897 resultados para ”Learning by doing”
Resumo:
Price knowledge as a construct has been one of the top behavioral pricing themes in the last four decades, especially in the Anglo-American literature. In Germany, scientists have paid relatively little attention to this topic during the last 15 years – with some notable exceptions. Therefore, this study analyzes German consumers' price knowledge and, by doing so, replicates and extends existing international work. After reviewing earlier attempts at assessing the construct, a measure is developed for the price estimation error “PEE”, based on explicit price knowledge stored in long-term memory. Results, including data from about 1,000 consumers on 69 products from a German retail chain, indicate that price knowledge in Germany is relatively low. Based on that observation, implications for the management are discussed.
Resumo:
In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in Wireless Sensor Networks (WSNs). In-Motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception, cognition and control, forming the basis for its intelligence. Our middleware incorporates technologies such as Linda-like tuplespaces and federated system architecture in order to obtain a high degree of collaboration and coordination for the agent society. A set of behavioral rules inspired by a community of bacterial strains is also generated as the means for robustness of the WSN. In this paper, we present In-Motes and provide a detailed evaluation of its implementation for MICA2 motes.
Resumo:
The results of research the intelligence multimodal man-machine interface and virtual reality means for assistive medical systems including computers and mechatronic systems (robots) are discussed. The gesture translation for disability peoples, the learning-by-showing technology and virtual operating room with 3D visualization are presented in this report and were announced at International exhibition "Intelligent and Adaptive Robots–2005".
Resumo:
Small and Medium Enterprises (SMEs) play an important part in the economy of any country. Initially, a flat management hierarchy, quick response to market changes and cost competitiveness were seen as the competitive characteristics of an SME. Recently, in developed economies, technological capabilities (TCs) management- managing existing and developing or assimilating new technological capabilities for continuous process and product innovations, has become important for both large organisations and SMEs to achieve sustained competitiveness. Therefore, various technological innovation capability (TIC) models have been developed at firm level to assess firms‘ innovation capability level. These models output help policy makers and firm managers to devise policies for deepening a firm‘s technical knowledge generation, acquisition and exploitation capabilities for sustained technological competitive edge. However, in developing countries TCs management is more of TCs upgrading: acquisitions of TCs from abroad, and then assimilating, innovating and exploiting them. Most of the TIC models for developing countries delineate the level of TIC required as firms move from the acquisition to innovative level. However, these models do not provide tools for assessing the existing level of TIC of a firm and various factors affecting TIC, to help practical interventions for TCs upgrading of firms for improved or new processes and products. Recently, the Government of Pakistan (GOP) has realised the importance of TCs upgrading in SMEs-especially export-oriented, for their sustained competitiveness. The GOP has launched various initiatives with local and foreign assistance to identify ways and means of upgrading local SMEs capabilities. This research targets this gap and developed a TICs assessment model for identifying the existing level of TIC of manufacturing SMEs existing in clusters in Sialkot, Pakistan. SME executives in three different export-oriented clusters at Sialkot were interviewed to analyse technological capabilities development initiatives (CDIs) taken by them to develop and upgrade their firms‘ TCs. Data analysed at CDI, firm, cluster and cross-cluster level first helped classify interviewed firms as leader, follower and reactor, with leader firms claiming to introduce mostly new CDIs to their cluster. Second, the data analysis displayed that mostly interviewed leader firms exhibited ‗learning by interacting‘ and ‗learning by training‘ capabilities for expertise acquisition from customers and international consultants. However, these leader firms did not show much evidence of learning by using, reverse engineering and R&D capabilities, which according to the extant literature are necessary for upgrading existing TIC level and thus TCs of firm for better value-added processes and products. The research results are supported by extant literature on Sialkot clusters. Thus, in sum, a TIC assessment model was developed in this research which qualitatively identified interviewed firms‘ TIC levels, the factors affecting them, and is validated by existing literature on interviewed Sialkot clusters. Further, the research gives policy level recommendations for TIC and thus TCs upgrading at firm and cluster level for targeting better value-added markets.
Resumo:
Motivated by the historically poor productivity performance of Northern Ireland firms and the longstanding productivity gap with the UK, the aim of this thesis is to examine, through the use of firm-level data, how exporting, innovation and public financial assistance impact on firm productivity growth. These particular activities are investigated due to the continued policy focus on their link to productivity growth and the theoretical claims of a direct positive relationship. In order to undertake these analyses a newly constructed dataset is used which links together cross-sectional and longitudinal data over the 1998-2008 period from the Annual Business Survey, the Manufacturing Sales and Export Survey; the Community Innovation Survey and Invest NI Selective Financial Assistance (SFA) payment data. Econometric methodologies are employed to estimate each of the relationships with regards to productivity growth, making use in particular of Heckman selection techniques and propensity score matching to take account of critical issues of endogeneity and selection bias. The results show that more productive firms self-select into exporting but there is no resulting productivity effect from starting to export; contesting the argument for learning-by-exporting. Product innovation is also found to have no impact on productivity growth over a four year period but there is evidence of a negative process innovation impact, likely to reflect temporary learning effects. Finally SFA assistance, including the amount of the payment, is found to have no short term impact on productivity growth suggesting substantial deadweight effects and/or targeting of inefficient firms. The results provide partial evidence as to why Northern Ireland has failed to narrow the productivity gap with the rest of the UK. The analyses further highlight the need for access to comprehensive firm-level data for research purposes, not least to underpin robust evidence-based policymaking.
Resumo:
External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.
Resumo:
In the last decade, non-technological and particularly organisational innovations have gained more and more importance and research focus. However, there is no consensus among the academic community either about the definition or about the broader theoretical and methodological foundations of this phenomena. In the present study the authors intend to partly improve this knowledge deficiency syndrome by analysing the most important theoretical contributions of organisational innovation and by reviewing the development in the methodological tools aimed to measure organisational innovation on a European level. By doing so, the authors will focus on the various waves of the Community Innovation Survey (CIS) as an employer-oriented and of the European Working Conditions Survey (EWCS) as an employee-oriented survey. Finally, they will formulate some remarks for further empirical research streams.
Resumo:
The aesthetic placement and period designation of Jorge Luis Borges (1899–1986) and José Lezama Lima (1910–1976) are complicated issues among critics. Borges is considered a predecessor of the Latin American literary “boom,” but despite that taxonomy his work transcends that definition and provides a foundation for new trends, such as the “neobarroco” cultivated by Severo Sarduy. Lezama is considered part of the second wave of the “boom,” but his work feeds, stylistically, from the Spanish baroque. At the same time, Lezama's daring treatment of homoeroticism and his system of images place him after the “boom” in a narrative style that is postmodern. This study undertakes a revision of external and internal issues, revealing the key fictive elements that characterize both writers. Through discourse analysis, a poetic system is formulated, which incorporates features of the “neobarroco,” and postmodern narrative styles. ^ This dissertation uses a polar structure to analyze both poetic visions and finds that they are symmetrical. From this perspective, Borges and Lezama belong to the “core” of literature that centers its emphasis in the creation of a system versus other modes of writing in which mimetic function prevails. By doing this and by recycling world culture, they create postmodern myth: the new building material for Hispanic American literature. ^ There are a few studies that explore the works of Borges and Lezama within the context of Baroque aesthetics. This dissertation offers a comprehensive analysis that considers their poetic visions at large. Besides the difference in perspective, defined as macro-spatial in Borges and micro-spatial in Lezama, there are many similarities. Both writers question the cause and effect relationship and the use of metaphor. They share a redefinition of genre as well as a hedonistic approach to literature. This kinship in poetic vision is revealed through the polar method used for this study, which proposes a new form of aesthetic placement and period designation. ^
Resumo:
Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.
Resumo:
Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.
Resumo:
This paper deals with finding the maximum number of security policies without conflicts. By doing so we can remove security loophole that causes security violation. We present the problem of maximum compatible security policy and its relationship to the problem of maximum acyclic subgraph, which is proved to be NP-hard. Then we present a polynomial-time approximation algorithm and show that our result has approximation ratio for any integer with complexity .
Resumo:
Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.
Resumo:
Japan is an important ally of the United States–the world’s third biggest economy, and one of the regional great powers in Asia. Making sense of Japan’s foreign and security policies is crucial for the future of peace and stability in Northeast Asia, where the possible sources of conflict such as territorial disputes or the disputes over Japan’s war legacy issues are observed. This dissertation explored Japan’s foreign and security policies based on Japan’s identities and unconscious ideologies. It employed an analysis of selected Japanese films from the late 1940s to the late 1950s, as well as from the late 1990s to the mid-2000s. The analysis demonstrated that Japan’s foreign and security policies could be understood in terms of a broader social narrative that was visible in Japanese popular cultural products, including films and literatures. Narratives of Japanese families from the patriarch’s point of view, for example, had constantly shaped Japan’s foreign and security policies. As a result, the world was ordered hierarchically in the eyes of the Japan Self. In the 1950s, Japan tenaciously constructed close but asymmetrical security relations with the U.S. in which Japan willingly subjugated itself to the U.S. In the 2000s, Japan again constructed close relations with the U.S. by doing its best to support American responses to the 9/11 terrorist attacks by mobilizing Japan’s SDFs in the way Japan had never done in the past. The concepts of identity and unconscious ideology are helpful in understanding how Japan’s own understanding of self, of others, and of the world have shaped its own behaviors. These concepts also enable Japan to reevaluate its own behaviors reflexively, which departs from existing alternative approaches. This study provided a critical analytical explanation of the dynamics at work in Japan’s sense of identity, particularly with regard to its foreign and security policies.
Resumo:
Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.
Resumo:
The aesthetic placement and period designation of Jorge Luis Borges (1899-1986) and José Lezama Lima (1910-1976) are complicated issues among critics. Borges is obviously considered a predecessor of the Latin American literary “boom,” but despite that taxonomy his work transcends that definition and provides a foundation for new trends and styles, such as the “neobarroco” cultivated by Severo Sarduy. Lezama is considered part of the second wave of the “boom,” but his work feeds, stylistically, from the Spanish baroque. At the same time, Lezama’s daring treatment of homoeroticism and his revolutionary system of images place him after the “boom” in a narrative style that is postmodern. This study undertakes a thorough revision of external and internal issues, revealing the key linguistic and fictive elements that characterize both writers. Through discourse analysis and close reading, a poetic system is formulated, which incorporate features of the “neobarroco,” “boom” and postmodern narrative styles. This dissertation uses a polar structure to analyze both poetic visions and concludes that they are compatible and symmetrical. From this perspective, Borges and Lezama belong to the “core” of literature that centers its emphasis in the creation of a system versus other modes of writing in which mimetic function prevails. By doing this and by recycling world culture, they create postmodern myth: the new building material for Hispanic American literature. There are only a few studies that explore the works of Borges and Lezama within the context of Baroque aesthetics. For the first time, this dissertation offers a comprehensive analysis that considers their poetic visions at large. Besides the difference in perspective, defined as macro-spatial in Borges and micro-spatial in Lezama, there are many similarities in content and form. Both writers question the cause and effect relationship and the modern use of metaphor. They also share a redefinition of genre as well as a hedonistic approach to literature and culture. This kinship in poetic vision is revealed through the polar method used for this study, which proposes a new form of aesthetic placement and period designation.