Sustainable Ethnomusicology

Most ethnomusicological training requires fieldwork and lab techniques in which students gain technical skills related to the acquisition of data related to fieldwork. Although the work we do as ethnomusicologists sits at the forefront of gathering engaging, relevant content related to musical expressions, most ethnomusicologists are ill equipped in delivering their findings to a broader audience through the use of new media and post-production techniques such as video, sound, and image editing, web development, database administration, and network administration, among many others. Although plenty of literature about developing these skills exists as stand-alone instruction, in this essay I present a bird’s-eye view of content production from an ethnomusicological perspective, providing an understanding of not only content production but how intersects with revenue and ethnomusicological goals. I do so by sharing more than twenty years of experience as an IT specialist and consultant and by exploring some examples of content production at Smithsonian Folkways.

Smart Moving Vehicle Detection System

In Vehicle detection is a computer skill that determines the locations, direction and speed of running vehicles in arbitrary (digital) images. Using vehicle features and ignores anything else, such as buildings, trees and bodies. Vehicle detection is currently an active research area in the computer vision community. Automobile localization and detection are frequently the primary step in bids such as face gratitude, video observation, vehicle computer interface and image database administration. Speed and tracking vehicle shapes is a prerequisite for recognition and/or vehicle features analysis, although it is often assumed that a normalized moving vehicle image is available. Machine Learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. In this paper, a machine learning algorithm created for analyzing vehicle detection, travel direction and speed measurement.

FORMING THE CONTENTS OF THE COURSE "DATABASES AND INFORMATION SYSTEMS" FOR FUTURE INFORMATIC TEACHERS

The article is devoted to the problems of content formation and software selection for the implementation of the course "Databases and Information Systems" as a necessary component of professional training of bachelors in the specialty 014 Secondary Education (Informatics). The current needs of the country in qualified IT specialists require the formation of computer science teachers' ability to work with popular programming environments and information and communication technologies. In particular, mastering the knowledge of such an important section of ICT as databases will allow pupils to implement the tasks of automating data processing and prepare them for future professional activities. Training of bachelors in the specialty 014 Secondary Education (Informatics) at the Volodymyr Vynnychenko Central Ukrainian State Pedagogical University is carried out on the basis of an educational and professional program, a mandatory component of which includes the discipline "Databases and Information Systems" as a necessary component of training in informatics. The discipline consists of the following thematic sections. Section 1. Basic concepts and architecture of databases and database management systems. Database design. Section 2. Creating and managing a relational database. Section 3. Use of CASE-tools and work in the database management systems terminal. Procedural SQL. Section 4. Database administration. Modern directions of database development. Theoretical and practical provisions of the course from sections 1 and 2, related to the issues of architecture, design and creation of databases, it is proposed to consider the example of Microsoft Office Access. Topics from sections 3 and 4 are offered to be considered on examples of "non-educational" database management systems. Thus, the study of system aspects of SQL, user security and authorization, data protection mechanisms, data backup and recovery, and database administration, it is proposed to carry out using the CASE-tool MySQL Workbench and the client terminal of the MySQL server This program was successfully tested in 2019-2020 academic year, when teaching 3rd year students majoring in 014 Secondary Education (Mathematics), educational program: Secondary Education (Mathematics, Informatics and Economics).

VOTE: Verifiable Auditing for Outsourced Database with Token Enforced Cloud Storage

Database deploying is one of the remarkable utilities in cloud computing where the Information Proprietor (IP) assigns the database administration to the Cloud Service Provider (CSP) in order to lower the administration overhead and preservation expenditures of the database. Regardless of its overwhelming advantages, it experiences few security problems such as confidentiality of deployed database and auditability of search outcome. In recent past, survey has been carried out on the auditability of search outcome of deployed database that gives preciseness and intactness of search outcome. But in the prevailing schemes, since there is flow of data between IP and the clients repeatedly, huge communication cost is incurred at the Information Proprietor side. To address this challenge, we introduce Verifiable Auditing of Outsourced Database with Token Enforced Cloud Storage (VOTE) mechanism based on Merkle Hash Tree (MHT), Invertible Bloom Filter(IBF) and Counting Bloom Filter(CBF). The proposed scheme reduces the huge communication cost at the Information Proprietor side and achieves preciseness and intactness of the search outcome. Experimental analysis show that the proposed scheme has totally reduced the huge communication cost at the Information Proprietor side, and simultaneously achieves the preciseness and intactness of search outcome though the semi- trusted CSP deliberately sends a null set

Categorization of Data Mining Systems and Data Secrecy Towards Wireless Sensor Networks

The reliable database administration systems have actually been very vital assets for monitoring of a large corpus of data as well as particularly for reliable as well as efficient access of particular information from a huge collection whenever required. The expansion of data source monitoring systems has actually also contributed to recent huge gathering of all kind of info. This paper deals with the classification of data mining systems and also issues available in Data Mining.