A Questioning Agent for Literary Discussion

Developing a compelling and cohesive thesis for analytical writing can be a daunting task, even for those who have produced many written works, and finding others to engage with in literary discussion can be equally challenging. In this paper, we describe our solution: Questioner, a discussion tool that engages users in conversation about an academic topic of their choosing for the purpose of collecting thoughts on a subject and constructing an argument. This system will ask informed questions that prompt further discussion about the topic and provide a discussion report after the conversation has ended. We found that our system is effective in providing users with unique questions and excerpts that are relevant, significant, and engaging. Such a discussion tool can be used by writers building theses, students looking for study tools, and instructors who want to create individualized in-class discussions. Once more data is gathered, efficient and accurate machine learning models can be used to further improve the quality of question and excerpt recommendations. Co-creative discussion tools like Questioner are useful in assisting users in developing critical analyses of written works, helping to maximize human creativity

Enhancing Query Processing on Stock Market Cloud-based Database

Cloud computing is rapidly expanding because it allows users to save the development and implementation time on their work. It also reduces the maintenance and operational costs of the used systems. Furthermore, it enables the elastic use of any resource rather than estimating workload, which may be inaccurate, as database systems can benefit from such a trend. In this paper, we propose an algorithm that allocates the materialized view over cloud-based replica sets to enhance the database system\u27s performance in stock market using a Peer-to-Peer architecture. The results show that the proposed model improves the query processing time and network transfer cost by distributing the materialized views over cloud-based replica sets. Also, it has a significant effect on decision-making and achieving economic returns

Assessing the vulnerabilities and securing MongoDB and Cassandra databases

Due to the increasing amounts and the different kinds of data that need to be stored in the databases, companies, and organizations are rapidly adopting NoSQL databases to compete. These databases were not designed with security as a priority. NoSQL open-source software was primarily developed to handle unstructured data for the purpose of business intelligence and decision support. Over the years, security features have been added to these databases but they are not as robust as they should be, and there is a scope for improvement as the sophistication of the hackers has been increasing. Moreover, the schema-less design of these databases makes it more difficult to implement traditional RDBMS like security features in these databases. Two popular NoSQL databases are MongoDB and Apache Cassandra. Although there is a lot of research related to security vulnerabilities and suggestions to improve the security of NoSQL databases, this research focusses specifically on MongoDB and Cassandra databases. This study aims to identify and analyze all the security vulnerabilities that MongoDB and Cassandra databases have that are specific to them and come up with a step-by-step guide that can help organizations to secure their data stored in these databases. This is very important because the design and vulnerabilities of each NoSQL database are different from one another and hence require security recommendations that are specific to them

From backend to Dashmobile: expanding the horizons of the drone engineering ecosystem

The Drone Engineering Ecosystem (DEE) project is a groundbreaking initiative that aims to simplify access to the world of drones and promote their responsible use, particularly in the educational domain. Traditional methods of drone control and interaction have been complex and fragmented. The DEE project seeks to overcome these challenges by integrating various technologies, including Python, Tkinter, FastAPI, MongoDB, Flutter, and Dart, to create a cohesive and user-friendly ecosystem. The project began with a comprehensive analysis of the existing drone ecosystem, identifying its limitations and areas for improvement. This was followed by the formulation of clear objectives and a detailed work plan, visualized through a Gantt chart. The development process encompassed the creation of a robust backend, significant enhancements to the existing dashboard, and the development of a mobile application using Flutter. One of the main challenges was the integration of new technologies like Flutter and Dart, which were learned specifically for this project. Rigorous testing and user experience evaluation were integral to ensuring the system's functionality and usability. The project's success not only achieved most of the set goals but also opened new avenues for future exploration and development in the drone technology field. My passion for programming and the application of my Telecommunications Engineering bachelor's degree were key drivers in the project's success. The project represents a significant contribution to the field, providing a platform for learning and promoting the responsible use of drones. It also reflects my commitment to challenging myself and applying my academic knowledge to real-world problems.Objectius de Desenvolupament Sostenible::4 - Educació de Qualita

BlackWatch:increasing attack awareness within web applications

Web applications are relied upon by many for the services they provide. It is essential that applications implement appropriate security measures to prevent security incidents. Currently, web applications focus resources towards the preventative side of security. Whilst prevention is an essential part of the security process, developers must also implement a level of attack awareness into their web applications. Being able to detect when an attack is occurring provides applications with the ability to execute responses against malicious users in an attempt to slow down or deter their attacks. This research seeks to improve web application security by identifying malicious behaviour from within the context of web applications using our tool BlackWatch. The tool is a Python-based application which analyses suspicious events occurring within client web applications, with the objective of identifying malicious patterns of behaviour. This approach avoids issues typically encountered with traditional web application firewalls. Based on the results from a preliminary study, BlackWatch was effective at detecting attacks from both authenticated, and unauthenticated users. Furthermore, user tests with developers indicated BlackWatch was user friendly, and was easy to integrate into existing applications. Future work seeks to develop the BlackWatch solution further for public release

Fine-Grained Access Control Within NoSQL Document-Oriented Datastores

The recent years have seen the birth of several NoSQL datastores, which are getting more and more popularity for their ability to handle high volumes of heterogeneous and unstructured data in a very efficient way. In several cases, NoSQL databases proved to outclass in terms of performance, scalability, and ease of use relational database management systems, meeting the requirements of a variety of today ICT applications. However, recent surveys reveal that, despite their undoubted popularity, NoSQL datastores suffer from some weaknesses, among which the lack of effective support for data protection appears among the most serious ones. Proper data protection mechanisms are therefore required to fill this void. In this work, we start to address this issue by focusing on access control and discussing the definition of a fine-grained access control framework for document-oriented NoSQL datastores. More precisely, we first focus on issues and challenges related to the definition of such a framework, considering theoretical, implementation, and integration aspects. Then, we discuss the reasons for which state-of-the-art fine-grained access control solutions proposed for relational database management systems cannot be used within the NoSQL scenario. We then introduce possible strategies to address the identified issues, which are at the basis of the framework development. Finally, we shortly report the outcome of an experience where the proposed framework has been used to enhance the data protection features of a popular NoSQL database

Research and Development Workstation Environment: the new class of Current Research Information Systems

Against the backdrop of the development of modern technologies in the field of scientific research the new class of Current Research Information Systems (CRIS) and related intelligent information technologies has arisen. It was called - Research and Development Workstation Environment (RDWE) - the comprehensive problem-oriented information systems for scientific research and development lifecycle support. The given paper describes design and development fundamentals of the RDWE class systems. The RDWE class system's generalized information model is represented in the article as a three-tuple composite web service that include: a set of atomic web services, each of them can be designed and developed as a microservice or a desktop application, that allows them to be used as an independent software separately; a set of functions, the functional filling-up of the Research and Development Workstation Environment; a subset of atomic web services that are required to implement function of composite web service. In accordance with the fundamental information model of the RDWE class the system for supporting research in the field of ontology engineering - the automated building of applied ontology in an arbitrary domain area, scientific and technical creativity - the automated preparation of application documents for patenting inventions in Ukraine was developed. It was called - Personal Research Information System. A distinctive feature of such systems is the possibility of their problematic orientation to various types of scientific activities by combining on a variety of functional services and adding new ones within the cloud integrated environment. The main results of our work are focused on enhancing the effectiveness of the scientist's research and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian. Published. Prepared for special issue (UkrPROG 2018 conference) of the scientific journal "Problems of programming" (Founder: National Academy of Sciences of Ukraine, Institute of Software Systems of NAS Ukraine

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed