International Journal of Sciences: Basic and Applied Research (IJSBAR)

The Phenomenological, Structural Synthesis Methodology for Art Theory

Narandorj Orgilbold — 2024-12-04

This paper reflects the practical importance of phenomenological, structural synthesis methods, which are universal research methods based on phenomenological methods. Also, the possibility of using this method in the interpretation of works of art was raised. In addition, phenomenological and structuralist synthesis method is explained within the framework of art theory, strengthening the possibility of using it within the popular categories of philosophy called Corporeality, anthropology and cultural studies.

Examining Risk in the Russian Economy through an Extreme Value Analysis of the Moscow Exchange (MOEX)

Jai Anand — 2024-10-30

The Russian Federation has long had a reputation for being a volatile country due to its geopolitical actions. Many investors are hesitant to invest in Russia as they question the practicality of it. This research seeks to answer their concerns using the statistical concept of extreme value theory (EVT), which existing literature has failed to apply to Russia in recent years. EVT is a branch of statistics that models values away from the center of the distribution, known as “extreme values.” In the context of this paper, this is an instances of heavy intraday stock loss. Essentially, EVT models can help answer the likelihood of losses and how much loss can happen. This research seeks to answer these concerns with an ex-post facto design in which data from Russia’s main stock index, the Moscow Exchange, is downloaded and analyzed using the Massachusetts Institute of Technology licensed Python package Pyextremes. After comparison to the main stock indices of India, France, and the USA, it was revealed that there is a likely greater risk associated with Russia in comparison to the other countries. Recommendations are made for those associated with Russia and its stock markets to manage investments, diversify portfolios, and seek resistance to mitigate the potential risks more carefully. Future research is suggested to use EVT in a more long-term analysis and to address the limitations of this study.

A Systematic Review of Deep Learning Methods: Classification, Selection, and Scientific Understanding

Zein Samira — 2024-11-11

This study, A Systematic Review of Deep Learning Methods: Classification, Selection, and Scientific Understanding, categorizes central deep learning (DL) models—including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), and Autoencoders (AEs)—based on their suitability for specific tasks and data types. While DL has achieved significant success in image recognition, language processing, and anomaly detection, several critical limitations pertain to interpretability, robustness, and scalability. This review summarizes the strengths and weaknesses of each model in a structured manner to guide the choice among DL models. Findings emphasize that theory must be advanced to improve transparency and reliability to better support practitioners and researchers in making informed choices for DL's responsible deployment across sectors.

Trending in Major Motivational Theories

Dragan Donev — 2024-10-16

This paper undertakes an examination of the driving forces behind the determination of student motivation both in the classroom setting and in other external circumstances. We initiate the analytical assessment with a brief introduction of the concept of motivation which reflects the central functional mechanism for the offering of motivational stimuli. The introduction encompasses the discussion of the primary major aspects affecting the understanding of what the motivation science says about its subject matter, presenting an overview of various research efforts which describe motivation as the driving force behind students' success in their academic pursuits. The following portions of the presentation propose a detailed illustration of other findings maintaining that success satisfaction is a key component of motivational human disposition. As we extend our investigation into the analytical framework of the area of motivational research, the factors that shape motivation are presented as well as the conditions that provide verification and support for student success. The paper extends its focus to the scrutiny of the overview of the trends in the major motivational theories showcasing a detailed report on the findings of various studies. The leading theoretical concepts and approaches within the discipline are outlined which cover the studies of motivation theories such as the self-worth theory of achievement motivation, the expectancy-value theory, the social cognitive theory, self-determination theory (SDT). Recommendations are likewise introduced for consideration regarding encouraging students to develop resilience in the course of study in order to solve challenges and stay motivated.

Exploring Shor's Algorithm in Cracking RSA Encryption

Aashutosh Srivastava — 2024-11-15

The present study explores the groundbreaking possibilities of Shor's algorithm in cracking RSA encryption, hence enhancing the security consequences of this extensively employed cryptographic protocol. Due to Shor's algorithm's exponential speed advantage over classical algorithms, RSA encryption—a popular public key cryptosystem—is vulnerable to quantum attacks. To keep its security, RSA depends on the difficulty of factoring huge semi-primes. RSA's security presumptions are called into question by Shor's algorithm's quick factorization on a quantum computer, which has prompted research into post-quantum cryptography solutions to guarantee secure communication in the quantum age. Even with parallel computation, the speed and storage capacity of classical computing are constrained. A key idea in quantum computing is quantum parallelism, which allows quantum systems to carry out several computations at once. In contrast to classical portions. The scope of this paper is to understand the fundamentals of Quantum Computing, the current state of Shor’s algorithm implementation, and efficiency, particularly its application in compromising public key cryptosystems like RSA. The project aims to achieve how factorization is done through classical methods and further, how is this done through Shor’s algorithm and QFT techniques.