Explain multimedia database in brief. What are the different applications of multimedia database?

-

 Multimedia Database 

A Multimedia database is the collection of interrelated multimedia data that includes text, graphics (sketches, drawings), images, animations, video, audio, etc., and has vast amounts of multisource multimedia data. The framework that manages different types of multimedia data which can be stored, delivered, and utilized in different ways is known as a multimedia database management system.

Multimedia databases provide features that allow users to store and query different types of multimedia information, which includes images (such as photos or drawings), video clips (such as movies, newsreels, or home videos), audio clips (such as songs, phone messages, or speeches), and documents (such as books or articles). The main types of database queries that are needed involve locating multimedia sources that contain certain objects of interest. For example, one may want to locate all video clips in a video database that includes a certain person, say Michael Jackson. One may also want to retrieve video clips based on certain activities included in them, such as video clips where a soccer goal is scored by a certain player or team. The contents of a multimedia database management system can be:
Media data: It is the actual data that represents an object. Media format data: The information such as resolution, sampling rate, encoding system, etc. about the format of the media data under consideration after it undergoes acquisition, processing, and encoding is the media format data.

Media keyword data: Media keyword data are the keyword description related to the generation of data. This data is also known as content descriptive data. Examples of content descriptive data are place, time, and date of recording.

Media feature data: Media feature data contains data that is content dependent such as kind of texture, distribution, and the different shapes present in the data.

Multimedia Database Applications

Documents and record management: Industries that keep a lot of documentation and records. Ex: Insurance claim industry.

Knowledge dissemination: Multimedia database is an extremely efficient tool for knowledge dissemination and providing several resources. Ex: electronic books

Education and training: Multimedia sources can be used to create resources useful in education and training. These are popular sources of learning in recent days. Ex: Digital libraries.

Real-time monitoring and control: Multimedia presentation when coupled with active database technology can be an effective means for controlling and monitoring complex tasks. Ex: Manufacture control

  1. Marketing
  2. Advertisement
  3. Retailing
  4. Entertainment
  5. Travel


Comments

Post a Comment

Popular posts from this blog

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

-
Image
a) A Snowflake Shema is shown in figure below: b) The specific OLAP operations to be performed: 1. Roll-up on course from course_id to department. 2. Roll-up on a student from student_id to university. 3. Dice on course, student with department ="CS" and university = "biguniversity" 4. Drill-down on a student from the university to student_name. c) N = 4 dimensions The cube will contain 54 = 625 cuboids.
Read more

Describe how cloud computing technology can be applied to support remote ECG monitoring.

-
Image
  Healthcare: ECG (Electrocardiogram) Analysis in cloud computing Healthcare is a field, subject, sector, or territory in which information technology has several uses. These apps are being used to aid businesses in supporting scientists in developing disease prevention solutions. Cloud computing has emerged as an appealing alternative for constructing health monitoring systems as a result of the development of the Internet or to put it another way, as a result of the availability of the internet. The ECG machine, for example, is a health monitoring device that measures the human body's heartbeat and prints the results on graph paper. The electrocardiogram (ECG) measures the electrical activity of the heart's Cardium. A waveform is created as a result of this action, which is repeated throughout time and symbolizes the heartbeat.  The analysis of the shape is used to identify arrhythmias, and it is the most common way of detecting heart diseases. Here the meaning of arrhythmias
Read more

Explain market-Oriented Cloud computing architecture.

-
Image
  Market Oriented Cloud Computing (Mocc) As customers rely on Cloud providers to cover all of their computing needs, they will expect certain Qe from their providers to fulfill their objectives and continue their operations. Cloud providers must examine and satisfy the various QoS standards of each unique consumer as stipulated in unique SLAs. To do this, cloud providers cannot continue to install traditional system-centric resource management architectures that do not give incentives for them to share their resources while still treating all service requests as equal insignificance. Instead, market-oriented resource management is required to maintain the supply and demand for Cloud resources at market equilibrium, provide feedback in the form of economic incentives for both Cloud consumers and providers, and promote QoS-based resource allocation mechanisms that differentiate service requests based on their utility. The diagram depicts a high-level architecture for enabling market-orie
Read more