Applications of Artificial Intelligence in Various Industries

Artificial intelligence is the area of the computer science which focuses on creating machines that can engage on behaviors that humans consider intelligent. Many AI applications are a major part in infrastructures of every industry. Applications of Artificial Intelligence in few industries are discussed below:

Medicine:
In the medical field artificial intelligence is used to organize bed schedules, make a staff rotation, and provide medical information. Artificial neural networks are used as clinical decision support system for medical diagnosis.

Transportation:
Fuzzy logic controllers are used in the gearboxes of the automobiles made by number of companies like, Volkswagen Caravell, it features the DSP transmission which utilizes Fuzzy logic and a number of Skoda variants also use this technology.

Finance:
Artificial intelligence is used in the banks to organize operations, invest in stocks and manage properties. Financial institutions also use artificial neural network systems to detect charges or claims outside of the norm.

Telecommunications:
Heuristic search is used by many telecommunication companies to manage their workplaces. For instance BT Group used this approach in a scheduling application that provides the work schedules of 20,000 engineers.

Heavy Industry:
Robots are the main application of the artificial intelligence in many manufacturing industries. Often robots are used in the workplaces that are considered dangerous to humans. Robots are also used in the jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration by the humans.

Music:
With the use of artificial intelligence scientists are trying to make the computer emulate the activities of the skillful musician and it is focusing on areas such as composition, performance, music theory, sound processing etc.

Aviation:
The Air Operation Division (AOD) uses AI for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.

Customer Service:
AI is implemented in automated online assistants and it reduces the operating and training costs for the organization. AI techniques are used in answering machines of call centers, text mining, natural language processing etc. These all techniques are used by the organization to improve the customer satisfaction.

AI is the latest rage in almost every industry. Due to its wide applications it is earning huge profits in the businesses.

Know About Machine Translation

Machine translation some times called as computer aided translation, is a component of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to other language. At the basic level Machine Translation performs simple substitution of words in one natural language for words in another, but that alone usually cannot produce a good translation of a text. Application of corpus and statistical techniques is a rapidly growing field that is leading to better translations and handles the differences in the linguistic typology.

There are many variants in the MT, most MT systems which have wider practical application have parts that can be named for the chapters in a linguistic text book. They have lexical, syntactic, morphological, and possibly semantic components, one for each of the two languages, for treating basic words, complex words, sentences and meanings. There is also a transfer component in the MT which is specialized for a particular pair of languages and converts most abstract source representation that can be achieved into a corresponding abstract target representation. Interlingua or intermediate language is present in some systems in which transfer stage is divided in to two stages, at one stage the system translates a source sentence into the interlingua and at the other stage the result obtained in the first stage is translated into an abstract representation in the target language.

Machine Translation system has wider applications and some of the examples of applications of Machine Translation system are Apertium, App Tek, Asia Online, Doc Translator, Google Translate, IdiomaX, Power Translator etc.

Data Mining and Its Uses in Different Fields

Data mining is a field of computer science which involves the process of extraction useful data from large databases by combining artificial intelligence and statistical methods with database management. Data mining has become important for modern business to transform unprecedented quantities of digital data into business intelligence. It is presently applied in wide range of profiling practices such as marketing, scientific rediscovering, surveillance and fraud detection.

Games:
The availability of oracle for certain combinatorial games with any beginning configuration has opened a new area for data mining. This is the extraction of human-usable strategies from these oracles. Current pattern recognition approaches do not seem to fully have the required high level of abstraction in order to be applied successfully.

Spatial Data Mining:
Spatial data mining is the application of data mining methods to spatial data. Data mining offers great potential benefits for applied GIS based decision making. Task of integrating these two technologies that is GIS and data mining has become critical, especially as various public and private sector organizations possessing huge databases with thematic and geographically referenced data.

Business:
Data mining when applied along with the other business applications like customer relationship management, can contribute significantly to the bottom line. Businesses employing data mining may see a return on investment, but also they recognize that the number of predictive models can quickly become very large. Data mining can also be helpful to human resources departments in identifying the characteristics of their most successful employees. Data mining also used in retail sales called as market basket analysis which is used to identify the purchase patterns of the Alpha customers.

Science and Engineering:
Data mining is very useful in the fields of science and engineering such as bio informatics, medicine, genetics, education and electrical power engineering. Data mining is very useful in the are of study on human genetics and these help to improve the diagnosis, prevention and treatment of the diseases. In the area of electrical power engineering, data mining methods have been widely used for condition monitoring of high voltage electrical equipment. Data mining is also useful in educational research and it is used to study the factors leading students to choose to engage in behaviors which reduce their learning.

Data mining is widely used in different fields. The above points clearly tell the applications of data mining in different fields.

Know about Profiling and Its Uses

Profiling is a form of dynamic program analysis and it is the process of investigation of a program's behavior using information gathered as the program executes. This analysis is performed to determine which sections of a program to optimize, that is to increase its overall speed, decrease its memory requirement or sometimes both. A profiler is a performance analysis tool that measures only the frequency and duration of function calls, but there are other specific types of profilers in addition to more comprehensive profilers. The important feature od a profiler is that, it can measure the complete behavior of a program, right from invocation to termination. Instruction set simulation, hardware interrupts, performance counters, operating system hooks, and code instrumentation are the various techniques used by profilers to collect data.

There are two types of profilers based on the out put - one is flat profiler and the other is call graph profiler.

• Flat Profiler - Flat profilers compute the average call times, from the calls, and do not break down the call times based on the callee or the context.
• Call Graph Profiler – These profilers show the call times, and frequencies of the functions, and also the call-chains involved based on the callee. But these profilers fail to preserve the content.

Uses of Profiling:
Profilers are the program analysis tools which plays an important role in understanding the program behavior.

Computer architects need such tools to evaluate how well programs will perform on new architectures.

Software writers use these tools to analyze their programs and identify critical sections of code. These tools helps the compiler writers to find out how well their instruction scheduling algorithm is performing.