927 resultados para Endogenous Information Structure
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Our research explores the possibility of categorizing webpages and webpage genre by structure or layout. Based on our results, we believe that webpage structure could play an important role, along with textual and visual keywords, in webpage categorization and searching.
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In the following paper a new class of executive information system is suggested. It is based on a selforganization in management and on a module modeling. The system is multifunctional and multidisciplinary. The structure elements of the system and the common features of the modules are discussed.
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The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure. One possible structure is proposed in order to form a basis for intelligent system that would be able to operate in complex environments. The basic elements of the proposed structure have found their implemented in software system. This software system is shortly presented in the paper. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are sketched.
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Systems analysis (SA) is widely used in complex and vague problem solving. Initial stages of SA are analysis of problems and purposes to obtain problems/purposes of smaller complexity and vagueness that are combined into hierarchical structures of problems(SP)/purposes(PS). Managers have to be sure the PS and the purpose realizing system (PRS) that can achieve the PS-purposes are adequate to the problem to be solved. However, usually SP/PS are not substantiated well enough, because their development is based on a collective expertise in which logic of natural language and expert estimation methods are used. That is why scientific foundations of SA are not supposed to have been completely formed. The structure-and-purpose approach to SA based on a logic-and-linguistic simulation of problems/purposes analysis is a step towards formalization of the initial stages of SA to improve adequacy of their results, and also towards increasing quality of SA as a whole. Managers of industrial organizing systems using the approach eliminate logical errors in SP/PS at early stages of planning and so they will be able to find better decisions of complex and vague problems.
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In the presented work the problem of management business-processes with changeable structure is considered and situational based approach to its decision is offered. The approach is based on situational model of management business-process according to which process is represented as a set of situations. The script defining necessary actions is connected with each situation. Management of process is carried out by means of the rules formalizing functional requirements to processes.
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DNA-binding proteins are crucial for various cellular processes and hence have become an important target for both basic research and drug development. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to establish an automated method for rapidly and accurately identifying DNA-binding proteins based on their sequence information alone. Owing to the fact that all biological species have developed beginning from a very limited number of ancestral species, it is important to take into account the evolutionary information in developing such a high-throughput tool. In view of this, a new predictor was proposed by incorporating the evolutionary information into the general form of pseudo amino acid composition via the top-n-gram approach. It was observed by comparing the new predictor with the existing methods via both jackknife test and independent data-set test that the new predictor outperformed its counterparts. It is anticipated that the new predictor may become a useful vehicle for identifying DNA-binding proteins. It has not escaped our notice that the novel approach to extract evolutionary information into the formulation of statistical samples can be used to identify many other protein attributes as well.
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Computing the similarity between two protein structures is a crucial task in molecular biology, and has been extensively investigated. Many protein structure comparison methods can be modeled as maximum weighted clique problems in specific k-partite graphs, referred here as alignment graphs. In this paper we present both a new integer programming formulation for solving such clique problems and a dedicated branch and bound algorithm for solving the maximum cardinality clique problem. Both approaches have been integrated in VAST, a software for aligning protein 3D structures largely used in the National Center for Biotechnology Information, an original clique solver which uses the well known Bron and Kerbosch algorithm (BK). Our computational results on real protein alignment instances show that our branch and bound algorithm is up to 116 times faster than BK.
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The focus of this thesis is the extension of topographic visualisation mappings to allow for the incorporation of uncertainty. Few visualisation algorithms in the literature are capable of mapping uncertain data with fewer able to represent observation uncertainties in visualisations. As such, modifications are made to NeuroScale, Locally Linear Embedding, Isomap and Laplacian Eigenmaps to incorporate uncertainty in the observation and visualisation spaces. The proposed mappings are then called Normally-distributed NeuroScale (N-NS), T-distributed NeuroScale (T-NS), Probabilistic LLE (PLLE), Probabilistic Isomap (PIso) and Probabilistic Weighted Neighbourhood Mapping (PWNM). These algorithms generate a probabilistic visualisation space with each latent visualised point transformed to a multivariate Gaussian or T-distribution, using a feed-forward RBF network. Two types of uncertainty are then characterised dependent on the data and mapping procedure. Data dependent uncertainty is the inherent observation uncertainty. Whereas, mapping uncertainty is defined by the Fisher Information of a visualised distribution. This indicates how well the data has been interpolated, offering a level of ‘surprise’ for each observation. These new probabilistic mappings are tested on three datasets of vectorial observations and three datasets of real world time series observations for anomaly detection. In order to visualise the time series data, a method for analysing observed signals and noise distributions, Residual Modelling, is introduced. The performance of the new algorithms on the tested datasets is compared qualitatively with the latent space generated by the Gaussian Process Latent Variable Model (GPLVM). A quantitative comparison using existing evaluation measures from the literature allows performance of each mapping function to be compared. Finally, the mapping uncertainty measure is combined with NeuroScale to build a deep learning classifier, the Cascading RBF. This new structure is tested on the MNist dataset achieving world record performance whilst avoiding the flaws seen in other Deep Learning Machines.
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Although people and events that disconfirm observers' expectancies can increase their creativity, sometimes such social schema violations increase observers' rigidity of thought and undermine creative cognition. Here we examined whether individual differences in the extent to which people prefer structure and predictability determine whether social schema violations facilitate or hamper creativity. Participants in Study 1 formed impressions of a schema-inconsistent female mechanic (vs. a schema-consistent male mechanic). Following schema-inconsistent rather than -consistent information, participants low (high) in need for structure showed better (impeded) creative performance. Participants in Study 2 memorized a series of images in which individuals were placed on a schema-inconsistent (vs. consistent) background (e.g., an Eskimo on the desert vs. on a snowy landscape). Following schema-inconsistent imagery, participants low (high) in need for structure increased (decreased) divergent thinking. © 2014 by the Society for Personality and Social Psychology, Inc.
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Corporate governance has become increasingly important in developed and developing countries just after a series of corporate scandals and failures in a number of countries. Corporate governance structure is often viewed as a means of corporate success despite prior studies reveal mixed, somewhere conflicting and ambiguous, and somewhere no relationship between governance structure and performance. This study empirically investigates the relationship between corporate governance mechanisms and financial performance of listed banking companies in Bangladesh by using two multiple regression models. The study reveals that a good number of companies do not comply with the regulatory requirements indicating remarkable shortfall in corporate governance practice. The companies are run by the professional managers having no duality and no ownership interest for which they are compensated by high remuneration to curb agency conflict. Apart from some inconsistent relationship between some corporate variables, the corporate governance mechanisms do not appear to have significant relationship with financial performances. The findings reveal an insignificant negative impact or somewhere no impact of independent directors and non-independent non-executive directors on the level of performance that strongly support the concept that the managers are essentially worthy of trust and earn returns for the owners as claimed by stewardship theory. The study provides support for the view that while much emphasis on corporate governance mechanisms is necessary to safeguard the interest of stakeholders; corporate governance on its own, as a set of codes or standards for corporate conformance, cannot make a company successful. Companies need to balance corporate governance mechanisms with performance by adopting strategic decision and risk management with the efficient utilization of the organization’s resources.
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The ultimate intent of this dissertation was to broaden and strengthen our understanding of IT implementation by emphasizing research efforts on the dynamic nature of the implementation process. More specifically, efforts were directed toward opening the "black box" and providing the story that explains how and why contextual conditions and implementation tactics interact to produce project outcomes. In pursuit of this objective, the dissertation was aimed at theory building and adopted a case study methodology combining qualitative and quantitative evidence. Precisely, it examined the implementation process, use and consequences of three clinical information systems at Jackson Memorial Hospital, a large tertiary care teaching hospital.^ As a preliminary step toward the development of a more realistic model of system implementation, the study proposes a new set of research propositions reflecting the dynamic nature of the implementation process.^ Findings clearly reveal that successful implementation projects are likely to be those where key actors envision end goals, anticipate challenges ahead, and recognize the presence of and seize opportunities. It was also found that IT implementation is characterized by the systems theory of equifinality, that is, there are likely several equally effective ways to achieve a given end goal. The selection of a particular implementation strategy appears to be a rational process where actions and decisions are largely influenced by the degree to which key actors recognize the mediating role of each tactic and are motivated to action. The nature of the implementation process is also characterized by the concept of "duality of structure," that is, context and actions mutually influence each other. Another key finding suggests that there is no underlying program that regulates the process of change and moves it form one given point toward a subsequent and already prefigured end. For this reason, the implementation process cannot be thought of as a series of activities performed in a sequential manner such as conceived in stage models. Finally, it was found that IT implementation is punctuated by a certain indeterminacy. Results suggest that only when substantial efforts are focused on what to look for and think about, it is less likely that unfavorable and undesirable consequences will occur. ^
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This study described teacher perceptions of TUPE program effectiveness in Florida in an attempt to improve programs by identifying factors that might influence teacher motivation and performance. Very little work has been done to examine how teachers' perceptions are related to the effectiveness of TUPE programs. A statewide survey provided information about how teachers' perceptions of program effectiveness are affected by variables such as: program structure, barriers, tobacco use norms, and training variables. Data were obtained from a telephone survey conducted in Florida as part of the Tobacco Pilot Project (TPP). The sample included 296 middle school teachers and 282 high school teachers as well as 193 middle school principals and 190 high school principals. Correlational and hierarchical regression analyses identified correlates and predictors of teachers' ratings of effectiveness. Results suggest that use of peer leaders, more frequent evaluations, a higher degree of parent involvement, fewer barriers, greater student interest, and lower tolerance for tobacco use were correlated with higher ratings of program effectiveness. Furthermore, student interest, peer, staff, and community tolerance norms, peer leaders, program evaluation, and parent involvement predicted middle school teachers' perceptions. Parent tolerance, student interest, number of barriers, and more frequent program evaluation predicted high school teachers' perceptions. In addition, middle school teachers who reported a lower number of factors negatively associated with teacher receptivity were more likely to view TUPE programs more favorably than teachers who reported a greater number of these risk factors. This relationship was not as robust among the high school teacher sample. Differences between the middle and high school sample were found in the magnitude and number of significant correlations, the proportion of variance accounted for by predictor variables, and the strength of the relationship between the number of factors negatively associated with teacher receptivity and teachers' perceptions of TUPE effectiveness. These findings highlighted the importance of the timing, program features, and the external environment for enhancing or minimizing teachers' ratings of TUPE program effectiveness. In conclusion, significant increases in TUPE teachers' self-efficacy will occur through the participation of peers, parents, staff, and community leaders in different aspects of TUPE programs. ^
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Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^
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Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^
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Computer Game Playing has been an active area of research since Samuel’s first Checkers player (Samuel 1959). Recently interest beyond the classic games of Chess and Checkers has led to competitions such as the General Game Playing competition, in which players have no beforehand knowledge of the games they are to play, and the Computer Poker Competition which force players to reason about imperfect information under conditions of uncertainty. The purpose of this dissertation is to explore the area of General Game Playing both specifically and generally. On the specific side, we describe the design and implementation of our General Game Playing system OGRE. This system includes an innovative method for feature extraction that helped it to achieve second and fourth place in two international General Game Playing competitions. On the more general side, we also introduce the Regular Game Language, which goes beyond current works to provide support for both stochastic and imperfect information games as well as the more traditional games.