Effectiveness of Cutting-Edge Technology for Library Management System

With technology advancing, manual systems must be converted to user friendly automated system. Researchers have designed the Library Management System to transfer the physical view of libraries into a digital view. This project offers knowledge on creating and putting in place an LMS. In traditional library system people have to search for a particular book from shelf to shelf which is a tedious and time-consuming work. It can be more cumbersome if the library hasn’t a properly maintained library system. The manual system isn’t user-friendly not only for the borrowers but also for librarians. They have to keep an eye on each and every book lending and borrowing. And They occasionally have to arrange and classify the books. The process of creating reports and analyzing data is also highly laborious. LMS assists the librarians for all these tasks. They can simply view, update, delete, read books and articles to manage the resources. Readers don’t have to stand in long queues and no need of going around to read a book. They can read a book just by clicking a single button. The full system is designed using MERN stack, with the aid of JWT authentications and JOY dependency validations

Reflective Relational Machines

AbstractWe propose a model of database programming withreflection(dynamic generation of queries within the host programming language), called thereflective relational machine, and characterize the power of this machine in terms of known complexity classes. In particular, the polynomial time restriction of the reflective relational machine is shown to express PSPACE, and to correspond precisely to uniform circuits of polynomial depth and exponential size. This provides an alternative, logic based formulation of the uniform circuit model, which may be more convenient for problems naturally formulated in logic terms, and establishes that reflection allows for more “intense” parallelism, which is not attainable otherwise (unless P=PSPACE). We also explore the power of the reflective relational machine subject to restrictions on the number of variables used, emphasizing the case of sublinear bounds

Object reational data base management systems and applications in document retrieval

http://deepblue.lib.umich.edu/bitstream/2027.42/96902/1/MBA_JayaramanaF_1996Final.pd

PanDA Workload Management System Meta-data Segmentation

AbstractThe PanDA (Production and Distributed Analysis) workload management system (WMS) was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. PanDA currently distributes jobs among more than 100,000 cores at well over 120 Grid sites, supercomputing centers, commercial and academic clouds. ATLAS physicists submit more than 1.5M data processing, simulation and analysis PanDA jobs per day, and the system keeps all meta-information about job submissions and execution events in Oracle RDBMS. The above information is used for monitoring and accounting purposes. One of the most challenging monitoring issues is tracking errors that has occurred during the execution of the jobs. Current meta-data storage technology doesn’t support inner tools for data aggregation, needed to build error summary tables, charts and graphs. Delegating these tasks to the monitor slows down the execution of requests.We will describe a project aimed at optimizing interaction between PanDA front-end and back-end, by meta-data storage segmentation into two parts – operational and archived. Active meta-data are remained in Oracle database (operational part), due to the high requirements for data integrity. Historical (read-only) meta-data used for the system analysis and accounting are exported to NoSQL storage (archived part). New data model based on usage of Cassandra as the NoSQL backend has been designed as a set of query-specific data structures. This allowed to remove most of data preparation workload from PanDA Monitor and improve its scalability and performance. Segmentation and synchronization between operational and archived parts of jobs meta-data is provided by a Hybrid Meta-data Storage Framework (HMSF). PanDA monitor was partly adopted to interact with HMSF. The operational data queries are forwarded to the primary SQL-based repository and the analytic data requests are processed by NoSQL database. The results of performance and scalability tests of HMSF-adopted part of PanDA Monitor shows that presented method of optimization, in conjunction with a properly configured NoSQL database and reasonable data model, provides performance improvements and scalability

The Hospital Management System

The hospital's management system includes improved profitability, improved administration, and better patient care. The goal of this study is to create a digital management system that will boost the hospital's effectiveness and systems integration standards. It was able to produce a module that would provide some facilities, like booking doctors, booking lab test slots, pharmacy services, and getting health programs. This system consists of an admin handling part, which means admin can manage users, pharmacy systems, health program management, and manage booking of doctor's appointments and lab tests. And through this system, the admin can generate multiple reports according to his needs[7]. A module that would manage the admission bills and pharmaceutical payments; and a module that could monitor the medicine inventory of the hospital pharmacy. Problem statement because hospitals are associated with ordinary people's lives and daily routines the manual handling of the record is time-consuming and highly prone to error. The purpose of this project is to automate, or make online, the process of day-to-day activities. Each phase guided the researchers in the development of the study and helped them organize the workflow of each task. In conclusion, the researchers found that the system could speed up the working progress and productivity of hospital employees. It could also generate hospital reports that could help the users to provide an overview of the hospital transaction within specific date. It also provided the facility for searching for the details of the inquiring patient in the receptionist module. The system could reduce the workloads in the hospital, resulting in better management and working performance. In general, the study resulted in a better improvement of hospital transactions. It has been recommended that there is a need to enhance the frontend design of the system

Query Optimization Technique in Relational Databases�

Computer Scienc

MongoDB Support for UnifiedPush Server

Tato diplomová práce se zabývá návrhem a implementací rozšíření pro UnifiedPush Server, které serveru umožní přistupovat k nerelační databázi MongoDB a využívá potenciál horiznotální škálovatelnosti neralačních databází. Součástí práce je i návrh výkonnostních testů a porovnání výkonu při behu na jednom a vícero uzlích, návrh migračního scénáře z MySQL na MongoDB, identifikace úzkých míst. Aplikace je implementována v jazyce Java a využívá Java Persistence API pro přístup k databázím. Pro přístup k nerelačním databázím používá implementaci standardu JPA Hibernate OGM.This thesis describes the design and implementation of extension for UnifiedPush Server, which allows the server to access non-relational MongoDB database and leverages the horizontal scalability potential of non-relational databases. The work includes a proposal for performance tests and compares results of single and multi node solutions, design migration scenario from MySQL to MongoDB, identification of bottlenecks. The application is implemented in Java and uses Java Persistence API for accessing databases. To access non-relational databases uses implementation of the JPA standard called Hibernate OGM.

A Flexible and Scalable Architecture for Real-Time ANT+ Sensor Data Acquisition and NoSQL Storage

Wireless Personal or Body Area Networks (WPANs or WBANs) are the main mechanisms to develop healthcare systems for an ageing society. Such systems offer monitoring, security, and caring services by measuring physiological body parameters using wearable devices. Wireless sensor networks allow inexpensive, continuous, and real-time updates of the sensor data, to the data repositories via an Internet. A great deal of research is going on with a focus on technical, managerial, economic, and social health issues. The technical obstacles, which we encounter, in general, are better methodologies, architectures, and context data storage. Sensor communication, data processing and interpretation, data interchange format, data transferal, and context data storage are sensitive phases during the whole process of body parameter acquisition until the storage. ANT+ is a proprietary (but open access) low energy protocol, which supports device interoperability by mutually agreeing upon device profile standards. We have implemented a prototype, based upon ANT+ enabled sensors for a real-time scenario. This paper presents a system architecture, with its software organization, for real-time message interpretation, event-driven based real-time bidirectional communication, and schema flexible storage. A computer user uses it to acquire and to transmit the data using a Windows service to the context server

A theory of relation learning and cross-domain generalization

People readily generalize knowledge to novel domains and stimuli. We present a theory, instantiated in a computational model, based on the idea that cross-domain generalization in humans is a case of analogical inference over structured (i.e., symbolic) relational representations. The model is an extension of the Learning and Inference with Schemas and Analogy (LISA; Hummel & Holyoak, 1997, 2003) and Discovery of Relations by Analogy (DORA; Doumas et al., 2008) models of relational inference and learning. The resulting model learns both the content and format (i.e., structure) of relational representations from nonrelational inputs without supervision, when augmented with the capacity for reinforcement learning it leverages these representations to learn about individual domains, and then generalizes to new domains on the first exposure (i.e., zero-shot learning) via analogical inference. We demonstrate the capacity of the model to learn structured relational representations from a variety of simple visual stimuli, and to perform cross-domain generalization between video games (Breakout and Pong) and between several psychological tasks. We demonstrate that the model’s trajectory closely mirrors the trajectory of children as they learn about relations, accounting for phenomena from the literature on the development of children’s reasoning and analogy making. The model’s ability to generalize between domains demonstrates the flexibility afforded by representing domains in terms of their underlying relational structure, rather than simply in terms of the statistical relations between their inputs and outputs

Open source face recognition API

Face recognition applications are widely used today for a variety of tasks, whether personal or professional. When looking for a service that provides face detection and classification, it is easy to find several solutions. In this project another way is described so that it is possible to perform this task according to the desired needs without the need to use proprietary software. With the emergence of the Django Rest Frame Work, web application development has become easier. This work describes development of stable foundation and features that offer an administration panel, relational database management, and support for a Restful Application Programming Interface (API). This takes advantage of the exclusive use of Open Source technologies thus the application code can be modified and distributed free of charge. For the development of an API that could perform detection and facial recognition, applying an Open Source philosophy, in addition to Django Rest Framework technologies such as Python, C++, MySql and JSON were used. The prototype is initially capable of recognizing the number of faces per image, assessing eyes, smile, age and gender. Flexibility is designed to increase application capabilities with new algorithms implemented in various programing languages.Atualmente, as aplicações de reconhecimento de facial são amplamente utilizadas para uma variedade de tarefas, pessoais ou profissionais. Ao procurarmos um serviço que forneça deteção e classificação de rosto, é fácil encontrar várias soluções. Neste projeto, é descrita outra maneira para que seja possível executar esta tarefa de acordo com as necessidades desejadas, sem a necessidade de usar software proprietário. Com o surgimento do Django Rest Framework, o desenvolvimento de aplicações web ficou mais fácil. Este trabalho descreve o desenvolvimento de bases e recursos estáveis que oferecem um painel de administração, gestão de uma base de dados relacional e o suporte para uma API (Application Programming Interface) Restful. Ao tirar proveito do uso exclusivo de tecnologias Open Source, é permitido que o código possa ser modificado e distribuído gratuitamente. Para o desenvolvimento de uma API que pudesse realizar a deteção e o reconhecimento facial, aplicando uma filosofia Open Source, para além da tecnologia Django Rest Framework foram utilizadas tecnologias como Python, C ++, MySql e JSON. O protótipo é inicialmente capaz de reconhecer o número de rostos por imagem, e avaliar olhos, sorriso, idade e sexo. Mas para além disso, foi projetada flexibilidade para aumentar os recursos através da implementação de novos algoritmos em várias linguagens de programação