Creación e implementación de una aplicación web para la administración de citas para un autolavado

According to a press release emitted by INEGI on December 2nd, 2020, 93.2% of the companies in Mexico reported problems caused by the current pandemic, and more than a million businesses closed their doors permanently. In this context, the need to create technological tools that promote the development of activities of micro, small and medium businesses emerged. In this project, the development and creation of an application for a car wash business that allows clients and workers to book and manage appointments and the payment of services are presented. The development of this project was carried out with the framework SCRUM, using different tools for collaborative development such as ASP.Net for web applications, Visual Studio as Integrated Development Environment (IDE), a relational database system, and Model-View-Controller (MVC) as an architectural pattern. This module can be adapted to any kind of business with the same needs in the same field or other fields.

Waste disposal systems of Addis Ababa City, the African Capital, Ethiopia

Industries have played vital roles for economic development that enable people to create new and better livelihoods, more income, and modern life systems. However, Ethiopia has little benefited from industry sector due to limited number of industries with less advanced technologies. This study was conducted in Addis Ababa, the Capital City of Africa. Datasets were collected from 2,204 institutions through structured interview, field observation and GPS points. Datasets were entered, cleaned and analyzed using a relational database system in Visual Basic and MS-access database environment. Spatial distribution of industries indicates that only 18% of industries were found in industry zones, while 82% are outside industry zones and of which 78% of them are found in residential areas. Industrial wastes are disposed either to nearest river or open field. The findings indicate that only 10% of industries treated and disposed their wastes whereas 90% didn’t treat industrial wastes but disposed to the environment. The major observed impacts were on: affecting human and animals’ health, pollute surface and groundwater, pollute soil and air, trigger firing, damage ditches, block canals and cause over floods, among others. It requires concerted efforts to minimize and avoid improper waste disposal systems so as to realize economically active, environmental suitable and socially conduce capital city for its residents, tourist and business people.

An Efficient Query Optimizer with Materialized Intermediate Views in Distributed and Cloud Environment

In cloud computing environment hardware resources required for the execution of query using distributed relational database system are scaled up or scaled down according to the query workload performance. Complex queries require large scale of resources in order to complete their execution efficiently. The large scale of resource requirements can be reduced by minimizing query execution time that maximizes resource utilization and decreases payment overhead of customers. Complex queries or batch queries contain some common subexpressions. If these common subexpressions evaluated once and their results are cached, they can be used for execution of further queries. In this research, we have come up with an algorithm for query optimization, which aims at storing intermediate results of the queries and use these by-products for execution of future queries. Extensive experiments have been carried out with the help of simulation model to test the algorithm efficiency

Working with Legacy Relational Data in A Graph-Based World

The Next Generation Linkage Management System (NGLMS) was designed around keeping all data in a graph database. However, this constraint, while easily achievable for greenfield projects and/or new data linkage units, may not be easily met where legacy data exists. Objectives and ApproachThe NGLMS was extended to encompassed system where data was held partially or even completely in a relational database. By grouping the data managed by the NGLMS into system metadata, record link data and record data and allowing system metadata and record data to be stored separately and independently in either a relational or a graph database, the NGLMS allows hybrid installations of mixed graph and relational data and, with some loss of functionality, purely relational installations. ResultsThe functionality of the NGLMS was expanded to allow review of existing legacy data stored in a relational database system. Through minor changes to the server used by the NGLMS Clerical Review tool (NGLMS-CR) the review tools was able to present the same interface and allow the same integration as project stored completely within the graph database. Hybrid projects where link information was stored in a graph could be accommodated with no loss of functionality.Relational-only projects allowed clerical review of identified clusters in a manner identical to the graph-only NGLMS but involved some curtailment of the advanced clustering, time-slicing, compositional and concurrent functionality of the NGLMS due to the loss of the functionality provided by a graph database. They do provide an upgrade pathway to hybrid projects and then graph-only projects. Conclusion / ImplicationsAllowing the NGLMS to be configured as a hybrid system enables a gradual adoption of the NGLMS toolset and software. purely relational data still allows the use of the NGLMS-CR with customisable workpools and workflows a hybrid relational/graph system where record data is still kept in a relational store but cluster and linkage information is kept in the graph store allows the use of legacy data without major disruption and provides a pathway to full adoption

Basic principles of blind write protocol

The current approach to handle interleaved write operation and preserve consistency in relational database system still relies on the locking protocol. If any entity is locked by any transaction, then it becomes temporary unavailable to other transaction until the lock is released. The temporary unavailability can be more often if the number of write operation increases as happens in the application systems that utilize IoT technology or smartphone devices to collect the data. To solve this problem, this research is proposed blind write protocol which does not lock the entity while the transaction is performing a write operation. This paper presents the basic principles of blind write protocol implementation in a relational database system

Biospytial: spatial graph-based computing for ecological Big Data

Background The exponential accumulation of environmental and ecological data together with the adoption of open data initiatives bring opportunities and challenges for integrating and synthesising relevant knowledge that need to be addressed, given the ongoing environmental crises. Findings Here we present Biospytial, a modular open source knowledge engine designed to import, organise, analyse and visualise big spatial ecological datasets using the power of graph theory. The engine uses a hybrid graph-relational approach to store and access information. A graph data structure uses linkage relationships to build semantic structures represented as complex data structures stored in a graph database, while tabular and geospatial data are stored in an efficient spatial relational database system. We provide an application using information on species occurrences, their taxonomic classification and climatic datasets. We built a knowledge graph of the Tree of Life embedded in an environmental and geographical grid to perform an analysis on threatened species co-occurring with jaguars (Panthera onca). Conclusions The Biospytial approach reduces the complexity of joining datasets using multiple tabular relations, while its scalable design eases the problem of merging datasets from different sources. Its modular design makes it possible to distribute several instances simultaneously, allowing fast and efficient handling of big ecological datasets. The provided example demonstrates the engine’s capabilities in performing basic graph manipulation, analysis and visualizations of taxonomic groups co-occurring in space. The example shows potential avenues for performing novel ecological analyses, biodiversity syntheses and species distribution models aided by a network of taxonomic and spatial relationships.