.
Full Text Available Transmission demand continues to grow and higher capacity optical communication systems are required to economically meet this ever-increasing need for communication services. This article expands and deepens the study of a novel optical communication system for high-capacity Local Area Networks (LANs, based on twisted optical fibers. The complete statistical behavior of this system is shown, designed for more efficient use of the fiber single-channel capacity by adopting an unconventional multilevel polarization modulation (called “bands of polarization”. Starting from simulative results, a possible reference mathematical model is proposed. Finally, the system performance is analyzed in the presence of shot-noise (coherent detection or thermal noise (direct detection.
Full Text Available The purpose of this research work is to evaluate the effects which some factors could have on articles publication regarding survey interviewer characteristics. For this, the author studied the existing literature from the various fields in which articles on survey interviewer characteristics has been published and which can be found in online articles database. The analysis was performed on 243 articles achieved by researchers in the time period 1949-2012. Using statistical software R and applying multilevel regression model, the results showed that the time period when the studied articles are made and the interaction between the number of authors and the number of pages affect the most their publication in journals with a certain level of impact factor.
Ottley, Jennifer Riggie; Ferron, John M; Hanline, Mary Frances
The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS University Edition, we fit multilevel models with time nested within children. Children's initial levels of communication and teachers' frequency of strategy use when directed at the children predicted children's communicative outcomes. These results indicate that teachers' implementation of evidence-based communication strategies, when directed toward children with disabilities, and the interaction between their use of the strategies and children's initial levels of communication predict children's communicative outcomes. Implications for research and practice are provided.
Baptista, Filipa Matos; Dahl, Jan; Nielsen, Liza Rosenbaum
In Denmark, a Surveillance-and-Control Programme for Salmonella in pigs has been in place for several years. This study investigated factors associated with Salmonella pig carcass contamination, namely estimated daily number of Salmonella seropositive pigs delivered to slaughter, average Salmonella...... seroprevalence of the source herds that delivered each of five pigs contributing to the pool, weekday, year, season and abattoir size. A total of 20128 pooled carcass swabs collected in 22 Danish abattoirs, from 2002 to 2008, were included in a multilevel logistic regression model. Study results indicate...... that the probability of Salmonella positive carcasses is mainly influenced by the Salmonella herd seroprevalence of the swabbed pigs, the number of seropositive pigs delivered to the abattoir on the same day and weekday. Further reduction in carcass pool Salmonella prevalence may require new or improved methods...
Criqui, Patrick; Mima, Silvana
In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)
Criqui, Patrick; Mima, Silvana
In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)
Yang, Ji Seung; Cai, Li
The main purpose of this study is to improve estimation efficiency in obtaining full-information maximum likelihood (FIML) estimates of contextual effects in the framework of a nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM…
Gkolia, Aikaterini; Koustelios, Athanasios; Belias, Dimitrios
The main aim of this study is to examine the effect of principals' transformational leadership on teachers' self-efficacy across 77 different Greek elementary and secondary schools based on a centralized education system. For the investigation of the above effect multilevel Structural Equation Modelling analysis was conducted, recognizing the…
Full Text Available Olatunde Aremu School of Health, Sport, and Bioscience, Health Studies Field, University of East London, London, United Kingdom Background: Contraceptives are one of the most cost effective public health interventions. An understanding of the factors influencing users' preferences for contraceptives sources, in addition to their preferred methods of contraception, is an important factor in increasing contraceptive uptake. This study investigates the effect of women’s contextual and individual socioeconomic positions on their preference for contraceptive sources among current users in Nigeria. Methods: A multilevel modeling analysis was conducted using the most recent 2008 Nigerian Demographic and Health Surveys data of women aged between 15 and 49 years old. The analysis included 1,834 ever married women from 888 communities across the 36 states of the federation, including the Federal Capital Territory of Abuja. Three outcome variables, private, public, and informal provisions of contraceptive sources, were considered in the modeling. Results: There was variability in women's preferences for providers across communities. The result shows that change in variance accounted for about 31% and 19% in the odds of women's preferences for both private and public providers across communities. Younger age and being from the richest households are strongly associated with preference for both private and public providers. Living in rural areas and economically deprived neighborhoods were the community level determinants of women's preferences. Conclusion: This study documents the independent association of contextual socioeconomic characteristics and individual level socioeconomic factors with women's preferences for contraceptive commodity providers in Nigeria. Initiatives that seek to improve modern contraceptive uptake should jointly consider users’ preferences for sources of these commodities in addition to their preference for contraceptive type
Wen, Tzai-Hung; Chen, Tzu-Hsin
Dengue fever is one of potentially life-threatening mosquito-borne diseases and IPCC Fifth Assessment Report (AR5) has confirmed that dengue incidence is sensitive to the critical weather conditions, such as effects of temperature. However, previous literature focused on the effects of monthly or weekly average temperature or accumulative precipitation on dengue incidence. The influence of intra- and inter-annual meteorological variability on dengue outbreak is under investigated. The purpose of the study focuses on measuring the effect of the intra- and inter-annual variations of temperature and precipitation on dengue outbreaks. We developed the indices of intra-annual temperature variability are maximum continuity, intermittent, and accumulation of most suitable temperature (MST) for dengue vectors; and also the indices of intra-annual precipitation variability, including the measure of continuity of wetness or dryness during a pre-epidemic period; and rainfall intensity during an epidemic period. We used multi-level modeling to investigate the intra- and inter-annual meteorological variations on dengue outbreaks in southern Taiwan from 1998-2015. Our results indicate that accumulation and maximum continuity of MST are more significant than average temperature on dengue outbreaks. The effect of continuity of wetness during the pre-epidemic period is significantly more positive on promoting dengue outbreaks than the rainfall effect during the epidemic period. Meanwhile, extremely high or low rainfall density during an epidemic period do not promote the spread of dengue epidemics. Our study differentiates the effects of intra- and inter-annual meteorological variations on dengue outbreaks and also provides policy implications for further dengue control under the threats of climate change. Keywords: dengue fever, meteorological variations, multi-level model
This ineffectiveness extends to promoting household food security within the context of encouraging biodiversity conservation on farm lands. To examine this, this paper draws on recently conducted research to sketch the current model within which extension pursues these seemingly dichotomous objectives and identifies ...
S.D.C. Wehner (Stephanie); J. Wullschleger
htmlabstractWe present a simplified framework for proving sequential composability in the quantum setting. In particular, we give a new, simulation-based, definition for security in the bounded-quantum-storage model, and show that this definition allows for sequential composition of protocols.
Full Text Available Today's, Organizations are exposed with huge and diversity of information and information assets that are produced in different systems shuch as KMS, financial and accounting systems, official and industrial automation sysytems and so on and protection of these information is necessary. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released.several benefits of this model cuses that organization has a great trend to implementing Cloud computing. Maintaining and management of information security is the main challenges in developing and accepting of this model. In this paper, at first, according to "design science research methodology" and compatible with "design process at information systems research", a complete categorization of organizational assets, including 355 different types of information assets in 7 groups and 3 level, is presented to managers be able to plan corresponding security controls according to importance of each groups. Then, for directing of organization to architect it’s information security in cloud computing environment, appropriate methodology is presented. Presented cloud computing security architecture , resulted proposed methodology, and presented classification model according to Delphi method and expers comments discussed and verified.
Technology & Learning, 2008
Anytime, anywhere, learning provides opportunities to create digital learning environments for new teaching styles and personalized learning. As part of making sure the program is effective, the safety and security of students and assets are essential--and mandated by law. The Children's Internet Protection Act (CIPA) addresses Internet content…
Zhang, Hua; Huang, Guo H; Wang, Dunling; Zhang, Xiaodong; Li, Gongchen; An, Chunjiang; Cui, Zheng; Liao, Renfei; Nie, Xianghui
Eutrophication of small prairie reservoirs presents a major challenge in water quality management and has led to a need for predictive water quality modeling. Studies are lacking in effectively integrating watershed models and reservoir models to explore nutrient dynamics and eutrophication pattern. A water quality model specific to small prairie water bodies is also desired in order to highlight key biogeochemical processes with an acceptable degree of parameterization. This study presents a Multi-level Watershed-Reservoir Modeling System (MWRMS) to simulate hydrological and biogeochemical processes in small prairie watersheds. It integrated a watershed model, a hydrodynamic model and an eutrophication model into a flexible modeling framework. It can comprehensively describe hydrological and biogeochemical processes across different spatial scales and effectively deal with the special drainage structure of small prairie watersheds. As a key component of MWRMS, a three-dimensional Willows Reservoir Eutrophication Model (WREM) is developed to addresses essential biogeochemical processes in prairie reservoirs and to generate 3D distributions of various water quality constituents; with a modest degree of parameterization, WREM is able to meet the limit of data availability that often confronts the modeling practices in small watersheds. MWRMS was applied to the Assiniboia Watershed in southern Saskatchewan, Canada. Extensive efforts of field work and lab analysis were undertaken to support model calibration and validation. MWRMS demonstrated its ability to reproduce the observed watershed water yield, reservoir water levels and temperatures, and concentrations of several water constituents. Results showed that the aquatic systems in the Assiniboia Watershed were nitrogen-limited and sediment flux played a crucial role in reservoir nutrient budget and dynamics. MWRMS can provide a broad context of decision support for water resources management and water quality
Ahmed, Naveed; Jensen, Christian D.
operational environment. In past, this often caused increasing the power of attacker model, for instance, now a days we also consider privacy concerns and side channel leakage beside the classic Dolev-Yao attacker. A protocol is labeled as insecure protocol once an effective attack or flaw is found in it....... In fact, the most of the published protocols are considered insecure from this point of view. In practice, however, this approach has a side effect, namely, we rarely bother to explore how much insecure is the protocol. This question asks us to explore the area between security and insecurity; after all...... and sometimes with additional capabilities such as dynamic corruption of communicating nodes. Then, one tries to show that the protocol achieves its objective under this specific attacker. Naturally there are three possibilities: one may succeed in constructing a security proof; one may fail in proving security...
Full Text Available We analyze the existing DS from the point of security and construct a two-level hierarchy of models. Such approach allows us to separate the abstraction (architecture level and the concrete (component level of ISS. The core set of methods, i. e. authentication and key exchange protocols, corresponds to the abstraction level and is defined as security infrastructure (SI. The final security parameters optimization and additional mechanisms such as authorization, routing and data auditing of the protection mechanisms are configured on the component level of the DS. In addition, we outline the systematic step-by-step ISS configuration method.
Gendron, Gerald; Roberts, David; Poole, Donold; Aquino, Anna
This paper proposes a cyber security modeling and simulation roadmap to enhance mission assurance governance and establish risk reduction processes within constrained budgets. The term mission assurance stems from risk management work by Carnegie Mellon's Software Engineering Institute in the late 19905. By 2010, the Defense Information Systems Agency revised its cyber strategy and established the Program Executive Officer-Mission Assurance. This highlights a shift from simply protecting data to balancing risk and begins a necessary dialogue to establish a cyber security roadmap. The Military Operations Research Society has recommended a cyber community of practice, recognizing there are too few professionals having both cyber and analytic experience. The authors characterize the limited body of knowledge in this symbiotic relationship. This paper identifies operational and research requirements for mission assurance M&S supporting defense and homeland security. M&S techniques are needed for enterprise oversight of cyber investments, test and evaluation, policy, training, and analysis.
Full Text Available The current study sought to meet three aims: (a to understand the optimal factor structure of the Professional Engineering (ProfEng test, a measure aiming to assess competency in engineering, within a multilevel (nested perspective; (b to examine the psychometric measurement invariance of the ProfEng test across levels due to nesting and across gender at the person level, and, (c to examine the internal consistency of the engineering competency measure at both levels in the analysis. Data involved 1,696 individuals across 21 universities who took a national licensure test as part of the professional accreditation process to obtain a work permit and practice the engineering profession in the Kingdom of Saudi Arabia. Data were analyzed by use of Multilevel Structural Equation Modeling (MLSEM. Results indicated that a 2-factor model at both levels of analysis provided the best fit to the data. We also examined violation of measurement invariance across clusters (cluster bias. Results showed that all factor loadings were invariant across levels, suggesting the presence of strong measurement invariance. Last, invariance across gender was tested by use of the MIMIC multilevel model. Results pointed to the existence of significant differences between genders on levels of personal and professional skills with females having higher levels on personal skills and males on professional. Estimates of internal consistency reliability also varied markedly due to nesting. It is concluded that ignoring a multilevel structure is associated with errors and inaccuracies in the measurement of person abilities as both measurement wise and precision wise the multilevel model provides increased accuracy at each level in the analysis.
Ryżyński, Grzegorz; Nałęcz, Tomasz
The efficient geological data management in Poland is necessary to support multilevel decision processes for government and local authorities in case of spatial planning, mineral resources and groundwater supply and the rational use of subsurface. Vast amount of geological information gathered in the digital archives and databases of Polish Geological Survey (PGS) is a basic resource for multi-scale national subsurface management. Data integration is the key factor to allow development of GIS and web tools for decision makers, however the main barrier for efficient geological information management is the heterogeneity of data in the resources of the Polish Geological Survey. Engineering-geological database is the first PGS thematic domain applied in the whole data integration plan. The solutions developed within this area will facilitate creation of procedures and standards for multilevel data management in PGS. Twenty years of experience in delivering digital engineering-geological mapping in 1:10 000 scale and archival geotechnical reports acquisition and digitisation allowed gathering of more than 300 thousands engineering-geological boreholes database as well as set of 10 thematic spatial layers (including foundation conditions map, depth to the first groundwater level, bedrock level, geohazards). Historically, the desktop approach was the source form of the geological-engineering data storage, resulting in multiple non-correlated interbase datasets. The need for creation of domain data model emerged and an object-oriented modelling (UML) scheme has been developed. The aim of the aforementioned development was to merge all datasets in one centralised Oracle server and prepare the unified spatial data structure for efficient web presentation and applications development. The presented approach will be the milestone toward creation of the Polish national standard for engineering-geological information management. The paper presents the approach and methodology
Full Text Available Abstract Background Estimates of disease prevalence for small areas are increasingly required for the allocation of health funds according to local need. Both individual level and geographic risk factors are likely to be relevant to explaining prevalence variations, and in turn relevant to the procedure for small area prevalence estimation. Prevalence estimates are of particular importance for major chronic illnesses such as cardiovascular disease. Methods A multilevel prevalence model for cardiovascular outcomes is proposed that incorporates both survey information on patient risk factors and the effects of geographic location. The model is applied to derive micro area prevalence estimates, specifically estimates of cardiovascular disease for Zip Code Tabulation Areas in the USA. The model incorporates prevalence differentials by age, sex, ethnicity and educational attainment from the 2005 Behavioral Risk Factor Surveillance System survey. Influences of geographic context are modelled at both county and state level, with the county effects relating to poverty and urbanity. State level influences are modelled using a random effects approach that allows both for spatial correlation and spatial isolates. Results To assess the importance of geographic variables, three types of model are compared: a model with person level variables only; a model with geographic effects that do not interact with person attributes; and a full model, allowing for state level random effects that differ by ethnicity. There is clear evidence that geographic effects improve statistical fit. Conclusion Geographic variations in disease prevalence partly reflect the demographic composition of area populations. However, prevalence variations may also show distinct geographic 'contextual' effects. The present study demonstrates by formal modelling methods that improved explanation is obtained by allowing for distinct geographic effects (for counties and states and for
This paper argues that security belongs to a specific category of commodities: “contested commodities” around which there is an ongoing and unsettled symbolic struggle over whether or not they can and should be though of as commodities (section 1). The contested nature of commodification has implications for how markets function; market practices tend to be defined and organized in ways that minimize their contentiousness and obfuscate their expansion. The paper looks at the implications of t...
Gordon, Melissa; Bergeron, Liz
Multilevel modeling has recently found a substantial niche in the context of educational research, although several details about the methodological application of these models have yet to be explored in an achievement data framework. This paper makes use of data provided by the International Baccalaureate (IB) in order to investigate modeling decisions and certain applications of the level two residual file in an effort to increase understanding about the way linear and logistic multilevel models function. The focus of this research is on the relationship between performances in two IB programmes: the Middle Years Programme (MYP) and the Diploma Programme (DP). The impact of predictors on the interpretation of the unconditional and conditional variance-covariance matrix as well as the reliability coefficients is discussed. Empirical findings suggest that students who perform better during MYP moderation tend to perform better on DP exams. Copyright © 2014 Elsevier Inc. All rights reserved.
Zohar, Dov; Lee, Jin
The study was designed to test a multilevel path model whose variables exert opposing effects on school bus drivers' performance. Whereas departmental safety climate was expected to improve driving safety, the opposite was true for in-vehicle disruptive children behavior. The driving safety path in this model consists of increasing risk-taking practices starting with safety shortcuts leading to rule violations and to near-miss events. The study used a sample of 474 school bus drivers in rural areas, driving children to school and school-related activities. Newly developed scales for measuring predictor, mediator and outcome variables were validated with video data taken from inner and outer cameras, which were installed in 29 buses. Results partially supported the model by indicating that group-level safety climate and individual-level children distraction exerted opposite effects on the driving safety path. Furthermore, as hypothesized, children disruption moderated the strength of the safety rule violation-near miss relationship, resulting in greater strength under high disruptiveness. At the same time, the hypothesized interaction between the two predictor variables was not supported. Theoretical and practical implications for studying safety climate in general and distracted driving in particular for professional drivers are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Konold, Timothy R; Cornell, Dewey
This study tested a conceptual model of school climate in which two key elements of an authoritative school, structure and support variables, are associated with student engagement in school and lower levels of peer aggression. Multilevel multivariate structural modeling was conducted in a statewide sample of 48,027 students in 323 public high schools who completed the Authoritative School Climate Survey. As hypothesized, two measures of structure (Disciplinary Structure and Academic Expectations) and two measures of support (Respect for Students and Willingness to Seek Help) were associated with higher student engagement (Affective Engagement and Cognitive Engagement) and lower peer aggression (Prevalence of Teasing and Bullying) on both student and school levels of analysis, controlling for the effects of school demographics (school size, percentage of minority students, and percentage of low income students). These results support the extension of authoritative school climate model to high school and guide further research on the conditions for a positive school climate. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Hatfield, L.A.; Gutreuter, S.; Boogaard, M.A.; Carlin, B.P.
Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data. ?? 2011, The International Biometric Society.
Holtmann, Jana; Koch, Tobias; Lochner, Katharina; Eid, Michael
Multilevel structural equation models are increasingly applied in psychological research. With increasing model complexity, estimation becomes computationally demanding, and small sample sizes pose further challenges on estimation methods relying on asymptotic theory. Recent developments of Bayesian estimation techniques may help to overcome the shortcomings of classical estimation techniques. The use of potentially inaccurate prior information may, however, have detrimental effects, especially in small samples. The present Monte Carlo simulation study compares the statistical performance of classical estimation techniques with Bayesian estimation using different prior specifications for a two-level SEM with either continuous or ordinal indicators. Using two software programs (Mplus and Stan), differential effects of between- and within-level sample sizes on estimation accuracy were investigated. Moreover, it was tested to which extent inaccurate priors may have detrimental effects on parameter estimates in categorical indicator models. For continuous indicators, Bayesian estimation did not show performance advantages over ML. For categorical indicators, Bayesian estimation outperformed WLSMV solely in case of strongly informative accurate priors. Weakly informative inaccurate priors did not deteriorate performance of the Bayesian approach, while strong informative inaccurate priors led to severely biased estimates even with large sample sizes. With diffuse priors, Stan yielded better results than Mplus in terms of parameter estimates.
José G Dias
Full Text Available This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state whenever no other indicators of household living conditions are available.
Dias, José G; de Oliveira, Isabel Tiago
This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available.
Full Text Available In some industries such as logistics services, bank services, and others, the use of automated systems that deliver critical business information anytime and anywhere play an important role in the decision making process. This paper introduces a "Generic model to send secure alerts and notifications", which operates as a middleware between enterprise data sources and its mobile users. This model uses Short Message Service (SMS as its main mobile messaging technology, however is open to use new types of messaging technologies. Our model is interoperable with existing information systems, it can store any kind of information about alerts or notifications at different levels of granularity, it offers different types of notifications (as analert when critical business problems occur,asanotificationina periodical basis or as 2 way query. Notification rules can be customized by final users according to their preferences. The model provides a security framework in the cases where information requires confidentiality, it is extensible to existing and new messaging technologies (like e–mail, MMS, etc. It is a platform, mobile operator and hardware independent. Currently, our solution is being used at the Comisión Federal de Electricidad (Mexico's utility company to deliver secure alerts related to critical events registered in the main power generation plants of our country.
Nozick, Linda Karen; Jones, Dean A.; Davis, Chad Edward; Turnquist, Mark Alan
A model of malicious intrusions in infrastructure facilities is developed, using a network representation of the system structure together with Markov models of intruder progress and strategy. This structure provides an explicit mechanism to estimate the probability of successful breaches of physical security, and to evaluate potential improvements. Simulation is used to analyze varying levels of imperfect information on the part of the intruders in planning their attacks. An example of an intruder attempting to place an explosive device on an airplane at an airport gate illustrates the structure and potential application of the model.
In contrast, law enforcement officers at a jail have a better gestalt understanding of homeland security threats and trends in the same...and my personal familiarity with each model. In his book Beyond the Two Disciplines of Scientific Psychology , Lee Cronbach claims that...muhajir.background/index.html Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology . Washington, D.C.: American Psychologist
Gallego, Blanca; Westbrook, Mary T; Dunn, Adam G; Braithwaite, Jeffrey
To use multilevel modelling to compare the patient safety cultures of types of services across a health system and to determine whether differences found can be accounted for by staffs' professions, organizational roles, ages and type of patient care provided. Application of a hierarchical two-level regression model. All services in the South Australian public health system. Approximately half of the health staff (n = 14 054) in the 46 organizations, classified into 18 types of service, which made up the South Australian public health system. Staff completed the Safety Attitudes Questionnaire. Attitudes regarding Teamwork Climate, Safety Climate, Job Satisfaction, Stress Recognition, Perception of Management and Working Conditions in participants' workplaces. All SAQ indices showed statistically significant although modest variations according to service type. However, most of these differences were not accounted for by the differences in the demographic composition of services' staff. Most favourable safety attitudes were found in the breast screening, primary/community health services, community nursing and metropolitan non-teaching hospitals. Poorer cultures were reported in the psychiatric hospital, mental health, metropolitan ambulance services and top-level teaching hospitals. Demographic differences in safety attitudes were observed; particularly, clinical, senior managerial, aged care and older staff held more favourable attitudes. Differences in staff attitudes have been demonstrated at a macro-level across the type of health services but for the most part, differences could not be explained by staffing composition.
Borchers, Allison M.; Xiarchos, Irene; Beckman, Jayson
This article offers the first national examination of the determinants of adoption of wind and solar energy generation on U.S. farming operations. The inclusion of state policies and characteristics in a multilevel modeling approach distinguishes this study from past research utilizing logit models of technology adoption which focus only on the characteristics of the farm operation. Results suggest the propensity to adopt is higher for livestock operations, larger farms, operators with internet access, organic operations, and newer farmers. The results find state characteristics such as solar resources, per capita income levels, and predominantly democratic voting increasing the odds of farm adoption. This research suggests the relevance of state policy variables in explaining farm level outcomes is limited, although in combination best practice net metering and interconnection policies—policies designed to encourage the development of small scale distributed applications—are shown to increase the likelihood of farm solar and wind adoption. The prevalence of electric cooperatives—which are often not subject to state renewable energy policies and often service farms—is negatively related with the propensity to adopt and suggests that policy design may be a factor. - Highlights: • This is the first national examination of wind and solar energy adoption on U.S. farms. • Controlling for state policies distinguishes this study from past research of technology adoption. • We find net metering and interconnection policies increase the likelihood of farm adoption. • Results suggest that the design of renewable energy policies may limit their impact on farms
Recent years have shown increased awareness of the importance of sample size determination in experimental research. Yet effective and convenient methods for sample size determination, especially in longitudinal experimental design, are still under development, and application of power analysis in applied research remains limited. This article presents a convenient method for sample size determination in longitudinal experimental research using a multilevel model. A fundamental idea of this method is transformation of model parameters (level 1 error variance [σ(2)], level 2 error variances [τ 00, τ 11] and its covariance [τ 01, τ 10], and a parameter representing experimental effect [δ]) into indices (reliability of measurement at the first time point [ρ 1], effect size at the last time point [Δ T ], proportion of variance of outcomes between the first and the last time points [k], and level 2 error correlation [r]) that are intuitively understandable and easily specified. To foster more convenient use of power analysis, numerical tables are constructed that refer to ANOVA results to investigate the influence on statistical power by respective indices.
Nikaein, Navid; Kanti Datta, Soumya; Marecar, Irshad; Bonnet, Christian
In this paper, we present a model for application distribution and related security attacks in dense vehicular ad hoc networks (VANET) and sparse VANET which forms a delay tolerant network (DTN). We study the vulnerabilities of VANET to evaluate the attack scenarios and introduce a new attacker`s model as an extension to the work done in . Then a VANET model has been proposed that supports the application distribution through proxy app stores on top of mobile platforms installed in vehicles. The steps of application distribution have been studied in detail. We have identified key attacks (e.g. malware, spamming and phishing, software attack and threat to location privacy) for dense VANET and two attack scenarios for sparse VANET. It has been shown that attacks can be launched by distributing malicious applications and injecting malicious codes to On Board Unit (OBU) by exploiting OBU software security holes. Consequences of such security attacks have been described. Finally, countermeasures including the concepts of sandbox have also been presented in depth.
Murphy, Daniel L.; Beretvas, S. Natasha
This study examines the use of cross-classified random effects models (CCrem) and cross-classified multiple membership random effects models (CCMMrem) to model rater bias and estimate teacher effectiveness. Effect estimates are compared using CTT versus item response theory (IRT) scaling methods and three models (i.e., conventional multilevel…
Darya Sergeevna Simonenkova
Full Text Available The subject of the research is modeling and security threat assessments of data processed in cloud based information systems (CBIS. This method allow to determine the current security threats of CBIS, state of the system in which vulnerabilities exists, level of possible violators, security properties and to generate recommendations for neutralizing security threats of CBIS.
Philippens CONTRACTING ORGANIZATION: TNO Defense Safety and Security RYSWYK 2288GJ REPORT DATE: September 2007...approach in a primate model system 5b. GRANT NUMBER W81XWH-05-1-0517 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Philippens , Ingrid, H.; Verhave... Philippens , 2006) it has generally accepted to have a well tolerated profile in human users (Bensimon et al., 1994). The ‘drowsiness’ does seem to have
Xu, Jinchao [Pennsylvania State Univ., University Park, PA (United States). Dept. of Mathematics
In this project, we carried out many studies on adaptive and parallel multilevel methods for numerical modeling for various applications, including Magnetohydrodynamics (MHD) and complex fluids. We have made significant efforts and advances in adaptive multilevel methods of the multiphysics problems: multigrid methods, adaptive finite element methods, and applications.
Efe Biresselioglu, Mehmet; Hakan Demir, Muhittin; Kandemir, Cansu
Turkey was among those countries which decided to increase its natural gas consumption in the 1990s, due to its relative low cost and lack of impact on the environment. However, a heavy dependence on imports, from Algeria, Qatar and Nigeria, respectively, creates a threat to energy security, both in terms of source and supply diversity. Accordingly, we follow an analytical approach to identify the accuracy of our assumption, considering the current economic, political and security risk. To this end, we formulate and solve a mixed integer programming model that determines the optimal sourcing strategy for Turkey’s increasing LNG demand. This model demonstrates a number of alternative policy options for LNG supply. Furthermore, we consider that increasing the proportion of LNG in the overall gas supply will contribute to the aim of improving Turkey’s level of energy security. - Highlights: ► Turkey’s best policy option is to increase the share of LNG. ► Turkey’s main suppliers of LNG will be Algeria, Egypt, Nigeria, and Trinidad and Tobago. ► Norway, Libya, and Oman contribute to the supply with rather smaller shares. ► With high risk scenario Algeria, Egypt, Nigeria and Libya will not be suppliers. ► Oman and Qatar will cover; even though they are high-cost suppliers.
Robert S. Anderson; Mark Schanfein; Trond Bjornard; Paul Moskowitz
Many critical infrastructure sectors have been investigating cyber security issues for several years especially with the help of two primary government programs. The U.S. Department of Energy (DOE) National SCADA Test Bed and the U.S. Department of Homeland Security (DHS) Control Systems Security Program have both implemented activities aimed at securing the industrial control systems that operate the North American electric grid along with several other critical infrastructure sectors (ICS). These programs have spent the last seven years working with industry including asset owners, educational institutions, standards and regulating bodies, and control system vendors. The programs common mission is to provide outreach, identification of cyber vulnerabilities to ICS and mitigation strategies to enhance security postures. The success of these programs indicates that a similar approach can be successfully translated into other sectors including nuclear operations, safeguards, and security. The industry regulating bodies have included cyber security requirements and in some cases, have incorporated sets of standards with penalties for non-compliance such as the North American Electric Reliability Corporation Critical Infrastructure Protection standards. These DOE and DHS programs that address security improvements by both suppliers and end users provide an excellent model for nuclear facility personnel concerned with safeguards and security cyber vulnerabilities and countermeasures. It is not a stretch to imagine complete surreptitious collapse of protection against the removal of nuclear material or even initiation of a criticality event as witnessed at Three Mile Island or Chernobyl in a nuclear ICS inadequately protected against the cyber threat.
Archer, Myla; Leonard, Elizabeth; Pradella, Matteo
Security-Enhanced (SE) Linux is a modification of Linux initially released by NSA in January 2001 that provides a language for specifying Linux security policies and, as in the Flask architecture, a security server...
Qianmu, Li; Jie, Yin; Jun, Hou; Jian, Xu; Hong, Zhang; Yong, Qi
A service access control model in cyberspace is proposed, which provides a generalized and effective mechanism of security management with some items constraint specifications. These constraint specifications are organized to form a construction, and an enact process is proposed to make it scalable and flexible to meet the need of diversified service application systems in cyberspace. The model of this paper erases the downward information flow by extended rules of read/write, which is the breakthrough of the limitations when applying the standard role-based access control in cyberspace.
Maxwell, Sophie; Reynolds, Katherine J; Lee, Eunro; Subasic, Emina; Bromhead, David
School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add "value" to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic demographics. Achievement was assessed using a national literacy and numeracy tests ( N = 760 staff and 2,257 students from 17 secondary schools). In addition, guided by the "social identity approach," school identification is investigated as a possible psychological mechanism to explain the relationship between school climate and achievement. In line with predictions, results show that students' perceptions of school climate significantly explain writing and numeracy achievement and this effect is mediated by students' psychological identification with the school. Furthermore, staff perceptions of school climate explain students' achievement on numeracy, writing and reading tests (while accounting for students' responses). However, staff's school identification did not play a significant role. Implications of these findings for organizational, social, and educational research are discussed.
Volpert-Esmond, Hannah I; Merkle, Edgar C; Levsen, Meredith P; Ito, Tiffany A; Bartholow, Bruce D
EEG data, and specifically the ERP, provide psychologists with the power to examine quickly occurring cognitive processes at the native temporal resolution at which they occur. Despite the advantages conferred by ERPs to examine processes at different points in time, ERP researchers commonly ignore the trial-to-trial temporal dimension by collapsing across trials of similar types (i.e., the signal averaging approach) because of constraints imposed by repeated measures ANOVA. Here, we present the advantages of using multilevel modeling (MLM) to examine trial-level data to investigate change in neurocognitive processes across the course of an experiment. Two examples are presented to illustrate the usefulness of this technique. The first demonstrates decreasing differentiation in N170 amplitude to faces of different races across the course of a race categorization task. The second demonstrates attenuation of the ERN as participants commit more errors within a task designed to measure implicit racial bias. Although the examples presented here are within the realm of social psychology, the use of MLM to analyze trial-level EEG data has the potential to contribute to a number of different theoretical domains within psychology. © 2017 Society for Psychophysiological Research.
The epidemics of sexually transmitted infections (STIs) have spread among older adults in the world, including China. This study addresses the deficiency of studies about the multiple contextual influences on condom use among mid-age female sex workers (FSWs) over 35 years old. A combination of an egocentric network design and multilevel modeling was used to investigate factors of condom use over mid-age FSWs (egos) particular relationships with sexual partners (alters). Of the 1245 mid-age FSWs interviewed, 73% (907) reported having at least one sexual partner who would provide social support to egos. This generated a total of 1300 ego-alter sex ties in egos' support networks. Condoms were consistently used among one-third of sex ties. At the ego level, condoms were more likely to be used consistently if egos received a middle school education or above, had stronger perceived behavioral control for condom use, or consistently used condoms with other sex clients who were not in their support networks. At the alter level, condoms were not consistently used over spousal ties compared to other ties. Condoms were less likely to be used among alters whom ego trusted and provided emotional support. Cross-level factors (egos' attitudes toward condom use and emotional support from alters) documented a significant positive interaction on consistent condom use. Given the low frequency of condom use, future interventions should focus on mid-age FSWs and their partners within and beyond their support networks.
Maxwell, Sophie; Reynolds, Katherine J.; Lee, Eunro; Subasic, Emina; Bromhead, David
School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add “value” to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic demographics. Achievement was assessed using a national literacy and numeracy tests (N = 760 staff and 2,257 students from 17 secondary schools). In addition, guided by the “social identity approach,” school identification is investigated as a possible psychological mechanism to explain the relationship between school climate and achievement. In line with predictions, results show that students' perceptions of school climate significantly explain writing and numeracy achievement and this effect is mediated by students' psychological identification with the school. Furthermore, staff perceptions of school climate explain students' achievement on numeracy, writing and reading tests (while accounting for students' responses). However, staff's school identification did not play a significant role. Implications of these findings for organizational, social, and educational research are discussed. PMID:29259564
Full Text Available OBJECTIVES: To investigate associations between nurse work practice environment measured at department level and individual level work-family conflict on burnout, measured as emotional exhaustion, depersonalization and personal accomplishment among Swedish RNs. METHODS: A multilevel model was fit with the individual RN at the 1st, and the hospital department at the 2nd level using cross-sectional RN survey data from the Swedish part of RN4CAST, an EU 7th framework project. The data analysed here is based on a national sample of 8,620 RNs from 369 departments in 53 hospitals. RESULTS: Generally, RNs reported high values of personal accomplishment and lower values of emotional exhaustion and depersonalization. High work-family conflict increased the risk for emotional exhaustion, but for neither depersonalization nor personal accomplishment. On department level adequate staffing and good leadership and support for nurses reduced the risk for emotional exhaustion and depersonalization. Personal accomplishment was statistically significantly related to staff adequacy. CONCLUSIONS: The findings suggest that adequate staffing, good leadership, and support for nurses are crucial for RNs' mental health. Our findings also highlight the importance of hospital managers developing policies and practices to facilitate the successful combination of work with private life for employees.
Full Text Available School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add “value” to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic demographics. Achievement was assessed using a national literacy and numeracy tests (N = 760 staff and 2,257 students from 17 secondary schools. In addition, guided by the “social identity approach,” school identification is investigated as a possible psychological mechanism to explain the relationship between school climate and achievement. In line with predictions, results show that students' perceptions of school climate significantly explain writing and numeracy achievement and this effect is mediated by students' psychological identification with the school. Furthermore, staff perceptions of school climate explain students' achievement on numeracy, writing and reading tests (while accounting for students' responses. However, staff's school identification did not play a significant role. Implications of these findings for organizational, social, and educational research are discussed.
van Cleeff, A.
In the interconnected world that we live in, traditional security barriers are broken down. Developments such as outsourcing, increased usage of mobile devices and wireless networks each cause new security problems. To address the new security threats, a number of solutions have been suggested,
Ralf Elsner; Manfred Krafft; Arnd Huchzermeier
We introduce Dynamic Multilevel Modeling (DMLM) to a multicatalog-brand environment to determine the optimal frequency, size, and customer segmentation of direct marketing activities. This optimization method leverages multicatalog-brand effects including the utilization of prior customer ordering behavior, maximization of customer value and customer share, and economies of scale and scope in printing and mailing. This enhancement of the original DMLM-approach is called Dynamic Multidimension...
Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric
Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.
Pegalajar Jurado, Antonio Manuel; Bredmose, Henrik; Borg, Michael
In the present paper the accuracy of three numerical models for a scaled 10MW TLP wind turbine is assessed by comparison with test data. The three models present different levels of complexity, and therefore different degrees of accuracy can be expected. A set of load cases including irregular an...
But, this higher in number of parameter cannot be considered as a disadvantage in a situation when model (5) better fits the data. Relationship between marginal and random effect model parameters. Zeger et al. (1988) derived an approximate relation- ship for the population averaged parameters (from. GEE) and subject ...
Full Text Available The growth of Internet online services has been very quick in recent years. Each online service requires Internet users to create a new account to use the service. The problem can be seen when each user usually needs more than one service and, consequently, has numerous accounts. These numerous accounts have to be managed in a secure and simple way to be protected against identity theft. Single sign-on (SSO and OpenID have been used to decrease the complexity of managing numerous accounts required in the Internet identity environment. Trusted Platform Module (TPM and Trust Multitenancy are great trusted computing-based technologies to solve security concerns in the Internet identity environment. Since trust is one of the pillars of security in the cloud, this paper analyzes the existing cloud identity techniques in order to investigate their strengths and weaknesses. This paper proposes a model in which One Time Password (OTP, TPM, and OpenID are used to provide a solution against phishing as a common identity theft in cloud environment.
Marí-Dell'Olmo, Marc; Martínez-Beneito, Miguel Ángel
In recent years, small-area-based ecological regression analyses have been published that study the association between a health outcome and a covariate in several cities. These analyses have usually been performed independently for each city and have therefore yielded unrelated estimates for the cities considered, even though the same process has been studied in all of them. In this study, we propose a joint ecological regression model for multiple cities that accounts for spatial structure both within and between cities and explore the advantages of this model. The proposed model merges both disease mapping and geostatistical ideas. Our proposal is compared with two alternatives, one that models the association for each city as fixed effects and another that treats them as independent and identically distributed random effects. The proposed model allows us to estimate the association (and assess its significance) at locations with no available data. Our proposal is illustrated by an example of the association between unemployment (as a deprivation surrogate) and lung cancer mortality among men in 31 Spanish cities. In this example, the associations found were far more accurate for the proposed model than those from the fixed effects model. Our main conclusion is that ecological regression analyses can be markedly improved by performing joint analyses at several locations that share information among them. This finding should be taken into consideration in the design of future epidemiological studies.
Full Text Available The goal of this contribution is especially to familiarize experts in various fields with the need for a new approach to the system-defined model and modelling of processes in the engineering practice and the expression of some state variables' possibilities for the modelling of real-world systems with regard to the highly dynamic development of structures and to the behaviour of systems of logistics. Thus, in this contribution, the necessity of making full use of cybernetics as a field for the management and communication of information is expressed, and also the environment of cybernetics as a much needed cybernetic realm (cyberspace, determining the steady state between cyber-attacks and cyber-defence as a modern knowledge-based potential in general and specifically of logistics in cyber security. Connected with this process is the very important area of lifelong training of experts in the dynamic world of science and technology (that is, also in a social system which is also expressed here briefly, and also the cyber and information security, all of which falls under the cyberspace of new perspective electronic learning (e-learning with the use of modern laboratories with new effects also for future possibilities of process modelling of artificial intelligence (AI with a perspective of mass use of UAVs in logistics.
Kroll, Andrew J.; Garcia, Tiffany S.; Jones, Jay E.; Dugger, Catherine; Murden, Blake; Johnson, Josh; Peerman, Summer; Brintz, Ben; Rochelle, Michael
Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29). Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions
Qing, Hai; Mishnaevsky, Leon
A 3D hierarchical computational model of damage and strength of wood is developed. The model takes into account the four scale microstructures of wood, including the microfibril reinforced structure at nanoscale, multilayered cell walls at microscale, hexagon-shape-tube cellular structure at meso...... arrangements and cellulose strength distributions on the tensile strength of wood is studied numerically. Good agreement of the theoretical results with experimental data has been obtained.......A 3D hierarchical computational model of damage and strength of wood is developed. The model takes into account the four scale microstructures of wood, including the microfibril reinforced structure at nanoscale, multilayered cell walls at microscale, hexagon-shape-tube cellular structure...
Full Text Available level random effects to capture facility heterogeneity and dependence between individuals in the same facility, and a set of covariates to account for individual heterogeneity. Identifiability associated with structural equations modeling is addressed...
Shaji, C.; Bahulayan, N.; Dube, S.K.; Rao, A.D.
on the observed circulation in the western tropical Indian Ocean. The model consists of equations of motion and continuity, sea surface topography, equations of state and temperature, and salinity diffusion equations. While the sea surface topography equation...
primacy effect and recency effect ). Otg: The consequence of a response, usually resulting in some change in the situation. ELLm = effect : This occurs...strong recency effect for conflicting evidence. In contrast, the discounting version of an anchoring-and-adjusting model (Tversky and 15 TM No. 86-2083...Kahneman, 1974) predicts a primacy effect for strongly held opinions. Bayesian models predict no order effects . Evidence for how beliefs are updated is
Dmitry N. Krasikov
Full Text Available Theoretical analysis of optimization options for the properties of CdTe absorber layer is an important task for increasing the efficiency of CdTe/CdS heterojunction based thin-film solar cells. Properties of the materials (e.g. the density of free carriers often depend essentially on the parameters of the deposition process and subsequent treatment which determine the defect composition of the material. In this work a model based on the lattice kinetic Monte-Carlo method is developed to describe the process of CdTe deposition as a function of temperature and Cd and Te fluxes. To determine the effect of the treatment conditions on CdTe conductivity, we developed a quasichemical model based on the electrical neutrality equation for point defect concentrations that are described by defect formation reaction constants. Parameters obtained from the first-principles density functional calculations were used for developing the models. The developed deposition model correctly describes the transition from evaporation to precipitation as well as the increased evaporation rates in excess of Cd. To explain the observed electrical properties of CdTe after Cl-treatment, we complemented the quasichemical defect model by a deep acceptor complex defect that allowed us to describe both the high-temperature dependence of conductivity on the Cd pressure and the dependence of resistivity on Cl concentration at room temperature.
El-Khatib, Walid Ziad; Holbøll, Joachim; Rasmussen, Tonny Wederberg
). This means that a high frequency model of the converter has to be designed, which gives a better overview of the impact of high frequency transients etc. The functionality of the model is demonstrated by application to grid connections of off-shore wind power plants. Grid connection of an offshore wind power...... plant using HVDC fundamentally changes the electrical environment for the power plant. Detailed knowledge and understanding of the characteristics and behavior of all relevant power system components under all conditions, including under transients, are required in order to develop reliable offshore...... wind power plant employing HVDC. In the present study, a back to back HVDC transmission system is designed in PSCAD/EMTDC. Simulations and results showing the importance of high frequent modeling are presented....
Full Text Available Background: Dairy products account for approximately 60% of the iodine intake in the Norwegian population. The iodine concentration in cow's milk varies considerably, depending on feeding practices, season, and amount of iodine and rapeseed products in cow fodder. The variation in iodine in milk affects the risk of iodine deficiency or excess in the population. Objective: The first goal of this study was to develop a model to predict the iodine concentration in milk based on the concentration of iodine and rapeseed or glucosinolate in feed, as a tool to securing stable iodine concentration in milk. A second aim was to estimate the impact of different iodine levels in milk on iodine nutrition in the Norwegian population. Design: Two models were developed on the basis of results from eight published and two unpublished studies from the past 20 years. The models were based on different iodine concentrations in the fodder combined with either glucosinolate (Model 1 or rapeseed cake/meal (Model 2. To illustrate the impact of different iodine concentrations in milk on iodine intake, we simulated the iodine contribution from dairy products in different population groups based on food intake data in the most recent dietary surveys in Norway. Results: The models developed could predict iodine concentration in milk. Cross-validation showed good fit and confirmed the explanatory power of the models. Our calculations showed that dairy products with current iodine level in milk (200 µg/kg cover 68, 49, 108 and 56% of the daily iodine requirements for men, women, 2-year-old children, and pregnant women, respectively. Conclusions: Securing a stable level of iodine in milk by adjusting iodine concentration in different cow feeds is thus important for preventing excess intake in small children and iodine deficiency in pregnant and non-pregnant women.
Zhang, Xinxin; Lind, Morten; Jørgensen, Sten Bay
situation and support operational decisions. This paper will provide a general MFM model of the primary side in a standard Westinghouse Pressurized Water Reactor ( PWR ) system including sub - systems of Reactor Coolant System, Rod Control System, Chemical and Volume Control System, emergency heat removal...
Lee, Sunghye; Koszalka, Tiffany A.
The First Principles of Instruction (FPI) represent ideologies found in most instructional design theories and models. Few attempts, however, have been made to empirically test the relationship of these FPI to instructional outcomes. This study addresses whether the degree to which FPI are implemented in courses makes a difference to student…
Tsai, S. L.; Smith, Michael; Hauser, R. M.
Roč. 90, č. 1 (2017), s. 64-88 ISSN 0038-0407 R&D Projects: GA ČR GCP404/12/J006; GA ČR GB14-36154G Institutional support: RVO:67985998 Keywords : MIMIC model * educational inequality * academic performance Subject RIV: AO - Sociology, Demography OBOR OECD: Sociology Impact factor: 2.697, year: 2016
Zhang, Yi; Wang, Huai; Wang, Zhongxu
Power cycling in semiconductor modules contributes to repetitive thermal-mechanical stresses, which in return accumulate as fatigue on the devices, and challenge the lifetime. Typically, lifetime models are expressed in number-of-cycles, within which the device can operate without failures under ...
Full Text Available The present study used the two-level testlet response model (MMMT-2 to assess impact, differential item functioning (DIF, and differential testlet functioning (DTLF in a reading comprehension test. The data came from 21,641 applicants into English Masters’ programs at Iranian state universities. Testlet effects were estimated, and items and testlets that were functioning differentially for test takers of different genders and majors were identified. Also parameter estimates obtained under MMMT-2 and those obtained under the two-level hierarchical generalized linear model (HGLM-2 were compared. The results indicated that ability estimates obtained under the two models were significantly different at the lower and upper ends of the ability distribution. In addition, it was found that ignoring local item dependence (LID would result in overestimation of the precision of the ability estimates. As for the difficulty of the items, the estimates obtained under the two models were almost the same, but standard errors were significantly different.
Klein Entink, R.H.; Fox, Gerardus J.A.; van der Linden, Willem J.
Response times on test items are easily collected in modern computerized testing. When collecting both (binary) responses and (continuous) response times on test items, it is possible to measure the accuracy and speed of test takers. To study the relationships between these two constructs, the model
Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew
Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and
Wu, Xuan; Wang, Xiaojie; Mei, Tao; Sun, Shaoming
This paper proposes a multi-level hierarchical model for the Tokay gecko (Gekko gecko) adhesive system and analyses the digital behaviour of the G. gecko under macro/meso-level scale. The model describes the structures of G. gecko's adhesive system from the nano-level spatulae to the sub-millimetre-level lamella. The G. gecko's seta is modelled using inextensible fibril based on Euler's elastica theorem. Considering the side contact of the spatular pads of the seta on the flat and rigid subst...
Netzer, Colonel Gideon
This paper presents a generic model for dealing with security problems along borders between countries. It presents descriptions and characteristics of various borders and identifies the threats to border security, while emphasizing cooperative monitoring solutions.
Short, C. Ian; Hauschildt, Peter H.; Baron, E.
We have used our PHOENIX multipurpose model atmosphere code to calculate atmospheric models that represent novae in the optically thick wind phases of their outburst. We have improved the treatment of non-local thermodynamic equilibrium (NLTE) effects by expanding the number of elements that are included in the calculations from 15 to 19 and the number of ionization stages from 36 to 87. The code can now treat a total of 10,713 levels and 102,646 lines in NLTE. Al, P, K, and Ni are included for the first time in the NLTE treatment, and most elements now have at least the lowest six ionization stages included in the NLTE calculation. We have investigated the effects of expanded NLTE treatment on the chemical concentration of astrophysically significant species in the atmosphere, the equilibrium structure of the atmosphere, and the emergent flux distribution. Although we have found general qualitative agreement with previous, more limited NLTE models, the expanded NLTE treatment leads to significantly different values for the size of many of the NLTE deviations. In particular, for the hottest model presented here (T eff =35,000 K), for which NLTE effects are largest, we find that the expanded NLTE treatment reduces the NLTE effects for these important variables: H i concentration, pressure structure, and emergent far-UV flux. Moreover, we find that the addition of new NLTE species may greatly affect the concentration of species that were already treated in NLTE, so that, generally, all species that contribute significantly to the e - reservoir or to the total opacity, or whose line spectrum overlaps or interlocks with that of a species of interest, must be treated in NLTE to ensure an accurate result for any particular species. (c) (c) 1999. The American Astronomical Society
Moghaddasi, Hamid; Sajjadi, Samad; Kamkarhaghighi, Mehran
Any information which is generated and saved needs to be protected against accidental or intentional losses and manipulations if it is to be used by the intended users in due time. As such, information managers have adopted numerous measures to achieve data security within data storage systems, along with the spread of information technology. The "data security models" presented thus far have unanimously highlighted the significance of data security management. For further clarification, the current study first introduces the "needs and improvement" cycle; the study will then present some independent definitions, together with a support umbrella, in an attempt to shed light on the data security management. Data security focuses on three features or attributes known as integrity, identity of sender(s) and identity of receiver(s). Management in data security follows an endless evolutionary process, to keep up with new developments in information technology and communication. In this process management develops new characteristics with greater capabilities to achieve better data security. The characteristics, continuously increasing in number, with a special focus on control, are as follows: private zone, confidentiality, availability, non-repudiation, possession, accountability, authenticity, authentication and auditability. Data security management steadily progresses, resulting in more sophisticated features. The developments are in line with new developments in information and communication technology and novel advances in intrusion detection systems (IDS). Attention to differences between data security and data security management by international organizations such as the International Standard Organization (ISO), and International Telecommunication Union (ITU) is necessary if information quality is to be enhanced.
Loeys, Tom; Josephy, Haeike; Dewitte, Marieke
In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be confounded by an (un)measured upper-level factor. When such confounding is left unaddressed, the effect of the lower-level predictor is estimated with bias. Separating this effect into a within- and between-component removes such bias in a linear random intercept model under a specific set of assumptions for the confounder. When the effect of the lower-level predictor is additionally moderated by another lower-level predictor, an interaction between both lower-level predictors is included into the model. To address unmeasured upper-level confounding, this interaction term ought to be decomposed into a within- and between-component as well. This can be achieved by first multiplying both predictors and centering that product term next, or vice versa. We show that while both approaches, on average, yield the same estimates of the interaction effect in linear models, the former decomposition is much more precise and robust against misspecification of the effects of cross-level and upper-level terms, compared to the latter.
Harvey, Natalie J.; Huntley, Nathan; Dacre, Helen F.; Goldstein, Michael; Thomson, David; Webster, Helen
Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational
N. J. Harvey
Full Text Available Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations
Watanabe, Mayumi; Yamauchi, Keita
Few studies have investigated the impact of psychosocial factors on overwork and employee well-being while taking into account the complex relationships between such factors and the effect of workplace. The present study aimed to examine the association between psychosocial factors of overtime work and work-nonwork balance using a multilevel structural equation modeling (SEM) technique. A survey was conducted among nurses working in three hospitals (n = 603) in Japan. After confirming the constructs of the factors by confirmatory factor analysis (CFA) and exploratory factor analysis (EFA), a multilevel SEM was conducted to investigate the direct and indirect effects of involuntary and voluntary overtime work on work-nonwork balance at both individual and workplace levels. Both involuntary and voluntary overtime work factors were further differentiated into two factors (four factors in total). Involuntary overtime work directly decreased work-nonwork balance on both levels; voluntary overtime work had a direct positive effect. However, voluntary overtime work had a negative indirect effect on work-nonwork balance satisfaction. The use of multilevel SEM techniques to evaluate the association of clinical factors with work-nonwork balance demonstrated that involuntary overtime work has a negative effect on work-nonwork balance and voluntary overtime work had a positive direct effect but a negative indirect effect.
Kubovcikova, Annamária; van Bakel, Marian
This article explores the immediate network context of self-initiated expatriates and how it influences their work information and emotional support. Building on the information seeking theory and the theory of weak and strong ties, we have created a model connecting specific characteristics...... employment status is then mediated to work information and emotional support on the other hand; negative effect of host country origin is affecting emotional support only. The effect of status was likely conflated with host country origin in the previously published results, leading to biased conclusions....
Full Text Available With the rapid development of economy, the supplier network is becoming more and more complicated. It is important to choose the right suppliers for improving the efficiency of the supply chain, so how to choose the right ones is one of the important research directions of supply chain management. This paper studies the partner selection problem from the perspective of supplier network global optimization. Firstly, this paper discusses and forms the evaluation system to estimate the supplier from the two indicators of risk and greenness and then applies the value as the weight of the network between two nodes to build a weighted-directed supplier network; secondly, the study establishes the optimal combination model of supplier selection based on the global network perspective and solves the model by the dynamic programming-tabu search algorithm and the improved ant colony algorithm, respectively; finally, different scale simulation examples are given to testify the efficiency of the two algorithms. The results show that the ant colony algorithm is superior to the tabu search one as a whole, but the latter is slightly better than the former when network scale is small.
Richmond-Bryant, Jennifer; Meng, Qingyu; Davis, J Allen; Cohen, Jonathan; Svendsgaard, David; Brown, James S; Tuttle, Lauren; Hubbard, Heidi; Rice, Joann; Kirrane, Ellen; Vinikoor-Imler, Lisa; Kotchmar, Dennis; Hines, Erin; Ross, Mary
National and local declines in lead (Pb) in blood (PbB) over the past several years coincide with the decline in ambient air Pb (PbA) concentrations. The objective of this work is to evaluate how the relationship between PbB levels and PbA levels has changed following the phase out of leaded gasoline and tightened controls on industrial Pb emissions over the past 30 years among a national population sample. Participant-level data from the National Health and Nutrition Examination Survey (NHANES) were employed for two time periods (1988-1994 and 1999-2008), and the model was corrected for housing, demographic, socioeconomic, and other covariates present in NHANES. NHANES data for PbB and covariates were merged with PbA data from the U.S. Environmental Protection Agency. Linear mixed effects models (LMEs) were run to assess the relationship of PbB with PbA; sample weights were omitted, given biases encountered with the use of sample weights in LMEs. The 1988-1994 age-stratified results found that ln(PbB) was statistically significantly associated with ln(PbA) for all age groups. The consistent influence of PbA on PbB across age groups for the years 1988-1994 suggests a ubiquitous exposure unrelated to age of the sample population. The comparison of effect estimates for ln(PbA) shows a statistically significant effect estimate and ANOVA results for ln(PbB) for the 6- to 11-year and 12- to 19-year age groups during 1999-2008. The more recent finding suggests that PbA has less consistent influence on PbB compared with other factors. Copyright © 2013 Elsevier B.V. All rights reserved.
Feng, Nan; Zheng, Chundong
Given the increasing cooperation between organizations, the flexible exchange of security information across the allied organizations is critical to effectively manage information systems (IS) security in a distributed environment. In this paper, we develop a cooperative model for IS security risk management in a distributed environment. In the proposed model, the exchange of security information among the interconnected IS under distributed environment is supported by Bayesian networks (BNs). In addition, for an organization's IS, a BN is utilized to represent its security environment and dynamically predict its security risk level, by which the security manager can select an optimal action to safeguard the firm's information resources. The actual case studied illustrates the cooperative model presented in this paper and how it can be exploited to manage the distributed IS security risk effectively.
Kim, Youngdeok; Cho, Jaehoon; Fuller, Dana K; Kang, Minsoo
The purpose of this study was to examine the correlates of physical activity (PA) with personal and environmental factors among people with disabilities in South Korea. Data from the 2011 National Survey for Physical Activity and Exercise for the Disabled, conducted by Korea Sports Association for the Disabled, was used (n = 1478). The personal characteristics (age, gender, occupation, types of disabilities, family income) and the numbers of public PA-related facilities (welfare center, public indoor gym, and public outdoor facilities) and social sports/exercise clubs for people with disabilities across 16 local areas were also obtained. Hierarchical generalized linear model was used to examine subjectively measured PA in relation to personal and environmental factors. The likelihood of engaging in PA was significantly lower for women with disabilities. People with hearing and intellectual disabilities were less likely to engage in PA compared with those with physical disabilities. The availability of sports/exercise clubs for people with disabilities was the only environmental factor that was significantly associated with PA. These findings suggest the need of systematic intervention strategies based upon personal characteristics of people with disabilities. Further public efforts to promote sports/exercise club activities should be encouraged in this population.
Zhang, Qiuwen; Yang, Xiaohong; Zhang, Yan; Zhong, Ming
Groundwater contamination is a serious threat to water supply. Risk assessment of groundwater contamination is an effective way to protect the safety of groundwater resource. Groundwater is a complex and fuzzy system with many uncertainties, which is impacted by different geological and hydrological factors. In order to deal with the uncertainty in the risk assessment of groundwater contamination, we propose an approach with analysis hierarchy process and fuzzy comprehensive evaluation integrated together. Firstly, the risk factors of groundwater contamination are identified by the sources-pathway-receptor-consequence method, and a corresponding index system of risk assessment based on DRASTIC model is established. Due to the complexity in the process of transitions between the possible pollution risks and the uncertainties of factors, the method of analysis hierarchy process is applied to determine the weights of each factor, and the fuzzy sets theory is adopted to calculate the membership degrees of each factor. Finally, a case study is presented to illustrate and test this methodology. It is concluded that the proposed approach integrates the advantages of both analysis hierarchy process and fuzzy comprehensive evaluation, which provides a more flexible and reliable way to deal with the linguistic uncertainty and mechanism uncertainty in groundwater contamination without losing important information.
Latimore, Amanda D; Burrell, Lori; Crowne, Sarah; Ojo, Kristen; Cluxton-Keller, Fallon; Gustin, Sunday; Kruse, Lakota; Hellman, Daniela; Scott, Lenore; Riordan, Annette; Duggan, Anne
The associations of family, home visitor and site characteristics with family engagement within the first 6 months were examined. The variation in family engagement was also explored. Home visiting program participants were drawn from 21 Healthy Families America sites (1707 families) and 9 Nurse-Family Partnership sites (650 families) in New Jersey. Three-level nested generalized linear mixed models assessed the associations of family, home visitor and site characteristics with family receipt of a high dose of services in the first 6 months of enrollment. A family was considered to have received a high dose of service in the first 6 months of enrollment if they were active at 6 months and had received at least 50% of their expected visits in the first 6 months. In general, both home visiting programs engaged, at a relatively high level (Healthy Families America (HFA) 59%, Nurse-Family Partnership (NFP) 64%), with families demonstrating high-risk characteristics such as lower maternal education, maternal smoking, and maternal mental health need. Home visitor characteristics explained more of the variation (87%) in the receipt of services for HFA, while family characteristics explained more of the variation (75%) in the receipt of services for NFP. At the family level, NFP may improve the consistency with which they engage families by increasing retention efforts among mothers with lower education and smoking mothers. HFA sites seeking to improve engagement consistency should consider increasing the flexible in home visitor job responsibilities and examining the current expected-visit policies followed by home visitors on difficult-to-engage families.
Lindgren, Peter; Taran, Yariv
secure—but we still have some steps to go before we reach the final destination. The paper gives a conceptual futuristic outlook on behalf of the input from SW2010 and state of the art business model research to what we can expect of business Model and business model innovation in a future secure cloud......The development and innovation of business models to a secure distributed cloud clustering society (DISC)—is indeed still a complex venture and has not been widely researched yet. Numerous types of security technologies are in these years proposed and in the “slip stream” of these the study...... of secure business models and how business models can be operated and innovated in a secure context have intensified tremendously. The development of new mobile and wireless security technologies gives hopes to really realize a secure cloud clustering society where business models can act and be innovated...
Full Text Available Researchers and practitioners often use standardized vocabulary tests such as the Peabody Picture Vocabulary Test-4 (PPVT-4; Dunn and Dunn, 2007 and its companion, the Expressive Vocabulary Test-2 (EVT-2; Williams, 2007, to assess English vocabulary skills as an indicator of children's school readiness. Despite their psychometric excellence in the norm sample, issues arise when standardized vocabulary tests are used to asses children from culturally, linguistically and ethnically diverse backgrounds (e.g., Spanish-speaking English language learners or delayed in some manner. One of the biggest challenges is establishing the appropriateness of these measures with non-English or non-standard English speaking children as often they score one to two standard deviations below expected levels (e.g., Lonigan et al., 2013. This study re-examines the issues in analyzing the PPVT-4 and EVT-2 scores in a sample of 4-to-5-year-old low SES Hispanic preschool children who were part of a larger randomized clinical trial on the effects of a supplemental English shared-reading vocabulary curriculum (Pollard-Durodola et al., 2016. It was found that data exhibited strong floor effects and the presence of floor effects made it difficult to differentiate the invention group and the control group on their vocabulary growth in the intervention. A simulation study is then presented under the multilevel structural equation modeling (MSEM framework and results revealed that in regular multilevel data analysis, ignoring floor effects in the outcome variables led to biased results in parameter estimates, standard error estimates, and significance tests. Our findings suggest caution in analyzing and interpreting scores of ethnically and culturally diverse children on standardized vocabulary tests (e.g., floor effects. It is recommended appropriate analytical methods that take into account floor effects in outcome variables should be considered.
Pawar, Pranav M.; Nielsen, Rasmus Hjorth; Prasad, Neeli R.
Applications of wireless sensor networks (WSNs) are growing tremendously in the domains of habitat, tele-health, industry monitoring, vehicular networks, home automation and agriculture. This trend is a strong motivation for malicious users to increase their focus on WSNs and to develop and initi......Applications of wireless sensor networks (WSNs) are growing tremendously in the domains of habitat, tele-health, industry monitoring, vehicular networks, home automation and agriculture. This trend is a strong motivation for malicious users to increase their focus on WSNs and to develop...... and initiate security attacks that disturb the normal functioning of the network in a severe manner. Such attacks affect the performance of the network by increasing the energy consumption, by reducing throughput and by inducing long delays. Of all existing WSN attacks, MAC layer attacks are considered...... the most harmful as they directly affect the available resources and thus the nodes’ energy consumption. The first endeavour of this paper is to model the activities of MAC layer security attacks to understand the flow of activities taking place when mounting the attack and when actually executing it...
Maria Gabriella Melchiorre
Full Text Available Several studies on elder abuse indicate that a large number of victims are women, but others report that men in later life are also significantly abused, especially when they show symptoms of disability and poor health, and require help for their daily activities as a result. This study focused on the prevalence of different types of abuse experienced by men and on a comparison of male victims and non-victims concerning demographic/socio-economic characteristics, lifestyle/health variables, social support and quality of life. Additionally, the study identified factors associated with different types of abuse experienced by men and characteristics associated with the victims.The cross-sectional data concerning abuse in the past 12 months were collected by means of interviews and self-response during January-July 2009, from a sample of 4,467 not demented individuals aged between 60-84 years living in seven European countries (Germany, Greece, Italy, Lithuania, Portugal, Spain and Sweden. We used a multilevel approach, within the framework of an Ecological Model, to explore the phenomenon of abuse against males as the complex result of factors from multiple levels: individual, relational, community and societal.Multivariate analyses showed that older men educated to higher levels, blue-collar workers and men living in a rented accommodation were more often victims than those educated to lower levels, low-rank white-collar workers and home owners, respectively. In addition, high scores for factors such as somatic and anxiety symptoms seemed linked with an increased probability of being abused. Conversely, factors such as increased age, worries about daily expenses (financial strain and greater social support seemed linked with a decreased probability of being abused.Male elder abuse is under-recognized, under-detected and under-reported, mainly due to the vulnerability of older men and to social/cultural norms supporting traditional male
Henry, Matthew H; Haimes, Yacov Y
The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.
Houghton, Robert F.
A long standing problem in information technology security is how to help reduce the security footprint. Many specific proposals exist to address specific problems in information technology security. Most information technology solutions need to be repeatable throughout the course of an information systems lifecycle. The Chain-Link Fence Model is…
Jensen, Meiko; Feja, Sven
The rising need for security in SOA applications requires better support for management of non-functional properties in web-based business processes. Here, the model-driven approach may provide valuable benefits in terms of maintainability and deployment. Apart from modeling the pure functionality...... of a process, the consideration of security properties at the level of a process model is a promising approach. In this work-in-progress paper we present an extension to the ARIS SOA Architect that is capable of modeling security requirements as a separate security model view. Further we provide...
Mediaty,; Said, Darwis; Syahrir,; Indrijawati, Aini
- This research aims to analyze the poverty, education, and health in social security system model based on accounting perspective using empirical study on South Sulawesi Province. Issued Law No. 40 for 2004 regarding National Social Security System is one of attentions from government about social welfare. Accounting as a social science deserves to create social security mechanisms. One of the crucial mechanisms is social security system. This research is a grounded exploratory research w...
Paletou, Frederic; Leger, Ludovick
The vast majority of recent advances in the field of numerical radiative transfer relies on approximate operator methods better known in astrophysics as Accelerated Lambda-Iteration (ALI). A superior class of iterative schemes, in term of rates of convergence, such as Gauss-Seidel and successive overrelaxation methods were therefore quite naturally introduced in the field of radiative transfer by Trujillo Bueno and Fabiani Bendicho [A novel iterative scheme for the very fast and accurate solution of non-LTE radiative transfer problems. Astrophys J 1995;455:646]; it was thoroughly described for the non-LTE two-level atom case. We describe hereafter in details how such methods can be generalized when dealing with non-LTE unpolarised radiation transfer with multilevel atomic models, in monodimensional geometry
Arenas, A.; Aziz, Benjamin; Bicarregui, J.; Matthews, B.; Yang, E.
In this paper, we discuss the use of formal requirements-engineering techniques in capturing security requirements for a Grid-based operating system. We use KAOS goal model to represent two security goals for Grid systems, namely authorisation and single-sign on authentication. We apply goal-refinement to derive security requirements for these two security goals and we develop a model of antigoals and show how system vulnerabilities and threats to the security goals can arise from such anti-m...
Houghton, Robert F.
A long standing problem in information technology security is how to help reduce the security footprint. Many specific proposals exist to address specific problems in information technology security. Most information technology solutions need to be repeatable throughout the course of an information systems lifecycle. The Chain-Link Fence Model is a new model for creating and implementing information technology procedures. This model was validated by two different methods: the first being int...
This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.
S. Morteza Ghayour
Full Text Available Any phenomenon can be considered and analyzed in terms of different perspectives. In multilevel theorists view, structure or structures of the studied phenomenon are used to consider or to analyze it, completely. Level of analysis indicates the purpose of a researcher or theorist that is intended to be explained or justified, like individual, group or organizational levels and then they are generalized. Contrary to multilevel approach, the conventional approach of theorizing considers micro level or macro level. It cannot perform a simultaneous micro–macro level analysis. A multilevel approach characterized by inter-level and multilevel organizational view to organizational phenomena is an attempt to expand the boundaries of knowledge and provide a new plan. This study uses documentary studies to analyze the multi-level approach of theorizing, multilevel models and multilevel analysis.
To ensure the likely success of an organisation’s Information Security Governance, discipline leaders recommend that organisations follow the guidelines as set out in Information Security Governance best practice documents. Best practices and related documents from the Information Security Governance discipline, as well as best practices and related documents from the Corporate Governance and Information Technology Governance disciplines, all include sections pertaining to Information Securit...
Sewe, Andreas; Bockisch, Christoph; Mezini, Mira
Various aspect-oriented languages, e.g., AspectJ, Aspect-Werkz, and JAsCo, have been proposed as extensions to one particular object-oriented base language, namely Java. But these extensions do not fully take the interactions with the Java 2 security model into account. In particular, the
Powell, John D.
This document discusses the verification of the Secure Socket Layer (SSL) communication protocol as a demonstration of the Model Based Verification (MBV) portion of the verification instrument set being developed under the Reducing Software Security Risk (RSSR) Trough an Integrated Approach research initiative. Code Q of the National Aeronautics and Space Administration (NASA) funds this project. The NASA Goddard Independent Verification and Validation (IV&V) facility manages this research program at the NASA agency level and the Assurance Technology Program Office (ATPO) manages the research locally at the Jet Propulsion Laboratory (California institute of Technology) where the research is being carried out.
System security assessment tools are either restricted to manual risk evaluation methodologies that are not appropriate for real-time application or used to determine the impact of certain events on the security status of networked systems. In this paper, we determine the strength of computer systems from the perspective of ...
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Pardalos, Panos; Värbrand, Peter
Researchers working with nonlinear programming often claim "the word is non linear" indicating that real applications require nonlinear modeling. The same is true for other areas such as multi-objective programming (there are always several goals in a real application), stochastic programming (all data is uncer tain and therefore stochastic models should be used), and so forth. In this spirit we claim: The word is multilevel. In many decision processes there is a hierarchy of decision makers, and decisions are made at different levels in this hierarchy. One way to handle such hierar chies is to focus on one level and include other levels' behaviors as assumptions. Multilevel programming is the research area that focuses on the whole hierar chy structure. In terms of modeling, the constraint domain associated with a multilevel programming problem is implicitly determined by a series of opti mization problems which must be solved in a predetermined sequence. If only two levels are considered, we have ...
This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Martinez-Moyano, I. J.; Samsa, M. E.; Burke, J. F.; Akcam, B. K.; Decision and Information Sciences; Rockefeller Coll. at the State Univ. of New York at Albany
This paper presents a generic model for information security implementation in organizations. The model presented here is part of an ongoing research stream related to critical infrastructure protection and insider threat and attack analysis. This paper discusses the information security implementation case.
An integrative developmental model is presented in which menstrual cycle-related symptoms are hypothesized to result in a cascade of developmental challenges that contribute to increased affective symptoms among adolescent girls, and to long-term developmental sequelae. To provide the basis for this model a broad foundation is developed considering (a) psychological symptoms and disorders associated with reproductive events across the life span, and (b) the many and complicated effects that female reproductive steroids (estrogen & progesterone) have which trigger a variety of physical and psychological changes that are commonly associated with the menstrual cycle. The Menstrual Cycle-Response and Developmental Affective-Risk Model is driven by 3 central concepts: (a) individual differences in response to steroids are very large and thus require analysis of individual response, rather than group-level tendencies; (b) the menstrual cycle itself represents an important and complex set of biological, physical, psychological, behavioral, and social changes, and should not be studied exclusively as changing steroid levels; and (c) the effects of the menstrual cycle during adolescence and early adulthood may have long-term developmental consequences. This model integrates specific effects of the menstrual cycle with contextual and social developmental variables, and with past theoretical models. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Banks, Sheila B.; Stytz, Martin R.
Simulation environments serve many purposes, but they are only as good as their content. One of the most challenging and pressing areas that call for improved content is the simulation of bot armies (botnets) and their effects upon networks and computer systems. Botnets are a new type of malware, a type that is more powerful and potentially dangerous than any other type of malware. A botnet's power derives from several capabilities including the following: 1) the botnet's capability to be controlled and directed throughout all phases of its activity, 2) a command and control structure that grows increasingly sophisticated, and 3) the ability of a bot's software to be updated at any time by the owner of the bot (a person commonly called a bot master or bot herder.) Not only is a bot army powerful and agile in its technical capabilities, a bot army can be extremely large, can be comprised of tens of thousands, if not millions, of compromised computers or it can be as small as a few thousand targeted systems. In all botnets, their members can surreptitiously communicate with each other and their command and control centers. In sum, these capabilities allow a bot army to execute attacks that are technically sophisticated, difficult to trace, tactically agile, massive, and coordinated. To improve our understanding of their operation and potential, we believe that it is necessary to develop computer security simulations that accurately portray bot army activities, with the goal of including bot army simulations within military simulation environments. In this paper, we investigate issues that arise when simulating bot armies and propose a combination of the biologically inspired MSEIR infection spread model coupled with the jump-diffusion infection spread model to portray botnet propagation.
Heckman, Mark; Joshi, Nikhil; Tylutki, Marcus; Levitt, Karl; Just, James; Clough, Lawrence
The goal of any intrusion detection, anti-virus, firewall or other security mechanism is not simply to stop attacks, but to protect a computing resource so that the resource can continue to perform its function...
.... Cameras, sensors and other components used along with the simple rules in the home automation software provide an environment where the lights, security and other appliances can be monitored and controlled...
D.Phil. Any organisation is dependent on its information technology resources. The challenges posed by new developments such as the World Wide Web and e-business, require new approaches to address the management and protection of IT resources. Various documents exist containing recommendations for the best practice to follow for information security management. BS7799 is such a code of practice for information security management. The most important problem to be addressed in this thesis i...
Dunn, Erin C.; Masyn, Katherine E.; Yudron, Monica; Jones, Stephanie M.; Subramanian, S.V.
The observation that features of the social environment, including family, school, and neighborhood characteristics, are associated with individual-level outcomes has spurred the development of dozens of multilevel or ecological theoretical frameworks in epidemiology, public health, psychology, and sociology, among other disciplines. Despite the widespread use of such theories in etiological, intervention, and policy studies, challenges remain in bridging multilevel theory and empirical research. This paper set out to synthesize these challenges and provide specific examples of methodological and analytical strategies researchers are using to gain a more nuanced understanding of the social determinants of psychiatric disorders, with a focus on children’s mental health. To accomplish this goal, we begin by describing multilevel theories, defining their core elements, and discussing what these theories suggest is needed in empirical work. In the second part, we outline the main challenges researchers face in translating multilevel theory into research. These challenges are presented for each stage of the research process. In the third section, we describe two methods being used as alternatives to traditional multilevel modeling techniques to better bridge multilevel theory and multilevel research. These are: (1) multilevel factor analysis and multilevel structural equation modeling; and (2) dynamic systems approaches. Through its review of multilevel theory, assessment of existing strategies, and examination of emerging methodologies, this paper offers a framework to evaluate and guide empirical studies on the social determinants of child psychiatric disorders as well as health across the lifecourse. PMID:24469555
Parker, R David
As political and social changes sweep the globe, there are opportunities to increase national security through innovative approaches. While traditional security methods such as defense forces and homeland security provide both pre-emptive and defensive protection, new methods could meet emerging challenges by responding to the political, financial, and social trends. One method is the integration of defense, medicine and public health. By assisting a nation by providing basic services, such as healthcare, collaborative efforts can increase stabilization in areas of unrest. Improved health outcomes leads to increased domestic security, which can create a ripple effect across a region. Assessment, uptake and sustainability by the host nation are critical for program success. The proposed methodology focuses on the use of primarily extant resources, such as programs used by Special Operations Forces and other health and defense programs. Additional components include evaluation, set objectives and mission collaborations. As the nexus between foreign affairs, security, and public health is increasingly validated through research and practice, standardized interventions should be developed to minimize overlapping expenditures, promote security and strengthen international relations. 2011.
Kovačević-Lepojević Marina M.
Full Text Available The model of technological pragmatism assumes awareness that technological development involves both benefits and dangers. Most modern security technologies represent citizens' mass surveillance tools, which can lead to compromising a significant amount of personal data due to the lack of institutional monitoring and control. On the other hand, people are interested in improving crime control and reducing the fear of potential victimization which this framework provides as a rational justification for the apparent loss of privacy, personal rights and freedoms. Citizens' perception on the categories of security and privacy, and their balancing, can provide the necessary guidelines to regulate the application of security technologies in the actual context. The aim of this paper is to analyze the attitudes of students at the University of Belgrade (N = 269 toward the application of security technology and identification of the key dimensions. On the basis of the relevant research the authors have formed assumptions about the following dimensions: security, privacy, trust in institutions and concern about the misuse of security technology. The Prise Questionnaire on Security Technology and Privacy was used for data collection. Factor analysis abstracted eight factors which together account for 58% of variance, with the highest loading of the four factors that are identified as security, privacy, trust and concern. The authors propose a model of technological pragmatism considering security and privacy. The data also showed that students are willing to change their privacy for the purpose of improving security and vice versa.
Shin, Jin Soo; Heo, Gyun Young; Kang, Hyun Gook; Son, Han Seong
There are several advantages to use digital equipment such as cost, convenience, and availability. It is inevitable to use the digital I and C equipment replaced analog. Nuclear facilities have already started applying the digital system to I and C system. However, the nuclear facilities also have to change I and C system even though it is difficult to use digital equipment due to high level of safety, irradiation embrittlement, and cyber security. A cyber security which is one of important concerns to use digital equipment can affect the whole integrity of nuclear facilities. For instance, cyber-attack occurred to nuclear facilities such as the SQL slammer worm, stuxnet, DUQU, and flame. The regulatory authorities have published many regulatory requirement documents such as U.S. NRC Regulatory Guide 5.71, 1.152, IAEA guide NSS-17, IEEE Standard, and KINS Regulatory Guide. One of the important problem of cyber security research for nuclear facilities is difficulty to obtain the data through the penetration experiments. Therefore, we make cyber security risk evaluation model with Bayesian network (BN) for nuclear reactor protection system (RPS), which is one of the safety-critical systems to trip the reactor when the accident is happened to the facilities. BN can be used for overcoming these problems. We propose a method to apply BN cyber security model to probabilistic safety assessment (PSA) model, which had been used for safety assessment of system, structure and components of facility. The proposed method will be able to provide the insight of safety as well as cyber risk to the facility
Pollock, Guylaine M.; Atkins, William Dee; Schwartz, Moses Daniel; Chavez, Adrian R.; Urrea, Jorge Mario; Pattengale, Nicholas; McDonald, Michael James; Cassidy, Regis H.; Halbgewachs, Ronald D.; Richardson, Bryan T.; Mulder, John C.
This paper describes a new hybrid modeling and simulation architecture developed at Sandia for understanding and developing protections against and mitigations for cyber threats upon control systems. It first outlines the challenges to PCS security that can be addressed using these technologies. The paper then describes Virtual Control System Environments (VCSE) that use this approach and briefly discusses security research that Sandia has performed using VCSE. It closes with recommendations to the control systems security community for applying this valuable technology.
Pawar, Pranav M.; Nielsen, Rasmus Hjorth; Prasad, Neeli R.
is the vulnerability to security attacks/threats. The performance and behavior of a WSN are vastly affected by such attacks. In order to be able to better address the vulnerabilities of WSNs in terms of security, it is important to understand the behavior of the attacks. This paper addresses the behavioral modeling...... of medium access control (MAC) security attacks in WSNs. The MAC layer is responsible for energy consumption, delay and channel utilization of the network and attacks on this layer can introduce significant degradation of the individual sensor nodes due to energy drain and in performance due to delays....... The behavioral modeling of attacks will be beneficial for designing efficient and secure MAC layer protocols. The security attacks are modeled using a sequential diagram approach of Unified Modeling Language (UML). Further, a new attack definition, specific to hybrid MAC mechanisms, is proposed....
Full Text Available Abstract Background Diarrhoea disease which has been attributed to poverty constitutes a major cause of morbidity and mortality in children aged five and below in most low-and-middle income countries. This study sought to examine the contribution of individual and neighbourhood socio-economic characteristics to caregiver's treatment choices for managing childhood diarrhoea at household level in sub-Saharan Africa. Methods Multilevel multinomial logistic regression analysis was applied to Demographic and Health Survey data conducted in 11 countries in sub-Saharan Africa. The unit of analysis were the 12,988 caregivers of children who were reported to have had diarrhoea two weeks prior to the survey period. Results There were variability in selecting treatment options based on several socioeconomic characteristics. Multilevel-multinomial regression analysis indicated that higher level of education of both the caregiver and that of the partner, as well as caregivers occupation were associated with selection of medical centre, pharmacies and home care as compared to no treatment. In contrast, caregiver's partners' occupation was negatively associated with selection medical centre and home care for managing diarrhoea. In addition, a low-level of neighbourhood socio-economic disadvantage was significantly associated with selection of both medical centre and pharmacy stores and medicine vendors. Conclusion In the light of the findings from this study, intervention aimed at improving on care seeking for managing diarrhoea episode and other childhood infectious disease should jointly consider the influence of both individual SEP and the level of economic development of the communities in which caregivers of these children resides.
Jürjens, J; Rumm, R
Health-care information systems are particularly security-critical. In order to make these applications secure, the security analysis has to be an integral part of the system design and IT management process for such systems. This work presents the experiences and results from the security analysis of the system architecture of the German Health Card, by making use of an approach to model-based security engineering that is based on the UML extension UMLsec. The focus lies on the security mechanisms and security policies of the smart-card-based architecture which were analyzed using the UMLsec method and tools. Main results of the paper include a report on the employment of the UMLsec method in an industrial health information systems context as well as indications of its benefits and limitations. In particular, two potential security weaknesses were detected and countermeasures discussed. The results indicate that it can be feasible to apply a model-based security analysis using UMLsec to an industrial health information system like the German Health Card architecture, and that doing so can have concrete benefits (such as discovering potential weaknesses, and an increased confidence that no further vulnerabilities of the kind that were considered are present).
Crowther, Michael J; Look, Maxime P; Riley, Richard D
Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.
Корнієнко, Б.Я.; кафедра комп`ютеризованих систем захисту інформації, Національний авіаційний університет; Галата, Л.П.; кафедра комп`ютеризованих систем захисту інформації, Національний авіаційний університет
This article presents simulation modeling process as the way to study the behavior of the Information Security system. Graphical Network Simulator is used for modeling such system and Kali Linux is used for penetration testing and security audit. The main approaches to simulation of computer networks are considered. The functional capabilities of the GNS3 package are explored. When building an imitation model, the main components of information protection were used. The Kali Linux package imp...
Yoshida, Kazuo; Tanabe, Fumiya; Kawase, Katumi.
It has been proposed to use the Multilevel Flow Modeling (MFM) by M. Lind as a framework for functional knowledge representation for qualitative reasoning in a complex process system such as nuclear power plant. To build a knowledge base with MFM framework makes it possible to represent functional characteristics in different levels of abstraction and aggregation. A pilot inference system based on the qualitative reasoning with MFM has been developed to diagnose a cause of abnormal events in a typical PWR power plant. Some single failure events has been diagnosed with this system to verify the proposed method. In the verification study, some investigation has been also performed to clarify the effects of this knowledge representation in efficiency of reasoning and ambiguity of qualitative reasoning. (author)
Hagiwara, Makoto; Nishimura, Kazutoshi; Akagi, Hirofumi
This paper presents a medium-voltage motor drive with a three-phase modular multilevel PWM inverter and focuses on its control method and operating performance. This motor drive is particularly suitable for fans, blowers, pumps, and compressors, in which the load torque is proportional to the square of the rotating speed. Particular attention is paid to the dc-capacitor voltage fluctuation of each chopper-cell because it may affect the voltage rating of the power switching devices used. This paper describes the theoretical equations related to the amount of the voltage fluctuation. A downscaled model rated at 400V and 15kW is designed and built to confirm the validity and effectiveness of the nine-level (17-level in line-to-line) PWM inverter that is intended for use in medium-voltage motor drives to achieve energy savings.
Gonzalez Eiras, Martin
I refine and extend the Markov perfect equilibrium of the social security policy game in Forni (2005) for the special case of logarithmic utility. Under the restriction that the policy function be continuous, instead of differentiable, the equilibrium is globally well defined and its dynamics alw...
Jonkers, Henk; Quartel, Dick; Kordy, Barbara; Ekstedt, Mathias; Seong Kim, Deng
The growing complexity of organizations and the increasing number of sophisticated cyber attacks asks for a systematic and integral approach to Enterprise Risk and Security Management (ERSM). As enterprise architecture offers the necessary integral perspective, including the business and IT aspects
Cederquist, J.G.; Dashti, M.T.
We formally describe an intruder that is suitable for checking fairness properties of security protocols. The intruder is proved to be equivalent to the Dolev-Yao intruder that respects the resilient communication channels assumption, in the sense that, if a fairness property holds in one of these
Full Text Available The lack of a fully inclusive guideline document to assist the functioning of sufficient Information Security Governance is common in the business environment. This article focuses on developing such a guideline document, based on a number of best...
Janssen, S.A.M.; Sharpans'kykh, Alexei; Bajo, J.; Vale, Z.; Hallenborg, K.; Rocha, A.P.; Mathieu, P.; Pawlewski, P.; Del Val, E.; Novais, P.; Lopes, F.; Duque Méndez, N.D.; Julián, V.; Holmgren, J.
Security Risk Assessment is commonly performed by using traditional methods based on linear probabilistic tools and informal expert judgements. These methods lack the capability to take the inherent dynamic and intelligent nature of attackers into account. To partially address the limitations,
Gonzalez Eiras, Martin
I refine and extend the Markov perfect equilibrium of the social security policy game in Forni (2005) for the special case of logarithmic utility. Under the restriction that the policy function be continuous, instead of differentiable, the equilibrium is globally well defined and its dynamics...
This paper provides an in-depth technical assessment of the security improvements implemented in the new Microsoft Windows Vista (officially released February, 2007), focusing primarily on the areas of User Account Protection and User Interface Privilege Isolation. This paper discusses these features and touches on ...
In public key cryptography, the security of private keys is very importance, for if ever compromised, it can be used to decrypt secret messages. Conventional methods that use textual passwords, graphical passwords and single modal biometric systems that are used to encryption and protect private keys do not provide ...
Gong, L.; Jin, C. L.; Li, Y. X.; Zhou, Z. L.
This study proposed an improved Water Poverty Index (WPI) model employed in evaluating Chinese regional water security. Firstly, the Chinese WPI index system was constructed, in which the indicators were obtained according to China River reality. A new mathematical model was then established for WPI values calculation on the basis of Center for Ecology and Hydrology (CEH) model. Furthermore, this new model was applied in Shiyanghe River (located in western China). It turned out that the Chinese index system could clearly reflect the indicators threatening security of river water and the Chinese WPI model is feasible. This work has also developed a Water Security Degree (WSD) standard which is able to be regarded as a scientific basis for further water resources utilization and water security warning mechanism formulation.
Full Text Available Capital structure selection is fundamentally important in corporate financial management as it influence on mutually return and risk to stakeholders. Despite of Malaysia’s position as one of the major players of Islamic Financial Market, there are still lack of studies has been conducted on the capital structure of shariah compliant firms especially related to hybrid securities. The objective of this study is to determine the hybrid securities issuance model among the shariah compliant firms in Malaysia. As such, this study is to expand the literature review by providing comprehensive analysis on the hybrid capital structure and to develop dynamic Islamic hybrid securities model for shariah compliant firms. We use panel data of 50 companies that have been issuing the hybrid securities from the year of 2004- 2012. The outcomes of the studies are based on the dynamic model GMM estimation for the determinants of hybrid securities. Based on our model, risk and growth are considered as the most determinant factors for issuing convertible bond and loan stock. These results suggest that, the firms that have high risk but having good growth prospect will choose hybrid securities of convertible bond. The model also support the backdoor equity listing hypothesis by Stein (1992 where the hybrid securities enable the profitable firms to venture into positive NPV project by issuing convertible bond as it offer lower coupon rate as compare to the normal debt rate
Full Text Available Allometric models of internodes are an important component of Functional-Structural Plant Models (FSPMs, which represent the shape of internodes in tree architecture and help our understanding of resource allocation in organisms. Constant allometry is always assumed in these models. In this paper, multilevel nonlinear mixed-effect models were used to characterize the variability of internode allometry, describing the relationship between the last internode length and biomass of Pinus tabulaeformis Carr. trees within the GreenLab framework. We demonstrated that there is significant variability in allometric relationships at the tree and different-order branch levels, and the variability decreases among levels from trees to first-order branches and, subsequently, to second-order branches. The variability was partially explained by the random effects of site characteristics, stand age, density, and topological position of the internode. Tree- and branch-level-specific allometric models are recommended because they produce unbiased and accurate internode length estimates. The model and method developed in this study are useful for understanding and describing the structure and functioning of trees.
Full Text Available Security measure is of great importance in both steganography and steganalysis. Considering that statistical feature perturbations caused by steganography in an image are always nondeterministic and that an image is considered nonstationary, in this paper, the steganography is regarded as a fuzzy process. Here a steganographic security measure is proposed. This security measure evaluates the similarity between two vague sets of cover images and stego images in terms of n-order Markov chain to capture the interpixel correlation. The new security measure has proven to have the properties of boundedness, commutativity, and unity. Furthermore, the security measures of zero order, first order, second order, third order, and so forth are obtained by adjusting the order value of n-order Markov chain. Experimental results indicate that the larger n is, the better the measuring ability of the proposed security measure will be. The proposed security measure is more sensitive than other security measures defined under a deterministic distribution model, when the embedding is low. It is expected to provide a helpful guidance for designing secure steganographic algorithms or reliable steganalytic methods.
Kendler, Kenneth S; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan
Both epidemiological and genetically informative studies indicate that shared environmental influences contribute to resemblance in siblings for drug abuse (DA). To what degree do these influences arise from living in the same household versus residing in the same community? We performed a cross-classified multi-level logistic regression on all individuals born in Sweden 1975-1990 (N = 1558,654). We assessed the proportion of the total population variation in DA that was due to household versus community effects controlling for genetic resemblance. DA was assessed from medical, criminal and pharmacy records. Expressed as an intraclass correlation (ICC), the combined household/community effects accounted for ~8 % of the total population variation in DA. The variance attributed to the community was greater than that seen for household (4.5 versus 3.4 %). In males, the variance components were slightly larger and nearly equal at the community (5.3 %) and household level (5.1 %). In females, household effects (4.8 %) were stronger than those arising from the community (3.2 %). In the total population and among males, community effects on DA were somewhat more potent than household effects. However, in females, household effects on DA were stronger than community effects. In Sweden, shared environmental effects for DA arise both at the household and at the community level. Community effects on DA are more potent in males than in females.
System models to assess the vulnerability of information systems to security threats typically represent a physical infrastructure (buildings) and a digital infrastructure (computers and networks), in combination with an attacker traversing the system while acquiring credentials. Other humans are
Pou, Sonia Alejandra; Díaz, María del Pilar; Osella, Alberto Rubén
Scientific literature has consistently shown the effects of certain diets on health but regional variations of dietary habits, and their relationship colorectal cancer (CRC) has been poorly studied in Argentina. Our aims were to identify dietary patterns and estimate their effect on CRC occurrence and to quantify the association between family history of CRC and CRC occurrence by applying multilevel models to estimate and interpret measures of variation. Principal components factor analysis was performed to identify dietary patterns that were then used in a multilevel logistic regression applied to an ongoing case-control data about dietary exposure and CRC occurrence taking into account familiar clustering. Three dietary patterns were identified: "Southern Cone pattern" (red meat, wine, and starchy vegetables), "High-sugar drinks pattern", and "Prudent pattern". The study considered 41 cases and 95 controls. There was a significant promoting effects on CRC of "Southern Cone" (OR 1.5, 95%CI 1.0-2.2) and "High-sugar drinks" (OR 3.8, 95%CI 2.0-7.1) patterns, whereas "Prudent pattern" (OR 0.3, 95%CI 0.2-0.4) showed a significant protective effect at third tertile level. BMI, use of NSAIDs, and to have medical insurance showed significant effects. Variance of the random effect of family history of CRC was highly significant. This novel approach for Argentina showed that Southern Cone and High-sugar drinks patterns were associated with a higher risk of CRC, whereas the Prudent pattern showed a protective effect. There was a significant clustering effect of family history of CRC.
23 G. INTELLIGENCE COMMUNITY AND BORDER DEFENSE ..........25 H. STATE AND LOCAL LAW ENFORCEMENT ..................................28 I...2014, 6, http://www.rand.org/content/dam/rand/pubs/testimonies/CT400/CT415/RAND_CT415.pdf. 5 changes in cargo security and the costs companies ...that private companies take. In the private sector, ROI is a measure of the overall profit or loss of an investment, expressed in percentage.25 For
Extremely long lines at airports in the United States have been sharply criticized. In order to find out the bottleneck in the existing security system and put forward reasonable improvement plans and proposal, the Petri net model and the Markov Chain are introduced in this paper. This paper uses data collected by transportation Security Agency (TSA), assuming the data can represent the average level of all airports in the Unites States, to analysis the performance of security check system. By calculating the busy probabilities and the utilization probabilities, the bottleneck is found. Moreover, recommendation is given based on the parameters’ modification in Petri net model.
Peleska, Jan; Feuser, Johannes; Haxthausen, Anne Elisabeth
A novel approach to managing development, verification, and validation artifacts for the European Train Control System as open, publicly available items is analyzed and discussed with respect to its implications on system safety, security, and certifiability. After introducing this so-called model......-driven openETCS approach, a threat analysis is performed, identifying both safety and security hazards that may be common to all model-based development paradigms for safety-critical railway control systems, or specific to the openETCS approach. In the subsequent sections state-of-the-art methods suitable...... of security hazards....
Fox, Gerardus J.A.
A structural multilevel model is presented where some of the variables cannot be observed directly but are measured using tests or questionnaires. Observed dichotomous or ordinal polytomous response data serve to measure the latent variables using an item response theory model. The latent variables
A. S. Polyakova
Full Text Available This article presents a research of Gordon—Loeb model for evaluating the optimal level of information security investment and a model of interdependent risks. One is provided by practical recommendations for choosing and applying models, for choosing a range of vulnerabilities to concentrate financial resources on, and weak points of models are discussed.
Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic
Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across
We present simple protocols for oblivious transfer and password-based identification which are secure against general attacks in the noisy-quantum-storage model as defined in R. König, S. Wehner, and J. Wullschleger [e-print arXiv:0906.1030]. We argue that a technical tool from König suffices to prove security of the known protocols. Whereas the more involved protocol for oblivious transfer from König requires less noise in storage to achieve security, our “canonical” protocols have the advantage of being simpler to implement and the security error is easier control. Therefore, our protocols yield higher OT rates for many realistic noise parameters. Furthermore, a proof of security of a direct protocol for password-based identification against general noisy-quantum-storage attacks is given.
We present simple protocols for oblivious transfer and password-based identification which are secure against general attacks in the noisy-quantum-storage model as defined in R. Koenig, S. Wehner, and J. Wullschleger [e-print arXiv:0906.1030]. We argue that a technical tool from Koenig et al. suffices to prove security of the known protocols. Whereas the more involved protocol for oblivious transfer from Koenig et al. requires less noise in storage to achieve security, our ''canonical'' protocols have the advantage of being simpler to implement and the security error is easier control. Therefore, our protocols yield higher OT rates for many realistic noise parameters. Furthermore, a proof of security of a direct protocol for password-based identification against general noisy-quantum-storage attacks is given.
Full Text Available In the context of modern information systems, security has become one of the most critical quality attributes. The purpose of this paper is to address the problem of quality of information security. An approach to solve this problem is based on the main assumption that security is a process oriented activity. According to this approach, product quality can be achieved by means of process quality - process capability. Introduced in the paper, SPICE conformant information security process capability model is based on process capability modeling elaborated by world-wide software engineering community during the last 25 years, namely ISO/IEC 15504 that defines the capability dimension and the requirements for process definition and domain independent integrated model for enterprise-wide assessment and Enterprise SPICE improvement
Bowen, Elizabeth A
Elevated HIV prevalence has been observed among urban U.S. individuals who use drugs and who lack stable housing. This article synthesizes extant research on this population and situates it in a multilevel, ecologically based model of HIV risk. Based on a multidisciplinary review of the literature, the model applies social-ecological theory on human development to identify factors shaping the HIV risk context for individuals who use drugs and who are unstably housed at global, societal, neighborhood, household, and individual levels of influence. At the global level, the model includes neoliberal ideologies contributing to the social inequalities that frame the HIV epidemic. U.S. housing and drug policy, including urban renewal, HOPE VI, and the War on Drugs, is the focus of the societal level. At the neighborhood level, mechanisms of the built environment and psychosocial mechanisms are explored for their salience to HIV risk. Research on the association between housing instability and HIV risk is reviewed at the household level. At the last level, relevant individual differences in biology, psychology, and cognition are discussed. Modeling risk at multiple levels of the environment underscores the need to expand the focus of research, treatment, and prevention interventions for HIV/AIDS and addictions beyond individuals and their risk behaviors to address facets of structural violence and incorporate the broader social, political, and economic contexts of risk and health.
Wu, Xuan; Wang, Xiaojie; Mei, Tao; Sun, Shaoming
This paper proposes a multi-level hierarchical model for the Tokay gecko ( Gekko gecko ) adhesive system and analyses the digital behaviour of the G. gecko under macro/meso-level scale. The model describes the structures of G. gecko 's adhesive system from the nano-level spatulae to the sub-millimetre-level lamella. The G. gecko 's seta is modelled using inextensible fibril based on Euler's elastica theorem. Considering the side contact of the spatular pads of the seta on the flat and rigid substrate, the directional adhesion behaviour of the seta has been investigated. The lamella-induced attachment and detachment have been modelled to simulate the active digital hyperextension (DH) and the digital gripping (DG) phenomena. The results suggest that a tiny angular displacement within 0.25° of the lamellar proximal end is necessary in which a fast transition from attachment to detachment or vice versa is induced. The active DH helps release the torque to induce setal non-sliding detachment, while the DG helps apply torque to make the setal adhesion stable. The lamella plays a key role in saving energy during detachment to adapt to its habitat and provides another adhesive function which differs from the friction-dependent setal adhesion system controlled by the dynamic of G. gecko 's body.
Sho, Jinsoo; Rahman, Khalil Ur; Heo, Gyunyoung; Son, Hanseong
The study on the qualitative risk due to cyber-attacks into research reactors was performed using bayesian Network (BN). This was motivated to solve the issues of cyber security raised due to digitalization of instrumentation and control (I and C) system. As a demonstrative example, we chose the reactor protection system (RPS) of research reactors. Two scenarios of cyber-attacks on RPS were analyzed to develop mitigation measures against vulnerabilities. The one is the 'insertion of reactor trip' and the other is the 'scram halt'. The six mitigation measures are developed for five vulnerability for these scenarios by getting the risk information from BN
van Herk, H.; Fischer, Ronald; van Herk, Hester; Torelli, Carlos J.
Multi-level structures are omnipresent. Consumers live in geographical locations, shop in specific stores, or are members of clubs. Consumers who belong to the same group share characteristics and are expected to be more similar than consumers belonging to another group. In data analysis this
Clark, Melvin G.
This guide is designed for teachers of multilevel classes in English as a Second Language (ESL) at the adult level. The first section discusses principles, methods, and techniques for classroom instruction, including student grouping, appropriate ESL teaching methods (audiolingual, vocational, language experience, natural approach,…
Mazzega, Pierre; Therond, Olivier; Debril, Thomas; March, Hug; Sibertin-Blanc, Christophe; Lardy, Romain; Sant'ana, Daniel
This paper presents the experience gained related to the development of an integrated simulation model of water policy. Within this context, we analyze particular difficulties raised by the inclusion of multi-level governance that assigns the responsibility of individual or collective decision-making to a variety of actors, regarding measures of which the implementation has significant effects toward the sustainability of socio-hydrosystems. Multi-level governance procedures are compared with the potential of model-based impact assessment. Our discussion is illustrated on the basis of the exploitation of the multi-agent platform MAELIA dedicated to the simulation of social, economic and environmental impacts of low-water management in a context of climate and regulatory changes. We focus on three major decision-making processes occurring in the Adour-Garonne basin, France: (i) the participatory development of the Master Scheme for Water Planning and Management (SDAGE) under the auspices of the Water Agency; (ii) the publication of water use restrictions in situations of water scarcity; and (iii) the determination of the abstraction volumes for irrigation and their allocation. The MAELIA platform explicitly takes into account the mode of decision-making when it is framed by a procedure set beforehand, focusing on the actors' participation and on the nature and parameters of the measures to be implemented. It is observed that in some water organizations decision-making follows patterns that can be represented as rule-based actions triggered by thresholds of resource states. When decisions are resulting from individual choice, endowing virtual agents with bounded rationality allows us to reproduce (in silico) their behavior and decisions in a reliable way. However, the negotiation processes taking place during the period of time simulated by the models in arenas of collective choices are not all reproducible. Outcomes of some collective decisions are very little or
Mohammed, Emad A; Slack, Jonathan C; Naugler, Christopher T
The use of electronic health records (EHRs) has continued to increase within healthcare systems in the developed and developing nations. EHRs allow for increased patient safety, grant patients easier access to their medical records, and offer a wealth of data to researchers. However, various bioethical, financial, logistical, and information security considerations must be addressed while transitioning to an EHR system. The need to encrypt private patient information for data sharing is one of the foremost challenges faced by health information technology. We describe the usage of the message digest-5 (MD5) and secure hashing algorithm (SHA) as methods for encrypting electronic medical data. In particular, we present an application of the MD5 and SHA-1 algorithms in encrypting a composite message from private patient information. The results show that the composite message can be used to create a unique one-way encrypted ID per patient record that can be used for data sharing. The described software tool can be used to share patient EMRs between practitioners without revealing patients identifiable data.