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  • The Ins and Outs of Effective Smart Grid Data Management

    - by caroline.yu
    Oracle Utilities and Accenture recently sponsored a one-hour Web cast entitled, "The Ins and Outs of Effective Smart Grid Data Management." Oracle and Accenture created this Web cast to help utilities better understand the types of data collected over smart grid networks and the issues associated with mapping out a coherent information management strategy. The Web cast also addressed important points that utilities must consider with the imminent flood of data that both present and next-generation smart grid components will generate. The three speakers, including Oracle Utilities' Brad Williams, focused on the key factors associated with taking the millions of data points captured in real time and implementing the strategies, frameworks and technologies that enable utilities to process, store, analyze, visualize, integrate, transport and transform data into the information required to deliver targeted business benefits. The Web cast replay is available here. The Web cast slides are available here.

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  • The Benefits of Smart Grid Business Software

    - by Sylvie MacKenzie, PMP
    Smart Grid Background What Are Smart Grids?Smart Grids use computer hardware and software, sensors, controls, and telecommunications equipment and services to: Link customers to information that helps them manage consumption and use electricity wisely. Enable customers to respond to utility notices in ways that help minimize the duration of overloads, bottlenecks, and outages. Provide utilities with information that helps them improve performance and control costs. What Is Driving Smart Grid Development? Environmental ImpactSmart Grid development is picking up speed because of the widespread interest in reducing the negative impact that energy use has on the environment. Smart Grids use technology to drive efficiencies in transmission, distribution, and consumption. As a result, utilities can serve customers’ power needs with fewer generating plants, fewer transmission and distribution assets,and lower overall generation. With the possible exception of wind farm sprawl, landscape preservation is one obvious benefit. And because most generation today results in greenhouse gas emissions, Smart Grids reduce air pollution and the potential for global climate change.Smart Grids also more easily accommodate the technical difficulties of integrating intermittent renewable resources like wind and solar into the grid, providing further greenhouse gas reductions. CostsThe ability to defer the cost of plant and grid expansion is a major benefit to both utilities and customers. Utilities do not need to use as many internal resources for traditional infrastructure project planning and management. Large T&D infrastructure expansion costs are not passed on to customers.Smart Grids will not eliminate capital expansion, of course. Transmission corridors to connect renewable generation with customers will require major near-term expenditures. Additionally, in the future, electricity to satisfy the needs of population growth and additional applications will exceed the capacity reductions available through the Smart Grid. At that point, expansion will resume—but with greater overall T&D efficiency based on demand response, load control, and many other Smart Grid technologies and business processes. Energy efficiency is a second area of Smart Grid cost saving of particular relevance to customers. The timely and detailed information Smart Grids provide encourages customers to limit waste, adopt energy-efficient building codes and standards, and invest in energy efficient appliances. Efficiency may or may not lower customer bills because customer efficiency savings may be offset by higher costs in generation fuels or carbon taxes. It is clear, however, that bills will be lower with efficiency than without it. Utility Operations Smart Grids can serve as the central focus of utility initiatives to improve business processes. Many utilities have long “wish lists” of projects and applications they would like to fund in order to improve customer service or ease staff’s burden of repetitious work, but they have difficulty cost-justifying the changes, especially in the short term. Adding Smart Grid benefits to the cost/benefit analysis frequently tips the scales in favor of the change and can also significantly reduce payback periods.Mobile workforce applications and asset management applications work together to deploy assets and then to maintain, repair, and replace them. Many additional benefits result—for instance, increased productivity and fuel savings from better routing. Similarly, customer portals that provide customers with near-real-time information can also encourage online payments, thus lowering billing costs. Utilities can and should include these cost and service improvements in the list of Smart Grid benefits. What Is Smart Grid Business Software? Smart Grid business software gathers data from a Smart Grid and uses it improve a utility’s business processes. Smart Grid business software also helps utilities provide relevant information to customers who can then use it to reduce their own consumption and improve their environmental profiles. Smart Grid Business Software Minimizes the Impact of Peak Demand Utilities must size their assets to accommodate their highest peak demand. The higher the peak rises above base demand: The more assets a utility must build that are used only for brief periods—an inefficient use of capital. The higher the utility’s risk profile rises given the uncertainties surrounding the time needed for permitting, building, and recouping costs. The higher the costs for utilities to purchase supply, because generators can charge more for contracts and spot supply during high-demand periods. Smart Grids enable a variety of programs that reduce peak demand, including: Time-of-use pricing and critical peak pricing—programs that charge customers more when they consume electricity during peak periods. Pilot projects indicate that these programs are successful in flattening peaks, thus ensuring better use of existing T&D and generation assets. Direct load control, which lets utilities reduce or eliminate electricity flow to customer equipment (such as air conditioners). Contracts govern the terms and conditions of these turn-offs. Indirect load control, which signals customers to reduce the use of on-premises equipment for contractually agreed-on time periods. Smart Grid business software enables utilities to impose penalties on customers who do not comply with their contracts. Smart Grids also help utilities manage peaks with existing assets by enabling: Real-time asset monitoring and control. In this application, advanced sensors safely enable dynamic capacity load limits, ensuring that all grid assets can be used to their maximum capacity during peak demand periods. Real-time asset monitoring and control applications also detect the location of excessive losses and pinpoint need for mitigation and asset replacements. As a result, utilities reduce outage risk and guard against excess capacity or “over-build”. Better peak demand analysis. As a result: Distribution planners can better size equipment (e.g. transformers) to avoid over-building. Operations engineers can identify and resolve bottlenecks and other inefficiencies that may cause or exacerbate peaks. As above, the result is a reduction in the tendency to over-build. Supply managers can more closely match procurement with delivery. As a result, they can fine-tune supply portfolios, reducing the tendency to over-contract for peak supply and reducing the need to resort to spot market purchases during high peaks. Smart Grids can help lower the cost of remaining peaks by: Standardizing interconnections for new distributed resources (such as electricity storage devices). Placing the interconnections where needed to support anticipated grid congestion. Smart Grid Business Software Lowers the Cost of Field Services By processing Smart Grid data through their business software, utilities can reduce such field costs as: Vegetation management. Smart Grids can pinpoint momentary interruptions and tree-caused outages. Spatial mash-up tools leverage GIS models of tree growth for targeted vegetation management. This reduces the cost of unnecessary tree trimming. Service vehicle fuel. Many utility service calls are “false alarms.” Checking meter status before dispatching crews prevents many unnecessary “truck rolls.” Similarly, crews use far less fuel when Smart Grid sensors can pinpoint a problem and mobile workforce applications can then route them directly to it. Smart Grid Business Software Ensures Regulatory Compliance Smart Grids can ensure compliance with private contracts and with regional, national, or international requirements by: Monitoring fulfillment of contract terms. Utilities can use one-hour interval meters to ensure that interruptible (“non-core”) customers actually reduce or eliminate deliveries as required. They can use the information to levy fines against contract violators. Monitoring regulations imposed on customers, such as maximum use during specific time periods. Using accurate time-stamped event history derived from intelligent devices distributed throughout the smart grid to monitor and report reliability statistics and risk compliance. Automating business processes and activities that ensure compliance with security and reliability measures (e.g. NERC-CIP 2-9). Grid Business Software Strengthens Utilities’ Connection to Customers While Reducing Customer Service Costs During outages, Smart Grid business software can: Identify outages more quickly. Software uses sensors to pinpoint outages and nested outage locations. They also permit utilities to ensure outage resolution at every meter location. Size outages more accurately, permitting utilities to dispatch crews that have the skills needed, in appropriate numbers. Provide updates on outage location and expected duration. This information helps call centers inform customers about the timing of service restoration. Smart Grids also facilitates display of outage maps for customer and public-service use. Smart Grids can significantly reduce the cost to: Connect and disconnect customers. Meters capable of remote disconnect can virtually eliminate the costs of field crews and vehicles previously required to change service from the old to the new residents of a metered property or disconnect customers for nonpayment. Resolve reports of voltage fluctuation. Smart Grids gather and report voltage and power quality data from meters and grid sensors, enabling utilities to pinpoint reported problems or resolve them before customers complain. Detect and resolve non-technical losses (e.g. theft). Smart Grids can identify illegal attempts to reconnect meters or to use electricity in supposedly vacant premises. They can also detect theft by comparing flows through delivery assets with billed consumption. Smart Grids also facilitate outreach to customers. By monitoring and analyzing consumption over time, utilities can: Identify customers with unusually high usage and contact them before they receive a bill. They can also suggest conservation techniques that might help to limit consumption. This can head off “high bill” complaints to the contact center. Note that such “high usage” or “additional charges apply because you are out of range” notices—frequently via text messaging—are already common among mobile phone providers. Help customers identify appropriate bill payment alternatives (budget billing, prepayment, etc.). Help customers find and reduce causes of over-consumption. There’s no waiting for bills in the mail before they even understand there is a problem. Utilities benefit not just through improved customer relations but also through limiting the size of bills from customers who might struggle to pay them. Where permitted, Smart Grids can open the doors to such new utility service offerings as: Monitoring properties. Landlords reduce costs of vacant properties when utilities notify them of unexpected energy or water consumption. Utilities can perform similar services for owners of vacation properties or the adult children of aging parents. Monitoring equipment. Power-use patterns can reveal a need for equipment maintenance. Smart Grids permit utilities to alert owners or managers to a need for maintenance or replacement. Facilitating home and small-business networks. Smart Grids can provide a gateway to equipment networks that automate control or let owners access equipment remotely. They also facilitate net metering, offering some utilities a path toward involvement in small-scale solar or wind generation. Prepayment plans that do not need special meters. Smart Grid Business Software Helps Customers Control Energy Costs There is no end to the ways Smart Grids help both small and large customers control energy costs. For instance: Multi-premises customers appreciate having all meters read on the same day so that they can more easily compare consumption at various sites. Customers in competitive regions can match their consumption profile (detailed via Smart Grid data) with specific offerings from competitive suppliers. Customers seeing inexplicable consumption patterns and power quality problems may investigate further. The result can be discovery of electrical problems that can be resolved through rewiring or maintenance—before more serious fires or accidents happen. Smart Grid Business Software Facilitates Use of Renewables Generation from wind and solar resources is a popular alternative to fossil fuel generation, which emits greenhouse gases. Wind and solar generation may also increase energy security in regions that currently import fossil fuel for use in generation. Utilities face many technical issues as they attempt to integrate intermittent resource generation into traditional grids, which traditionally handle only fully dispatchable generation. Smart Grid business software helps solves many of these issues by: Detecting sudden drops in production from renewables-generated electricity (wind and solar) and automatically triggering electricity storage and smart appliance response to compensate as needed. Supporting industry-standard distributed generation interconnection processes to reduce interconnection costs and avoid adding renewable supplies to locations already subject to grid congestion. Facilitating modeling and monitoring of locally generated supply from renewables and thus helping to maximize their use. Increasing the efficiency of “net metering” (through which utilities can use electricity generated by customers) by: Providing data for analysis. Integrating the production and consumption aspects of customer accounts. During non-peak periods, such techniques enable utilities to increase the percent of renewable generation in their supply mix. During peak periods, Smart Grid business software controls circuit reconfiguration to maximize available capacity. Conclusion Utility missions are changing. Yesterday, they focused on delivery of reasonably priced energy and water. Tomorrow, their missions will expand to encompass sustainable use and environmental improvement.Smart Grids are key to helping utilities achieve this expanded mission. But they come at a relatively high price. Utilities will need to invest heavily in new hardware, software, business process development, and staff training. Customer investments in home area networks and smart appliances will be large. Learning to change the energy and water consumption habits of a lifetime could ultimately prove even more formidable tasks.Smart Grid business software can ease the cost and difficulties inherent in a needed transition to a more flexible, reliable, responsive electricity grid. Justifying its implementation, however, requires a full understanding of the benefits it brings—benefits that can ultimately help customers, utilities, communities, and the world address global issues like energy security and climate change while minimizing costs and maximizing customer convenience. This white paper is available for download here. For further information about Oracle's Primavera Solutions for Utilities, please read our Utilities e-book.

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  • Macbook Pro - Randomly sleeps and won't wake up

    - by James
    All, I have a Macbook Pro 13" (mid 2009) that has had a long time issues which seems to be getting worse. Occasionally, I will go to wake the computer with the keyboard and can't wake it. The HDD spins up, the light on the front of the computer stops blinking, but as soon as it seems like the display should light up, the HDD stops and the light begins blinking again. More rarely, the computer will suddenly sleep while I am using it and then enters the same sleep loop. The only way to resume working on the computer is to wait. Doing a hard restart just puts it right back into the 'sleep loop.' Here is an excerpt from kernel.log showing the laptops apparent narcolepsy: Jun 5 22:20:40 james-hales-macbook-pro kernel[0]: Wake reason: OHC1 Jun 5 22:20:40 james-hales-macbook-pro kernel[0]: Previous Sleep Cause: 5 Jun 5 22:20:40 james-hales-macbook-pro kernel[0]: The USB device Apple Internal Keyboard / Trackpad (Port 6 of Hub at 0x4000000) may have caused a wake by issuing a remote wakeup (2) Jun 5 22:20:40 james-hales-macbook-pro kernel[0]: HID tickle 31 ms Jun 5 22:20:41 james-hales-macbook-pro kernel[0]: 00000000 00000020 NVEthernet::setLinkStatus - not Active Jun 5 22:20:45 james-hales-macbook-pro kernel[0]: MacAuthEvent en1 Auth result for: 20:4e:7f:48:c0:ef MAC AUTH succeeded Jun 5 22:20:45 james-hales-macbook-pro kernel[0]: wlEvent: en1 en1 Link UP Jun 5 22:20:45 james-hales-macbook-pro kernel[0]: AirPort: Link Up on en1 Jun 5 22:20:45 james-hales-macbook-pro kernel[0]: en1: BSSID changed to 20:4e:7f:48:c0:ef Jun 5 22:20:46 james-hales-macbook-pro kernel[0]: AirPort: RSN handshake complete on en1 Jun 5 22:20:48 james-hales-macbook-pro kernel[0]: 00000000 00000020 NVEthernet::setLinkStatus - not Active Jun 5 22:20:54 james-hales-macbook-pro kernel[0]: Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: Wake reason: OHC1 Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: Previous Sleep Cause: 5 Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: The USB device Apple Internal Keyboard / Trackpad (Port 6 of Hub at 0x4000000) may have caused a wake by issuing a remote wakeup (2) Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: wlEvent: en1 en1 Link DOWN Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: AirPort: Link Down on en1. Reason 4 (Disassociated due to inactivity). Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: HID tickle 26 ms Jun 5 22:20:55 james-hales-macbook-pro kernel[0]: 00000000 00000020 NVEthernet::setLinkStatus - not Active Jun 5 22:20:58 james-hales-macbook-pro kernel[0]: MacAuthEvent en1 Auth result for: 20:4e:7f:48:c0:ef MAC AUTH succeeded Jun 5 22:20:58 james-hales-macbook-pro kernel[0]: wlEvent: en1 en1 Link UP Jun 5 22:20:58 james-hales-macbook-pro kernel[0]: AirPort: Link Up on en1 Jun 5 22:20:58 james-hales-macbook-pro kernel[0]: en1: BSSID changed to 20:4e:7f:48:c0:ef Jun 5 22:20:58 james-hales-macbook-pro kernel[0]: AirPort: RSN handshake complete on en1 Jun 5 22:21:02 james-hales-macbook-pro kernel[0]: 00000000 00000020 NVEthernet::setLinkStatus - not Active Jun 5 22:21:08 james-hales-macbook-pro kernel[0]: I have tried reseting the SMC and reinstalling Lion (short of erasing and installing) to no avail. The Genius bar has insisted that the problem would be resolved by reinstalling Lion (which they did, but didn't fix anything, still insisting...). Please don't say "logic board." Thoughts?

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  • LLBLGen Pro feature highlights: automatic element name construction

    - by FransBouma
    (This post is part of a series of posts about features of the LLBLGen Pro system) One of the things one might take for granted but which has a huge impact on the time spent in an entity modeling environment is the way the system creates names for elements out of the information provided, in short: automatic element name construction. Element names are created in both directions of modeling: database first and model first and the more names the system can create for you without you having to rename them, the better. LLBLGen Pro has a rich, fine grained system for creating element names out of the meta-data available, which I'll describe more in detail below. First the model element related element naming features are highlighted, in the section Automatic model element naming features and after that I'll go more into detail about the relational model element naming features LLBLGen Pro has to offer in the section Automatic relational model element naming features. Automatic model element naming features When working database first, the element names in the model, e.g. entity names, entity field names and so on, are in general determined from the relational model element (e.g. table, table field) they're mapped on, as the model elements are reverse engineered from these relational model elements. It doesn't take rocket science to automatically name an entity Customer if the entity was created after reverse engineering a table named Customer. It gets a little trickier when the entity which was created by reverse engineering a table called TBL_ORDER_LINES has to be named 'OrderLine' automatically. Automatic model element naming also takes into effect with model first development, where some settings are used to provide you with a default name, e.g. in the case of navigator name creation when you create a new relationship. The features below are available to you in the Project Settings. Open Project Settings on a loaded project and navigate to Conventions -> Element Name Construction. Strippers! The above example 'TBL_ORDER_LINES' shows that some parts of the table name might not be needed for name creation, in this case the 'TBL_' prefix. Some 'brilliant' DBAs even add suffixes to table names, fragments you might not want to appear in the entity names. LLBLGen Pro offers you to define both prefix and suffix fragments to strip off of table, view, stored procedure, parameter, table field and view field names. In the example above, the fragment 'TBL_' is a good candidate for such a strip pattern. You can specify more than one pattern for e.g. the table prefix strip pattern, so even a really messy schema can still be used to produce clean names. Underscores Be Gone Another thing you might get rid of are underscores. After all, most naming schemes for entities and their classes use PasCal casing rules and don't allow for underscores to appear. LLBLGen Pro can automatically strip out underscores for you. It's an optional feature, so if you like the underscores, you're not forced to see them go: LLBLGen Pro will leave them alone when ordered to to so. PasCal everywhere... or not, your call LLBLGen Pro can automatically PasCal case names on word breaks. It determines word breaks in a couple of ways: a space marks a word break, an underscore marks a word break and a case difference marks a word break. It will remove spaces in all cases, and based on the underscore removal setting, keep or remove the underscores, and upper-case the first character of a word break fragment, and lower case the rest. Say, we keep the defaults, which is remove underscores and PasCal case always and strip the TBL_ fragment, we get with our example TBL_ORDER_LINES, after stripping TBL_ from the table name two word fragments: ORDER and LINES. The underscores are removed, the first character of each fragment is upper-cased, the rest lower-cased, so this results in OrderLines. Almost there! Pluralization and Singularization In general entity names are singular, like Customer or OrderLine so LLBLGen Pro offers a way to singularize the names. This will convert OrderLines, the result we got after the PasCal casing functionality, into OrderLine, exactly what we're after. Show me the patterns! There are other situations in which you want more flexibility. Say, you have an entity Customer and an entity Order and there's a foreign key constraint defined from the target of Order and the target of Customer. This foreign key constraint results in a 1:n relationship between the entities Customer and Order. A relationship has navigators mapped onto the relationship in both entities the relationship is between. For this particular relationship we'd like to have Customer as navigator in Order and Orders as navigator in Customer, so the relationship becomes Customer.Orders 1:n Order.Customer. To control the naming of these navigators for the various relationship types, LLBLGen Pro defines a set of patterns which allow you, using macros, to define how the auto-created navigator names will look like. For example, if you rather have Customer.OrderCollection, you can do so, by changing the pattern from {$EndEntityName$P} to {$EndEntityName}Collection. The $P directive makes sure the name is pluralized, which is not what you want if you're going for <EntityName>Collection, hence it's removed. When working model first, it's a given you'll create foreign key fields along the way when you define relationships. For example, you've defined two entities: Customer and Order, and they have their fields setup properly. Now you want to define a relationship between them. This will automatically create a foreign key field in the Order entity, which reflects the value of the PK field in Customer. (No worries if you hate the foreign key fields in your classes, on NHibernate and EF these can be hidden in the generated code if you want to). A specific pattern is available for you to direct LLBLGen Pro how to name this foreign key field. For example, if all your entities have Id as PK field, you might want to have a different name than Id as foreign key field. In our Customer - Order example, you might want to have CustomerId instead as foreign key name in Order. The pattern for foreign key fields gives you that freedom. Abbreviations... make sense of OrdNr and friends I already described word breaks in the PasCal casing paragraph, how they're used for the PasCal casing in the constructed name. Word breaks are used for another neat feature LLBLGen Pro has to offer: abbreviation support. Burt, your friendly DBA in the dungeons below the office has a hate-hate relationship with his keyboard: he can't stand it: typing is something he avoids like the plague. This has resulted in tables and fields which have names which are very short, but also very unreadable. Example: our TBL_ORDER_LINES example has a lovely field called ORD_NR. What you would like to see in your fancy new OrderLine entity mapped onto this table is a field called OrderNumber, not a field called OrdNr. What you also like is to not have to rename that field manually. There are better things to do with your time, after all. LLBLGen Pro has you covered. All it takes is to define some abbreviation - full word pairs and during reverse engineering model elements from tables/views, LLBLGen Pro will take care of the rest. For the ORD_NR field, you need two values: ORD as abbreviation and Order as full word, and NR as abbreviation and Number as full word. LLBLGen Pro will now convert every word fragment found with the word breaks which matches an abbreviation to the given full word. They're case sensitive and can be found in the Project Settings: Navigate to Conventions -> Element Name Construction -> Abbreviations. Automatic relational model element naming features Not everyone works database first: it may very well be the case you start from scratch, or have to add additional tables to an existing database. For these situations, it's key you have the flexibility that you can control the created table names and table fields without any work: let the designer create these names based on the entity model you defined and a set of rules. LLBLGen Pro offers several features in this area, which are described in more detail below. These features are found in Project Settings: navigate to Conventions -> Model First Development. Underscores, welcome back! Not every database is case insensitive, and not every organization requires PasCal cased table/field names, some demand all lower or all uppercase names with underscores at word breaks. Say you create an entity model with an entity called OrderLine. You work with Oracle and your organization requires underscores at word breaks: a table created from OrderLine should be called ORDER_LINE. LLBLGen Pro allows you to do that: with a simple checkbox you can order LLBLGen Pro to insert an underscore at each word break for the type of database you're working with: case sensitive or case insensitive. Checking the checkbox Insert underscore at word break case insensitive dbs will let LLBLGen Pro create a table from the entity called Order_Line. Half-way there, as there are still lower case characters there and you need all caps. No worries, see below Casing directives so everyone can sleep well at night For case sensitive databases and case insensitive databases there is one setting for each of them which controls the casing of the name created from a model element (e.g. a table created from an entity definition using the auto-mapping feature). The settings can have the following values: AsProjectElement, AllUpperCase or AllLowerCase. AsProjectElement is the default, and it keeps the casing as-is. In our example, we need to get all upper case characters, so we select AllUpperCase for the setting for case sensitive databases. This will produce the name ORDER_LINE. Sequence naming after a pattern Some databases support sequences, and using model-first development it's key to have sequences, when needed, to be created automatically and if possible using a name which shows where they're used. Say you have an entity Order and you want to have the PK values be created by the database using a sequence. The database you're using supports sequences (e.g. Oracle) and as you want all numeric PK fields to be sequenced, you have enabled this by the setting Auto assign sequences to integer pks. When you're using LLBLGen Pro's auto-map feature, to create new tables and constraints from the model, it will create a new table, ORDER, based on your settings I previously discussed above, with a PK field ID and it also creates a sequence, SEQ_ORDER, which is auto-assigns to the ID field mapping. The name of the sequence is created by using a pattern, defined in the Model First Development setting Sequence pattern, which uses plain text and macros like with the other patterns previously discussed. Grouping and schemas When you start from scratch, and you're working model first, the tables created by LLBLGen Pro will be in a catalog and / or schema created by LLBLGen Pro as well. If you use LLBLGen Pro's grouping feature, which allows you to group entities and other model elements into groups in the project (described in a future blog post), you might want to have that group name reflected in the schema name the targets of the model elements are in. Say you have a model with a group CRM and a group HRM, both with entities unique for these groups, e.g. Employee in HRM, Customer in CRM. When auto-mapping this model to create tables, you might want to have the table created for Employee in the HRM schema but the table created for Customer in the CRM schema. LLBLGen Pro will do just that when you check the setting Set schema name after group name to true (default). This gives you total control over where what is placed in the database from your model. But I want plural table names... and TBL_ prefixes! For now we follow best practices which suggest singular table names and no prefixes/suffixes for names. Of course that won't keep everyone happy, so we're looking into making it possible to have that in a future version. Conclusion LLBLGen Pro offers a variety of options to let the modeling system do as much work for you as possible. Hopefully you enjoyed this little highlight post and that it has given you new insights in the smaller features available to you in LLBLGen Pro, ones you might not have thought off in the first place. Enjoy!

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  • Smart Help with UPK

    - by [email protected]
    A short lesson on how awesome Smart Help is. In Oracle UPK speak, there are targeted and non-targeted applications. Targeted applications are Oracle EBS, PeopleSoft, Siebel, JD Edwards, SAP and a few others. Non-targeted applications are either custom built or other third party off the shelf applications. For most targeted applications you'll see better object recognition (during recording) and also Help Integration for that application. Help integration means that someone technical modifies the help link in your application to call up the UPK content that has been created. If you have seen this presented before, this is usually where the term context sensitive help is mentioned and the Do It mode shows off. The fact that UPK builds context sensitive help for its targeted applications automatically is awesome enough, but there is a whole new world out there and it's called "custom and\or third party apps." For the purposes of Smart Help and this discussion, I'm talking about the browser based applications. How does UPK support these apps? It used to be that you had to have your vendor try to modify the Help link to point to UPK or if your company had control over the applications configuration menus, then you get someone on your team to modify this for you. But as you start to use UPK for more than one, two or three applications, the administration of this starts to become daunting. Multiple administrators, multiple player packages, multiple call points, multiple break points, help doesn't always work the same way for every application (picture the black white infomercial with an IT person trying to configure a bunch of wires or something funny like that). Introducing Smart Help! (in color of course, new IT person, probably wearing a blue shirt and smiling). Smart help eliminates the need to configure multiple browser help integration points, and adds a icon to the users browser itself. You're using your browser to read this now correct? Look up at the icons on your browser, you have the home link icon, print icon, maybe an RSS feed icon. Smart Help is icon that gets added to the users browser just like the others. When you click it, it first recognizes which application you're in and then finds the UPK created material for you and returns the best possible match, for (hold on to your seat now) both targeted and non-targeted applications (browser based applications). But wait, there's more. It does this automatically! You don't have to do anything! All you have to do is record content, UPK and Smart Help do the rest! This technology is not new. There are customers out there today that use this for as many as six applications! The real hero here is SMART MATCH. Smart match is the technology that's used to determine which application you're in and where you are when you click on Smart Help. We'll save that for a one-on-one conversation. Like most other awesome features of UPK, it ships with the product. All you have to do is turn it on. To learn more about Smart Help, Smart Match, Targeted and Non-Targeted applications, contact your UPK Sales Consultant or me directly at [email protected]

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  • WD1000FYPS harddrive is marked 0 mb in 3ware (and no SMART)

    - by osgx
    After reboot my SATA 1TB WD1000FYPS (previously is was "Drive error") is marked 0 mb in 3ware web gui. Complete message: Available Drives (Controller ID 0) Port 1 WDC WD1000FYPS-01ZKB0 0.00 MB NOT SUPPORTED [Remove Drive] SMART gives me only Device Model and ATA protocol version 1 (not 7-8 as it must be for SATA) What does it mean? Just before reboot, when is was marked only with "Device Error", smart was: Device Model: WDC WD1000FYPS-01ZKB0 Serial Number: WD-WCASJ1130*** Firmware Version: 02.01B01 User Capacity: 1,000,204,886,016 bytes Device is: Not in smartctl database [for details use: -P showall] ATA Version is: 8 ATA Standard is: Exact ATA specification draft version not indicated Local Time is: Sun Mar 7 18:47:35 2010 MSK SMART support is: Available - device has SMART capability. SMART support is: Enabled SMART overall-health self-assessment test result: PASSED SMART Attributes Data Structure revision number: 16 Vendor Specific SMART Attributes with Thresholds: ID# ATTRIBUTE_NAME FLAG VALUE WORST THRESH TYPE UPDATED WHEN_FAILED RAW_VALUE 1 Raw_Read_Error_Rate 0x000f 200 200 051 Pre-fail Always - 0 3 Spin_Up_Time 0x0003 188 186 021 Pre-fail Always - 7591 4 Start_Stop_Count 0x0032 100 100 000 Old_age Always - 229 5 Reallocated_Sector_Ct 0x0033 199 199 140 Pre-fail Always - 3 7 Seek_Error_Rate 0x000e 193 193 000 Old_age Always - 125 9 Power_On_Hours 0x0032 078 078 000 Old_age Always - 16615 10 Spin_Retry_Count 0x0012 100 100 000 Old_age Always - 0 11 Calibration_Retry_Count 0x0012 100 253 000 Old_age Always - 0 12 Power_Cycle_Count 0x0032 100 100 000 Old_age Always - 77 192 Power-Off_Retract_Count 0x0032 198 198 000 Old_age Always - 1564 193 Load_Cycle_Count 0x0032 146 146 000 Old_age Always - 164824 194 Temperature_Celsius 0x0022 117 100 000 Old_age Always - 35 196 Reallocated_Event_Count 0x0032 199 199 000 Old_age Always - 1 197 Current_Pending_Sector 0x0012 200 200 000 Old_age Always - 0 198 Offline_Uncorrectable 0x0010 200 200 000 Old_age Offline - 0 199 UDMA_CRC_Error_Count 0x003e 200 200 000 Old_age Always - 0 200 Multi_Zone_Error_Rate 0x0008 200 200 000 Old_age Offline - 0 What can be wrong with he? Can it be restored? PS new smart is === START OF INFORMATION SECTION === Device Model: WDC WD1000FYPS-01ZKB0 Serial Number: [No Information Found] Firmware Version: [No Information Found] Device is: Not in smartctl database [for details use: -P showall] ATA Version is: 1 ATA Standard is: Exact ATA specification draft version not indicated Local Time is: Mon Mar 8 00:29:44 2010 MSK SMART is only available in ATA Version 3 Revision 3 or greater. We will try to proceed in spite of this. SMART support is: Ambiguous - ATA IDENTIFY DEVICE words 82-83 don't show if SMART supported. Checking for SMART support by trying SMART ENABLE command. Command failed, ata.status=(0x00), ata.command=(0x51), ata.flags=(0x01) Error SMART Enable failed: Input/output error SMART ENABLE failed - this establishes that this device lacks SMART functionality. A mandatory SMART command failed: exiting. To continue, add one or more '-T permissive' options. PPS There was a rapid grow of " 192 Power-Off_Retract_Count " before dying. The hard was used in raid, with several hards from the same fabric packaging box (close id's). The hard drives were placed identically. Rapid means almost linear grow from 300 to 1700 in 6-7 hours. Maximal temperature was 41C. (thanks to munin's smart monitoring)

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  • Praise for Europe's Smart Metering & Conservation Efforts

    - by caroline.yu
    Recently, a writer at the Home Energy Team praised the UK for its efforts towards smart metering and energy conservation, with an article entitled UK Blazing A Trail With Smart Metering At Home? The article highlighted that the Department of Energy and Climate Change has announced that smart metering will be introduced in the next decade and that all UK households will have smart meters by the year 2020. In fact, the UK is not the only country striving to achieve carbon reduction targets, as many of its European counterparts have begun to take positive steps towards tackling the issue of energy conservation by implementing innovative new metering and billing technologies as well as promoting alternative energy solutions, such as wind and solar power. Since 1997, the states of the European Union, including France, Germany and Spain, have been working towards achieving a target of 12 percent renewable energy electricity by 2010. Germany in particular has made a significant achievement so far, having surpassed the target early in 2007. This success is largely due to the German Renewable Energy Act (EEG), which promoted the use of renewable energy. Recently, analysis from the European Wind Energy Association (EWEA) found that 21 of the EU Member States are meeting or exceeding their national target to achieve 20 percent renewable energy by 2020. However, six states - Belgium, Italy, Luxembourg, Malta, Bulgaria and Denmark - say they will not manage to reach their target through domestic action alone. Bulgaria and Denmark believe that with fresh national initiatives they could meet or exceed their targets, but others, including Italy, may need to import renewable energy from neighboring non-EU countries. Top achievers, according to the EWEA report, are Spain, which believes its renewable energy will reach 22.7 percent by 2020, as well as Germany, Estonia, Greece, Ireland, Poland, Slovakia and Sweden, who will all exceed their targets. "Importantly, the way that this renewable energy is controlled and distributed must be addressed in order to ensure its success," said Bastian Fischer, vice president and general manager EMEA, Oracle Utilities. "A smart gird infrastructure can enable utilities to deal with load distribution in times of increased need and ensure power is always available from these means. A smart grid also underpins the success of metering and billing technologies, such as smart metering, and allows utilities to deal with increased usage data and provide accurate billing." Outside of Europe, Australia has made significant steps towards improving water conservation. The Australian Department of Sustainability and Environment took some of the recent advancements made in the energy sector, including new metering and billing solutions, and applied them to the water industry, enhancing customer service and reducing consumption as a result. The adoption of smart metering in Europe is mainly driven by regulation, but significant technological improvements are being made the world over to change the way we use all kinds of energy. However, the developing markets are lagging behind. One of the primary reasons for this is the lack of infrastructure in place to use as a foundation for setting up energy-saving solutions, which is slowing the adoption of technologies such as smart meters. However, these countries do benefit from fewer outdated infrastructure and legacy systems, which is often cited by others as a difficult barrier to deploying new solutions. As a result, some countries should find new technologies easier to implement and adapt to in the immediate future, without this roadblock.

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  • What's So Smart About Oracle Exadata Smart Flash Cache?

    - by kimberly.billings
    Want to know what's so "smart" about Oracle Exadata Smart Flash Cache? This three minute video explains how Oracle Exadata Smart Flash Cache helps solve the random I/O bottleneck challenge and delivers extreme performance for consolidated database applications. Exadata Smart Flash Cache is a feature of the Sun Oracle Database Machine. With it, you get ten times faster I/O response time and use ten times fewer disks for business applications from Oracle and third-party providers. Read the whitepaper for more information. var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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  • How to enable SMART?

    - by Pratik Koirala
    I want to conduct a SMART test on my drive but it was disabled. So, i used sudo smartctl -s on /dev/sda but the result was smartctl 5.41 2011-06-09 r3365 [i686-linux-3.2.0-26-generic] (local build) Copyright (C) 2002-11 by Bruce Allen, http://smartmontools.sourceforge.net === START OF ENABLE/DISABLE COMMANDS SECTION === Error SMART Enable failed: scsi error aborted command Smartctl: SMART Enable Failed. A mandatory SMART command failed: exiting. To continue, add one or more '-T permissive' options. How to overcome this problem?

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  • Samsung SSD SMART failure warning on macbook proA

    - by user37303
    My 9 month old 256GB Samsung SSD is now reporting the following SMART failures: Rsvd_Blk_Cnt_Chip FAILING NOW 184 Available_Reservd_Space FAILING NOW 20 Can anyone explain the meaning of these two attributes that appear to be failing (Rsvd_Blk_Cnt_Chip and Available_Reservd_Space? Also, also aren't SSDs much more immune to these types of failures? Everything seems to be working fine now, but I'm fearful of a looming failure.

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  • LLBLGen Pro v3.0 with Entity Framework v4.0 (12m video)

    - by FransBouma
    Today I recorded a video in which I illustrate some of the database-first functionality available in LLBLGen Pro v3.0. LLBLGen Pro v3.0 also supports model-first functionality, which I hope to illustrate in an upcoming video. LLBLGen Pro v3.0 is currently in beta and is scheduled to RTM some time in May 2010. It supports the following frameworks out of the box, with more scheduled to follow in the coming year: LLBLGen Pro RTL (our own o/r mapper framework), Linq to Sql, NHibernate and Entity Framework (v1 and v4). The video I linked to below illustrates the creation of an entity model for Entity Framework v4, by reverse engineering the SQL Server 2008 example database 'AdventureWorks'. The following topics (among others) are included in the video: Abbreviation support (example: convert 'Qty' into 'Quantity' during name construction) Flexible, framework specific settings Attribute definitions for various elements (so no requirement for buddy-classes or messing with generated code or templates) Retrieval of relational model data from a database Reverse engineering of tables into entities, automatically placed in groups Auto-creation of inheritance hierarchies Refactoring of entity fields into Value Type Definitions (DDD) Mapping a Typed view onto a stored procedure resultset Creation of a Typed list (definition of a query with a projection) on a set of related entities Validation and correction of found inconsistencies and errors Generating code using one of the pre-defined presets Illustration of the code in vs.net 2010 It also gives a good overview of what it takes with LLBLGen Pro v3.0 to start from a new project, point it to a database, get an entity model, perform tweaks and validation and generate code which is ready to run. I am no video recording expert so there's no audio and some mouse movements might be a little too quickly. If that's the case, please pause the video. It's rather big (52MB). Click here to open the HTML page with the video (Flash). Opens in a new window. LLBLGen Pro v3.0 is currently in beta (available for v2.x customers) and scheduled to be released somewhere in May 2010.

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  • SMART Status Data Interpretation - Disk Utility

    - by Mah
    Last week my external harddisk (Seagate Barracuda 1.5TB in a custom enclosure) showed signs of failure (Disk Utility SMART Pre-failure status - several bad sectors) and I decided to change it. I bought a new HDD (Seagate Barracuda 2TB) and connected it to my Ubuntu box with a SATA to USB cable that could not report SMART status. I copied all the contents of the old HDD to the new HDD (one partition with rsync, the other with parted cp) and then gently replaced the old HDD with the new one inside my aluminum enclosure. For obscure reasons after reconnecting the new HDD through the old enclosure, the Linux box could not detect my partitions. I recovered the partitions with testdisk and restarted the computer. After the restart I checked the SMART status of the new HDD an I get this: Read Error Rate --------------- Normalized 108 Worst 99 Threshold 6 Value 16737944 I got a high value on the Seek Error Rate as well. Wondering why this happens I copied 2 GB directory from one partition to the other and rechecked the SMART status (5 minutes later). This time I got the following: Read Error Rate --------------- Normalized 109 Worst 99 Threshold 6 Value 24792504 As you see there has been an increase in the error rate. I am unable to interpret these numbers. Is my new hard disk already dying? What are the acceptable values in these fields for Seagate hard disks? Then why the assessment is still good? While I could get temperature and airflow temperature data from my old HDD, I can not fetch them for the new one. I noticed that my old hdd had got really hot sometimes. Is it possible that the enclosure is killing the harddisks due to high temperature?... Thanks

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  • Oracle Database Smart Flash Cache: Only on Oracle Linux and Oracle Solaris

    - by sergio.leunissen
    Oracle Database Smart Flash Cache is a feature that was first introduced with Oracle Database 11g Release 2. Only available on Oracle Linux and Oracle Solaris, this feature increases the size of the database buffer cache without having to add RAM to the system. In effect, it acts as a second level cache on flash memory and will especially benefit read-intensive database applications. The Oracle Database Smart Flash Cache white paper concludes: Available at no additional cost, Database Smart Flash Cache on Oracle Solaris and Oracle Linux has the potential to offer considerable benefit to users of Oracle Database 11g Release 2 with disk-bound read-mostly or read-only workloads, through the simple addition of flash storage such as the Sun Storage F5100 Flash Array or the Sun Flash Accelerator F20 PCIe Card. Read the white paper.

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  • Smart View és az Office verziók

    - by Fekete Zoltán
    A Smart View többek között az Oracle Essbase (Hyperion) lekérdezo-elemzo-kontrolling-adatbeviteli stb felülete is. A Smart View egy MS Excel add-in-ként áll rendelkezésre. Teljes mértékben támogatja a tervezési, költségvetéskészítési, kontrolling és elemzési munkát. Az Essbase a kontrollerek szívéhez és kezéhez közelálló OLAP szerver, ami a Hyperion Planningnek is az alapja. Milyen MS Office verziókat támogat a Smart View? MS Office 2000 (XP), 2003, 2007 verziókat. Ezt az információt az Oracle Enterprise Performance Management Products - Supported Platforms Matrices helyen felsorolt dokumentumok írják le. Az Oracle Enterprise Performance Management aktuális verziójának 11.1.1.3 teljes dokumentácója megtalálható itt.

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  • LLBLGen Pro feature highlights: grouping model elements

    - by FransBouma
    (This post is part of a series of posts about features of the LLBLGen Pro system) When working with an entity model which has more than a few entities, it's often convenient to be able to group entities together if they belong to a semantic sub-model. For example, if your entity model has several entities which are about 'security', it would be practical to group them together under the 'security' moniker. This way, you could easily find them back, yet they can be left inside the complete entity model altogether so their relationships with entities outside the group are kept. In other situations your domain consists of semi-separate entity models which all target tables/views which are located in the same database. It then might be convenient to have a single project to manage the complete target database, yet have the entity models separate of each other and have them result in separate code bases. LLBLGen Pro can do both for you. This blog post will illustrate both situations. The feature is called group usage and is controllable through the project settings. This setting is supported on all supported O/R mapper frameworks. Situation one: grouping entities in a single model. This situation is common for entity models which are dense, so many relationships exist between all sub-models: you can't split them up easily into separate models (nor do you likely want to), however it's convenient to have them grouped together into groups inside the entity model at the project level. A typical example for this is the AdventureWorks example database for SQL Server. This database, which is a single catalog, has for each sub-group a schema, however most of these schemas are tightly connected with each other: adding all schemas together will give a model with entities which indirectly are related to all other entities. LLBLGen Pro's default setting for group usage is AsVisualGroupingMechanism which is what this situation is all about: we group the elements for visual purposes, it has no real meaning for the model nor the code generated. Let's reverse engineer AdventureWorks to an entity model. By default, LLBLGen Pro uses the target schema an element is in which is being reverse engineered, as the group it will be in. This is convenient if you already have categorized tables/views in schemas, like which is the case in AdventureWorks. Of course this can be switched off, or corrected on the fly. When reverse engineering, we'll walk through a wizard which will guide us with the selection of the elements which relational model data should be retrieved, which we can later on use to reverse engineer to an entity model. The first step after specifying which database server connect to is to select these elements. below we can see the AdventureWorks catalog as well as the different schemas it contains. We'll include all of them. After the wizard completes, we have all relational model data nicely in our catalog data, with schemas. So let's reverse engineer entities from the tables in these schemas. We select in the catalog explorer the schemas 'HumanResources', 'Person', 'Production', 'Purchasing' and 'Sales', then right-click one of them and from the context menu, we select Reverse engineer Tables to Entity Definitions.... This will bring up the dialog below. We check all checkboxes in one go by checking the checkbox at the top to mark them all to be added to the project. As you can see LLBLGen Pro has already filled in the group name based on the schema name, as this is the default and we didn't change the setting. If you want, you can select multiple rows at once and set the group name to something else using the controls on the dialog. We're fine with the group names chosen so we'll simply click Add to Project. This gives the following result:   (I collapsed the other groups to keep the picture small ;)). As you can see, the entities are now grouped. Just to see how dense this model is, I've expanded the relationships of Employee: As you can see, it has relationships with entities from three other groups than HumanResources. It's not doable to cut up this project into sub-models without duplicating the Employee entity in all those groups, so this model is better suited to be used as a single model resulting in a single code base, however it benefits greatly from having its entities grouped into separate groups at the project level, to make work done on the model easier. Now let's look at another situation, namely where we work with a single database while we want to have multiple models and for each model a separate code base. Situation two: grouping entities in separate models within the same project. To get rid of the entities to see the second situation in action, simply undo the reverse engineering action in the project. We still have the AdventureWorks relational model data in the catalog. To switch LLBLGen Pro to see each group in the project as a separate project, open the Project Settings, navigate to General and set Group usage to AsSeparateProjects. In the catalog explorer, select Person and Production, right-click them and select again Reverse engineer Tables to Entities.... Again check the checkbox at the top to mark all entities to be added and click Add to Project. We get two groups, as expected, however this time the groups are seen as separate projects. This means that the validation logic inside LLBLGen Pro will see it as an error if there's e.g. a relationship or an inheritance edge linking two groups together, as that would lead to a cyclic reference in the code bases. To see this variant of the grouping feature, seeing the groups as separate projects, in action, we'll generate code from the project with the two groups we just created: select from the main menu: Project -> Generate Source-code... (or press F7 ;)). In the dialog popping up, select the target .NET framework you want to use, the template preset, fill in a destination folder and click Start Generator (normal). This will start the code generator process. As expected the code generator has simply generated two code bases, one for Person and one for Production: The group name is used inside the namespace for the different elements. This allows you to add both code bases to a single solution and use them together in a different project without problems. Below is a snippet from the code file of a generated entity class. //... using System.Xml.Serialization; using AdventureWorks.Person; using AdventureWorks.Person.HelperClasses; using AdventureWorks.Person.FactoryClasses; using AdventureWorks.Person.RelationClasses; using SD.LLBLGen.Pro.ORMSupportClasses; namespace AdventureWorks.Person.EntityClasses { //... /// <summary>Entity class which represents the entity 'Address'.<br/><br/></summary> [Serializable] public partial class AddressEntity : CommonEntityBase //... The advantage of this is that you can have two code bases and work with them separately, yet have a single target database and maintain everything in a single location. If you decide to move to a single code base, you can do so with a change of one setting. It's also useful if you want to keep the groups as separate models (and code bases) yet want to add relationships to elements from another group using a copy of the entity: you can simply reverse engineer the target table to a new entity into a different group, effectively making a copy of the entity. As there's a single target database, changes made to that database are reflected in both models which makes maintenance easier than when you'd have a separate project for each group, with its own relational model data. Conclusion LLBLGen Pro offers a flexible way to work with entities in sub-models and control how the sub-models end up in the generated code.

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  • Making sense of S.M.A.R.T

    - by James
    First of all, I think everyone knows that hard drives fail a lot more than the manufacturers would like to admit. Google did a study that indicates that certain raw data attributes that the S.M.A.R.T status of hard drives reports can have a strong correlation with the future failure of the drive. We find, for example, that after their first scan error, drives are 39 times more likely to fail within 60 days than drives with no such errors. First errors in re- allocations, offline reallocations, and probational counts are also strongly correlated to higher failure probabil- ities. Despite those strong correlations, we find that failure prediction models based on SMART parameters alone are likely to be severely limited in their prediction accuracy, given that a large fraction of our failed drives have shown no SMART error signals whatsoever. Seagate seems like it is trying to obscure this information about their drives by claiming that only their software can accurately determine the accurate status of their drive and by the way their software will not tell you the raw data values for the S.M.A.R.T attributes. Western digital has made no such claim to my knowledge but their status reporting tool does not appear to report raw data values either. I've been using HDtune and smartctl from smartmontools in order to gather the raw data values for each attribute. I've found that indeed... I am comparing apples to oranges when it comes to certain attributes. I've found for example that most Seagate drives will report that they have many millions of read errors while western digital 99% of the time shows 0 for read errors. I've also found that Seagate will report many millions of seek errors while Western Digital always seems to report 0. Now for my question. How do I normalize this data? Is Seagate producing millions of errors while Western digital is producing none? Wikipedia's article on S.M.A.R.T status says that manufacturers have different ways of reporting this data. Here is my hypothesis: I think I found a way to normalize (is that the right term?) the data. Seagate drives have an additional attribute that Western Digital drives do not have (Hardware ECC Recovered). When you subtract the Read error count from the ECC Recovered count, you'll probably end up with 0. This seems to be equivalent to Western Digitals reported "Read Error" count. This means that Western Digital only reports read errors that it cannot correct while Seagate counts up all read errors and tells you how many of those it was able to fix. I had a Seagate drive where the ECC Recovered count was less than the Read error count and I noticed that many of my files were becoming corrupt. This is how I came up with my hypothesis. The millions of seek errors that Seagate produces are still a mystery to me. Please confirm or correct my hypothesis if you have additional information. Here is the smart status of my western digital drive just so you can see what I'm talking about: james@ubuntu:~$ sudo smartctl -a /dev/sda smartctl version 5.38 [x86_64-unknown-linux-gnu] Copyright (C) 2002-8 Bruce Allen Home page is http://smartmontools.sourceforge.net/ === START OF INFORMATION SECTION === Device Model: WDC WD1001FALS-00E3A0 Serial Number: WD-WCATR0258512 Firmware Version: 05.01D05 User Capacity: 1,000,204,886,016 bytes Device is: Not in smartctl database [for details use: -P showall] ATA Version is: 8 ATA Standard is: Exact ATA specification draft version not indicated Local Time is: Thu Jun 10 19:52:28 2010 PDT SMART support is: Available - device has SMART capability. SMART support is: Enabled === START OF READ SMART DATA SECTION === SMART overall-health self-assessment test result: PASSED SMART Attributes Data Structure revision number: 16 Vendor Specific SMART Attributes with Thresholds: ID# ATTRIBUTE_NAME FLAG VALUE WORST THRESH TYPE UPDATED WHEN_FAILED RAW_VALUE 1 Raw_Read_Error_Rate 0x002f 200 200 051 Pre-fail Always - 0 3 Spin_Up_Time 0x0027 179 175 021 Pre-fail Always - 4033 4 Start_Stop_Count 0x0032 100 100 000 Old_age Always - 270 5 Reallocated_Sector_Ct 0x0033 200 200 140 Pre-fail Always - 0 7 Seek_Error_Rate 0x002e 200 200 000 Old_age Always - 0 9 Power_On_Hours 0x0032 098 098 000 Old_age Always - 1468 10 Spin_Retry_Count 0x0032 100 100 000 Old_age Always - 0 11 Calibration_Retry_Count 0x0032 100 100 000 Old_age Always - 0 12 Power_Cycle_Count 0x0032 100 100 000 Old_age Always - 262 192 Power-Off_Retract_Count 0x0032 200 200 000 Old_age Always - 46 193 Load_Cycle_Count 0x0032 200 200 000 Old_age Always - 223 194 Temperature_Celsius 0x0022 105 102 000 Old_age Always - 42 196 Reallocated_Event_Count 0x0032 200 200 000 Old_age Always - 0 197 Current_Pending_Sector 0x0032 200 200 000 Old_age Always - 0 198 Offline_Uncorrectable 0x0030 200 200 000 Old_age Offline - 0 199 UDMA_CRC_Error_Count 0x0032 200 200 000 Old_age Always - 0 200 Multi_Zone_Error_Rate 0x0008 200 200 000 Old_age Offline - 0

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  • Why Garbage Collection if smart pointers are there

    - by Gulshan
    This days, so many languages are garbage collected. Even it is available for C++ by third parties. But, C++ has RAII and smart pointers. So, what's the point of using garbage collection? Is it doing something extra? And in other languages like C#, if all the references are treated as smart pointers(keeping RAII aside), by specification and by implementation, will there be still any need of garbage collectors? If no, then why this is not so?

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  • Brightness keeps changing in Windows 8.1 (on Macbook Pro Retina)

    - by gzak
    Before anyone gets too excited, it's not the "Adaptive Brightness" feature of the OS. I've already turned that off. Also it seems to have nothing to do with ambient light. It actually seems to do with the average "color" of the display. If I'm working in dark-themed Visual Studio, the brightness "pops" brighter. When I switch to the browser, it "pops" darker. So it's kind of adaptive brightness based on average pixel color (or something like that). What makes it rather annoying is that the brightness pops, rather than transitioning gradually. What is this feature, and how do I disable it (or at least make it smoother)?

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  • LLBLGen Pro v3.1 released!

    - by FransBouma
    Yesterday we released LLBLGen Pro v3.1! Version 3.1 comes with new features and enhancements, which I'll describe briefly below. v3.1 is a free upgrade for v3.x licensees. What's new / changed? Designer Extensible Import system. An extensible import system has been added to the designer to import project data from external sources. Importers are plug-ins which import project meta-data (like entity definitions, mappings and relational model data) from an external source into the loaded project. In v3.1, an importer plug-in for importing project elements from existing LLBLGen Pro v3.x project files has been included. You can use this importer to create source projects from which you import parts of models to build your actual project with. Model-only relationships. In v3.1, relationships of the type 1:1, m:1 and 1:n can be marked as model-only. A model-only relationship isn't required to have a backing foreign key constraint in the relational model data. They're ideal for projects which have to work with relational databases where changes can't always be made or some relationships can't be added to (e.g. the ones which are important for the entity model, but are not allowed to be added to the relational model for some reason). Custom field ordering. Although fields in an entity definition don't really have an ordering, it can be important for some situations to have the entity fields in a given order, e.g. when you use compound primary keys. Field ordering can be defined using a pop-up dialog which can be opened through various ways, e.g. inside the project explorer, model view and entity editor. It can also be set automatically during refreshes based on new settings. Command line relational model data refresher tool, CliRefresher.exe. The command line refresh tool shipped with v2.6 is now available for v3.1 as well Navigation enhancements in various designer elements. It's now easier to find elements like entities, typed views etc. in the project explorer from editors, to navigate to related entities in the project explorer by right clicking a relationship, navigate to the super-type in the project explorer when right-clicking an entity and navigate to the sub-type in the project explorer when right-clicking a sub-type node in the project explorer. Minor visual enhancements / tweaks LLBLGen Pro Runtime Framework Entity creation is now up to 30% faster and takes 5% less memory. Creating an entity object has been optimized further by tweaks inside the framework to make instantiating an entity object up to 30% faster. It now also takes up to 5% less memory than in v3.0 Prefetch Path node merging is now up to 20-25% faster. Setting entity references required the creation of a new relationship object. As this relationship object is always used internally it could be cached (as it's used for syncing only). This increases performance by 20-25% in the merging functionality. Entity fetches are now up to 20% faster. A large number of tweaks have been applied to make entity fetches up to 20% faster than in v3.0. Full WCF RIA support. It's now possible to use your LLBLGen Pro runtime framework powered domain layer in a WCF RIA application using the VS.NET tools for WCF RIA services. WCF RIA services is a Microsoft technology for .NET 4 and typically used within silverlight applications. SQL Server DQE compatibility level is now per instance. (Usable in Adapter). It's now possible to set the compatibility level of the SQL Server Dynamic Query Engine (DQE) per instance of the DQE instead of the global setting it was before. The global setting is still available and is used as the default value for the compatibility level per-instance. You can use this to switch between CE Desktop and normal SQL Server compatibility per DataAccessAdapter instance. Support for COUNT_BIG aggregate function (SQL Server specific). The aggregate function COUNT_BIG has been added to the list of available aggregate functions to be used in the framework. Minor changes / tweaks I'm especially pleased with the import system, as that makes working with entity models a lot easier. The import system lets you import from another LLBLGen Pro v3 project any entity definition, mapping and / or meta-data like table definitions. This way you can build repository projects where you store model fragments, e.g. the building blocks for a customer-order system, a user credential model etc., any model you can think of. In most projects, you'll recognize that some parts of your new model look familiar. In these cases it would have been easier if you would have been able to import these parts from projects you had pre-created. With LLBLGen Pro v3.1 you can. For example, say you have an Oracle schema called CRM which contains the bread 'n' butter customer-order-product kind of model. You create an entity model from that schema and save it in a project file. Now you start working on another project for another customer and you have to use SQL Server. You also start using model-first development, so develop the entity model from scratch as there's no existing database. As this customer also requires some CRM like entity model, you import the entities from your saved Oracle project into this new SQL Server targeting project. Because you don't work with Oracle this time, you don't import the relational meta-data, just the entities, their relationships and possibly their inheritance hierarchies, if any. As they're now entities in your project you can change them a bit to match the new customer's requirements. This can save you a lot of time, because you can re-use pre-fab model fragments for new projects. In the example above there are no tables yet (as you work model first) so using the forward mapping capabilities of LLBLGen Pro v3 creates the tables, PK constraints, Unique Constraints and FK constraints for you. This way you can build a nice repository of model fragments which you can re-use in new projects.

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  • SMART: DISK FAILURE IS IMMINENT (under 24 hours?)

    - by flix
    I have on my hard drive 2 OSes: Ubuntu 12.04 and Windows Vista( I keep it just because of school). Everything was OK on both OSes,but one day on Ubuntu I was getting awkward noises from my notebooks's hard drive and then everything stops and I couldn't do anything. On Windows everything was ok. Everytime I boot on Ubuntu I can get 5 minutes of normal run, without problems. After that the hard drive sounds crazy and nothing works. I could run S.M.A.R.T tests from a older Ubuntu CD (10.04) from the GUI(Disk Utility, or something like that and from terminal). From the GUI I got that the DISK FAILURE IS IMMINENT and I have ~700 bad blocks(or broken blocks, I had that test I while ago) on my HDD. From the terminal ( I don't remember if it was fsck or a SMART test command) I got that the HDD will fail in under 24 hours. Since then it passed 2-3 weeks. I've tried "badblocks" but after 10 hours it was still running and I had to stop it. Now I have to use cygwin and other alternatives for my linux apps on Windows. PLEASE HELP!!! How can I separate the bad blocks from Ubuntu so it wouldn't use them?

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  • Why are SMART error rates going down?

    - by Jeff Shattock
    I have a hard drive that's part of a Linux software raid5 array. SMART has reported that its multi_zone_error_rate was 0, then 1, then 3. So I figured I better start backing up more frequently and prepare to replace the drive. Now, today, the multi_zone_error_rate of that very same drive is back down to 1. It seems that 2 errors unhappened while I wasn't looking. I've also seen simliar behaviour by inspecting the syslog on the server. Jun 7 21:01:17 FS1 smartd[25593]: Device: /dev/sdc, SMART Usage Attribute: 7 Seek_Error_Rate changed from 200 to 100 Jun 7 21:01:17 FS1 smartd[25593]: Device: /dev/sde, SMART Usage Attribute: 7 Seek_Error_Rate changed from 200 to 100 Jun 7 21:01:18 FS1 smartd[25593]: Device: /dev/sdg, SMART Usage Attribute: 7 Seek_Error_Rate changed from 200 to 100 Jun 8 02:31:18 FS1 smartd[25593]: Device: /dev/sdg, SMART Usage Attribute: 7 Seek_Error_Rate changed from 100 to 200 Jun 8 03:01:17 FS1 smartd[25593]: Device: /dev/sdc, SMART Usage Attribute: 7 Seek_Error_Rate changed from 100 to 200 Jun 8 03:01:17 FS1 smartd[25593]: Device: /dev/sde, SMART Usage Attribute: 7 Seek_Error_Rate changed from 100 to 200 These are raw values, not the human-useful values that smartctl -a produces, but the behaviour is similar: error rates changing, then undoing the change. None of these are the drive that had the multi_zone weirdness. I haven't seen any problems from the RAID; its most recent scrub ( < 24 hours ago) came back totally clean. The only thing I can think of is that the SMART reporting circuitry on the drive isn't working properly all the time. The cables are in tight on the drive and board. What's going on here?

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  • LLBLGen Pro v3.5 has been released!

    - by FransBouma
    Last weekend we released LLBLGen Pro v3.5! Below the list of what's new in this release. Of course, not everything is on this list, like the large amount of work we put in refactoring the runtime framework. The refactoring was necessary because our framework has two paradigms which are added to the framework at a different time, and from a design perspective in the wrong order (the paradigm we added first, SelfServicing, should have been built on top of Adapter, the other paradigm, which was added more than a year after the first released version). The refactoring made sure the framework re-uses more code across the two paradigms (they already shared a lot of code) and is better prepared for the future. We're not done yet, but refactoring a massive framework like ours without breaking interfaces and existing applications is ... a bit of a challenge ;) To celebrate the release of v3.5, we give every customer a 30% discount! Use the coupon code NR1ORM with your order :) The full list of what's new: Designer Rule based .NET Attribute definitions. It's now possible to specify a rule using fine-grained expressions with an attribute definition to define which elements of a given type will receive the attribute definition. Rules can be assigned to attribute definitions on the project level, to make it even easier to define attribute definitions in bulk for many elements in the project. More information... Revamped Project Settings dialog. Multiple project related properties and settings dialogs have been merged into a single dialog called Project Settings, which makes it easier to configure the various settings related to project elements. It also makes it easier to find features previously not used  by many (e.g. type conversions) More information... Home tab with Quick Start Guides. To make new users feel right at home, we added a home tab with quick start guides which guide you through four main use cases of the designer. System Type Converters. Many common conversions have been implemented by default in system type converters so users don't have to develop their own type converters anymore for these type conversions. Bulk Element Setting Manipulator. To change setting values for multiple project elements, it was a little cumbersome to do that without a lot of clicking and opening various editors. This dialog makes changing settings for multiple elements very easy. EDMX Importer. It's now possible to import entity model data information from an existing Entity Framework EDMX file. Other changes and fixes See for the full list of changes and fixes the online documentation. LLBLGen Pro Runtime Framework WCF Data Services (OData) support has been added. It's now possible to use your LLBLGen Pro runtime framework powered domain layer in a WCF Data Services application using the VS.NET tools for WCF Data Services. WCF Data Services is a Microsoft technology for .NET 4 to expose your domain model using OData. More information... New query specification and execution API: QuerySpec. QuerySpec is our new query specification and execution API as an alternative to Linq and our more low-level API. It's build, like our Linq provider, on top of our lower-level API. More information... SQL Server 2012 support. The SQL Server DQE allows paging using the new SQL Server 2012 style. More information... System Type converters. For a common set of types the LLBLGen Pro runtime framework contains built-in type conversions so you don't need to write your own type converters anymore. Public/NonPublic property support. It's now possible to mark a field / navigator as non-public which is reflected in the runtime framework as an internal/friend property instead of a public property. This way you can hide properties from the public interface of a generated class and still access it through code added to the generated code base. FULL JOIN support. It's now possible to perform FULL JOIN joins using the native query api and QuerySpec. It's left to the developer to check whether the used target database supports FULL (OUTER) JOINs. Using a FULL JOIN with entity fetches is not recommended, and should only be used when both participants in the join aren't the target of the fetch. Dependency Injection Tracing. It's now possible to enable tracing on dependency injection. Enable tracing at level '4' on the traceswitch 'ORMGeneral'. This will emit trace information about which instance of which type got an instance of type T injected into property P. Entity Instances in projections in Linq. It's now possible to return an entity instance in a custom Linq projection. It's now also possible to pass this instance to a method inside the query projection. Inheritance fully supported in this construct. Entity Framework support The Entity Framework has been updated in the recent year with code-first support and a new simpler context api: DbContext (with DbSet). The amount of code to generate is smaller and the context simpler. LLBLGen Pro v3.5 comes with support for DbContext and DbSet and generates code which utilizes these new classes. NHibernate support NHibernate v3.2+ built-in proxy factory factory support. By default the built-in ProxyFactoryFactory is selected. FluentNHibernate Session Manager uses 1.2 syntax. Fluent NHibernate mappings generate a SessionManager which uses the v1.2 syntax for the ProxyFactoryFactory location Optionally emit schema / catalog name in mappings Two settings have been added which allow the user to control whether the catalog name and/or schema name as known in the project in the designer is emitted into the mappings.

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  • New Product: Oracle Java ME Embedded 3.2 – Small, Smart, Connected

    - by terrencebarr
    The Internet of Things (IoT) is coming. And, with todays launch of the Oracle Java ME Embedded 3.2 product, Java is going to play an even greater role in it. Java in the Internet of Things By all accounts, intelligent embedded devices are penetrating the world around us – driving industrial processes, monitoring environmental conditions, providing better health care, analyzing and processing data, and much more. And these devices are becoming increasingly connected, adding another dimension of utility. Welcome to the Internet of Things. As I blogged yesterday, this is a huge opportunity for the Java technology and ecosystem. To enable and utilize these billions of devices effectively you need a programming model, tools, and protocols which provide a feature-rich, consistent, scalable, manageable, and interoperable platform.  Java technology is ideally suited to address these technical and business problems, enabling you eliminate many of the typical challenges in designing embedded solutions. By using Java you can focus on building smarter, more valuable embedded solutions faster. To wit, Java technology is already powering around 10 billion devices worldwide. Delivering on this vision and accelerating the growth of embedded Java solutions, Oracle is today announcing a brand-new product: Oracle Java Micro Edition (ME) Embedded 3.2, accompanied by an update release of the Java ME Software Development Kit (SDK) to version 3.2. What is Oracle Java ME Embedded 3.2? Oracle Java ME Embedded 3.2 is a complete Java runtime client, optimized for ARM architecture connected microcontrollers and other resource-constrained systems. The product provides dedicated embedded functionality and is targeted for low-power, limited memory devices requiring support for a range of network services and I/O interfaces.  What features and APIs are provided by Oracle Java ME Embedded 3.2? Oracle Java ME Embedded 3.2 is a Java ME runtime based on CLDC 1.1 (JSR-139) and IMP-NG (JSR-228). The runtime and virtual machine (VM) are highly optimized for embedded use. Also included in the product are the following optional JSRs and Oracle APIs: File I/O API’s (JSR-75)  Wireless Messaging API’s (JSR-120) Web Services (JSR-172) Security and Trust Services subset (JSR-177) Location API’s (JSR-179) XML API’s (JSR-280)  Device Access API Application Management System (AMS) API AccessPoint API Logging API Additional embedded features are: Remote application management system Support for continuous 24×7 operation Application monitoring, auto-start, and system recovery Application access to peripheral interfaces such as GPIO, I2C, SPIO, memory mapped I/O Application level logging framework, including option for remote logging Headless on-device debugging – source level Java application debugging over IP Connection Remote configuration of the Java VM What type of platforms are targeted by Oracle Java ME 3.2 Embedded? The product is designed for embedded, always-on, resource-constrained, headless (no graphics/no UI), connected (wired or wireless) devices with a variety of peripheral I/O.  The high-level system requirements are as follows: System based on ARM architecture SOCs Memory footprint (approximate) from 130 KB RAM/350KB ROM (for a minimal, customized configuration) to 700 KB RAM/1500 KB ROM (for the full, standard configuration)  Very simple embedded kernel, or a more capable embedded OS/RTOS At least one type of network connection (wired or wireless) The initial release of the product is delivered as a device emulation environment for x86/Windows desktop computers, integrated with the Java ME SDK 3.2. A standard binary of Oracle Java ME Embedded 3.2 for ARM KEIL development boards based on ARM Cortex M-3/4 (KEIL MCBSTM32F200 using ST Micro SOC STM32F207IG) will soon be available for download from the Oracle Technology Network (OTN).  What types of applications can I develop with Oracle Java ME Embedded 3.2? The Oracle Java ME Embedded 3.2 product is a full-featured embedded Java runtime supporting applications based on the IMP-NG application model, which is derived from the well-known MIDP 2 application model. The runtime supports execution of multiple concurrent applications, remote application management, versatile connectivity, and a rich set of APIs and features relevant for embedded use cases, including the ability to interact with peripheral I/O directly from Java applications. This rich feature set, coupled with familiar and best-in class software development tools, allows developers to quickly build and deploy sophisticated embedded solutions for a wide range of use cases. Target markets well supported by Oracle Java ME Embedded 3.2 include wireless modules for M2M, industrial and building control, smart grid infrastructure, home automation, and environmental sensors and tracking. What tools are available for embedded application development for Oracle Java ME Embedded 3.2? Along with the release of Oracle Java ME Embedded 3.2, Oracle is also making available an updated version of the Java ME Software Development Kit (SDK), together with plug-ins for the NetBeans and Eclipse IDEs, to deliver a complete development environment for embedded application development.  OK – sounds great! Where can I find out more? And how do I get started? There is a complete set of information, data sheet, API documentation, “Getting Started Guide”, FAQ, and download links available: For an overview of Oracle Embeddable Java, see here. For the Oracle Java ME Embedded 3.2 press release, see here. For the Oracle Java ME Embedded 3.2 data sheet, see here. For the Oracle Java ME Embedded 3.2 landing page, see here. For the Oracle Java ME Embedded 3.2 documentation page, including a “Getting Started Guide” and FAQ, see here. For the Oracle Java ME SDK 3.2 landing and download page, see here. Finally, to ask more questions, please see the OTN “Java ME Embedded” forum To get started, grab the “Getting Started Guide” and download the Java ME SDK 3.2, which includes the Oracle Java ME Embedded 3.2 device emulation.  Can I learn more about Oracle Java ME Embedded 3.2 at JavaOne and/or Java Embedded @ JavaOne? Glad you asked Both conferences, JavaOne and Java Embedded @ JavaOne, will feature a host of content and information around the new Oracle Java ME Embedded 3.2 product, from technical and business sessions, to hands-on tutorials, and demos. Stay tuned, I will post details shortly. Cheers, – Terrence Filed under: Mobile & Embedded Tagged: "Oracle Java ME Embedded", Connected, embedded, Embedded Java, Java Embedded @ JavaOne, JavaOne, Smart

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  • Smart Grid Gurus

    - by caroline.yu
    Join Paul Fetherland, AMI director at Hawaiian Electric Company (HECO) and Keith Sturkie, vice president of Information Technology, Mid-Carolina Electric Cooperative (MCEC) on Thursday, April 29 at 12 p.m. EDT for the free "Smart Grid Gurus" Webcast. In this Webcast, underwritten by Oracle Utilities, Intelligent Utility will profile Paul Fetherland and Keith Sturkie to examine how they ended up in their respective positions and how they are making smarter grids a reality at their companies. By attending, you will: Gain insight from the paths taken and lessons learned by HECO and MCEC as these two utilities add more grid intelligence to their operations Identify the keys to driving AMI deployment, increasing operational and productivity gains, and targeting new goals on the technology roadmap Learn why HECO is taking a careful, measured approach to AMI deployment, and how Hawaii's established renewable portfolio standard of 40% and an energy efficiency standard of 30%, both by 2030, impact its efforts Discover how MCEC's 45,000-meter AMI deployment, completed in 2005, reduced field trips for high-usage complaints by 90% in the first year, and MCEC's immediate goals for future technology implementation To register, please follow this link.

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  • How Do I interpret HDD S.M.A.R.T Results?

    - by Marty
    My laptop has recently started to become a bit unreliable, and for some reason I started to suspect that my HDD was starting to fail. After a bit of hunting on the internet, I found Ubuntu's Disk Utility in the System menu and ran the long SMART diagnostics from this. However, since the documentation for Disk Utility is very poor (palimpsest?), I'm not sure how to interpret the results: For example, the Read Error Rate is over 50 million (!), yet the Assessment is rated "Good". So would someone mind explaining to me how to interpret the results of these tests (especially the Normalized, Worst, Threshold and Value numbers)? And maybe tell me what they think of the results I got for my HDD? (Thanks)

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