Main Memory database systems store data primarily in main memory for faster access compared to disk-based systems. The T tree is proposed as an index structure for main memory databases that provides fast search, insert and delete performance while using relatively little memory space. The Dali storage manager is designed for main memory databases and provides persistence, availability and recovery guarantees similar to disk-based databases through the use of logging, locking, checkpointing and other techniques while leveraging the speed of main memory.
Denormalization involves transforming normalized database relations into unnormalized physical tables to improve performance. This is done by reducing the number of necessary joins. While it improves speed, it also risks data duplication, wasted storage, and integrity issues. Common situations for denormalization include one-to-one relationships, many-to-many relationships with attributes, and reference data. Physical files are portions of disk storage allocated for storing records. File organization techniques determine how records are physically arranged, such as sequentially or through indexing, and affect retrieval speed, storage usage, and data protection.
Data Never Lies Presentation for beginners in data field.pptxTusharAgarwal49094
This document provides an overview of data concepts including:
1. It explores core data concepts such as structured, semi-structured, and unstructured data.
2. It examines roles and responsibilities in data including database administrators.
3. Key concepts of relational data are described like tables, normalization, and indexes.
4. Non-relational data types like key-value stores and document databases are explored.
5. Data analytics concepts such as data ingestion, processing, ETL, and visualization techniques are covered.
This document discusses database management systems and contains slides related to external data storage, file organization, indexing, and performance comparisons. Specifically, it provides information on different file organizations like heap files, sorted files, and indexed files. It also describes index structures like B+ trees and hash indexes. The slides provide comparisons of the cost of common operations like scans, searches, and updates between different file organization approaches.
This document discusses file structure and organization. It defines what a file is and different types of file organization including sequential, hashed/direct access, and indexed sequential access.
It also covers logical vs physical files, basic file operations, record types, indexing, and different index types like primary, secondary, dense, sparse, and clustered indexes. Indexing improves query performance but decreases performance for insert/update/delete operations due to additional space required.
This document discusses different methods for organizing and indexing data stored on disk in a database management system (DBMS). It covers unordered or heap files, ordered or sequential files, and hash files as methods for physically arranging records on disk. It also discusses various indexing techniques like primary indexes, secondary indexes, dense vs sparse indexes, and multi-level indexes like B-trees and B+-trees that provide efficient access to records. The goal of file organization and indexing in a DBMS is to optimize performance for operations like inserting, searching, updating and deleting records from disk files.
This document discusses different types of file organization methods. It describes sequential file organization methods like pile file and sorted file. It also covers hash file organization, B+ tree file organization, indexed sequential access method (ISAM), and cluster file organization. The B+ tree method stores records only at leaf nodes and uses intermediate nodes as pointers to efficiently access records based on a primary key. Cluster file organization stores related records from multiple tables in the same data block to reduce joining costs.
This document discusses different file organization and indexing techniques for databases. It begins by describing common operations like scans, searches, inserts and deletes. It then outlines three main file organization techniques: heap files, sorted files using tree-based indexing, and hash-based indexing. For each technique, it provides the cost in terms of disk I/O for the different operations. It also discusses concepts like primary and secondary indices, dense vs sparse indexing, and multilevel indexing. The document provides examples and diagrams to illustrate these concepts.
Main Memory database systems store data primarily in main memory for faster access compared to disk-based systems. The T tree is proposed as an index structure for main memory databases that provides fast search, insert and delete performance while using relatively little memory space. The Dali storage manager is designed for main memory databases and provides persistence, availability and recovery guarantees similar to disk-based databases through the use of logging, locking, checkpointing and other techniques while leveraging the speed of main memory.
Denormalization involves transforming normalized database relations into unnormalized physical tables to improve performance. This is done by reducing the number of necessary joins. While it improves speed, it also risks data duplication, wasted storage, and integrity issues. Common situations for denormalization include one-to-one relationships, many-to-many relationships with attributes, and reference data. Physical files are portions of disk storage allocated for storing records. File organization techniques determine how records are physically arranged, such as sequentially or through indexing, and affect retrieval speed, storage usage, and data protection.
Data Never Lies Presentation for beginners in data field.pptxTusharAgarwal49094
This document provides an overview of data concepts including:
1. It explores core data concepts such as structured, semi-structured, and unstructured data.
2. It examines roles and responsibilities in data including database administrators.
3. Key concepts of relational data are described like tables, normalization, and indexes.
4. Non-relational data types like key-value stores and document databases are explored.
5. Data analytics concepts such as data ingestion, processing, ETL, and visualization techniques are covered.
This document discusses database management systems and contains slides related to external data storage, file organization, indexing, and performance comparisons. Specifically, it provides information on different file organizations like heap files, sorted files, and indexed files. It also describes index structures like B+ trees and hash indexes. The slides provide comparisons of the cost of common operations like scans, searches, and updates between different file organization approaches.
This document discusses file structure and organization. It defines what a file is and different types of file organization including sequential, hashed/direct access, and indexed sequential access.
It also covers logical vs physical files, basic file operations, record types, indexing, and different index types like primary, secondary, dense, sparse, and clustered indexes. Indexing improves query performance but decreases performance for insert/update/delete operations due to additional space required.
This document discusses different methods for organizing and indexing data stored on disk in a database management system (DBMS). It covers unordered or heap files, ordered or sequential files, and hash files as methods for physically arranging records on disk. It also discusses various indexing techniques like primary indexes, secondary indexes, dense vs sparse indexes, and multi-level indexes like B-trees and B+-trees that provide efficient access to records. The goal of file organization and indexing in a DBMS is to optimize performance for operations like inserting, searching, updating and deleting records from disk files.
This document discusses different types of file organization methods. It describes sequential file organization methods like pile file and sorted file. It also covers hash file organization, B+ tree file organization, indexed sequential access method (ISAM), and cluster file organization. The B+ tree method stores records only at leaf nodes and uses intermediate nodes as pointers to efficiently access records based on a primary key. Cluster file organization stores related records from multiple tables in the same data block to reduce joining costs.
This document discusses different file organization and indexing techniques for databases. It begins by describing common operations like scans, searches, inserts and deletes. It then outlines three main file organization techniques: heap files, sorted files using tree-based indexing, and hash-based indexing. For each technique, it provides the cost in terms of disk I/O for the different operations. It also discusses concepts like primary and secondary indices, dense vs sparse indexing, and multilevel indexing. The document provides examples and diagrams to illustrate these concepts.
Relational databases allow data to be stored and linked across multiple tables. This structured format makes the data more organized, avoids duplications, and enables complex queries across different aspects of the data. The key components are tables with unique identifiers, relationships between tables established through common fields, and queries to extract specific data combinations. Proper database design upfront is important to ensure the tables and relationships accurately capture and connect all the relevant entities and attributes in the study.
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This document discusses how databases physically organize and access data through different file organizations and indexing methods. It describes three main file organizations (heap, ordered, and hash files), how each supports insert, search, and delete operations, and when each performs best. It also explains what indexing is, different index types like primary and secondary indexes, and how to create indexes using SQL. The document aims to explain how databases optimize data storage and access.
files,indexing,hashing,linear and non linear hashingRohit Kumar
The document discusses different file organization techniques used in database management systems (DBMS) to store data on hard disks. It describes three main types of file organization - unordered or heap files, ordered or sequential files, and hash files. For each type, it explains how record insertion, searching, and deletion operations are performed, and the relative speeds of each operation for the different file organization methods. It also discusses indexing techniques like primary and secondary indexing that can be used to improve search performance.
This document provides an overview of database management systems. It defines key database concepts like entities, fields, records and tables. It describes different database models like hierarchical, network, relational and object-oriented models. It also explains relational database structures, the role of a database management system, querying databases using SQL, and common database functions like creating tables, sorting records, generating reports and database normalization.
CS101- Introduction to Computing- Lecture 37Bilal Ahmed
This document discusses database software and relational databases. It begins by focusing on issues with data management as the amount of data increases. Relational databases are introduced as a way to organize large amounts of interrelated data across multiple tables that can be queried. Examples of database management software are provided. The document then demonstrates creating related tables to store book inventory and customer order data. It discusses how a report can be generated by combining data from these tables. Finally, an assignment is provided to design a database with two tables, populate them with data, and generate a report.
This document discusses key concepts in relational database design and management. It defines relational databases as storing data in tables that are associated through shared attributes. It also describes entities, attributes, primary keys, foreign keys, and relationships. Database normalization is introduced as a process to minimize duplication and inconsistencies by breaking tables into multiple tables and defining relationships between them. Common database operations like create, read, update, and delete are also summarized.
This document provides an overview of basic concepts in databases including:
1. It defines what a database is and examples of databases like a phone book. It also defines what a database refers to in computers as a collection of organized data.
2. It explains the functions of a database to store, delete, organize, use and present data. It provides an example of data stored in an Access database.
3. It defines what a DBMS is and its purpose to create, manage and query databases. It lists examples of common DBMS like Microsoft Access, MySQL, and Oracle.
4. It outlines different database models including hierarchical, network, object-oriented, and relational models and provides examples
1. Carefully check the sampling process and ensure the right population is being sampled.
2. Thoroughly prepare the questionnaire and pilot test it to fix any issues.
3. Use competent and well-trained staff for data collection and processing.
4. Provide respondents with adequate information to improve response accuracy.
overview of storage and indexing BY-Pratik kadam pratikkadam78
The document provides an overview of storage and indexing in databases. It discusses how data is stored on external storage devices like disks and tapes. It also describes different file organizations like heap files and cluster files that arrange records on storage. Finally, it covers indexing, explaining that indexes allow efficient retrieval of records based on key fields and common types of indexes include primary, secondary, and clustering indexes.
The document discusses physical database design, including:
- Designing fields by choosing data types, coding techniques, and controlling data integrity.
- Denormalizing relations through joining tables or data replication to improve processing speed at the cost of storage space and integrity.
- Organizing physical files through sequential, indexed, or hashed arrangements and using indexes to efficiently locate records.
- Database architectures including legacy systems, current technologies, and data warehouses.
Lec20.pptx introduction to data bases and information systemssamiullahamjad06
The document provides an overview of databases and information systems. It defines what a database is, how data is organized in a hierarchy from bits to files, and the different types of database models including hierarchical, network, and relational. It also discusses how structured query language and query by example are used to retrieve data in relational databases. Finally, it outlines different types of computer-based information systems used in organizations like transaction processing systems, management information systems, and decision support systems.
Types of data in a database include internal and external data. Business intelligence in law enforcement uses data to help pinpoint crime patterns and allocate manpower. Database files can be accessed sequentially, randomly, or through indexed sequential access. The logical and physical views of databases differ in how data is organized and retrieved by users. Common database models include hierarchical, network, and relational models.
This chapter discusses data design concepts and structures. It explains key data design terminology like entities, fields, records and files. Different data models are covered, including relational and object-oriented databases. The chapter also describes logical and physical data storage, data coding, data warehousing, and security controls for databases.
UNIT machine learning unit 1,algorithm pdfOmarFarooque9
This document provides an introduction to database management systems. It defines key concepts like data, databases, and file processing systems. It describes the disadvantages of file processing systems like data redundancy, inconsistency, isolation, and integrity and security issues. It then contrasts file processing systems with database management systems, which aim to address those disadvantages. The document discusses different types of databases and data models, including relational, entity-relationship, object-based, and semi-structured models. It also covers database architecture, data abstraction, and DBMS components.
Good database design involves structuring data to minimize duplication and inconsistencies through a process called normalization. In normalization, data is broken into multiple tables that are linked through relationships. The three main types of database relationships are one-to-one, one-to-many, and many-to-many. Primary and foreign keys are used to define these relationships and ensure referential integrity between tables. Structured Query Language (SQL) provides commands to define, manipulate, and query data in a relational database.
This presentation gives an overview of Databases and Term used in used in Databases Aspect. It also, help you to understand the clear description of Database Learning. Best Suited for Beginners and advanced level learners.
This document discusses different methods for organizing data, including non-computerized and computerized databases. It describes flat file databases which organize data into tables with records and fields. Relational databases organize data into linked tables with entities, attributes, and relationships. The document also discusses data modeling, schemas, entity relationship diagrams, and hypermedia including hyperlinks and storyboards.
Relational databases allow data to be stored and linked across multiple tables. This structured format makes the data more organized, avoids duplications, and enables complex queries across different aspects of the data. The key components are tables with unique identifiers, relationships between tables established through common fields, and queries to extract specific data combinations. Proper database design upfront is important to ensure the tables and relationships accurately capture and connect all the relevant entities and attributes in the study.
Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsaDsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexing content for dsa dsa Dsa data indexing content for dsa dsa dsa Dsa data indexing content for dsa dsa Dsa data indexing content Dsa data indexin
This document discusses how databases physically organize and access data through different file organizations and indexing methods. It describes three main file organizations (heap, ordered, and hash files), how each supports insert, search, and delete operations, and when each performs best. It also explains what indexing is, different index types like primary and secondary indexes, and how to create indexes using SQL. The document aims to explain how databases optimize data storage and access.
files,indexing,hashing,linear and non linear hashingRohit Kumar
The document discusses different file organization techniques used in database management systems (DBMS) to store data on hard disks. It describes three main types of file organization - unordered or heap files, ordered or sequential files, and hash files. For each type, it explains how record insertion, searching, and deletion operations are performed, and the relative speeds of each operation for the different file organization methods. It also discusses indexing techniques like primary and secondary indexing that can be used to improve search performance.
This document provides an overview of database management systems. It defines key database concepts like entities, fields, records and tables. It describes different database models like hierarchical, network, relational and object-oriented models. It also explains relational database structures, the role of a database management system, querying databases using SQL, and common database functions like creating tables, sorting records, generating reports and database normalization.
CS101- Introduction to Computing- Lecture 37Bilal Ahmed
This document discusses database software and relational databases. It begins by focusing on issues with data management as the amount of data increases. Relational databases are introduced as a way to organize large amounts of interrelated data across multiple tables that can be queried. Examples of database management software are provided. The document then demonstrates creating related tables to store book inventory and customer order data. It discusses how a report can be generated by combining data from these tables. Finally, an assignment is provided to design a database with two tables, populate them with data, and generate a report.
This document discusses key concepts in relational database design and management. It defines relational databases as storing data in tables that are associated through shared attributes. It also describes entities, attributes, primary keys, foreign keys, and relationships. Database normalization is introduced as a process to minimize duplication and inconsistencies by breaking tables into multiple tables and defining relationships between them. Common database operations like create, read, update, and delete are also summarized.
This document provides an overview of basic concepts in databases including:
1. It defines what a database is and examples of databases like a phone book. It also defines what a database refers to in computers as a collection of organized data.
2. It explains the functions of a database to store, delete, organize, use and present data. It provides an example of data stored in an Access database.
3. It defines what a DBMS is and its purpose to create, manage and query databases. It lists examples of common DBMS like Microsoft Access, MySQL, and Oracle.
4. It outlines different database models including hierarchical, network, object-oriented, and relational models and provides examples
1. Carefully check the sampling process and ensure the right population is being sampled.
2. Thoroughly prepare the questionnaire and pilot test it to fix any issues.
3. Use competent and well-trained staff for data collection and processing.
4. Provide respondents with adequate information to improve response accuracy.
overview of storage and indexing BY-Pratik kadam pratikkadam78
The document provides an overview of storage and indexing in databases. It discusses how data is stored on external storage devices like disks and tapes. It also describes different file organizations like heap files and cluster files that arrange records on storage. Finally, it covers indexing, explaining that indexes allow efficient retrieval of records based on key fields and common types of indexes include primary, secondary, and clustering indexes.
The document discusses physical database design, including:
- Designing fields by choosing data types, coding techniques, and controlling data integrity.
- Denormalizing relations through joining tables or data replication to improve processing speed at the cost of storage space and integrity.
- Organizing physical files through sequential, indexed, or hashed arrangements and using indexes to efficiently locate records.
- Database architectures including legacy systems, current technologies, and data warehouses.
Lec20.pptx introduction to data bases and information systemssamiullahamjad06
The document provides an overview of databases and information systems. It defines what a database is, how data is organized in a hierarchy from bits to files, and the different types of database models including hierarchical, network, and relational. It also discusses how structured query language and query by example are used to retrieve data in relational databases. Finally, it outlines different types of computer-based information systems used in organizations like transaction processing systems, management information systems, and decision support systems.
Types of data in a database include internal and external data. Business intelligence in law enforcement uses data to help pinpoint crime patterns and allocate manpower. Database files can be accessed sequentially, randomly, or through indexed sequential access. The logical and physical views of databases differ in how data is organized and retrieved by users. Common database models include hierarchical, network, and relational models.
This chapter discusses data design concepts and structures. It explains key data design terminology like entities, fields, records and files. Different data models are covered, including relational and object-oriented databases. The chapter also describes logical and physical data storage, data coding, data warehousing, and security controls for databases.
UNIT machine learning unit 1,algorithm pdfOmarFarooque9
This document provides an introduction to database management systems. It defines key concepts like data, databases, and file processing systems. It describes the disadvantages of file processing systems like data redundancy, inconsistency, isolation, and integrity and security issues. It then contrasts file processing systems with database management systems, which aim to address those disadvantages. The document discusses different types of databases and data models, including relational, entity-relationship, object-based, and semi-structured models. It also covers database architecture, data abstraction, and DBMS components.
Good database design involves structuring data to minimize duplication and inconsistencies through a process called normalization. In normalization, data is broken into multiple tables that are linked through relationships. The three main types of database relationships are one-to-one, one-to-many, and many-to-many. Primary and foreign keys are used to define these relationships and ensure referential integrity between tables. Structured Query Language (SQL) provides commands to define, manipulate, and query data in a relational database.
This presentation gives an overview of Databases and Term used in used in Databases Aspect. It also, help you to understand the clear description of Database Learning. Best Suited for Beginners and advanced level learners.
This document discusses different methods for organizing data, including non-computerized and computerized databases. It describes flat file databases which organize data into tables with records and fields. Relational databases organize data into linked tables with entities, attributes, and relationships. The document also discusses data modeling, schemas, entity relationship diagrams, and hypermedia including hyperlinks and storyboards.
This document provides an overview of key concepts related to information systems. It defines data, information, and knowledge, explaining how data is transformed into information and knowledge. It also defines what a system is and its typical components. Different types of information systems are described, including transaction processing systems, ERP, MIS, DSS, and expert systems. The development of information systems is discussed, outlining typical development steps. Lastly, it covers strategic information systems and how organizations can use systems to achieve competitive advantages.
The document summarizes an electrical safety workshop that covers:
- How electric current can affect the body at both low and high amp levels.
- The legal duties and obligations around electricity safety.
- Basic electrical safety precautions.
- A demonstration circuit diagram and procedure for wiring a simple house circuit and testing it, to teach students practical wiring skills and safety.
The document discusses electrical safety devices and their importance. It describes how safety features like insulators and circuit breakers help isolate faulty circuits to prevent fires from short circuits. The key safety devices discussed are fuses, circuit breakers, and earthing. Fuses and circuit breakers help protect against overcurrent while earthing protects against leakage current. The document explains how these devices work to rapidly detect faults and shut off power to protect people and equipment.
The document discusses basic electrical tools, wires, cables, and connectors. It provides details on common tools like pliers, screwdrivers, hammers and their uses. It also describes different types of wires like solid core, stranded, and braided wires. Various cable types are explained including paired, twisted, coaxial and fiber optic cables. Finally, common electrical connectors like 110-volt, banana, barrier strip and alligator connectors are mentioned. The goal is to understand electrical components and their applications.
The document discusses electrical safety, hazards, and precautions. It covers how electric current affects the body, risks from electricity, legal duties, and basic safety steps. The key points are: electric current between 1mA-16mA can cause shocks, those most at risk are maintenance and construction workers, employers have a duty to maintain safe electrical systems, and basic safety includes using the right equipment, maintenance, secure wiring, switching off tools before handling, and competent work.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
2. 2
The Name of the Game
• Information is a valuable resource.
• It is expensive to collect, maintain, and use.
• The goal of database management it to
– maximize the benefits gained from information
• maximize the accuracy of information
– minimize the costs associated with information
3. 3
Keeping Track of Things
• Entity - person, place, thing or event on
which we maintain information.
• Attribute - A single piece of information
describing a particular entity.
4. 4
Data Hierarchy
• Database - a collection of related files
• File - a collection of uniform records
• Record - a collection of related fields
• Field - a collection of bytes
• Byte (& words)
• Bit
6. 6
Key Field(Attribute)
• A key field is an attribute that uniquely
identifies a record in a file.
– Examples: SSN, NAID
• The values in the key field MUST be
unique.
• It is possible to use several fields to form a
composite key.
– Example: Lastname + firstname + middlename
7. 7
Natural Keys
• It is convenient and desirable to use
attributes which “naturally occur” with an
entity as a key.
• Example - most students have a SSN by the
time they enroll at HU, so the SSN would
be natural key.
8. 8
Accessing Information
• Lookup items(records) by the value of their
key.
• Methods of access:
– Sequential Access
– Direct Access
– Indexed Sequential Access
9. 9
Ordered vs. Unordered
• A database file (collection of records) may
be:
• ordered - physically arranged in the file so
that the key field increases (or decreases) in
a sequential fashion.
• unordered - physically arranged in the file
so the key field has no ordered relation with
the preceding or succeeding key.
10. 10
Costs & Benefits of Ordering
• “In general” a record can be found faster in
an ordered list than in an unordered list.
– I’ll use the term file & list interchangeably.
• “In general” you can turn an unordered list
into an ordered list by sorting.
• Sorting is a cost of keeping a list ordered.
• In this course we will generally be dealing
with ordered lists.
11. 11
Sequential Access
• Look at key of first record in file,
• if not the target then look at next record,
• if not the target then look at next record, …
• If file has N records on average will have to
look at N/2 records to find a random target.
• Question - Why not just “skip over” some
of the records?
12. 12
Sequential Access
• An employee database might use SSN as
the key field.
• If the target SSN is 540-12-3763, and
• the first record SSN is 120-11-0007, then
• how many records should you skip?
• This is why sequential access has to look at
every record.
13. 13
Sequential Access
• Historically data was stored on tapes.
• Tapes store information sequentially and
“only” allow for sequential access.
• DASD (disks drives) can also store files
sequentially. Files are written to the disk
track-by-track, cylinder-by-cylinder in a
“physically contiguous” fashion.
14. 14
Direct Access
• Direct access means that given a value for
the key attribute the system can move
“directly” to the corresponding record
without having to look at an intervening
records in the file.
• Direct access requires that the system
“know” the physical location of the target
record on the disk.
15. 15
Hashing Algorithms
• To find the physical location on the disk a
computation is performed on the key value
which yields a “unique” physical address
for the corresponding record.
• Perfect hashing algorithms get you to a
unique address.
• Imperfect algorithms may hash several keys
to the same address.
16. 16
Hashing Example
• Suppose that I were using SSN as the key
and wanted to keep track of 100 entities.
• Select 101 (a prime number closest to the
number of records) and divide this into the
SSN.
• Remainder will always be a number
between 0 and 100.
17. 17
Hashing Example
• The remainder represents the disk address.
– A remainder of 52 could represent
– cylinder 5, surface 2
• If two or more SSNs have the same
remainder (hash to the same address) this is
called a collision. Essentially these records
are then searched sequentially.
18. 18
Direct Access Note
• The physical addresses in Direct Access
have no relation to the sequential “order” of
the keys.
• For any two adjacent sequential keys there
is no guarantee about the relationship
between their physical locations on the disk,
they may not be “physically contiguous”.
19. 19
Sequential vs. Direct Access
• Sequential Access
– good when you want to process all records in
key order, next record is always ready to be
read/written.
• Direct Access
– good when you want to process records in a
random order, next record can be found
directly.
20. 20
Indexed Sequential Access
Method (ISAM)
• Combines a sequential file with one or more
levels of indexes.
• Each index relates a physical location to the
highest key value stored in that location.
• You find physical location by looking in
each level of the index and then sequentially
searching the last physical location.
21. 21
ISAM
• In the library the books are laid out
sequentially by call number (the key).
• Look at floor index to determine the floor
• Look at shelf index to determine the shelf
• Sequentially search the shelf
22. 22
ISAM
• ISAM tries to give the best of both worlds.
• When you want to process items
sequentially you have an underlying
sequential file.
• When you want direct access you go
through the indexes to get close, then a
“small” sequential search at end.
23. 23
Traditional File Systems
• Also called:
– flat file organization
– data file approach
• Typically an organization or a department
within an organization would develop their
applications and associated data files in an
independent fashion.
24. 24
Problems with Traditional Files
• Data Redundancy
– conflicting data
• Program-Data Dependence
– lack of flexibility
• Lack of Data Sharing
– no common names for attributes & entities
• Poor Security
25. 25
DBMS Approach
• Database Management Systems approach
places a common interface between the
users of data (the application programs) and
the data files.
26. 26
DBMS Components
• Data Definition Language, DDL
• Data Manipulation Language, DML
– Structured Query Language, SQL
• Data Dictionary, DD
27. 27
Logical & Physical Views
• Logical View
– how the user sees the data
• Physical View
– how the data is physically saved on the storage
media
• The DBMS gives each user their own
logical view while storing the data using a
single physical view.
28. 28
Advantages of DBMS
• Complexity & Confusion reduced
– all data stored in single centralized physical
view
• Data redundancy & inconsistency reduced
– data dictionary shows what data elements are
available, data element only present “once”
• Program-data dependence reduced
– each user can get desired logical view
29. 29
Advantages of DBMS
• Security
– single point of access to data
• Reduced cost
– initial purchase cost of DBMS and related staff
are high, but savings in future development and
maintenance usually offset these costs
– Access & Flexibility
– DML usually provides easier access to data
32. 32
Hierarchical Data Model
• Data records are broken into segments
• Each segment contains some attributes
• Segments are arranged into a hierarchical
“tree-like” structure
• Physical locations pointers join related
segments into records
• Child segments can only have one parent
36. 36
Relating Fields
A1 Author 1
A2 Author 2
A3 Author 3
Book 1 A1 P1
Book 2 A3 P2
Book 3 A2 P2
Book 4 A1 P2
Book 5 A1 P1
P1 Publisher 1
P2 Publisher 2
37. 37
Relating Fields
A1 Author 1
A2 Author 2
A3 Author 3
Book 1 A1 P1
Book 2 A3 P2
Book 3 A2 P2
Book 4 A1 P2
Book 5 A1 P1
P1 Publisher 1
P2 Publisher 2
38. 38
Relational Data Model
ID Publisher
P1 Publisher 1
P2 Publisher 2
ID Author
A1 Author 1
A2 Author 2
A3 Author 3
Publisher-table
Author-table
Title AID PID
Book 1 A1 P1
Book 2 A3 P2
Book 3 A2 P2
Book 4 A1 P2
Book 5 A1 P1
Book-table
39. 39
Relational Data Model
• Data Records are broken into segments
• Each segment contains some attributes
• Segments are arranged in tables
• There are NO “physical” location pointers
between tables
• Relations between tables are “implied” by
relating fields
40. 40
Relations Generated When Asked
• Relationships between segments are not
predefined by pointers in the relational
model.
• Tables are JOINed together to display
relationships.
• JOINs occur at query time.
• Tables must have a common data element to
be joined.
41. 41
Example JOIN
Select
Author, Title, Publisher
FROM
Author-table, Book-table, Publisher-table
WHERE
Author-table.ID = Book-table.AID, and
Book-table.PID = Publisher-table.ID
42. 42
Results of Join
Author Title Publisher
Author 1 Book 1 Publisher 1
Author 1 Book 4 Publisher 2
Author 1 Book 5 Publisher 1
Author 2 Book 3 Publisher 2
Author 3 Book 4 Publisher 2
Answer-table
43. 43
Relational Model Operations
• Selection
– select which rows to display
• Projection
– select which columns to display
• Join
– combine two or more tables
45. 45
Name of the game
• Using the relational model,
• Represent each type of relationship
– as simply as possible (using the fewest tables),
– with a minimum of duplicated data, and
– with a minimum of wasted space (empty fields)
46. 46
Tables needed for 1-1
Author Title
Author1 Book1
Author2 Book2
Author3 Book3
Book
47. 47
Tables needed for 1-n
ID Name
1 Author1
2 Author2
3 Author3
Author
ID Title
1 Book1
1 Book2
2 Book3
3 Book4
2 Book5
Book
48. 48
Tables needed for n-n
ID Name
1 Author1
2 Author2
3 Author3
AID BID
1 1
1 2
2 1
2 2
3 1
3 5
3 4
1 5
2 5
ID Title
1 Book1
2 Book2
3 Book3
4 Book4
5 Book5
Author
Book
Writes
49. 49
Advantages & Disadvantages
• Hierarchical & Network Data Models
– faster for “pre-defined” queries
– slower for ad-hoc queries
– inflexible, more expensive to maintain
• Relational Data Models
– flexible, less expensive to maintain
– most queries require joins and are slower than
“pre-defined” queries mentioned above
50. 50
Entity-relationship diagram
• A conceptual model useful in database
design.
• Illustrates the relationships between various
entities in the database.
• Entities are represented by rectangles.
• Relationships represented by diamonds.
• Attributes can be assigned to both entities
and relationships.
52. 52
Centralized Database
• All database files are stored on a central
computer.
• All database processing is performed by the
central computer.
• Problems
– can overload central system
– not very fault tolerant
– communications costs can be high
53. 53
Distributed Databases
• Distributed Processing
– processing is performed locally by processors
connected by a communications network.
• Distributed Databases
– the physical files that make up the database are
stored in more than one location
54. 54
Distributed Databases
• Duplicate Database
– each location has its own copy of the entire
database.
• Partitioned Database
– each location has a copy of the portion of the
database that it needs.
55. 55
Distributed Databases
• Central Index
– Records are stored locally, but a centralized
index is maintained to quickly located any
record.
• Ask-the-network
– Records are stored locally and the network
must be polled each time a record is needed.
56. 56
Data Warehousing
• A database with associated reporting and
query tools,
• that stores current and historical data
extracted from various operational systems
• and consolidated for management reporting
and analysis.
57. 57
A Data Warehouse...
• Sits on top of existing isolated legacy
systems, “islands of information”, to
provide an enterprise-wide database.
• Provides single platform, standardized
access to current operational data and
historical data (not normally maintained on
legacy systems).
58. 58
Obstacles to Database
Implementation
• Organizational
– structural changes
– political changes
• Cost/benefit considerations
• Placement of Data Management Function
– need data administration and planning at
highest possible organizational level