Journal of Technical Science and Technologies

Compare and Analysis of Different Access Controlling Mechanisms in OAuth 2.0

2024-04-29T12:19:18+04:00

This article analyses the basic concepts associated with authorization methods and how existing solutions face the common problems in the modern world. Different possible methods are introduced to solve such kind of problems. This paper proposes a model for attribute-based access control for cross-domain sources using APIs. The model includes basic architectural decisions and principles of ABAC (attribute based access control), RBAC (role based access control) and OAuth. Within the capabilities of OAuth 2.0 and ABAC will allow you to implement an end-to-end security model that can protect the privacy of customers and employees, the most important transactions for the financial sectors, business, and in general the most sensitive data over the API gateway. It is also possible to filter the response message, which is very important for customers.

A study of blood glucose determination by means of an interlaboratory test

2024-04-29T12:26:12+04:00

Through inter-laboratory comparison, based on the measurement process and measuring equipment conducted according to predetermined criteria, it is possible to evaluate the performance of the participants, which is known as qualification testing and is regulated in accordance with ISO 17043:2017/2018.
In the medical field, the term “external quality assessment” is used for qualification testing schemes or wider programs where samples (standard, certified, attested), products, artefacts, pieces of equipment, measurement standards, data sets or other information are used for qualification testing. The processing of measurement data, which in many cases includes a random error detector along with a systematic error detector, is carried out using mathematical statistics methods, including statistical methods that are less sensitive to small deviations from the basic assumptions surrounding the probabilistic model, which are known as robust methods. Robust methods are a powerful tool for demonstrating competence in performing tests and measurements related to qualification testing schemes.

Technological Aspects of Open Journal Systems (OJS)

2024-04-29T12:33:46+04:00

The traditional scholarly publishing landscape, dominated by large commercial publishers, has come under fire for high costs, limited access, and slow publication times. Open- source platforms are emerging as a powerful alternative, offering transparent, affordable, and accessible solutions for researchers to share their work with the world.Open Journal Systems (OJS) stands out as a powerful and adaptable open-source platform designed for managing and publishing academic journals (Ndungu, 2020)[2]. The architecture of OJS is a critical factor in its widespread adoption and success. Here’s a breakdown of key components

Artificial Intelligence for Decision Making in the Supply Chain

2024-04-29T14:47:55+04:00

Artificial intelligence (AI) is a technology that has the potential to significantly impact organizational decision-making. In supply chain management (SCM), data analysis and organizational decision-mak- ing play a crucial role in providing insights into various aspects of the supply chain, such as relevant goods, inventory levels, order processing times, delivery times, and transportation costs. By analyzing data, companies can identify inefficiencies in their supply chain and take corrective actions to improve performance. The SC system is a customer-oriented and integrated system that determines planning, administration, and management processes for internal and external material and related flows, for- mulating the optimal factor of added value. In this study, we aim to identify hazardous products by analyzing product identification information at customs checkpoints and locations where vendible items are delivered to customers. We have identified several commodity groups and substances that are potentially harmful and dangerous to human health.

Fall Detection System based on iOS Smartphone Sensors

2024-04-29T14:58:58+04:00

Activities of daily living (ADLs) are a crucial aspect of human life, especially in remote health monitoring and fall detection. As smartphones have become an integral part of our daily routines, with their ability to perform complex calculations, connect to the internet, and incorporate various sensors, researchers have been inspired to explore human activity recognition systems. This paper focuses on accelerometer and gyroscope data from iOS-based smartphones. We developed a data collection app to record fall types (e.g., Falling Right, Falling Left) and fall-like activities (e.g., Sitting Fast, Jumping). Volunteers carried smartphones naturally in their pockets during experiments, presenting a challenge of noise but enhancing user comfort. We applied different Machine Learning algorithms (Decision Trees, Random Forest, Logistic Regression, k-Nearest Neighbor, XGBoost, LightGBM, and Neural Networks) to analyze the collected dataset. In contrast to typical studies, our approach replicated real-world smartphone usage. The paper presents and analyzes promising results from the study. Furthermore, we implemented the trained model as a real-time mobile application for potential users. This research illustrates the potential of smartphones in fall detection and opens the way for user-friendly solutions in remote health monitoring.