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Corliss Group Online Financial Mag Hong Kong 5 Can’t Miss Investing Stories Last Week Let the good times roll! The S&P/TSX Composite Index (TSX:^OSPTX) continued its month-long winning streak last week with the equity gauge nearing a three-year high. However, there were a number of important corporate reports for investors to shift through as well. Here are the top five can’t-miss headlines from the past week. 1. BlackBerry signals shift to enterprise Shares of BlackBerry (TSX:BB)(NYSE:BBRY) rallied this week, up almost 8%, after a series of interesting product announcements. New Chief Executive John Chen unveiled several new initiatives at the Mobile World Congress in Barcelona including a new Q20 model that brings back its “classic” keyboard and a cheaper Z3 BlackBerry that will cost under US$200. The company is also releasing BBM for enterprise users and revamping its BlackBerry Enterprise Server. These new initiatives suggest that Mr. Chen’s focus is squarely on the corporate
Samsung Galaxy S® II Software Upgrade Samsung has released a software update for the C Spire Samsung Galaxy S II(SCH-R760), OS Jelly Bean software version 4.1.2 version build GB28. Please follow the instructions below to download and install Simple Upgrade Tool using your Windows PC. This software upgrade is only valid for the C Spire Samsung Galaxy S II (SCH-R760). It is incompatible with all other models. Requirements Computer Desktop/Laptop computer running either Microsoft Windows 7, Vista, or XP Currently, there is no support at this time for Apple computers All firewall & anti-virus programs should be disabled Administrative privileges required to download & install software including drivers An available USB port on the PC that supports 2.0 USB Mobile Device Fully charged battery Other USB data cable (included in Retail Box) Note: this is the same cable used to charge your device Direct connection of the USB cable to the computer's USB port is strongly advised. The use of a USB hub or docking station is not recommended. Your PC must be connected to a live internet connection to download the SimpleDL tool Back Up Your Information Important: This update was designed to simply upgrade the operating system of the device while leaving certain types of user data intact. This user data includes pictures, videos, messages and contacts. Certain settings, such as wallpaper and ringtone assignments, may be reset back to factory default. To be safe, it is best practice to always back up all data and assume that everything will be lost. Below you will find options to backup contacts, messages and help to reinstall third party applications. Note: When you sync to your Google Gmail and Exchange ActiveSync® accounts, you are backing up your information. Google Gmail and Exchange ActiveSync information on your device including contacts are stored remotely on the Google and Microsoft Exchange server. Contacts Save Contacts to SD Card Export to SD Card 1. From the Home screen, touch Contacts > Menu > More. 2. Touch Import/Export > Export to SD card. 3. Confirm export by selecting OK. Import to SD Card 1. From the Home screen, touch Contacts > Menu > More. 2. Touch Import/Export, then touch Import from SD card. 3. Confirm export by selecting OK.
http://tserverhq.com/teamspeak-3-server - The teamspeak 3 server or named among the connoisseurs too short TS3 server combines ingenious features with a tremendously narrow bandwidth. Even the earlier version, the TS2 server was popular with many. With the new TS3 server, users have many new features and enhanced features are available.
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NoSQL databases represent a development in enterprise application architecture, continuing the evolution of the past twenty years. In the 1990’s, vertically integrated applications gave way to client-server architectures, and more recently, client-server architectures gave way to three-tier web application architectures. In parallel, the demands of web-scale data analysis added map-reduce processing into the mix and data architects started eschewing transactional consistency in exchange for incremental scalability and large-scale distribution. The NoSQL movement emerged out of this second ecosystem. NoSQL is often characterized by what it’s not – depending on whom you ask, it’s either not only a SQL-based relational database management system or it’s simply not a SQL-based RDBMS. While those definitions explain what NoSQL is not, they do little to explain what NoSQL is. Consider the fundamentals that have guided data management for the past forty years. RDBMS systems and large-scale data management have been characterized by the transactional ACID properties of Atomicity, Consistency, Isolation, and Durability. In contrast, NoSQL is sometimes characterized by the BASE acronym: Basically Available: Use replication to reduce the likelihood of data unavailability and use sharding, or partitioning the data among many different storage servers, to make any remaining failures partial. The result is a system that is always available, even if subsets of the data become unavailable for short periods of time. Soft state: While ACID systems assume that data consistency is a hard requirement, NoSQL systems allow data to be inconsistent and relegate designing around such inconsistencies to application developers. Eventually consistent: Although applications must deal with instantaneous consistency, NoSQL systems ensure that at some future point in time the data assumes a consistent state. In contrast to ACID systems that enforce consistency at transaction commit, NoSQL guarantees consistency only at some undefined future time. NoSQL emerged as companies, such as Amazon, Google, LinkedIn and Twitter dealt with unprecedented data and operation volumes under tight latency constraints. Analyzing highvolume, real time data, such as web-site click streams, provides significant business advantage by harnessing unstructured and semi-structured data sources to create more business value. Traditional relational databases were not up to the task, so enterprises built upon a decade of research on Distributed Hash Tables (DHTs) and either conventional relational database systems or embedded key/value stores, such as Oracle’s Berkeley DB, to develop highly available, distributed key-value stores. Although some of the early NoSQL solutions built their systems atop existing relational database engines, they quickly realized that such systems were designed for SQL-based access patterns and latency demands that are quite different from those of NoSQL systems, so these same organizations began to develop brand new storage layers. In contrast, Oracle’s Berkeley DB product line was the original key/value store; Oracle Berkeley DB Java Edition has been in commercial use for over eight years. By using Oracle Berkeley DB Java Edition as the underlying storage engine beneath a NoSQL system, Oracle brings enterprise robustness, stability, and High Availability to the NoSQL landscape.
hardware as it became available. When that didn’t work, they tried to scale existing relational solutions by simplifying their database schema, de-normalizing the schema, relaxing durability and referential integrity, introducing various query caching layers, separating read-only from write-dedicated replicas, and, finally, data partitioning in an attempt to address these new requirements. Although each of these techniques extended the functionality of existing relational technologies, none fundamentally addressed the core limitations, and they all introduced additional overhead and technical tradeoffs. In other words, these were good band-aids but not cures. A major influence on the eventual design of NoSQL databases came from a dramatic shift in IT operations. When the majority of relational database technology was designed, the predominant model for hardware deployments involved buying large servers attached to dedicated storage area networks (SANs). Databases were designed with this model in mind: They expected there to be a single machine with the responsibility of managing the consistent state of the database on that system’s connected storage. In other words, databases managed local data in files and provided as much concurrent access as possible given the machine’s hardware limitations. Replication of data to scale concurrent access across multiple systems was generally unnecessary, as most systems met design goals with a single server and reliability goals with a hot stand-by ready to take over query processing in the event of master failure. Beyond simple failover replication, there were only a few options, and they were all predicated on this same notion of completely consistent centralized data management. Technologies such as two-phase commit and products such as Oracle’s RAC were available, but they were hard to manage, very expensive, and scaled to only a handful of machines. Other solutions available included logical SQL statement-level replication, single-master multi-replica log-based replication, and other home-grown approaches, all of which have serious limitations and generally introduce a lot of administrative and technical overhead. In the end, it was the common architecture and design assumptions underlying most relational databases that failed to address the scalability, latency, and availability requirements of many of the largest sites during the massive growth of the Internet. Given that databases were centralized and generally running on an organization’s most expensive hardware containing its most precious information, it made sense to create an organizational structure that required at least a 1:1 ratio of database administrators to database systems to protect and nurture that investment. This, too, was not easy to scale, was costly, and could slow innovation. A growing number of companies were still hitting the scalability and performance wall even when using the best practices and the most advanced technologies of the time. Database architects had sacrificed many of the most central aspects of a relational database, such as joins and fully consistent data, while introducing many complex and fragile pieces into the operations puzzle. Schema devolved from many interrelated fully expressed tables to something much more like a simple key/value look-up. Deployments of expensive servers were not able to keep up with demand. At this point these companies had taken relational databases so far outside their intended use cases that it was no wonder that they were unable to meet performance requirements. It quickly became clear to them that they could do much better by building something in-house that was tailored to their particular workloads. These in-house custom solutions are the inspiration behind the many NoSQL products we now see on the market.
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Download from http://www.esri.com/software/arcgis/arcgis-for-autocad/index.html 1. Open the folder with the unzipped setup files. 2. Right-click setup.exe and click Run as Administrator. 3. In the Welcome to the ArcGIS for AutoCAD 250 Setup dialog box, click Next. 4. Follow installation instructions on the screen. Install - once on your pc 1. Type “netload” into the AutoCAD Command Line and press enter. Load Program in AutoCAD - load at each use* 2. In the Choose .NET Assembly dialog, browse to locate ArcGISForAutoCAD.dll in C:\Program Files\ArcGIS for AutoCAD250 *NOTE: You’ll need to ‘netload’ the .dll every time AutoCAD is started (repeat steps above). However, the location of the map service and/or ESRI maps will be saved for you. 4. ArcGIS for AutoCAD will be located in a ribbon at the top of the screen: 1. Select the Add Map button from the Add panel in the ArcGIS for AutoCAD tab: Add a Map Service 2. In the Add Map Service dialog - Server URL copy/paste this link: http://giswww.westchestergov.com/arcgis/services Leave User Name and Password blank and press Connect – at every use 3. For Map Name, click the drop-down arrow, select a map - then Press Add More Map Services: MappingWestchesterCounty_AerialPhoto1947 Example – Digital Surface Model: Settings Map Services displays a panel where you can configure settings for the added maps: Zoom to extent, send to back, remove, switch to a different service previously added, etc.: 1. Select the Map Features button from the Identify tool in the ArcGIS for AutoCAD tab. Identify a Map Feature 2. Select the first and second corners surrounding the feature of interest. 3. An Identify dialog box will list those features within the selected area. Select a feature on the left to display its attributes on the right:
[217 Pages Report] Video Surveillance As A Service (VSaaS) Market segments the global market on the basis of Components (Storage, Camera, Server, Analytics, Video), Service (Managed, Hosted, Hybrid), Application & by Geography