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Slide 0 - Unicaja
Slide 0 - Unicaja

... This document has been prepared by Unicaja Banco, S.A. (“Unicaja Banco”). By attending the meeting where this document is presented, or by reading the slides contained herein, you will be deemed to have: (i) agreed to the following limitations and notifications and made the following undertakings; a ...
Analyses of Online Advertising Performance Using
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... The purpose of this Thesis is to create a framework to analyze user data to understand the impact of online marketing efforts on customer conversion rates. The framework is used to support decision making in planning and coordination of online marketing activities to maximize the number of converted ...
Master Data Listing
Master Data Listing

... A person registered within Banner for the purpose of providing them with a CSU account that has access to limited CSU services. A person who has been 'sent' a formal offer or has accepted an offer of admission into a course of study at CSU. Associated teachers who are paid by the University for the ...
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... As part of Eclipsys Diagnostic Imaging Solutions™, Sunrise RIS can be integrated with Sunrise picture archiving and communication system, Sunrise PACS™, powered by Sectra. This provides real-time connectivity and a complete paperless toolset for managing every stage of a radiology exam — from the mo ...
LN26 - WSU EECS
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... – Typical methods: DBSCAN, OPTICS, DenClue  Grid-based approach: ...
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Citrix ICA Priority Packet Tagging

... TCP requires an acknowledgement of receipt for each TCP segment in the TCP buffer before sending additional segments. This prevents QoS solutions from being able to implement functionality that holds back printing ICA data and forwards on Thinwire ICA data within a single ICA stream (which is also a ...
ClusterAnalysis
ClusterAnalysis

...  Typical methods: DBSACN, OPTICS, DenClue Grid-based approach:  based on a multiple-level granularity structure  Typical methods: STING, WaveCluster, CLIQUE ...
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... the data set and renaming the new data set to have the same name as the previous version. So, you really wind up with a completely “new” data set that has the same name as the original one. Relational databases don’t work this way: creating a table is normally a long-term commitment, with changes ma ...
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traffic collision database system
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... give you just the information you need. Using the system's query screens, you can select date ranges and locations; you can make your query as inclusive as you wish, covering all collisions citywide or narrowing the search to include only collisions with specific attributes of fields such as primary ...
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Biclustering: Methods, Software and Application

... text mining: objects = documents, variables = words We are now interested in finding homogenous groups of objects, such as coregulated genes or market segments. In all applications, it is reasonable to assume that different groups may be defined by different variables. For example, if we want to sel ...
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... ODBC is a Microsoft spec that allows users to share information in a relational database across multiple and diverse platforms. Examples: Microsoft SQL Server, MS Access, QuickBooks, Crystal Reports, MS Visual Basic, DB2 for PCs The application must be ODBC-compliant QODBC is included with QuickBook ...
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... 34(3) of the Planning and Development Act 2000, has had regard to submissions or observations received in accordance with the Planning and Development Regulations 2001-2006, in relation to these decisions. It is the responsibility of those wishing to use the personal data on weekly lists for direct ...
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... of investments can fall as well as rise as a result of market or currency movements Potential investors should be aware that investment in Emerging Markets involves an above average degree of risk and should be seen as long-term in nature. Less developed markets are generally less well regulated tha ...
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... There are many practical problems involved in the use of cluster analysis. The selection of variables to be included in the analysis, the choice of distance measure and the criteria for combining cases into clusters are all critical. Because the selected clustering method can itself impose a certain ...
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... Ferda Advantages Modular and extensible architecture, usage of middleware, support for distributed computing  Ferda’s box model: ability implement and include new boxes, possible engine for EverMiner  Comprehensive user interface including new features such as box archive ...
Serial Dependence and Portfolio Performance in the Swedish Stock
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... evaluated and compared to the performance of a contrarian and an unconditional sample mean arbitrage portfolio. For daily data the VAR model works quite well, yielding a higher Sharpe ratio than the two other arbitrage portfolios. For weekly and monthly data, the performance is not as good. In the w ...
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... These standards are in effect for all new development efforts beginning 2/4/2016. The use of Oracle or DB2 as a RDBMS platform is no longer allowed for newly developed applications. Existing systems that are already implemented in either of these contained RDBMS platforms may continue to use them fo ...
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... Start with physical asset-level data. High quality transition risk assessment will in almost all cases have to rely on asset level data in order to provide forward-looking, geographic granularity around potential risk exposure. While at this stage access to such data can be expensive and difficult t ...
Querying XML Documents
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... stored for efficient retrieval using modern Database Management Systems (DBMSs). The current state-of-the-art in database management is represented by the Object-Oriented (OO) and Object-Relational (OR) DBMSs each with their own query languages, Object Query Language (OQL, v.2) [CBB+ ] and Structure ...
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... the foundation by providing additional opportunities to create open client access to SAS software. Lets take a look at the evolution of these products and their enabling technologies. For years SAS/CONNECT software has provided the essential tools for sharing data and applications across multiple co ...
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Business intelligence

Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI technologies are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic business opportunities. The goal of BI is to allow for the easy interpretation of these large volumes of data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability.BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.BI can be used to support a wide range of business decisions ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic business decisions include priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined, external and internal data can provide a more complete picture which, in effect, creates an ""intelligence"" that cannot be derived by any singular set of data.
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