Perceptual computing is an application of Zadeh's theory of computing with words on the field of assisting people to make subjective judgments. == Perceptual computer == The perceptual computer – Per-C – an instantiation of perceptual computing – has the architecture that is depicted in Fig. 1 [2]–[6]. It consists of three components: encoder, CWW engine and decoder. Perceptions – words – activate the Per-C and are the Per-C output (along with data); so, it is possible for a human to interact with the Per-C using just a vocabulary. A vocabulary is application (context) dependent, and must be large enough so that it lets the end-user interact with the Per-C in a user-friendly manner. The encoder transforms words into fuzzy sets (FSs) and leads to a codebook – words with their associated FS models. The outputs of the encoder activate a Computing With Words (CWW) engine, whose output is one or more other FSs, which are then mapped by the decoder into a recommendation (subjective judgment) with supporting data. The recommendation may be in the form of a word, group of similar words, rank or class. Although many details are needed in order to implement the Per-C's three components – encoder, decoder and CWW engine – and they are covered in [5], it is when the Per-C is applied to specific applications, that the focus on the methodology becomes clear. Stepping back from those details, the methodology of perceptual computing is: Focus on an application (A). Establish a vocabulary (or vocabularies) for A. Collect interval end-point data from a group of subjects (representative of the subjects who will use the Per-C) for all of the words in the vocabulary. Map the collected word data into word-FOUs by using the Interval Approach [1], [5, Ch. 3]. The result of doing this is the codebook (or codebooks) for A, and completes the design of the encoder of the Per-C. Choose an appropriate CWW engine for A. It will map IT2 FSs into one or more IT2 FSs. Examples of CWW engines are: IF-THEN rules [5, Ch. 6] and Linguistic Weighted Averages [6], [5, Ch. 5]. If an existing CWW engine is available for A, then use its available mathematics to compute its output(s). Otherwise, develop such mathematics for the new kind of CWW engine. The new CWW engine should be constrained so that its output(s) resemble the FOUs in the codebook(s) for A. Map the IT2 FS outputs from the CWW engine into a recommendation at the output of the decoder. If the recommendation is a word, rank or class, then use existing mathematics to accomplish this mapping [5, Ch. 4]. Otherwise, develop such mathematics for the new kind of decoder. == Applications of Per-C == To-date a Per-C has been implemented for the following four applications: (1) investment decision-making, (2) social judgment making, (3) distributed decision making, and (4) hierarchical and distributed decision-making. A specific example of the fourth application is the so-called Journal Publication Judgment Advisor [5, Ch. 10] in which for the first time only words are used at every level of the following hierarchical and distributed decision making process: n reviewers have to provide a subjective recommendation about a journal article that has been sent to them by the Associate Editor, who then has to aggregate the independent recommendations into a final recommendation that is sent to the Editor-in-Chief of the journal. Because it is very problematic to ask reviewers to provide numerical scores for paper-evaluation sub-categories (the two major categories are Technical Merit and Presentation), such as importance, content, depth, style, organization, clarity, references, etc., each reviewer will only be asked to provide a linguistic score for each of these categories. They will not be asked for an overall recommendation about the paper because in the past it is quite common for reviewers who provide the same numerical scores for such categories to give very different publishing recommendations. By leaving a specific recommendation to the associate editor such inconsistencies can hope to be eliminated. How words can be aggregated to reflect each reviewer's recommendation as well as the expertise of each reviewer about the paper's subject matter is done using a linguistic weighted average. Although the journal publication judgment advisor uses reviewers and an associate editor, the word “reviewer” could be replaced by judge, expert, low-level manager, commander, referee, etc., and the term “associate editor” could be replaced by control center, command center, higher-level manager, etc. So, this application has potential wide applicability to many other applications. Recently, a new Per-C based Failure mode and effects analysis (FMEA) methodology was developed, with its application to edible bird's nest farming, in Borneo, has been reported. In addition, application of Per-C based method to educational assessment, for cooperative learning of students has been reported. In summary, the Per-C (whose development has taken more than a decade) is the first complete implementation of Zadeh's CWW paradigm, as applied to assisting people to make subjective judgments.
RemObjects Software
RemObjects Software is an American software company founded in 2002 by Alessandro Federici and Marc Hoffman. It develops and offers tools and libraries for software developers on a variety of development platforms, including Embarcadero Delphi, Microsoft .NET, Mono, and Apple's Xcode. == History == RemObjects Software was founded in the summer of 2002. Its first product was RemObjects SDK 1.0 for Delphi, the company's remoting solution which is now in its 6th version. In late 2003 RemObjects expanded its product portfolio to add Data Abstract for Delphi, a multi-tier database framework built on top of the SDK. In 2004, Carlo Kok, who would eventually become Chief Compiler Architect for Oxygene, joined the company, adding the open source Pascal Script library for Delphi to the company's portfolio. Initial development began on Oxygene (which was then named Chrome) based on Carlo's experience from writing the widely used Pascal Script scripting engine. Towards the end of 2004, RemObjects SDK for .NET was released, expanding the remoting framework to its second platform. Chrome 1.0 was released in mid-2005, providing support for .NET 1.1 and .NET 2.0, which was still in beta at the time - making Chrome the first shipping language for .NET that supported features such as generics. It was followed by Chrome 1.5 when .NET 2.0 shipped in November of the same year. 2005 also saw the expansion of Data Abstract to .NET as a second platform. Data Abstract for .NET was the first RemObjects product (besides Oxygene itself) to be written in Oxygene. Hydra 3.0, was released for .NET in December 2006, bringing a paradigm shift to the product, away from a regular plugin framework, and focusing on interoperability between plugins and host applications written in either .NET or Delphi/Win32, essentially enabling the use of both managed and unmanaged code in the same project. In Summer 2007, RemObjects released Chrome 'Joyride' which added official support for .NET 3.0 and 3.5. Chrome once again was the first language to ship release level support for new .NET framework features supported by that runtime - most importantly Sequences and Queries (aka LINQ). Development continued and in May 2008 Oxygene 3.0 was released, dropping the "Chrome" moniker. Oxygene once again brought major language enhancements, including extensive support for concurrency and parallel programming as part of the language syntax. In October 2008, RemObjects Software and Embarcadero Technologies announced plans to collaborate and ship future versions of Oxygene under the Delphi Prism moniker, later changed to Embarcadero Prism. The first of these releases of Prism became available in December 2008. Over the course of 2009, RemObjects software completed the expansion of its Data Abstract and RemObjects SDK product combo to a third development platform - Xcode and Cocoa, for both Mac OS X and iPhone SDK client development. RemObjects SDK for OS X shipped in the spring of 2009, followed by Data Abstract for OS X in the fall. In 2011, Oxygene was expanded to add support for the Java platform, in addition to NET. In 2014, RemObjects introduced a C# compiler which runs as a Visual Studio 2013 plugin, that can output code for iOS, MacOS (Cocoa) and Android, in addition to .NET compatible code. In addition, an IDE called Fire was introduced for macOS which works with their C# and Oxygene compilers. Together, the compiler supporting both Oxygene and C# was rebranded as the Elements Compiler, with CE# having the Code name "Hydrogene". In February 2015, RemObjects introduced a beta version of a Swift compiler called Silver as part of its Elements effort. Silver, too, could create code that will execute on Android, the JVM, .NET platform and also create native Cocoa code. Silver added new features to the Swift language, such as exceptions and has a few differences and limitations compared to Apple's Swift. In February 2020, support for the Go programming language was introduced with RemObjects Gold, including the ability to compile Go language code for all Elements platforms, and a port of the extensive Go Base Library available to all Elements languages. In 2021, Mercury was added to the Elements compiler as the sixth language, providing a future for the Visual Basic .NET language recently deprecated by Microsoft. Mercury supports building and maintaining existing VB.NET projects, as well as using the language for new projects both on .NET and the other platforms. == Commercial products == Elements is a development toolchain that targets .NET runtime, Java/Android virtual machines, the Apple ecosystem (macOS, iOS, tvOS), WebAssembly and native and Windows/Linux/Android NDK processor-native machine code in conjunction with a runtime library that does automatic garbage collection on non-ARC environments and ARC on ARC-based environments, such as iOS and MacOS. Because Java, C#, Swift, and Oxygene all can import each other's APIs, Elements effectively functions as Java bonded together with C# bonded together with Swift bonded together with Oxygene as a confederation of languages cooperating together quite intimately. Oxygene, a unique programming language based on Object Pascal, which can import Java, C#, and Swift APIs from the runtime of the target operating system; RemObjects C#, an implementation of C# programming language, which can import Java, Swift, and Oxygene APIs from the runtime of the target operating system and which is intended as a competitor of Xamarin, but Hydrogene's C# targets JVM bytecode instead of Xamarin's C# compiling to only Common Language Infrastructure byte code and needing the accompanying Mono Common Language Runtime to be present in such JVM-centric environments as Android; Silver, a free implementation of the Swift programming language, which can import Java, C#, and Oxygene APIs from the runtime of the target operating system; Iodine, an implementation of the Java programming language. Gold, an implementation of the Go programming language. Mercury, an implementation of the Visual Basic .NET programming language. Fire an integrated development environment for macOS. Water an integrated development environment for Windows. Data Abstract Remoting SDK, a.k.a. RemObjects SDK Hydra Oxfuscator Oxidizer, an automatic translator from Java, C#, Objective-C, and Delphi to Oxygene, from Java, Objective-C, and C# to Swift, and from Java and Objective-C to C#. == Open source projects == Train is an open-source JavaScript-based tool for building and running build scripts and automation. Internet Pack for .NET is a free, open source library for building network clients and servers using TCP and higher level protocols such as HTTP or FTP, using the .NET or Mono platforms. It includes a range of ready to use protocol implementations, as well as base classes that allow the creation of custom implementations. RemObjects Script for .NET is a fully managed ECMAScript implementation for .NET and Mono. Pascal Script for Delphi is a widely used implementation of Pascal as scripting language. == Involvement of other projects == The Oxygene Compiler Oxygene is a language based on Object Pascal and designed to efficiently target the Microsoft .NET and Mono managed runtimes; it expands Object Pascal with a range of additional language features, such as Aspect Oriented Programming, Class Contracts and support for Parallelism. It integrates with the Microsoft Visual Studio and MonoDevelop IDEs.
Signatures with efficient protocols
Signatures with efficient protocols are a form of digital signature invented by Jan Camenisch and Anna Lysyanskaya in 2001. In addition to being secure digital signatures, they need to allow for the efficient implementation of two protocols: A protocol for computing a digital signature in a secure two-party computation protocol. A protocol for proving knowledge of a digital signature in a zero-knowledge protocol. In applications, the first protocol allows a signer to possess the signing key to issue a signature to a user (the signature owner) without learning all the messages being signed or the complete signature. The second protocol allows the signature owner to prove that he has a signature on many messages without revealing the signature and only a (possibly) empty subset of the messages. The combination of these two protocols allows for the implementation of digital credential and ecash protocols.
Social network hosting service
A social network hosting service is a web hosting service that specifically hosts the user creation of web-based social networking services, alongside related applications. Such services are also known as vertical social networks due to the creation of SNSes which cater to specific user interests and niches; like larger, interest-agnostic SNSes, such niche networking services may also possess the ability to create increasingly niche groups of users. == List of social network hosting services == Federated Media Publishing's BigTent BroadVision Clearvale Ning Wall.fm
Cognos ReportNet
Cognos ReportNet (CRN) was a web-based software product for creating and managing ad hoc and custom-made reports. ReportNet was developed by the Ottawa-based company Cognos (formerly Cognos Incorporated), an IBM company. The web-based reporting tool was launched in September 2003. Since IBM's acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet like all other Cognos products. ReportNet uses web services standards such as XML and Simple Object Access Protocol and also supports dynamic HTML and Java. ReportNet is compatible with multiple databases including Oracle, SAP, Teradata, Microsoft SQL server, DB2 and Sybase. The product provides interface in over 10 languages, has Web Services architecture to meet the needs of multi-national, diversified enterprises and helps reduce total cost of ownership. Multiple versions of Cognos ReportNet have since been released by the company. Cognos ReportNet was awarded the Software and Information Industry Association (SIIA) 2005 Codie awards for the "Best Business Intelligence or Knowledge Management Solution" category. CRN's capabilities have been further used in IBM Cognos 8 BI (2005), the latest reporting tool. CRN comes with its own software development kit (SDK). == Launch == Early adopters of Cognos ReportNet for their corporate reporting needs included Bear Stearns, BMW and Alfred Publishing. Around this same time of launch, Cognos competitor Business Objects released version 6.1 of its enterprise reporting tool. Cognos ReportNet has been successful since its launch, raising revenues in 2004 from licensing fees. == Controversy == Cognos rival Business Objects announced in 2005 that BusinessObjects XI significantly outperformed Cognos ReportNet in benchmark tests conducted by VeriTest, an independent software testing firm. The tests performed showed Cognos ReportNet performed poorly when processing styled reports, complex business reports and combination of both. The tests reported a massive 21 times higher report throughput for BusinessObjects XI than Cognos ReportNet at capacity loads. Cognos soon dismissed the claims by stating Business Objects dictated the environment and testing criteria and Cognos did not provide the software to participate in benchmark test. Cognos later performed their own test to demonstrate Cognos ReportNet capabilities. == Components == Cognos Report Studio – A Web-based product for creating complex professional looking reports. Cognos Query Studio - A Web-based product for creating ad-hoc reports. Cognos Framework Manager – A metadata modeling tool to create BI metadata for reporting and dashboard applications. Cognos Connection – Main portal used to access reports, schedule reports and perform administrator activities. == Versions == Cognos ReportNet 1.1 – Java EE-style professional web-based authoring tool. (base version) Cognos ReportNet IBM Special Edition – comes with an embedded version of IBM WebSphere as its application server and IBM DB2 as its data store. Cognos Linux – for Intel-based Linux platforms.
Data exploration
Data exploration is an approach similar to initial data analysis, whereby a data analyst uses visual exploration to understand what is in a dataset and the characteristics of the data, rather than through traditional data management systems. These characteristics can include size or amount of data, completeness of the data, correctness of the data, possible relationships amongst data elements or files/tables in the data. Data exploration is typically conducted using a combination of automated and manual activities. Automated activities can include data profiling or data visualization or tabular reports to give the analyst an initial view into the data and an understanding of key characteristics. This is often followed by manual drill-down or filtering of the data to identify anomalies or patterns identified through the automated actions. Data exploration can also require manual scripting and queries into the data (e.g. using languages such as SQL or R) or using spreadsheets or similar tools to view the raw data. All of these activities are aimed at creating a mental model and understanding of the data in the mind of the analyst, and defining basic metadata (statistics, structure, relationships) for the data set that can be used in further analysis. Once this initial understanding of the data is had, the data can be pruned or refined by removing unusable parts of the data (data cleansing), correcting poorly formatted elements and defining relevant relationships across datasets. This process is also known as determining data quality. Data exploration can also refer to the ad hoc querying or visualization of data to identify potential relationships or insights that may be hidden in the data and does not require to formulate assumptions beforehand. Traditionally, this had been a key area of focus for statisticians, with John Tukey being a key evangelist in the field. Today, data exploration is more widespread and is the focus of data analysts and data scientists; the latter being a relatively new role within enterprises and larger organizations. == Interactive Data Exploration == This area of data exploration has become an area of interest in the field of machine learning. This is a relatively new field and is still evolving. As its most basic level, a machine-learning algorithm can be fed a data set and can be used to identify whether a hypothesis is true based on the dataset. Common machine learning algorithms can focus on identifying specific patterns in the data. Many common patterns include regression and classification or clustering, but there are many possible patterns and algorithms that can be applied to data via machine learning. By employing machine learning, it is possible to find patterns or relationships in the data that would be difficult or impossible to find via manual inspection, trial and error or traditional exploration techniques. == Software == Trifacta – a data preparation and analysis platform Paxata – self-service data preparation software Alteryx – data blending and advanced data analytics software Microsoft Power BI - interactive visualization and data analysis tool OpenRefine - a standalone open source desktop application for data clean-up and data transformation Tableau software – interactive data visualization software
Commit (data management)
In computer science and data management, a commit is a behavior that marks the end of a transaction and provides Atomicity, Consistency, Isolation, and Durability (ACID) in transactions. The submission records are stored in the submission log for recovery and consistency in case of failure. In terms of transactions, the opposite of committing is giving up tentative changes to the transaction, which is rolled back. Due to the rise of distributed computing and the need to ensure data consistency across multiple systems, commit protocols have been evolving since their emergence in the 1970s. The main developments include the Two-Phase Commit (2PC) first proposed by Jim Gray, which is the fundamental core of distributed transaction management. Subsequently, the Three-phase Commit (3PC), Hypothesis Commit (PC), Hypothesis Abort (PA), and Optimistic Commit protocols gradually emerged, solving the problems of blocking and fault recovery. Today, new fields such as e-commerce payment and blockchain technology are emerging, and submission protocols play a significant role in various business areas. By effectively handling transactions, resolving faults and recovering problems, the commit protocol becomes crucial in ensuring the reliability and consistency of data management. == History == The concept of Commit originated in the late 1960s and early 1970s, when computer technology was rapidly advancing and data management was becoming an important requirement in business and finance. Enterprises have gradually replaced the traditional paper records with computers, which has fully improved the work efficiency. The reliability and consistency of data have become a necessary requirement. Transaction management at this stage is relatively simple, limited to using a single computer for processing. It merely effectively records the changes in data to ensure that the data remains stable after the transaction is completed or terminated. In the late 1970s, as database systems moved from a single calculator operation to multiple distributed collaborations, ensuring data consistency and reliability became a new challenge. In 1978, computer scientist Jim Gray proposed the famous two-phase Commit Protocol (2PC), which became an effective solution for distributed transaction management, successfully managing data synchronization problems between multiple nodes. However, this commit protocol has some potential transaction blocking problems when nodes fail. In the early 1980s, researchers discovered that although the two-step commit protocol was effective at synchronizing data, there could be long waits and even system crashes, with limitations. To improve this problem, people have begun to explore new and effective methods, including enhancing efficiency by reducing message communication during the protocol process. IBM's R database introduced the Assumed Commit and Assumed abort protocols, which contributed significantly to transaction management efficiency. These two protocols have greatly improved the processing efficiency of distributed transactions by reducing communication overhead and have become an important breakthrough in the technology of transaction commit protocols. By the early 1990s, with the increase in business demands and the complexity of transactions, enterprises required higher efficiency in distributed transaction processing. In order to adapt to the needs of different environments, the scientific community has gradually developed various variants of commit protocols to provide more flexible transaction management options for different needs. For example, the three-phase commit protocol promotes the commit of transactions more effectively and reduces the occurrence of blocking problems by adding a pre-commit protocol and a timeout mechanism. In the 21st century, with the popularization of mobile Internet and wireless technology, the commit protocol has been further developed, and researchers have begun to pay attention to how to reduce the blocking in the transaction process to solve the problem of broadband limitation, battery life and network instability in the mobile environment. The proposal of optimistic commit protocol marks the extension of commit technology from traditional database to the emerging mobile data field. This protocol allows transactions to temporarily use unconfirmed data, improving the user experience in cases of poor network conditions. In recent years, with the rise of blockchain and decentralized technologies, submission protocols and consensus mechanisms have gradually merged. These consensus algorithms play a role in tamper-proofing and preventing malicious attacks on node pairs in a decentralized environment. This enables commit to no longer be confined to the scope of traditional database management, but to become the core technology of trust computing and distributed ledgers, further expanding the application field of commit in the digital age. This integration has brought about extensive application impacts. Each transaction can achieve the effect of tracking global submissions through the verification of the consensus mechanism, becoming an important technical foundation for promoting the circulation of digital assets, the operation of cryptocurrencies and decentralized applications. == Commit Protocol Types == In the world of data management, a transaction is a series of database operations, such as bank transfers and order submission. In order to ensure the accuracy, consistency, and security of the data, transactions are usually completed completely, or cancelled completely, leaving no partially completed results. Commit protocol is the method used to coordinate this process. Different protocols are applicable to different submission scenarios and have their own advantages and disadvantages. There are four major commit protocols. === Two-Phase Commit (2PC) === The two-phase commit protocol is the most classic and broadest approach to distributed transactions, which includes both a preparation phase and a commit phase. This commit protocol is designed to allow the database coordinator to determine if all participating nodes agree. The preparation phase is the phase in which the coordination node sends a ready to commit request to all nodes participating in the transaction. The commit phase is a global commit after all participating nodes are ready, and if no agreement is reached, all nodes roll back the transaction and undo all previous operations. Although the two-phase commit protocol is the easiest to operate and widely used, its obvious drawback is that it can cause transactions to be blocked for a long time when nodes fail, resulting in a decline in system performance and making it difficult to terminate or continue immediately. === Three-Phase Commit (3PC) === The three-phase commit protocol is an improved non-blocking protocol based on 2PC, which is divided into three stages: preparation, pre-commit and commit. Firstly, each node sends a "preparation" request. After confirmation, a "pre-submission" stage is added. At this point, each node has completed most of the preparatory work and is waiting for the final confirmation. Finally, in the formal commit stage, after all nodes send the "commit" request, the transaction is completed and committed. Compared with 2PC, it increases the timeout mechanism, avoids the blocking problem caused by single point of failure, and improves the reliability of the system. The three-phase commit protocol significantly optimizes transaction reliability, but adds additional overhead for message transmission and state maintenance. It is more suitable for distributed application scenarios with high transaction sensitivity and no acceptance of long waiting times. === Presumed Commit (PC) and Presumed Abort (PA) === Presumed Commit (PC) is the default that the transaction will be committed successfully and rollback will be notified unless an anomaly is encountered. This commit reduces the message overhead and logging costs of a normal commits. Presumed Abort (PA) is assumed that the default state of the transaction is a rollback and will only be committed when all nodes have explicitly agreed. This commit is applicable to transactions that are not updated frequently or have a low probability of successful commit. The IBM R Distributed Database management System was the first to propose and practice the PC and PA protocols, handling distributed transaction management very efficiently and becoming a classic case in the field of database transaction management. === Optimistic Commit Protocol === With the rise of the Internet, the previous commit protocols are facing new challenges, especially in mobile scenarios with unstable networks. Excessively long transaction waiting times can affect the user experience. The Optimistic Commit Protocol allows a transaction to temporarily access uncommitted data before committing to avoid wait times. This type of commit is suitable f