Oracle Cloud Research Articles

Modernizing Academic Institutions using Oracle Cloud

Educational Institutions are fast transforming themselves in the way they operate and serve by shifting more towards digital medium. With steady increase in applicants and student enrolments every year, colleges and universities are gearing themselves to provide the best courses possible, while managing the campus to provide safe and welcoming environment to the students to study and grow. The changing expectations from the students and the demand for new niche skills has forced the educational institutions to use technology and modern applications to help them evolve. In addition to the educating the students, the schools also need to manage ensure the proper functioning of various departments, such as their financials, student and staff management, marketing, and administrative tasks. These challenges can be taken care by leveraging the academic solutions provided by Oracle Cloud, in various areas, such as Campus Management, Student Management, etc., which can be an optimal solution for all the academic needs. With the industry leading cloud solutions and digital tools, it not only provides an out of the box solution but allows a personalized solution that best suits the academia. Keywords : Oracle Cloud, Oracle Student Management, Modernizing Educational Institutions, Digitalizing Academic Institutions, Oracle Digital Assistant, Oracle Cloud Campus Solutions.

DESENVOLVIMENTO DE UM SISTEMA DE GESTÃO PARA CLOUD (INFRAESTRUTURA MULTI-CLOUD)

This work aims to develop a multi-cloud resource management system to simplify the administration of infrastructures distributed across different cloud providers, such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI). The system was built using Node.js for the backend and Vue.js for the frontend, leveraging generic SDKs for integration with cloud services. The platform enables users to centrally view and manage resources such as computing instances, virtual networks, and object storage efficiently. The project concluded that the system fully met the established functional requirements, highlighting the importance of technological solutions in the modern context of resource management in multi-cloud environments. The developed solution stands out for its robustness and ability to optimize the administration of complex infrastructures, making it essential for companies operating across multiple cloud environments in an integrated manner.

Fortifying Electronic Medical Record (EMR) Applications: Advanced Security Controls in Oracle Cloud Infrastructure (OCI)

Fortifying Electronic Medical Record (EMR) Applications: Advanced Security Controls in Oracle Cloud Infrastructure (OCI)

Comparative analysis of security models in cloud platforms

This article is dedicated to the importance of data security on cloud platforms, highlighting the subject relevance in an era where threats to information security are becoming increasingly complex and sophisticated. The primary focus is a comparative analysis of security models employed by leading cloud platforms such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM Cloud, and Oracle Cloud. The research covers various crucial security aspects, including data encryption, identity and access management, monitoring mechanisms and incident response. The article sheds light on current trends and technologies in cloud data protection, including the use of artificial intelligence and machine learning to enhance threat detection efficiency and the implementation of confidential computing and blockchain technologies to improve data protection. Issues of compliance with legal requirements and data security standards are discussed, along with recommendations for organisations to optimise information protection in the cloud environment.

Implementation of cloud computing in the digital accounting system of logistics companies

The aim of the article is to determine the capabilities of cloud services for meeting the needs of logistics companies in the management of supply chains and digital accounting. The study provides a review of current academic publications, analysis of official documentation of cloud service provider companies, and expert opinion of the authors of the study. The study was based on information about the 5 most popular cloud services used by companies to perform mathematical calculations. Amazon Web Services focus on reliability and scalability, providing a wide range of data storage and processing services, as well as performing serverless mathematical calculations. Microsoft Azure stands out for its integrated solutions, as well as data management and analytics services. Google Cloud offers a wide range of development and analytics tools, including data visualization and data sharing. Oracle Cloud provides comprehensive financial and database management solutions. SAP Cloud Platform specializes in financial management and analytics solutions. The results of the research open up prospects for studying the problems of integrating services built on different platforms and finding optimal solutions for combining the existing system of mathematical calculations in a logistics company with the offered cloud-based services.

A super SDM (species distribution model) ‘in the cloud’ for better habitat-association inference with a ‘big data’ application of the Great Gray Owl for Alaska

The currently available distribution and range maps for the Great Grey Owl (GGOW; Strix nebulosa) are ambiguous, contradictory, imprecise, outdated, often hand-drawn and thus not quantified, not based on data or scientific. In this study, we present a proof of concept with a biological application for technical and biological workflow progress on latest global open access ‘Big Data’ sharing, Open-source methods of R and geographic information systems (OGIS and QGIS) assessed with six recent multi-evidence citizen-science sightings of the GGOW. This proposed workflow can be applied for quantified inference for any species-habitat model such as typically applied with species distribution models (SDMs). Using Random Forest—an ensemble-type model of Machine Learning following Leo Breiman’s approach of inference from predictions—we present a Super SDM for GGOWs in Alaska running on Oracle Cloud Infrastructure (OCI). These Super SDMs were based on best publicly available data (410 occurrences + 1% new assessment sightings) and over 100 environmental GIS habitat predictors (‘Big Data’). The compiled global open access data and the associated workflow overcome for the first time the limitations of traditionally used PC and laptops. It breaks new ground and has real-world implications for conservation and land management for GGOW, for Alaska, and for other species worldwide as a ‘new’ baseline. As this research field remains dynamic, Super SDMs can have limits, are not the ultimate and final statement on species-habitat associations yet, but they summarize all publicly available data and information on a topic in a quantified and testable fashion allowing fine-tuning and improvements as needed. At minimum, they allow for low-cost rapid assessment and a great leap forward to be more ecological and inclusive of all information at-hand. Using GGOWs, here we aim to correct the perception of this species towards a more inclusive, holistic, and scientifically correct assessment of this urban-adapted owl in the Anthropocene, rather than a mysterious wilderness-inhabiting species (aka ‘Phantom of the North’). Such a Super SDM was never created for any bird species before and opens new perspectives for impact assessment policy and global sustainability.

Project Orchestrator

The ever-increasing growth and complexity of software-intensive systems over the past 20 years and the ensuing rise in geographically distributed projects are trends that are here to stay. Solving the distributed project management problem by automating it is a top priority, one that relies not simply on the intelligent application of technology, but also on coordinated, complementary efforts focused on people and processes. These systems must evolve to support increased decision velocity and cohesiveness in today’s increasingly distributed world. The unique features of a software product line organization challenge the conventional definition of project management. Among those features are different project types, each of which adds value in a different way. A Project Management Office System (PMOS) is designed to help project office personnel manage project and resource information. The system, built using Oracle Application Express (APEX) and hosted on Oracle Cloud, shall allow input of new project and new resource details, and manipulation of project/resource information. It will facilitate the allocation of resources to projects and the transfer of resources across projects. The system will also manage training requirements, training schedules, and training closure functions.

Automation of Databases in Oracle

Abstract: Ever since notable advancements were made concerning Database Management and regulation in the early 2000s, Automation of Databases in the Oracle environment have long been a crucial topic for research and development within the Computer Science and Information Technology sector. This research paper aims to explain what all factors necessarily require automation whilst bringing into light the growing demand for automation database management. As organizations across the globe face the imminent issue of overwhelming volumes of data, efficient database management systems that offer minimum complications are highly in demand. The paper not only highlights automation of various tasks such as routine maintenance, performance tuning, backup and recovery routine, but also emphasises the importance of security enhancements, real-time monitoring and scalability whilst placing forth key requirements of automation in general. The research presents a smarter and more robust database system model that can manage itself without the need of constant monitoring or intervention. Furthermore, we discuss the combining of cloud-based technologies such as Oracle Cloud and other containerization techniques to make the database more flexible and sustainable, all while keeping in mind the importance of having absolute rules and procedures for managing data in an automated system, which ensures that the data is well-organized, complies with legal requirements and is ready to be audited for accountability if needed. To conclude, the paper suggests nurturing practices of setting up systems that keep track of changes and versions to automate the infrastructure and managing of databases more consistently and efficiently. As organizations delve deeper into the landscape of database automation, they inadvertently face several challenges such as accuracy, security and accessibility of the data. This research paper specifically explores the requirements that promise to reshape the future of data management.

Magnets to Adversaries—An Analysis of the Attacks on Public Cloud Servers

Security adversaries are always constantly looking for targets to exploit. The mechanism of exploitation used by security adversaries varies significantly. Many focus on easy compromises as mere pivots to extend their attacks from these exploited systems to continue accomplishing their original goals. The cloud environment is a highly susceptible target for adversaries and provides a solid mechanism for observing adversary behavior. The sheer volume of attacks on the cloud provides insights into the attacker’s objectives and attack patterns, which can be leveraged for protecting infrastructure. This work deep dives into the practices used by adversaries on the commonly exposed protocols in the Amazon Web Services (AWS), Microsoft Azure (Azure), Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI) platforms. A robust honeypot model is documented that compares attacker behavior across various ports and protocols running in multiple cloud environments. This work illustrates that adversary activity is highly versatile in the public cloud environment, with an average of 700 new and unique IP addresses found attacking honeypot infrastructure daily. Further, this article illustrates the security safeguards a typical organization can leverage to mitigate the threats from these adversaries constantly probing insecure targets on the cloud platform.

WarpDOCK: Large-Scale Virtual Drug Discovery Using Cloud Infrastructure.

warpDOCK is an open-source pipeline for virtual small-molecule drug discovery using cloud infrastructure. warpDOCK is designed from the ground up for the Oracle Cloud Infrastructure (OCI), enabling harmonious parallelism of docking calculations over thousands to hundreds of thousands of cores. This enables cost-effective sampling of ultra-large chemical libraries, potentially reducing the time to identify lead drug candidates by orders of magnitude. By utilizing established docking software and automating each step of the process, warpDOCK makes large-scale virtual screening accessible to a broad user group. The warpDOCK code can be found at the BruningLab GitHub repository (https://github.com/BruningLab/warpDOCK).

Poland Supplier Whitelisting Process for Issuing Payments in the ERP System

The increasing complexity of global supply chains has underscored the need for robust and secure supplier management solutions within Enterprise Resource Planning (ERP) systems. This article explores the implementation and benefits of a Supplier Whitelisting Solution in the Oracle Cloud ERP system, with a specific focus on its application in Poland. The solution is designed to enhance the security and compliance of procurement processes by allowing only pre-approved and verified suppliers to participate in transactions. The paper examines the key features of the whitelisting functionality, including its integration with local regulatory requirements, and outlines the operational advantages it provides, such as risk mitigation, improved supplier relationship management, and streamlined auditing processes. Additionally, it discusses the challenges encountered during deployment and offers best practices for successful implementation. This article serves as a guide for organizations looking to enhance their supplier management capabilities within the Oracle Cloud ERP environment, particularly in the context of Poland’s regulatory landscape

Critique of “A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery” by SCC Team From ShanghaiTech University

In SC20, Srivastava <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> [6] proposed a Parallel F <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ram</b> ework for <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</b> ayesian <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Le</b> arning, or ramBLe, for short, which is a highly parallel and efficient framework for learning the structure of Bayesian Networks (BNs) from samples, particularly large genome-scale networks. As part of our participation in the SC21 Student Cluster Competition, our task was to verify conclusions from the original work [6]. Here we present the outcome of our experiments, which were performed on a four-node cluster from the Oracle Cloud HPC platform. We reproduce the numerical results from [6], namely the algorithm's performance and scaling behavior using MPI and different Python and Boost libraries on the Oracle cloud.

Modelling of diffraction of X-rays in perovskite superlattices

Nowadays, different perovskite structures are widely investigated because they can be potentially used in many branches of industry. If two materials are deposited alternately on a substrate, then a superlattice having some unique properties can be formed. However, X-ray intensity distributions for perovskite superlattices, especially for very thin films, are difficult to be computationally determined, because many different parameters need to be considered to reproduce a superstructure of a sample. The main purpose of this work is to demonstrate how basic intensity distributions can be generated for perovskites, XRD technique and how to improve results using specific numerical methods. The computer application with a user-friendly graphical interface has been developed employing Unity software (with 3D graphics tools) and Oracle Database (through Oracle Cloud Infrastructure). The calculations are based on the kinematical theory of diffraction. The values of some important parameters and the results are stored in the assigned database. It is assumed that epitaxial superlattices can be prepared on substrates using molecular beam epitaxy or pulsed laser deposition methods. The desktop application allows for designing samples of different thicknesses and combinations of monolayers. The results are more realistic if Monte Carlo simulations are done although longer computation time is required. The software developed should be helpful to compare in detail virtual model results with experimental data.

Interpretation on the Google Cloud Platform and Its Wide Cloud Services

Cloud computing is growing wide and first-rate promising technology. There are three forms of cloud computing: infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). There are many cloud service providers. Among these, AWS (Amazon Web Service), Azure (Microsoft Cloud), IBM Cloud, Oracle Cloud, and VMware are immensely popular. In this paper, the authors study the Google Cloud Platform (GCP) and a few principally used popular services. Google Cloud Platform could be a cloud provider; they supply servers and services that are used on-demand and at scale. Google Cloud Platform is the fastest growing cloud service supplier now.

Cloud Computing Services for Mobile Applications

Mobile applications are now dominating the marketplace, and the ease with which users can install and use the applications has also increased. To solve the problem of back-end infrastructure not being to handle high amounts of traffic generated by worldwide audiences, mobile developers now use cloud computing technologies. There are different options available in the market. In this research paper, we will go through the cloud service providers like AWS, Google Cloud, Oracle Cloud, and Microsoft Azure Cloud and compare their offerings.

E-LEARNING WEB APPLICATION FOR TEACHING ENGLISH FOR SPECIFIC PURPOSES - “ENGLISH AT A CLICK”

The web application "English at a Click", presented in this paper is used for learning specialized English. The application can be integrated into a part of a larger distance learning system, used as a supplement to traditional learning or as an independent web application. The current version of the application is implemented as an independent web application. The basic goal is to show the different contexts in which an English word can be used, which helps the user to choose the most appropriate term when translating a text from English into Serbian language and inversely. The application is in the prototype phase and it’s being tested. The tool presented in this paper was created on a free workspace on Oracle Cloud that the author uses for teaching purposes. The application was created with the idea to facilitate the learning of specialized English using modern technologies. The main advantage of the application compared to similar solutions is that it allows automatic text editing. The words from the text are replaced by the selected synonym only in the sentences that the user marks, very simply, with just a few clicks.

A pragmatic step to deploy low-code web apps on apex cloud services for emerging business assistance

Traditional approaches to web application development using the full-stack development model are inefficient. In today's rapidly changing business environment, organizations must rely on technology solutions that can be built and deployed in days or weeks, not months or years. Low-Code Development Platforms (LCDPs) compete with various features and technologies to provide business applications without prior knowledge of Internet technologies. Oracle Application Express (APEX) assists in the development of fantastic applications with little or no code in the Oracle database, as well as in the deployment of modern data-driven applications on the Oracle cloud platform, allowing users to quickly build secure business web applications with the best options., which can be accessed using an internet browser on desktop computers or mobile phones through its responsive web design without cost and time. Therefore, this paper demonstrates a pragmatic step toward deploying applications in a standalone database cloud using APEX services, which is focused on creating tables or converting spreadsheets into scalable, secure, and responsive web applications in minutes and providing automatic chart analysis reports for the business. As a result, individuals, Small- Scale Industries (SSIs), and Small and Medium Enterprises (SMEs) are encouraged to use cloud services that are always free with a 20 GB storage limit, which is outstanding resilience for cloudless web applications designed for new trends and business support free of charge. Machine learning in APEX Services can also be used to make web apps better for business intelligence in the future.

Generativity and the paradox of stability and flexibility in a platform architecture: A case of the Oracle Cloud Platform

Generativity is a technology’s capability of producing new outputs without input from the originator. Platforms are important technologies that embrace generativity. While the literature generally assumes that generativity arises from platform governance and high-level platform design, we propose that generativity also arises from a platform’s three architectural components: the base, the interface, and the add-ons. Drawing on a case study of the Oracle Cloud Platform, we reveal how generativity emerges through the paradox of stability and flexibility in a platform’s architectural components. Further, standardization navigates this paradox by coordinating the dependencies between stability and flexibility across heterogeneous stakeholders.

Cloud enabling educational platforms with corc

In this paper, it is shown how teaching platforms at educational institutions can utilize cloud platforms to scale a particular service, or gain access to compute instances with accelerator capability such as GPUs. Specifically at the University of Copenhagen (UCPH), it is demonstrated how the internal JupyterHub service, named Data Analysis Gateway (DAG), could utilize compute resources in the Oracle Cloud Infrastructure (OCI). This is achieved by utilizing the introduced Cloud Orchestrator (corc) framework, in conjunction with the novel JupyterHub spawner named MultipleSpawner. Through this combination, we are able to dynamically orchestrate, authenticate, configure, and access interactive Jupyter Notebooks in the OCI with user defined hardware capabilities. These capabilities include settings such as the minimum amount of CPU cores, memory and GPUs the particular orchestrated resources must have. This enables teachers and students at educational institutions such as UCPH to gain easy access to the required capabilities for a particular course. In addition, we lay out how this groundwork, will enable us to establish a Grid of Clouds between multiple trusted institutions. This enables the exchange of surplus computational resources that could be employed across their organisational boundaries.

Leveraging AWS and OCI for Optimized Cloud Database Management

Cloud database management has become a critical component for businesses seeking to enhance scalability, flexibility, and efficiency. In this paper, we explore the optimization of cloud database management through the integration of Amazon Web Services (AWS) and Oracle Cloud Infrastructure (OCI). Both platforms provide advanced solutions for database management, but their unique features, cost structures, performance characteristics, and security mechanisms demand careful evaluation. This paper presents a comprehensive analysis of AWS and OCI, comparing their respective database services, security models, and cost-efficiency techniques. We propose a hybrid approach that leverages the strengths of both platforms to achieve optimal database performance and scalability. Through experimental evaluations and simulations, we highlight how cloud service selection impacts critical metrics such as query response time, data throughput, and operational cost. Finally, we discuss the future potential for multi-cloud architectures, focusing on continuous innovations in database automation, machine learning integration, and real-time analytics.