Journal of Information Technology and Sciences (e-ISSN: 2581-849X)

Hashing Applications in Next-Generation Software

Sai Sukeerthi Yarlagaada, Manas Kumar Yogi — Thu, 09 Nov 2023 00:00:00 +0530

Hashing has emerged as a fundamental and versatile technique with a wide array of applications in the next generation of software systems. This paper explores the multifaceted role of hashing in modern software development, focusing on its significance and implications. In this context, hashing serves as a cornerstone in data security, ensuring data integrity and confidentiality through cryptographic hash functions, and protecting sensitive information from unauthorized access or tampering. It also plays a pivotal role in data retrieval and indexing, optimizing search operations, and enhancing data retrieval efficiency in large datasets, thus enabling faster and more responsive applications. Furthermore, hashing is instrumental in load-balancing algorithms, distributing data across multiple servers or nodes in a scalable and fault-tolerant manner. This helps achieve high availability and reliability, essential for next-generation cloud and distributed systems. Hashing also aids in data de-duplication, reducing storage overhead by identifying and eliminating duplicate data. Additionally, in machine learning and artificial intelligence applications, hashing assists in feature engineering, dimensionality reduction, and similarity computations, enhancing the performance of algorithms in various domains. In conclusion, the applications of hashing in next-generation software are vast and ever-evolving, contributing to the efficiency, security, and scalability of software systems. This paper delves into these applications and their potential to reshape the software landscape.

Research on Finite State Machine and Its Real Life Time Applications

Kirti Verma, Sateesh Kourav, Mukul Jangid, Uma Sahu, Neeraj Shivhare — Tue, 19 Dec 2023 00:00:00 +0530

In computer science, finite-state machines are widely used to characterize application behaviour control theory, hardware digital system design, software engineering, compilers, network protocols, and computational linguistics. Finite state machines can illustrate a system in which certain inputs induce defined state changes. Finite state machines are used to test the formation of algorithmic patterns on the under-test circuit. A finite state machine is a system that has a finite number of states and can only be in one of them at any one moment. FSMs are used to model and control application and system behaviour. They are especially effective for modeling systems that have distinct states and transitions between them. They can, for example, be used to simulate the behaviour of a vending machine, with the states representing the various states of the machine. FSMs are critical in hardware design for regulating the functioning of digital circuitry. They aid in the design of sequential logic circuits like counters, controllers, and state machines. In software engineering, FSMs may be used to design and construct systems with distinct modes or states. A traffic light controller, for example, can be implemented in a software program utilizing an FSM to handle the various states of the traffic lights. Compilers frequently employ FSMs during the lexical analysis and parsing stages to discover and analyze programming language components. Lexical analysers utilize FSMs to scan source code and find tokens, whereas parsers use FSMs to generate the syntax tree. FSMs are used to manage communication between networked devices during network protocol design and implementation. These protocols often feature well-defined states and transitions based on the messages sent. FSMs are used in natural language processing and computational linguistics to model language structures, perform morphological analysis, and detect patterns in text or speech. FSMs are used to build algorithmic test patterns in hardware testing. A Mealy finite state machine (FSM) model can be used to explain sequential blocks in digital systems. The logic component count, frequency of operation, and power consumption of the FSM must all be kept to a minimum. The study presents a novel design method for maximizing LUT counts in Mealy FSMs using LUTs. In the testing, traditional benchmarks were used. The results of the experiments show that, when compared to current approaches for single-level FSM synthesis, the proposed solution reduces LUT counts by 12% to 59% on average. Furthermore, by 9% to 20%, our strategy beats the previous two-level FSM synthesis strategies. This enhancement is followed by a little decrease in FSM performance.

IoT Framework for Early Fire Detection and Control in Public Large Buildings: A Review

Donald Mwambeleko — Wed, 20 Dec 2023 00:00:00 +0530

Fire destruction in large public and private buildings, particularly in markets, public offices, education, and industries, has devastated properties, costing millions while taking people’s lives. Fire destruction also extends to environmental degradation. Complete fire prevention is unattainable. However, an effort could be made to early fire detection and control to lessen the tragedy. There are several technologies for real time fire detection, like heat detection, gas detection, flame detection, and smoke detection. A maximal mix of fire detecting algorithms should be utilized to maximize accuracy and eliminate false fire confirmation. This research paper presents an early fire detection and control framework for large public and private buildings that utilizes the available fire detection technologies reviewed from various pieces of literature. In justification of the framework adaptability, the research paper examined the current state of firefighting infrastructures in large and private buildings. The review was based on ten (10) large public and private buildings. The buildings were divided into four strata (business centres, public offices, education and industries). In addition, information from the Fire and Rescue Force (Mbeya Office) was used to further envision the possibility of the framework adaptation. Generally, effort should be made to ensure old and new large public and private buildings have well functioning firefighting infrastructures as stipulated in policies and laws for public safety. Furthermore, slight infrastructure improvement is required, particularly in sustainable power supply, internet connectivity, and automatic fire detection and alarm systems, to adapt the presented early fire detection and control framework smoothly.

Enhancing Product Information from Agricultural Offices: A Path towards Improved Production of Agriculture

Sat, 30 Dec 2023 00:00:00 +0530

The agricultural sector's productivity and food security hinge on the availability of high-quality seeds. Across the globe, agriculture offices function as crucial repositories of seed information, acting as intermediaries connecting farmers with seed producers. Despite their pivotal role, the efficiency and accessibility of seed information from these offices can be refined to better serve farmers in their decision-making processes. This paper delves into an exploration of diverse strategies and technologies that can be deployed to enhance the dissemination of seed information from agriculture offices. The ultimate objective is to contribute to heightened agricultural productivity and the promotion of sustainable farming practices. By facilitating improved access to pertinent seed details, the aim is to empower stakeholders to make informed decisions, optimize agricultural practices, and foster a more resilient and efficient food production system. This comprehensive approach seeks to address existing gaps, ensuring that the vital link between seed information and successful farming is strengthened for the benefit of global agriculture.

Poor Quality Image Enhancement using Histogram Equalization Adaptive Sigmoid Function

Sandeep, Raghu Nandan.R, Mahantesh C. Elemmi, Yogeesh.G.H, Yashaswini H R — Sat, 30 Dec 2023 00:00:00 +0530

In this article, we provide a method for improving low-resolution photographs using the Bi-Histogram Equalization technique. One of the most common ways to improve contrast is by using histogram equalization. However, because of the over-enhancement nature, it might result in an unnatural look. In the proposed work, the RGB model is transformed into the HSV model, where Hue (H) and Saturation (S) represent the color channel value represents the luminance intensity and the V-channel is considered for image enhancement. To determine the cumulative density function and probability for every sub-histogram, we have made use of two sigmoid functions. These functions will be equalized independently using histogram equalization and stretched to achieve a smooth curve. After applying the histogram distribution to each sub-histogram, the origins of the sub-histograms are placed on their medians. The results are computed using the proposed methodology and also compared with the existing methodologies. The proposed method is observed to provide better accuracy than the other existing methods.