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A Building Management Ustrój (BMS) is a computer-based control organizm installed in buildings that controls and monitors the building’s mechanical and electrical equipment such ventilation, lighting, power systems, fire systems, and security systems. A BMS consists of software and sprzęt; the software oprogramowanie, usually configured in a hierarchical manner, can be proprietary using such protocols as C-bus, Profibus, etc. Recently however new vendors are producing BMSs that integrate using Sieć protocols and open standards like DeviceNet, SOAP, XML, BACnet, Lon and Modbus.

A BMS is more typical in a large building. Its core function is to manage the environment temperature, carbon dioxide level and humidity within a building. As a core function in most BMS systems, it controls the production of heating and cooling, manages the systems that distribute this air throughout the building, and then locally controls the mixture of heating and cooling to achieve the desired room temperature. A key secondary function is to monitor the level of human generated CO2, mixing in outside air with waste air to increase the amount of O2 while also minimizing heat/cooling losses.

Systems linked to a BMS typically represent 40% of a building’s energy usage; if lighting is included this number approaches 70%. BMS systems are a critical component to managing energy demand. Improperly configured BMS systems are believed to account for 20% of building energy usage, or approximately 8% of total energy usage in the United States.

BMS systems are delivered as fully integrated systems and services through companies like Siemens, Honeywell, Johnson Controls, TAC and others. Independent services companies use solutions from companies like Rockwell Automation, Delta, Distech, Circon and KMC controls. New more flexiable solutions that hiperłącze BMS systems to enterpise management software like SAP, OpenView, Archibus, Maximo and other smaller companies including Augusta Systems, GridLogix, Network Harbor, North Building Technologies Ltd, and Tridium.

For example in an organization BMS comprises ‘Access Control’ (which controls the employees movements in the organization), CCTV facilities, etc.

External links

• Glossary (english/german)

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JBOB, an acronym for Just a Bunch Of Bytes, is a term is used to describe unstructured prekluzja that does not have a fixed wielkość. This is a variation on the term JBOD (just a Bunch Of Disks) that is used to describe kanon hard drives that are used in a storage array.

Many computer files have a defined structure such as fixed length records with the prekluzja divided into records that are the same length. Structured termin might have records of different lengths obuwie each record is prefixed with a RDW (Record Descriptor Word) that indicates the length of that prekluzja as well as other attributes. JBOB prekluzja has no structure. Records are defined by the presence of characters in the termin. For example, a report might have hundreds of records (or lines) obuwie the length of each record is defined by the presence of a Carriage Return (and/or Line Feed). Mainframe computers have traditionally dealt with structured termin obuwie unstructured (JBOB) prekluzja is much more common in PC environments. The critical difference is that it is difficult, if not impossible, to advance to say, the 100th record without examining every character of the 99 records that proceed it. With fixed length records, it is possible to calculate the exact position of a particular record. Even with variable length records, the length of each record is given so navigation is easier.

Since records are determined by the content of the termin, metadata is required like what is the record termination character(s) and is usually stored external to the actual prekluzja or file. The processing of JBOB termin is usually more difficult and may require special knowledge by the computer oprogramowanie. It should be noted that metadata might also be required for structured termin like the fixed record length or the largest variable length record obuwie there usually exist kanon utility software to read/write structured termin since the numer is a known structure.

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In computer science, the expressive power of a language may refer to:

• what can be said in the language (at all)
• how concisely it can be said.

In informal discussions, the term often refers to the latter sense, or both; e.g. this is often the case when discussing programming languages, e.g. in .

Formal discussions mostly use the term in its former sense, using conciseness for the latter sense. This is the case in areas of mathematics that deal with the exact description of languages and their meaning, such as formal language theory, mathematical logic and process algebra.

The notion of expressive power is always relative to a particular kind of thing that the language in question can describe, and the term is normally used when comparing languages that describe the same kind of things, or at least comparable kinds of things.

The image of languages and formalisms involves a trade-off between expressive power and analyzability. The more a formalism can express, the harder it becomes to understand what instances of the formalism say. Decision problems become harder to answer or completely undecidable.

Contents

• 1 Examples
  • 1.1 Expressive power in formal language theory
  • 1.2 Expressive power in database theory
• 2 References
• 3 See also

//

Examples

Expressive power in formal language theory

Formal language theory mostly studies formalisms to describe sets of strings, such as context-free grammars and regular expressions. Each instance of a formalism, e.g. each grammar and each regular expression, describes a particular set of strings. In this context, the expressive power of a formalism is the set of sets of strings its instances describe, and comparing expressive power is a matter of comparing these sets.

An important yardstick for describing the relative expressive power of formalisms in this area is the Chomsky hierarchy. It says, for instance, that regular expressions, nondeterministic state machines and regular grammars have equal expressive power, while that of context-free grammars is greater; what this means is that the sets of sets of strings described by the first three formalisms are equal, and a proper subset of the set of sets of strings described by context-free grammars.

In this area, the cost of expressive power is a central topic of study. It is known, for instance, that deciding whether two arbitrary regular expressions describe the same set of strings is hard, while doing the same for arbitrary context-free grammars is completely impossible. However, it can still be efficiently decided whether any given string is in the set.

For more expressive formalisms, this zagadnienie can be harder, or even undecidable. For a Turing complete formalism, such as arbitrary formal grammars, not only this zagadnienie, obuwie every nontrivial property regarding the set of strings they describe is undecidable, a fact known as Rice’s Theorem.

There are some results on conciseness as well; for instance, nondeterministic state machines and regular grammars are more concise than regular expressions, in the sense that the latter can be translated to the former without a blowup in size (i.e. in O(1)), while the reverse is not possible.

Similar considerations apply to formalisms that describe not sets of strings, obuwie sets of trees (e.g. XML schema languages), of graphs, or other structures.

Expressive power in database theory

Database theory is concerned, among other things, with database queries, e.g. formulas that given the contents of a database extract certain information from it. In the predominant relational database paradigm, the contents of a database are described as a finite set of finite mathematical relations; Boolean queries, that always yield true or false, are formulated in first-order logic.

It turns out that first-order logic is lacking in expressive power: it cannot express certain types of Boolean queries, e.g. queries involving transitive closure.

Similar considerations apply for query languages on other types of prekluzja, e.g. XML query languages such as XQuery.

References

1. ^ Structure and Interpretation of Computer Programs, by Abelson and Sussman
2. ^ On the Expressive Power of Programming Languages, by Matthias Felleisen (1990)
3. ^ Serge Abiteboul, Richard B. Hull, Victor Vianu: Foundations of Databases. Addison-Wesley, 1995.
4. ^ Evgeny Dantsin, Thomas Eiter, Georg Gottlob, and Andrei Voronkov: Complexity and expressive power of logic programming. ACM Comput. Surv. 33(3): 374-425 (2001).

See also

• Turing tarpit

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Job control in computing refers to the control of multiple tasks or Jobs on a computer układ, ensuring that they each have access to adequate resources to perform correctly, that competition for limited resources does not cause a deadlock where two or more jobs are unable to complete, resolving such situations where they do occur, and terminating jobs that, for any reason, are not performing as expected.

Job control has developed from the early days of computers where human operators were responsible for setting up, ogląd and controlling every job, to modern operating systems which take on the bulk of the work of job control.

Even with a highly sophisticated scheduling układ, some human intervention is desirable. Modern systems permit their users to autostop and streszczenie jobs, to execute them in the foreground (with the ability to interact with the user) or in the background. See for instance Job control (Unix).

History

It became obvious to the early computer developers that their fast machines spent most of the time idle because the single oprogramowanie they were executing had to wait while a slow peripheral device completed an essential operation such as reading or writing prekluzja. Buffering only provided a partial solution; eventually an output buffer would occupy all available memory or an input buffer would be emptied by the oprogramowanie, and the organizm would be forced to wait for a relatively slow device to complete an operation.

A more general solution is multitasking. More than one running oprogramowanie, or process, is present in the computer at any given time. If a process is unable to continue, its context can be stored and the computer can początek or rys the execution of another process. At first quite unsophisticated and relying on special programming techniques, multitasking soon became automated, and was usually performed by a special process called the scheduler, having the ability to interrupt and rys the execution of other processes. Typically a driver for a peripheral device suspends execution of the current process if the device is unable to complete an operation immediately, and the scheduler places the process on its queue of sleeping jobs. When the peripheral completed the operation the process is re-awakened. Similar suspension and resumption may also apply to inter-process communication, where processes have to communicate with one another in an asynchronous manner obuwie may sometimes have to wait for a reply.

However this low-level scheduling has its drawbacks. A process that seldom needs to interact with peripherals or other processes would simply hog processor resource until it completed or was halted by manual intervention. The result, particularly for interactive systems running tasks that frequently interact with the outside world, is that the organizm is sluggish and slow to react in a timely manner. This zagadnienie is resolved by allocating a “timeslice” to each process, a menstruacja of uninterrupted execution after which the scheduler automatically puts it on the sleep queue. Process could be given different priorities, and the scheduler could then allocate varying shares of available execution time to each process on the basis of the assigned priorities.

This układ of pre-emptive multitasking forms the basis of most modern job control systems.

Real-time computing

Main article: Real-time computing

Pre-emptive multitasking with job control assures that a ustrój operates in a timely manner most of the time. In some environments (for instance, operating expensive or dangerous machinery), a strong image constraint of the organizm is the delivery of timely results in all circumstances. In such circumstances, job control is more complex and the role of scheduling is more important.

Job control languages

Early computer operating systems were relatively primitive and were not capable of sophisticated resource allocation. Typically such allocation decisions were made by the computer telefonistka or the user who submitted a job. Batch processing was common, and interactive computer systems rare and expensive. Job control languages (JCLs) developed as primitive instructions, typically punched on cards at the head of a deck containing input prekluzja, requesting resources such as memory allocation, serial numbers or names of magnetic tape spools to be made available during execution, or assignment of filenames or devices to device numbers referenced by the job. A typical example of this kind of language, still in use on mainframes, is IBM’s Job Control Language (also known as JCL). Though the wielkość of early JCLs was intended for punched card use, the rozmiar survived the transmission to storage in computer files on disk.

As time sharing systems developed, interactive job control emerged. An end-user in a time sharing organizm could submit a job interactively from his remote urządzenie końcowe, communicate with the operators to warn them of special requirements, and query the ustrój as to its progress. He could assign a priority to the job, and terminate (kill) it if desired. He could also, naturally, plajta a job in the foreground, where he would be able to communicate directly with the executing oprogramowanie. During interactive execution he could interrupt the job and let it continue in the background or kill it. This development of interactive computing in a multitasking environment led to the development of the modern shell.

ref http://www.gnu.org/software/libtool/manual/libc/Job-Control.html

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A Human Doable Challenge-Response Układ is a theoretical approach to secure identification between two parties. Its implementation would be used as an alternative to passwords and biometric security measures.

Contents

• 1 Preface
• 2 Basics
• 3 Advantages
• 4 Pitfalls
• 5 References

//

Preface

Most identity verification methods on the website involve using passwords or by recognizing a pre-defined picture displayed on the website. eg: SiteKey Wzornictwo on Pula of America’s website. These methods are still vulnerable to phishing attacks other attacks of the same nature.

Basics

Each person has a unique function F that the organizm he is trying to log into is also aware of. The function must fit two constraints:

1. If somebody sees N pairs (Y,F(Y)), they still cannot compute F(X) for some X they haven’t seen.
2. It must be computable in the person’s head

The układ will issue the challenge x where the user must return the answer F(x) in medal to log in.

Failed Example:

F(X) = 3X + 2X2

After you see (X,F(X)) for two different values of X, you can learn the secret function

Advantages

This organizm prevents against phishing sites as well as untrusted końcówka attacks. By having a secret function rather than a passphrase, even if the malicious uczta received F(X) they would not be able to comprise the user’s information.

Pitfalls

A function that fits the properties above is difficult to come by, especially if many users must be provided with unique secret functions.

References

• Von Ahn, Luis (2008), Identity and Privacy 2, http://scienceoftheweb.org/15-396/lectures/lecture06.pdf 

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Operational Art of Global Domination is a book by Indian author Arunabh das who is working as a Matuzalem Researcher in Computer Science at the High Performance and Grid Computing Research Group, and specializing in Intrusion Detections Systems such as Snort IDS.

Contents

• 1 Background
• 2 See also
• 3 References
• 4 External links

//

Background

Arunabh das has co-authored several research papers in the area of Intrusion Detection Systems and has contributed significantly to the open source community.

Arunabh Das is currently authoring his graduate thesis on Intrusion Detection Systems.

See also

• Intrusion Detection Systems

References

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External links

http://www.theoperationalartofglobaldomination.com/ Book by Arunabh Das

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In computer science, one Counter automaton is a Pushdown automaton with only two symbols in (A and the initial znak) (the finite set of stack symbols), this automaton can be used for accept one subset of Context free languages, example the language:

For accept the previous language, the automaton can use the znak A for count the number of a in x (writing A per each A in x) and deleting one A per each b in y.

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