The work become acquainted with history and rise databases globally. Construes philosophy structuralization, sorting and purpose using. Work further deal with concrete databases softwares intended directly to processing audio signals. Further treat of programmes that the make possible generation personal database structures. Work deal about SUSAS database and analysing its content. It is created self database of music signals, which includes several musical groups always similar in certain aspect. Speech database contains records from the SUSAS database and records from television programs, reality-shows, sports broadcasts, reports and documents, when speakers are subjected to stress and emotions. The work is a database program that can effectively classify all records and processes. The database can be freely extended. The resulting program was realized into Czech and English version.

In recent years, there has been a flood of continuously changing information from a variety of web resources such as web databases, web sites, web services and programs. Online Social Networks (OSNs) represent such a field where huge amounts of information are being posted online over time. Due to the nature of OSNs, which offer a productive source for qualitative and quantitative personal information, researchers from various disciplines contribute to developing methods for extracting data from OSNs. However, there is limited research which addresses extracting data automatically. To the best of the author's knowledge, there is no research which focuses on tracking the real time changes of information retrieved from OSN profiles over time and this motivated the present work. This thesis presents different approaches for automated Data Extraction (DE) from OSN: crawler, parser, Multi Agent System (MAS) and Application Programming Interface (API). Initially, a parser was implemented as a centralized system to traverse the OSN graph and extract the profile's attributes and list of friends from Myspace, the top OSN at that time, by parsing the Myspace profiles and extracting the relevant tokens from the parsed HTML source files. A Breadth First Search (BFS) algorithm was used to travel across the generated OSN friendship graph in order to select the next profile for parsing. The approach was implemented and tested on two types of friends: top friends and all friends. In case of top friends, 500 seed profiles have been visited; 298 public profiles were parsed to get 2197 top friends' profiles and 2747 friendship edges, while in case of all friends, 250 public profiles have been parsed to extract 10,196 friends' profiles and 17,223 friendship edges. This approach has two main limitations. The system is designed as a centralized system that controlled and retrieved information of each user's profile just once. This means that the extraction process will stop if the system fails to process one of the profiles; either the seed profile (first profile to be crawled) or its friends. To overcome this problem, an Online Social Network Retrieval System (OSNRS) is proposed to decentralize the DE process from OSN through using MAS. The novelty of OSNRS is its ability to monitor profiles continuously over time. The second challenge is that the parser had to be modified to cope with changes in the profiles' structure. To overcome this problem, the proposed OSNRS is improved through use of an API tool to enable OSNRS agents to obtain the required fields of an OSN profile despite modifications in the representation of the profile's source web pages. The experimental work shows that using API and MAS simplifies and speeds up the process of tracking a profile's history. It also helps security personnel, parents, guardians, social workers and marketers in understanding the dynamic behaviour of OSN users. This thesis proposes solutions for web database processing on data extraction from OSNs by the use of parser and MAS and discusses the limitations and improvements.

The development of system architectures and applications for smart homes and ambient assisted living has been the main activity of a number of academic and industrial research projects around the world. Existing system architectures for smart environments usually employ different architectural styles in a multi-layer logical architecture to support the integration and interoperation of heterogeneous hardware and software technologies, which are subsequently used to provide two major functionalities: monitoring and assistance. It is also usual among existing architectures that the database management system is the most common but the least exploited architectural component, existing in the periphery of the system and devoted exclusively for data storage and retrieval. However, database technology has advanced and matured considerably over the years, and, as a result, current database management systems can be and do more. This thesis considers the hypothesis of several features of modern database management systems being employed to address functional (e.g. well-being and security monitoring, automated control, data processing) and non-functional (e.g. interoperability, extensibility, data security and privacy) requirements of smart environments, i.e. the database management system serves as a platform for smart environments. The scope of this thesis is therefore to investigate the possibility of using different features supported by database management systems to create a database-centric system architecture for the development of smart home environments and ambient assisted living. The thesis also investigates the development of applications for health monitoring and assistance: 1) a serious game for fall prevention that assists people in practicing Tai Chi at home, and 2) a non-intrusive home-based method for sleep assessment. These features are explored in this thesis to address general functional aspects of smart environments, such as monitoring, processing, coordination and control of various types of events in a given environment. Extensibility and security features and cross-platform capabilities of database management systems are employed to accommodate non-functional, but still technical, properties of smart environments, including interoperability, extensibility, portability, scalability, security and privacy. Heterogeneous technologies are integrated into the system using programming language and platform independent software resource adapters. Interoperation among integrated technologies is mediated in an active database. The feasibility of the proposed database-centric system architecture was pragmatically investigated with the development of a "smart bedroom'' demonstrator and with the implementation of a number of short-term and long-term types of services to support active aging, aging in place and ambient assisted living. In the proposed architecture, active in-database processing maintains sensitive data within the database. This increases data security and independence from external software applications for data analysis. Changes in the system are managed during runtime, which improves flexibility and avoids system downtime. The proposed system architecture was evaluated taking into account different application scenarios and heterogeneous computing platforms. As a conclusion, modern database management systems support features that can be successfully employed in a database-centric system architecture to effectively and efficiently address functional and non-functional requirements of smart environments.

In recent years, there has been a ood of continuously changing information from a variety of web resources such as web databases, web sites, web services and programs. Online Social Networks (OSNs) represent such a eld where huge amounts of information are being posted online over time. Due to the nature of OSNs, which o er a productive source for qualitative and quantitative personal information, researchers from various disciplines contribute to developing methods for extracting data from OSNs. However, there is limited research which addresses extracting data automatically. To the best of the author's knowledge, there is no research which focuses on tracking the real time changes of information retrieved from OSN pro les over time and this motivated the present work. This thesis presents di erent approaches for automated Data Extraction (DE) from OSN: crawler, parser, Multi Agent System (MAS) and Application Programming Interface (API). Initially, a parser was implemented as a centralized system to traverse the OSN graph and extract the pro- le's attributes and list of friends from Myspace, the top OSN at that time, by parsing the Myspace pro les and extracting the relevant tokens from the parsed HTML source les. A Breadth First Search (BFS) algorithm was used to travel across the generated OSN friendship graph in order to select the next pro le for parsing. The approach was implemented and tested on two types of friends: top friends and all friends. In case of top friends, 500 seed pro les have been visited; 298 public pro les were parsed to get 2197 top friends pro les and 2747 friendship edges, while in case of all friends, 250 public pro les have been parsed to extract 10,196 friends' pro les and 17,223 friendship edges. This approach has two main limitations. The system is designed as a centralized system that controlled and retrieved information of each user's pro le just once. This means that the extraction process will stop if the system fails to process one of the pro les; either the seed pro le ( rst pro le to be crawled) or its friends. To overcome this problem, an Online Social Network Retrieval System (OSNRS) is proposed to decentralize the DE process from OSN through using MAS. The novelty of OSNRS is its ability to monitor pro les continuously over time. The second challenge is that the parser had to be modi ed to cope with changes in the pro les' structure. To overcome this problem, the proposed OSNRS is improved through use of an API tool to enable OSNRS agents to obtain the required elds of an OSN pro le despite modi cations in the representation of the pro le's source web pages. The experimental work shows that using API and MAS simpli es and speeds up the process of tracking a pro le's history. It also helps security personnel, parents, guardians, social workers and marketers in understanding the dynamic behaviour of OSN users. This thesis proposes solutions for web database processing on data extraction from OSNs by the use of parser and MAS and discusses the limitations and improvements. / Taibah University