382 resultados para Empirical Mode Decomposition


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The effective implementation of such an ISO 9001 Quality Management System (QMS) in construction companies requires a proper and full implementation of the system to allow companies to improve the way they operate, by this means increasing profitability and market share, producing innovative and sustainable construction products, or improving employee and customer satisfaction. In light of this, this paper discusses the current status of QMS implementation, particularly related to the twenty elements of ISO 9001 within the grade 7 (G-7) category of Indonesian construction companies. A survey was conducted involving 403 respondents from 77 companies, to solicit an evaluation of the current implementation levels of the ISO 9001 elements. The survey findings indicated that for a large percentage of the sector surveyed they had ‘not so fully implemented’ the elements. Scrutiny of the data had also indicated elements that are ‘minimally implemented’, whilst none of the elements fell in the category of ‘fully implemented’. Based on these findings, it is suggested that the G-7 contractors may need to fully commit to practicing control of customer-supplied product and statistical techniques in order to enhance an effective implementation of ISO 9001 elements for ensuring better quality performance. These two elements are recognized as the least implemented of the quality elements.

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Spatially resolved cathodoluminescence (CL) study of a ZnO nanonail, having thin shank, tapered neck, and hexagonal head sections, is reported. Monochromatic imaging and line scan profiling indicate that the wave guiding and leaking from growth imperfections in addition to the oxygen deficiency variation determine the spatial contrast of CL emissions. Occurrence of resonance peaks at identical wavelengths regardless of CL-excitation spots is inconsistent with the whispering-gallery mode (WGM) resonances of a two-dimensional cavity in the finite difference time domain simulation. However, three dimensioanl cavity simulation produced WGM peaks that are consistent with the experimental spectra, including transverse-electric resonances that are comparable to transverse-magnetic ones.

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In this paper, the level of lean manufacturing implementation by Saudi manufacturing companies is investigated, the extent of application of lean manufacturing practice is identified and the benefits and barriers of Lean implementation are evaluated. The results reported in this paper are based on data collected from a survey using a standard questionnaire administered to 120 manufacturers in Saudi Arabia. Evidence indicates that large size companies are more likely to implement and gain the advantages of lean manufacturing than small and medium size companies. The most implemented lean manufacturing tools are Computerized Planning Systems, TQM, Maintenance Optimization and CIP. Main barriers against lean manufacturing implementation include the organization culture, lack of management commitment and lack of skilled workers. Results also show that benefits gained from lean manufacturing implementation are significant and are correlated with the level of implementation of lean strategies.

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This paper makes distinctions among four investigative thinking styles of detectives: method style, challenge style, skill style, and risk style. Based on previous research, this study empirically tested, to what extent there are cumulative relationships among these thinking styles. Furthermore, this research studied relationships between investigative thinking styles and creativity in police investigations. Significant relationships were found between the extent of the challenge and risk styles and the extent of creativity.

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The great majority of police officers are committed to honourable and competent public service and consistently demonstrate integrity and accountability in carrying out the often difficult, complex and sometimes dangerous, activities involved in policing by consent. However, in every police agency there exists an element of dishonesty, lack of professionalism and criminal behaviour. This article is based on archival research of criminal behaviour in the Norwegian police force. A total of 60 police employees were prosecuted in court because of misconduct and crime from 2005 to 2010. Court cases were coded as two potential predictors of court sentence in terms of imprisonment days, ie, type of deviance and level of deviance. Categories of police crime and levels were organised according to a conceptual framework developed for assessing and managing police deviance. Empirical findings support the hypothesis that as the seriousness of police crime increases in breadth and depth so also does the severity of the court sentence as measured by time in prison.

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Inter-Vehicular Communications (IVC) are considered a promising technological approach for enhancing transportation safety and improving highway efficiency. Previous theoretical work has demonstrated the benefits of IVC in vehicles strings. Simulations of partially IVC-equipped vehicles strings showed that only a small equipment ratio is sufficient to drastically reduce the number of head on collisions. However, these results are based on the assumptions that IVC exhibit lossless and instantaneous messages transmission. This paper presents the research design of an empirical measurement of a vehicles string, with the goal of highlighting the constraints introduced by the actual characteristics of communication devices. A warning message diffusion system based on IEEE 802.11 wireless technology was developed for an emergency breaking scenario. Preliminary results are presented as well, showing the latencies introduced by using 802.11a and discussing early findings and experimental limitations

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Small business has been shown to contribute significantly to a nation’s economic development. Small business owners typically confront challenges, uncertainty, and risks while operating new businesses. Franchising has become a way to minimize the risks of small business management (Chiou et al., 2004); however, a franchise system is not a guarantee of business success (Lee and Karkovista, 2001). A poor franchising relationship between franchisors and franchisees can result in franchise failure, such as termination and closure, or franchisee exit (Frazer and Winzar, 2005).

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Six Sigma is considered to be an important management philosophy to obtain satisfied customers. But financial service organisations have been slow to adopt Six Sigma issues so far. Despite the extensive effort that has been invested and benefits that can be obtained, the systematic implementation of Six Sigma in financial service organisations is limited. As a company wide implementation framework is missing so far, this paper tries to fill this gap. Based on theory, a conceptual framework is developed and evaluated by experts from financial institutions. The results show that it is very important to link Six Sigma with the strategic as well as the operations level. Furthermore, although Six Sigma is a very important method for improving quality of processes others such as Lean Management are also used This requires a superior project portfolio management to coordinate resources and projects of Six Sigma with the other methods used. Beside the theoretical contribution, the framework can be used by financial service companies to evaluate their Six Sigma activities. Thus, the framework grounded through literature and empirical data will be a useful guide for sustainable and successful implementation of a Six Sigma initiative in financial service organisations.

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Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

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A fundamental principle of the resource-based (RBV) of the firm is that the basis for a competitive advantage lies primarily in the application of bundles of valuable strategic capabilities and resources at a firm’s or supply chain’s disposal. These capabilities enact research activities and outputs produced by industry funded R&D bodies. Such industry lead innovations are seen as strategic industry resources, because effective utilization of industry innovation capacity by sectors such as the Australian beef industry are critical, if productivity levels are to increase. Academics and practitioners often maintain that dynamic supply chains and innovation capacity are the mechanisms most likely to deliver performance improvements in national industries.. Yet many industries are still failing to capitalise on these strategic resources. In this research, we draw on the resource-based view (RBV) and embryonic research into strategic supply chain capabilities. We investigate how two strategic supply chain capabilities (supply chain performance differential capability and supply chain dynamic capability) influence industry-led innovation capacity utilization and provide superior performance enhancements to the supply chain. In addition, we examine the influence of size of the supply chain operative as a control variable. Results indicate that both small and large supply chain operatives in this industry believe these strategic capabilities influence and function as second-order latent variables of this strategic supply chain resource. Additionally respondents acknowledge size does impacts both the amount of influence these strategic capabilities have and the level of performance enhancement expected by supply chain operatives from utilizing industry-led innovation capacity. Results however also indicate contradiction in this industry and in relation to existing literature when it comes to utilizing such e-resources.

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Providing effective IT support for business processes has become crucial for enterprises to stay competitive. In response to this need numerous process support paradigms (e.g., workflow management, service flow management, case handling), process specification standards (e.g., WS-BPEL, BPML, BPMN), process tools (e.g., ARIS Toolset, Tibco Staffware, FLOWer), and supporting methods have emerged in recent years. Summarized under the term “Business Process Management” (BPM), these paradigms, standards, tools, and methods have become a success-critical instrument for improving process performance.

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Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.