Database Storage Research Articles

Auto JSON: An Automatic Transformation Model for Converting Relational Database to Non-relational Documents

In recent days, the demand for dealing large set of distributed data obsoletes the relational database and its structured query language (SQL) solutions in practice and paves the way for novel solutions in the name of non-relational database as not-only SQL (NoSQL). The NoSQL offers dynamic, flexible, scalable, highly available, greater performance and near real-time access to the distributed nature of voluminous data used for current industrial applications. Apart from these giant features of NoSQL, the SQL is still found to be in operation because of its popularity and standard. This paper projected an algorithm to convert the relational documents of MySQL into any document oriented NoSQL databases automatically without destructing the existing relational database setup and installing the NoSQL from scratch in the core machines. Java Script Object Notation (JSON) is a human readable data interchange format, being used in web development. The characteristics of JSON widened its use cases from web development to database storage. The Mongo DB, one of the most popular document oriented NoSQL adapts JSON format for its storage. The proposed algorithm is built based on its schema definition and the performance is captured through evaluating it against a sample database from hospital management system. The findings are discussed with great interest of addressing the challenges and revealing the scope for improvement.

Introduction to Distributed Nearest Hash: On Further Optimizing Cloud Based Distributed kNN Variant

K-Nearest Neighbors (KNN) are very popular supervised machine learning algorithm which can be effectively used for both multi-class classification and regression utilizing multiple features of the dataset. It trains extremely fast, that is with time complexity of O(n). However, the time complexity for generating results with KNN is O(n3dk) (where k=number of neighbours, d=dimension of data, n=number of training points) and hence it becomes very difficult to work with larger dataset. Although there are parallelizing and distributed computing techniques available for speeding up KNN, it still have limitations on horizontal scalability, fault tolerance and incremental learning capabilities. To solve these issues, the paper presents a KNN inspired novel Supervised Machine Learning algorithm called Distributed Nearest Hash utilizing unique usage of hashmap and primary key clustering order with help of wide column store databases facilitating easy incremental near-realtime scalability to train unlimited datapoints with O(n) time complexity and also predict them in near realtime with O(1) time complexity considering n >> d. This can be readily integrated in any system that uses KNN as a base classifier or regressor. The experimental results shows that the proposed DNH model is 25% faster than state of the art distributed KNN algorithm. Integrating with fuzzy logic the algorithm can be used for several class classification. Using this could aid in building very powerful smart decision making systems with very little computational power.

Perancangan Aplikasi Administrasi Pada Fakultas Keguruan dan Ilmu Pendidikan Menggunakan Java Netbeans Ide 8.1 dan Mysql

Faculty of Teacher Training and Administrative Education is an administrative service at Bung Hatta University, Padang City. The data collection process for incoming and outgoing letters at the FKIP Administrative Unit is still said to be using the manual method. This study aims to produce a desktop-based administrative information system at the Teaching and Education Faculty with the aim of facilitating managers in recording incoming and outgoing mail numbers. This study uses the waterfall method with the design stages starting from analysis, system design using models including Context Diagrams, Data Flow Diagrams (DFD), and Unified Modeling Language (UML). Database storage using MySQL. The design phase ends with testing the program to produce an administration application at the Bung Hatta University FKIP using Java Netbeans IDE 8.1 and MySQL. This application can facilitate and speed up the process of data collection and search for incoming and outgoing mail numbers in the FKIP Administration.

An Examination of How Robots, Artificial Intelligence, and Machinery Learning are Being Applied in the Medical and Healthcare Industries

Machine learning techniques are associated with diagnostics systems to apply methods that enable computers to link patient data to earlier data and give instructions to correct the disease.In recent years, researchers have promoted two or three data mining based techniques for disease diagnosis. Each function in machine learning and data mining techniques is built through characteristics and features.As a part of prognosis, information must be separated from patient data and information retrieved in stored databases and comparative records. For any disease, early diagnosis or diagnosis will determine the chances of a correct recovery. Disease prediction therefore becomes a more important task to support physicians in delivering efficient treatment to people.In health care, data is being created and disposed of at an extraordinary rate compared to the health care sectors. Data for medical profiling is often found in a variety of sources such as electronic health records, lab and imaging systems, doctor notes and accounts. The medical records database will then contain irrelevant data sourced from multiple sources. Preprocessing data and eliminating irrelevant data then immediately opening it up for predictive analysis is one of the significant difficulties of the health care industry.

Non-destructive technique for erosion and corrosion monitoring system

Erosion and corrosion of pipeline occurs over time and this data should be given the same care as other data in oil and gas industry. Moreover, most notification systems available send an alert only when the issue is at a late stage. Therefore, the aim of this study is to create a monitoring system that would help in minimizing the impact of erosion and corrosion of pipeline related issues. There are three objectives includes: data separation, online and offline database storage and an email notification system. This study also emphasizes the importance of incorporating a database for evaluation of oil and gas pipeline’s wall thickness data in terms of its health status. As the data obtained is essential, a web application is created to store the data whenever internet is available. Otherwise, it will be stored in a temporary offline database known as MYSQL Workbench, and the data is automatically uploaded once the internet is available. A notification system via internet is developed to notify the executives regarding unhealthy pipeline status. A healthy pipeline wall thickness is between 4.3mm and 4.5mm. Thus, data with lower than 4.3mm is noted as eroded while data greater than 4.5mm is recorded as corroded. The monitoring system designed for online and offline data storage along with email notification performed accordingly. Therefore, the developed system fulfils the objectives and help in mitigating erosion and corrosion of pipelines related issues at an earlier stage in saving lives, maintenance fees and the environment.

A Multi-Port Hardware Energy Meter System for Data Centers and Server Farms Monitoring.

Nowadays the rationalization of electrical energy consumption is a serious concern worldwide. Energy consumption reduction and energy efficiency appear to be the two paths to addressing this target. To achieve this goal, many different techniques are promoted, among them, the integration of (artificial) intelligence in the energy workflow is gaining importance. All these approaches have a common need: data. Data that should be collected and provided in a reliable, accurate, secure, and efficient way. For this purpose, sensing technologies that enable ubiquitous data acquisition and the new communication infrastructure that ensure low latency and high density are the key. This article presents a sensing solution devoted to the precise gathering of energy parameters such as voltage, current, active power, and power factor for server farms and datacenters, computing infrastructures that are growing meaningfully to meet the demand for network applications. The designed system enables disaggregated acquisition of energy data from a large number of devices and characterization of their consumption behavior, both in real time. In this work, the creation of a complete multiport power meter system is detailed. The study reports all the steps needed to create the prototype, from the analysis of electronic components, the selection of sensors, the design of the Printed Circuit Board (PCB), the configuration and calibration of the hardware and embedded system, and the implementation of the software layer. The power meter application is geared toward data centers and server farms and has been tested by connecting it to a laboratory server rack, although its designs can be easily adapted to other scenarios where gathering the energy consumption information was needed. The novelty of the system is based on high scalability built upon two factors. Firstly, the one-on-one approach followed to acquire the data from each power source, even if they belong to the same physical equipment, so the system can correlate extremely well the execution of processes with the energy data. Thus, the potential of data to develop tailored solutions rises. Second, the use of temporal multiplexing to keep the real-time data delivery even for a very high number of sources. All these ensure compatibility with standard IoT networks and applications, as the data markup language is used (enabling database storage and computing system processing) and the interconnection is done by well-known protocols.

Trojan Horse Infection Detection in Cloud Based Environment Using Machine Learning

Cloud computing technology is known as a distributed computing network, which consists of a large number of servers connected via the internet. This technology involves many worthwhile resources, such as applications, services, and large database storage. Users have the ability to access cloud services and resources through web services. Cloud computing provides a considerable number of benefits, such as effective virtualized resources, cost efficiency, self-service access, flexibility, and scalability. However, many security issues are present in cloud computing environment. One of the most common security challenges in the cloud computing environment is the trojan horses. Trojan horses can disrupt cloud computing services and damage the resources, applications, or virtual machines in the cloud structure. Trojan horse attacks are dangerous, complicated and very difficult to be detected. In this research, eight machine learning classifiers for trojan horse detection in a cloud-based environment have been investigated. The accuracy of the cloud trojan horses detection rate has been investigated using dynamic analysis, Cukoo sandbox, and the Weka data mining tool. Based on the conducted experiments, the SMO and Multilayer Perceptron have been found to be the best classifiers for trojan horse detection in a cloud-based environment. Although SMO and Multilayer Perceptron have achieved the highest accuracy rate of 95.86%, Multilayer Perceptron has outperformed SMO in term of Receiver Operating Characteristic (ROC) area.

Aplikasi Mobile Periklanan Digiprom Berbasis Android

Digiprom is a startup that provides ad serving services. These advertisements will later be shown in public places, such as supermarkets, cafes, malls, and others. The problem faced by Digiprom is that there is no information technology to help interact between Digiprom and its clients (businessman). The interactions in question are such as registration as a client, the process of making a contract between the client and Digiprom, the process of monitoring the contract that has been made and the delivery of other information about Digiprom. To solve this problem, an Android-based mobile application will be developed to help Digiprom interact with its clients. This research focuses on the development side of the Android application, while the server side is not included in this study. The development of this application will use the Waterfall method and tested using black box testing and user acceptance testing. The system design is described using three UML diagrams, namely use case diagrams, activity diagrams and class diagrams. Program code written using Kotlin language with MVVM architecture (Model, View, ViewModel). There are three main objects in this system, namely users (businessman/clients), ads (advertisements) and location (advertising locations). Each object will have its own repository. The repository has three data sources, namely network (server), Room Database, and Data Store. The use of MVVM architecture facilitates the development and maintenance process, because if there is a change in the data structure of an object, it will not affect the data structure of other objects. The results of this research (Android application) will be uploaded to the Google Play Store under the name Digiprom.

PERANCANGAN SISTEM INFORMASI PINJAMAN PADA KOPERASI SERBA USAHA ANUGRAH USAHA KITO BERBASIS WEB

Anugrah Usaha Kito Multipurpose Cooperative is a financial institution that provides loan transaction services. The Multipurpose Business Cooperative Anugrah Usaha Kito needs to have an information system to facilitate data processing, carry out tasks appropriately, and minimize errors in recording transactions and financial calculations, because the existing system cannot support the activities carried out by the Multipurpose Business Cooperative Anugrah Usaha Kito, especially Another problem with the running program is that it still uses a manual system. To meet the above requirements, it is necessary to design a loan information system. This information system is made using the PHP programming language through the CodeIgniter framework, and MySQL as the database storage. By using database storage, the cooperative information system can facilitate the processing of member data, loan data and installment data because it has been stored in 1 central database. This web-based information system is an alternative to improve the quality of data processing and cooperative loan services. The facilities contained in this information system include processing member data, loans, installments, late fees.

Software Tool for the Extrinsic Calibration of Infrared and RGBD Cameras Applied to Thermographic Inspection

Context: Thermographic inspections are currently used to assess energy efficiency in electrical equipment and civil structures or to detect failures in cooling systems and electrical or electronic devices. However, thermal images lack texture details, which does not allow for a precise identification of the geometry of the scene or the objects in it. Method: In this work, the development of the software tool called DepTherm is described. This tool allows performing intrinsic and extrinsic calibration between infrared and RGBD cameras in order to fuse thermal, RGB, and RGBD images, as well as to record thermal and depth data. Additional features include user management, a visualization GUI for all three types of images, database storage, and report generation. Results: In addition to the integration tests performed to validate the functionality of DepTherm, two quantitative tests were conducted in order to evaluate its accuracy. A maximum re-projection error of 1,47±0,64 pixels was found, and the maximum mean error in registering an 11 cm side cube was 4,15 mm. Conclusions: The features of the DepTherm software tool are focused on facilitating thermographic inspections by capturing 3D scene models with thermal data.

Monitoring System of the ATLAS ITk Laboratory

The ATLAS ITk Upgrade project, culminating in the installation into the experiment in 2026, enters this year its production period. Cooperating laboratories dealing with the strip part of the project needs to meet various conditions in clean rooms and testing environments to ensure safety for production components during assembly and measurement procedures. One of the ITk laboratories, located in Prague, prepared for modules’ production is presented as a model case. For this purpose, dedicated DAQ software called ITSDAQ is used together with the slow control monitoring system based on RS232/GPIB standards, MySQL database entry and Grafana visualization platform. Data are stored in the local database storage, a subset of them and the test results are also sent into the ITk Production Database. Such an integrated tool offers real-time plotting of crucial parameters and the possibility of receiving an immediate notification in case of exceeding any threshold.

Design of remote sensing-based geographic information system

To deal with problems of traditional geographic information collection, such as low real-time, poor authenticity of the data, and unclear description of detailed areas, a design scheme of remote sensing-based geographic information system is proposed. The system mainly consists of information collection, imaging processing, data storage management, scene control and data transmission module. By use of remote sensing technology, the reflected and radiated electromagnetic waves of the target area are collected from a long distance to form an image, and the hue–intensity–saturation (HIS) transformation method is used to enhance the image definition. Weighted fusion algorithm is adopted to process the details of the image. The spatial database stores and manages the text and image data respectively, and establishes the attribute self-correlation mechanism to render the ground objects in the picture with SketchUp software. Finally, using RS422 protocol to transmit information can achieve the effect of multi-purpose, and enhance the anti-interference of the system. The experimental results show that the practical experience of the proposed system is excellent, the geographic information image presented is clear, and the edge details are clearly visible, which can provide users with effective geographic information data.

A Novel Approach to Improve the Performance of the Database Storing Big Data with Time Information

Big data is defined as data sets that are too large and/or complex to be processed by classical data processing methods. Big data analysis is essential because it enables more competent business movements, more efficient operations, and higher profits by using the data of institutions and organizations. However, large datasets are difficult to analyze because they are produced quickly, require large storage areas in computer systems, and the diversity of their data. In this study, a new approach using the denormalization method is proposed to accelerate the response time of the database in database systems where large volumes of data containing historical information are stored. Denormalization is defined as the process of adding rows or columns that are not needed to increase the reading performance of the database to the database system that has been normalized. In the proposed approach in this study, a large-volume dataset consisting of real spatial data belonging to Kayseri Metropolitan Municipality, containing temporal information and having approximately 96,000,000 row records, was used. In the proposed approach, the response time of the query is accelerated by recording the time information as numbers to increase the query performance of large volumes of data recorded in date format due to the temporal query process. The performance of the proposed method is compared with the performance of the normalization method using actual data on Microsoft SQL Server and Oracle database systems. The method proposed in the experimental evaluations shows that it works approximately eight times faster. In addition, the experimental results showed that the proposed method improves query performance more than the normalization-based method as the data size increases.

Learning Media Application of Knowledge Sharing Room to Improve Student and Community Literacy

The development of technology that is increasingly fast and sophisticated makes it easy for everyone to obtain or disseminate information, discuss and share thoughts between one person and another. Information Technology has an important role in all fields. Electronic learning or distance learning is a new breakthrough in the development of information technology in the field of education, e-learning is a teaching and learning process using the Internet as a learning system. Building a digital literacy culture needs to involve the active role of the community together. The success of building digital literacy is one indicator of achievement in the fields of education and culture. In an effort to improve literacy for students and the community, this research will develop a digital-based literacy resource called the Mobile Web-Based Knowledge Sharing Application. The system development method used in this study uses the System Development Life Cycle (SDLC) method, and the research flow is described using the Fishbone Mapping Chart model. In realizing the Knowledge Sharing Room application, the design stage is used using a structured model using Use Case Diagrams, Entity Relationship Diagrams (ERD) with website design using Hypertext Preprocessor programming, HTML, Java Script as a programming language, and My Structured Query Language (MySQL) as a database storage medium.

Learning Media Application of Knowledge Sharing Room to Improve Student and Community Literacy

The development of technology that is increasingly fast and sophisticated makes it easy for everyone to obtain or disseminate information, discuss and share thoughts between one person and another. Information Technology has an important role in all fields. Electronic learning or distance learning is a new breakthrough in the development of information technology in the field of education, e-learning is a teaching and learning process using the Internet as a learning system. Building a digital literacy culture needs to involve the active role of the community together. The success of building digital literacy is one indicator of achievement in the fields of education and culture. In an effort to improve literacy for students and the community, this research will develop a digital-based literacy resource called the Mobile Web-Based Knowledge Sharing Application. The system development method used in this study uses the System Development Life Cycle (SDLC) method, and the research flow is described using the Fishbone Mapping Chart model. In realizing the Knowledge Sharing Room application, the design stage is used using a structured model using Use Case Diagrams, Entity Relationship Diagrams (ERD) with website design using Hypertext Preprocessor programming, HTML, Java Script as a programming language, and My Structured Query Language (MySQL) as a database storage medium.

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model.

Currently, livestock and poultry farming is gradually developing towards modernization and scale, and closed livestock and poultry farms are widely used for poultry feeding management, but at the same time, the farming risks of large-scale farms are increasing. In this paper, based on the study of wireless sensor networks and biological neural network models, the environmental factors that mainly affect the growth of domestic rabbits are analyzed as an example, and the technology is used to design and implement an environmental monitoring system for modern farms. The design of the system is divided into three main parts: hardware design of each node, software design, and upper computer monitoring software design. The hardware part of the system uses coordinator nodes, router nodes, sensor nodes, and control nodes to form a wireless sensor network in the farm, carries out the hardware circuit design of each node, and based on the protocol stack, designs the software program of each node to realize the collection, transmission, and regulation of environmental information in the farm. In the upper computer part, the design and development of the upper computer monitoring software interface are used to complete the real-time display of environmental data, historical query, database storage, and curve drawing, and to design a remote client data query system based on the architecture to realize the query of environmental data of the farm by remote users and to carry out monitoring fault intelligent identification alarm. At the same time, the paper investigates the optimal deployment of wireless sensor network nodes and searches for the optimal location of sensor nodes through an improved biological neural network algorithm to maximize the network coverage and reduce the coverage of blind areas, and conducts simulation experiments with the coverage rate of a rabbit farm as the optimization target.

PRISM: A decision support system for forest planning

PRISM, a new forest management decision support system, was developed for United States national forest planning at the same time existing tools were deprecated. PRISM has a friendly graphical user interface to facilitate model development, database management, sensitivity analysis, and data visualization. It integrates SQLITE engine for database storage and exploration. It supports both classic forest planning Model I and II to schedule management activities and achieve multiple management objectives through the lifecycle of a forest plan. Multiple models may be created through the PRISM interface and solved in batch mode for convenient sensitivity analysis. Various options to visualize model outputs are available through the embedded JFREECHART library. The open-source nature of PRISM makes it free to use and allows for long-term software development and collaboration. This paper presents the architecture, core functionality, and selected applications of PRISM in the United States national forest planning.

Development of Website-Based Thousand Island Tour Package Booking Application Using Waterfall Method

PT. Khatulistiwa Global Wisata is a company engaged in tourism and offers a Tour and Travel service called Explore Thousand Islands. Currently, the process of booking Pulau Seribu tour packages at Explore Seribu Pulau Tour and Travel is still done manually, causing visitor data, bookings, payments, and visitor reviews to not be recorded properly. This website-based thousand island tour package online booking application is designed using the Waterfall method, CodeIgniter as a framework, PHP for designing the web, and MySQL as a database storage. Research has been conducted to overcome problems by creating features such as tour package list features, tour package bookings, tour package payments, manage payments, approve payments, manage assignment trips, complete trip assignments, and give trip reviews. The features developed make it easier for visitors to find information on tour packages, book, pay, and review tour trips that have been carried out. In addition, the existence of the report feature can improve performance and make it easier for tourism agents to record reports from booking thousand island tour packages through the website.

ANALYSIS OF LINEAR REGRESSION AND TREND MOMENT METHODS IN PREDICTING SALES USING MAPE

ABSTRACK- Sales transaction data stored in the database stores a large number of transaction records, causing the amount of data to continue to increase every day. To explore sales transaction data, data mining techniques are used. One of the goals of data mining is prediction. Prediction is basically an assumption or estimate about the occurrence of an event or event in the future. Through prediction, it is expected to minimize the influence of uncertainty from the future, so that getting results that have the least prediction error is the goal of prediction. This shows that prediction is a very important tool in planning effectively and efficiently. The discussion method used to predict sales is the time series method by using a comparison of two types of prediction methods, namely the Linear Regression method and the Trend Moment method. The use of these two methods will be a better basis for making decisions to determine which method is suitable for predicting future sales. The result of a prediction cannot always be verified in absolute 100%. Therefore, the parameters used to determine the better method are based on the smallest error accuracy rate calculated using MAPE. Based on the results of the comparative prediction analysis of the Linear Regression method and the Trend Moment method, the recommended prediction result is to use the Trend Momnet method because the resulting MAPE error value is smaller, namely 0.439845%. Meanwhile, the MAPE error value with the Linear Regression method is 1.511509%..

Design and Realization of Seeding Quality Monitoring System for Air-Suction Vibrating Disc Type Seed Meter

To improve the seeding qualification rate and stability of the air-suction vibrating disc type seed meter on the rice seedling raising line, in this paper, an improved wireless sensor network node layout optimization algorithm was proposed, and the operation monitoring system of the seed meter was designed using the Internet of Things and configuration software. In the system, the upper computer software adopted the Kingview software, the lower computer took the STM32F429IGT and CC2530 as the core controllers, and ZigBee was selected for data transmission to build the wireless sensor network. The acquisition of field status information and the sending of control instructions were realized through the sensor nodes constructed by the CC2530 core controller. The data was sent to the coordinator node in real-time through the wireless sensor network. The coordinator node realized the bidirectional transmission of data with Kingview and the upper computer control instructions forwarding using the ASCII protocol The host computer monitoring and management software was developed based on configuration software to realize real-time data monitoring, access database storage, fault alarm, control command sending and other functions. The experimental results showed that the detection accuracy of the system for the seeding amount and missed seeding amount was 94.3% and 95.6%, respectively, which could realize the monitoring of the primary working status of the seed meter. The system realized effective data transmission and data remote wireless transmission function, which provided sufficient theoretical and data support for the performance optimization of the seed meter, and laid a good foundation for the visualization and intelligence of information data.