856 resultados para HIERARCHICAL ORGANIZATION


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La connectomique est l’étude des cartes de connectivité du cerveau (animal ou humain), qu’on nomme connectomes. À l’aide des outils développés par la science des réseaux complexes, la connectomique tente de décrire la complexité fonctionnelle et structurelle du cerveau. L’organisation des connexions du connectome, particulièrement la hiérarchie sous-jacente, joue un rôle majeur. Jusqu’à présent, les modèles hiérarchiques utilisés en connectomique sont pauvres en propriétés émergentes et présentent des structures régulières. Or, la complexité et la richesse hiérarchique du connectome et de réseaux réels ne sont pas saisies par ces modèles. Nous introduisons un nouveau modèle de croissance de réseaux hiérarchiques basé sur l’attachement préférentiel (HPA - Hierarchical preferential attachment). La calibration du modèle sur les propriétés structurelles de réseaux hiérarchiques réels permet de reproduire plusieurs propriétés émergentes telles que la navigabilité, la fractalité et l’agrégation. Le modèle permet entre autres de contrôler la structure hiérarchique et apporte un support supplémentaire quant à l’influence de la structure sur les propriétés émergentes. Puisque le cerveau est continuellement en activité, nous nous intéressons également aux propriétés dynamiques sur des structures hiérarchiques produites par HPA. L’existence d’états dynamiques d’activité soutenue, analogues à l’état minimal de l’activité cérébrale, est étudiée en imposant une dynamique neuronale binaire. Bien que l’organisation hiérarchique favorise la présence d’un état d’activité minimal, l’activité persistante émerge du contrôle de la propagation par la structure du réseau.

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Os projetos multimédia são uma forma única de desenvolver produtos e serviços inovadores, com recurso a um conjunto distintivo de membros de equipa, conhecimentos e metodologias. Grande parte dos estudos desenvolvidos em torno do conceito de desenvolvimento ágil são orientados para a área da engenharia de software, não sendo, muitas vezes, ajustados às particularidades dos projetos multimédia. Ainda que seja possível desenvolver e gerir projetos multimédia com recurso a métodos ágeis, é fundamental aprofundar o conhecimento nesta área apresentando estudos que comprovem a efetiva adequação das metodologias ágeis a esta tipologia projetual. O trabalho desenvolvido nesta dissertação pretendeu, não só analisar e compreender as metodologias, instrumentos e ferramentas de desenvolvimento ágil, considerando as particularidades da área da multimédia, como também analisar dados recolhidos num contexto real de desenvolvimento, observando práticas e eventos de um projeto específico; tais dados foram confrontados com metodologias existentes, de modo a permitir o desenho e a proposta de uma metodologia de suporte ao desenvolvimento ágil de um projeto multimédia. Os dados foram recolhidos em quatro fases e com objetivos distintos: conhecer o projeto e os elementos envolvidos; observar dinâmicas de trabalho em equipa; recolher informações sobre eventos de interação e partilha, organização hierárquica, controlo e monitorização e tomada de decisão e, por fim, recolher a opinião dos envolvidos sobre a proposta da metodologia de suporte. Esta proposta de metodologia constituiu, portanto, o principal resultado do estudo, apontando para a necessidade de (i) recorrer a uma ferramenta online de suporte à gestão de tempo e tarefas, (ii) utilizar uma ferramenta de partilha que permita um acesso constante por todos os elementos da equipa e (iii) promover reuniões periódicas, com ordem de trabalho definida.

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In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

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The mechanisms responsible for containing activity in systems represented by networks are crucial in various phenomena, for example, in diseases such as epilepsy that affect the neuronal networks and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided into modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory, through which containment of activity is achieved by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, namely, random, Barabasi-Albert and geographical networks. The generality of this finding was confirmed by showing that modularity is no longer needed if the dynamics based on the integrate-and-fire dynamics incorporated the decay factor. Taken together, these results provide a proof of principle that persistent, restrained network activation might occur in the absence of any particular topological structure. This may be the reason why neuronal activity does not spread out to the entire neuronal network, even when no special topological organization exists.

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Az államigazgatásban – itthon és külföldön is – a projektek jelentős százaléka időben csúszik, nem azt eredményezi, amit eredetileg elvártak, a szakmai résztvevők szerint túladminisztrált, a munkatársak tevékenysége nem áttekinthető. Ezeknek a problémáknak a nagy része a projektszervezet és a hierarchikusfunkcionális- hivatali szervezet egymás mellett éléséből és a nehezen szinkronizálható együttműködésből fakad. A cikkben egy, a gyakorlatban bevált módszertant mutat be a szerző, amely adott feltételrendszer mellett nagymértékben kiküszöböli a fent említett hiányosságokat és a szervezet napi működésébe illeszkedő tevékenységek sorozatára vezeti vissza a projekttevékenységeket. A módszer egy gyakorlati problémából – a volt APEH-es és VP-s rendszerek integrálása a NAV-ba – indult ki, azonban a szerző véleménye szerint alkalmazható más, funkcionális alapokon felépülő szervezetnél is. _____ The high percentage of public sector projects slips in time, the result is not that what was expected initially, those are overadministrated by according to the professional participants’ opinion, and the activity of staff does not clear. In this article the author describes a best practice methodology, which led the project activities to series of activities which fit to the organization’s daily operations. The method started from a practical problem, but according to the author’s opinion it can be applied to other structured functional basis organizations.

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This paper considers the ethical concerns that surface around hierarchy as structure in knowledge organization systems. In order to do this, I consider the relationship between semantics and structure and argue for a separation of the two in design and critique of knowledge organization systems. The paper closes with an argument that agency and intention, as ethical concerns in knowledge organization, lead us to argue for a neutral stance on hierarchy.

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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

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Client satisfaction with health care services has usually been researched in terms of socio-demographic and predispositional characteristics associated with the client. The present study included organizational characteristics as predictors of client satisfaction with health care services. Participants in the research were clients and employees of an Australian public-sector health care organization who responded to separate client and employee questionnaires. Hierarchical regression analyses indicated that, after controlling for a number of client characteristics, organizational characteristics, as perceived by employees, accounted for a significant proportion of additional variance in client satisfaction with health care services. Results of the present study provided some support for the proposition that employee perceptions of the working environment should be considered in a more comprehensive understanding of client satisfaction with health care services. Limitations of the study highlight practical difficulties in the assessment of client outcomes and methodological complexities in linking individual and organizational processes.

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An approach is presented for hierarchical control of an ammonia reactor, which is a key unit process in a nitrogen fertilizer complex. The aim of the control system is to ensure safe operation of the reactor around the optimal operating point in the face of process variable disturbances and parameter variations. The four different layers perform the functions of regulation, optimization, adaptation, and self-organization. The simulation for this proposed application is conducted on an AD511 hybrid computer in which the AD5 analog processor is used to represent the process and the PDP-11/ 35 digital computer is used for the implementation of control laws. Simulation results relating to the different layers have been presented.

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The term acclimation has been used with several connotations in the field of acclimatory physiology. An attempt has been made, in this paper, to define precisely the term “acclimation” for effective modelling of acclimatory processes. Acclimation is defined with respect to a specific variable, as cumulative experience gained by the organism when subjected to a step change in the environment. Experimental observations on a large number of variables in animals exposed to sustained stress, show that after initial deviation from the basal value (defined as “growth”), the variables tend to return to basal levels (defined as “decay”). This forms the basis for modelling biological responses in terms of their growth and decay. Hierarchical systems theory as presented by Mesarovic, Macko & Takahara (1970) facilitates modelling of complex and partially characterized systems. This theory, in conjunction with “growth-decay” analysis of biological variables, is used to model temperature regulating system in animals exposed to cold. This approach appears to be applicable at all levels of biological organization. Regulation of hormonal activity which forms a part of the temperature regulating system, and the relationship of the latter with the “energy” system of the animal of which it forms a part, are also effectively modelled by this approach. It is believed that this systematic approach would eliminate much of the current circular thinking in the area of acclimatory physiology.

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Dominance and subordinate behaviors are important ingredients in the social organizations of group living animals. Behavioral observations on the two eusocial species Ropalidia marginata and Ropalidia cyathiformis suggest varying complexities in their social systems. The queen of R. cyathiformis is an aggressive individual who usually holds the top position in the dominance hierarchy although she does not necessarily show the maximum number of acts of dominance, while the R. marginata queen rarely shows aggression and usually does not hold the top position in the dominance hierarchy of her colony. In R. marginata, more workers are involved in dominance-subordinate interactions as compared to R. cyathiformis. These differences are reflected in the distribution of dominance-subordinate interactions among the hierarchically ranked individuals in both the species. The percentage of dominance interactions decreases gradually with hierarchical ranks in R. marginata while in R. cyathiformis it first increases and then decreases. We use an agent-based model to investigate the underlying mechanism that could give rise to the observed patterns for both the species. The model assumes, besides some non-interacting individuals, the interaction probabilities of the agents depend on their pre-differentiated winning abilities. Our simulations show that if the queen takes up a strategy of being involved in a moderate number of dominance interactions, one could get the pattern similar to R. cyathiformis, while taking up the strategy of very low interactions by the queen could lead to the pattern of R. marginata. We infer that both the species follow a common interaction pattern, while the differences in their social organization are due to the slight changes in queen as well as worker strategies. These changes in strategies are expected to accompany the evolution of more complex societies from simpler ones.

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The transcriptional regulation of gene expression is orchestrated by complex networks of interacting genes. Increasing evidence indicates that these `transcriptional regulatory networks' (TRNs) in bacteria have an inherently hierarchical architecture, although the design principles and the specific advantages offered by this type of organization have not yet been fully elucidated. In this study, we focussed on the hierarchical structure of the TRN of the gram-positive bacterium Bacillus subtilis and performed a comparative analysis with the TRN of the gram-negative bacterium Escherichia coli. Using a graph-theoretic approach, we organized the transcription factors (TFs) and sigma-factors in the TRNs of B. subtilis and E. coli into three hierarchical levels (Top, Middle and Bottom) and studied several structural and functional properties across them. In addition to many similarities, we found also specific differences, explaining the majority of them with variations in the distribution of s-factors across the hierarchical levels in the two organisms. We then investigated the control of target metabolic genes by transcriptional regulators to characterize the differential regulation of three distinct metabolic subsystems (catabolism, anabolism and central energy metabolism). These results suggest that the hierarchical architecture that we observed in B. subtilis represents an effective organization of its TRN to achieve flexibility in response to a wide range of diverse stimuli.

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A shear-lag model is used to study the mechanical properties of bone-like hierarchical materials. The relationship between the overall effective modulus and the number of hierarchy level is obtained. The result is compared with that based on the tension-shear chain model and finite element simulation, respectively. It is shown that all three models can be used to describe the mechanical behavior of the hierarchical material when the number of hierarchy levels is small. By increasing the number of hierarchy level, the shear-lag result is consistent with the finite element result. However the tension-shear chain model leads to an opposite trend. The transition point position depends on the fraction of hard phase, aspect ratio and modulus ratio of hard phase to soft phase. Further discussion is performed on the flaw tolerance size and strength of hierarchical materials based on the shear-lag analysis.

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A templateless, surfactantless, electrochemical approach is proposed to directly fabricate hierarchical flowerlike gold microstructures (HFGMs) on an indium tin oxide (ITO) substrate. The as-prepared HFGMs have been characterized by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and cyclic voltammetry.