891 resultados para Power-knowledge


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Scoping behavioral variations to dynamic extents is useful to support non-functional requirements that otherwise result in cross-cutting code. Unfortunately, such variations are difficult to achieve with traditional reflection or aspects. We show that with a modification of dynamic proxies, called delegation proxies, it becomes possible to reflectively implement variations that propagate to all objects accessed in the dynamic extent of a message send. We demonstrate our approach with examples of variations scoped to dynamic extents that help simplify code related to safety, reliability, and monitoring.

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Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

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Passive positioning systems produce user location information for third-party providers of positioning services. Since the tracked wireless devices do not participate in the positioning process, passive positioning can only rely on simple, measurable radio signal parameters, such as timing or power information. In this work, we provide a passive tracking system for WiFi signals with an enhanced particle filter using fine-grained power-based ranging. Our proposed particle filter provides an improved likelihood function on observation parameters and is equipped with a modified coordinated turn model to address the challenges in a passive positioning system. The anchor nodes for WiFi signal sniffing and target positioning use software defined radio techniques to extract channel state information to mitigate multipath effects. By combining the enhanced particle filter and a set of enhanced ranging methods, our system can track mobile targets with an accuracy of 1.5m for 50% and 2.3m for 90% in a complex indoor environment. Our proposed particle filter significantly outperforms the typical bootstrap particle filter, extended Kalman filter and trilateration algorithms.

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There has been increasing interest in the discursive aspects of strategy over the last two decades. In this editorial we review the existing literature, focusing on six major bodies of discursive scholarship: post-structural, critical discourse analysis, narrative, rhetoric, conversation analysis and metaphor. Our review reveals the significant contributions of research on strategy and discourse, but also the potential to advance research in this area by bringing together research on discursive practices and research on other practices we know to be important in strategy work. We explore the potential of discursive scholarship in integrating between significant theoretical domains (sensemaking, power and sociomateriality), and realms of analysis (institutional, organizational and the episodic), relevant to strategy scholarship. This allows us to place the papers published in the special issue Strategy as Discourse: Its Significance, Challenges and Future Directions among the body of knowledge accumulated thus far, and to suggest a way forward for future scholarship.

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Objective. The purpose of the study is to provide a holistic depiction of behavioral & environmental factors contributing to risky sexual behaviors among predominantly high school educated, low-income African Americans residing in urban areas of Houston, TX utilizing the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory. ^ Methods. A cross-sectional study was conducted via questionnaires among 215 Houston area residents, 149 were women and 66 were male. Measures used to assess behaviors of the population included a history of homelessness, use of crack/cocaine among several other illicit drugs, the type of sexual partner, age of participant, age of most recent sex partner, whether or not participants sought health care in the last 12 months, knowledge of partner's other sexual activities, symptoms of depression, and places where partner's were met. In an effort to determine risk of sexual encounters, a risk index employing the variables used to assess condom use was created categorizing sexual encounters as unsafe or safe. ^ Results. Variables meeting the significance level of p<.15 for the bivariate analysis of each theory were entered into a binary logistic regression analysis. The block for each theory was significant, suggesting that the grouping assignments of each variable by theory were significantly associated with unsafe sexual behaviors. Within the regression analysis, variables such as sex for drugs/money, low income, and crack use demonstrated an effect size of ≥±1, indicating that these variables had a significant effect on unsafe sexual behavioral practices. ^ Conclusions. Variables assessing behavior and environment demonstrated a significant effect when categorized by relation to designated theories. ^

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Despite the recent decline in adolescent pregnancy rates, adolescent pregnancy continues to be a significant public health issue in the United States. The United States consistently reports the highest rate of adolescent pregnancy among developed countries. Adolescent mothers are more likely to have multiple pregnancies, to access welfare and other social services, and to be unmarried. Teen mothers are less likely to complete high school, enter college, and typically command much less earning power throughout their lifetime as compared to women who delay childbirth until later. Moreover, the United States spends approximately $9.1 billion annually on teen pregnancies. ^ Additionally disconcerting is recent data which demonstrates that the decline in teen pregnancy rates is leveling off and that the rate of adolescent pregnancy has increased for the first time since 1993. Contraceptive use is a key component to the prevention of adolescent pregnancy. Contraceptive nonuse and failure result in unintended pregnancies among adolescents. This review sought to assess the levels of knowledge and attitudes toward contraception among adolescent females.^ Levels of knowledge of contraception among adolescents are tolerable; however, there is substantial room for improvement. Misperceptions about the side effects and mechanisms of action of contraception are pervasive among this population. Adolescents who have low levels of knowledge regarding contraception tend to discontinue usage or use inconsistently. Attitudes toward contraception are greatly influenced by levels of knowledge. As a result, adolescents tend to develop more positive attitudes as misperceptions are abated. Moreover, clear disparities persist among adolescents with minority and young adolescents being at increased risk of pregnancy, poor contraceptive use, and insufficient knowledge about contraception.^ Understanding the level of knowledge of and attitudes toward contraceptives among adolescents is essential to the development of effective pregnancy prevention programs. In order to effectively reduce adolescent pregnancy, prevention initiatives must target the vulnerable populations and incorporate the necessary cultural components.^

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Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.

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The magazine of the Spanish Nuclear Society (SNE), “Nuclear España” is a scientific-technical publication with almost thirty years of uninterrupted edition and more than 300 numbers published. Their pages approach technical subjects related to the nuclear energy, as well as the activities developed by the SNE, especially in national and international meetings. The main part of the magazine is composed by articles written by known specialist of the energy industry. One of the top goals of the magazine is to help on transferring the knowledge from the generation that built the nuclear power plants in Spain and the new generation of professionals that have started its nuclear career in the last years. Each number is monographic, trying to cover as many aspects on an issue as it is possible, with collaborations from the companies, the research centers and universities that helps to have complementary points of view. On the other hand the articles help to deep in the issue´s topic, broadening the view of the readers about the nuclear field and helping to share knowledge across the industry. The news section of the Magazine picks up the actuality of the sector as a whole. The editorial section reflects the opinion of the SNE Governing Board and the Magazine Committee on the subjects of interest in this field. On the other hand, the monthly interview sets out the professional outstanding opinions. With a total of eleven numbers per year, three of them have a noticeable international character: the one dedicated to the operative experiences on the Spanish and European nuclear power plants, the monographic issue devoted tothe Annual Meeting of the SNE and the international issue, which covers the last activities of the Spanish industry in international projects. Both first are bilingual issues (Spanish-English), whereas the international edition is published completely in English. Besides its diffusion through all the members of the SNE, the Magazine is distributed, in the national scope, to companies and organisms related to the nuclear power, universities, research centers, representatives of the Central, Autonomic and Local Administrations, mass media and communication professionals. It is also sent to the utilities and research centers in Europe, United States, South America and Asia.

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The recognition of the relevance of energy, especially of the renewable energies generated by the sun, water, wind, tides, modern biomass or thermal is growing significantly in the global society based on the possibility it has to improve societies′ quality of life, to support poverty reduction and sustainable development. Renewable energy, and mainly the energy generated by large hydropower generation projects that supply most of the renewable energy consumed by developing countries, requires many technical, legal, financial and social complex processes sustained by innovations and valuable knowledge. Besides these efforts, renewable energy requires a solid infrastructure to generate and distribute the energy resources needed to solve the basic needs of society. This demands a proper construction performance to deliver the energy projects planned according to specifications and respecting environmental and social concerns, which implies the observance of sustainable construction guidelines. But construction projects are complex and demanding and frequently face time and cost overruns that may cause negative impacts on the initial planning and thus on society. The renewable energy issue and the large renewable energy power generation and distribution projects are particularly significant for developing countries and for Latin America in particular, as this region concentrates an important hydropower potential and installed capacity. Using as references the performance of Venezuelan large hydropower generation projects and the Guri dam construction, this research evaluates the tight relationship existing between sustainable construction and knowledge management and their impact to achieve sustainability goals. The knowledge management processes are proposed as a basic strategy to allow learning from successes and failures obtained in previous projects and transform the enhancement opportunites into actions to improve the performance of the renewable energy power generation and distribution projects.

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Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

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Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.

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"Credit is largely due to Frank D. Graham ... for the authorship of the Guides, and for the original sketches illustrating electrical principles and construction."--Pref. to no. 1.

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The Palestinian region is changing rapidly, with both economic and cultural consequences. One way of approaching this very political process is thru the concept of landscape. By viewing the region as a multiprocessual, dynamic landscape the analysis allows for a holistic read where historical and contemporary projections, interpretations and notions of power are fused. This thesis draws on the scholarly fields of humanistic landscape research and aerial image interpretation as well as theories of orientalism and power. A case study of two regions of the West Bank is performed; interviews and observations provide localized knowledge that is then used in open-access image interpretation. By performing image interpretations this thesis explores the power embedded in mapping and the possible inclinations the development towards open-access geospatial analytic tools could have on the functions of power in the Palestinian landscape. By investigating the spatial configuration of the Palestinian landscape and tracing its roots this thesis finds four major themes that are particularly pivotal in the processual change of the Palestinian landscape: the Israeli/Palestinian time-space, the blurring of the conflict, the dynamics of the frontier region and the orientalist gaze. 

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Currently there is no structured data standard for representing elements commonly found in transmedia fictional universes. There are websites dedicated to individual universes, however, information found on these sites separates the various formats into books, movies, comics, etc.; concentrate on only the bibliographic aspects of the material; and are only full-text searchable. We have created an ontological model that will allow researchers, fans, brand managers, and creators to search for and retrieve the information contained in these worlds based on how they are structured. We conducted a domain analysis and user studies based on the contents of Harry Potter, Lord of the Rings, the Marvel Universe, and Star Wars in order to build a new model using the Ontology Web Language (OWL) and an artificial intelligence reasoning engine. This model can infer connections between characters, elements of power, items, places, events, etc. This model will facilitate better search and retrieval of the information contained within these vast story universes for all users interested in them. The result of this project is and OWL ontology that is intuitive for users; can be used by AI systems; and has been updated to reflect real user needs based on user research.

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Thesis (Master's)--University of Washington, 2016-06