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IJHCS
Published by Research Parks Publishing
ISSN : 26151898     EISSN : 26158159     DOI : https://doi.org/10.31149/ijhcs.v7i1
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Neuroscience
The International Journal of Human Computing Studies (IJHCS) publishes original research over the whole spectrum of work relevant to the theory and practice of modern interactive systems of the contemporary world. IJHCS accepts papers in forms of original research articles, review articles, book reviews, case reports, and discussions to answer important and interesting questions of the innovative research points.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 417 Documents
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A QR Code-Based Real-Time Auditing System for Safe Online Data Storage S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 6 No. 1 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i1.5186

Abstract

Up until now, auditing systems have only had a web module; these modules are complicated and not user-friendly. Protecting sensitive data stored in the cloud requires the time-consuming and laborious procedure of encrypting all of the files. To verify a user's identification in the current system, the client must input biometric data. Next, in order to safeguard the user's identity and privacy, a signature key will be validated. One major problem with biometric data is that there are a lot of circumstances that might cause it to vary, so it can't always be matched precisely. An auditing and data storage app built for the cloud is the focus of this paper. The reference ID that the client creates is used to remotely store the financial audit data in the cloud. Using a QR code scanner, this reference ID that was generated for the client is immediately transformed into a QR code. You can access the required documents by downloading them and then opening them in a dedicated app. In the event that the client's internal storage becomes corrupted or lost, this file can be restored from the cloud.
Utilizing Deep Learning Classification Method for the Detection of Potholes T, Shynu; Rajest, S. Suman; Regin, R.; Raj, Steffi
International Journal on Human-Computing Studies Vol. 6 No. 1 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i1.5230

Abstract

The existence of potholes on the roadways is one of the primary factors that contribute to the occurrence of crashes involving automobiles. In order to find a solution to this issue, a number of different strategies have been explored. Among these methods are the employment of vibration-based sensors, manual reporting to authorities, and laser imaging for the reconstruction of three-dimensional space. The high cost of installation, potential danger during detection, and lack of night vision are just a few of the drawbacks of some of these systems. Researching the feasibility and accuracy of using thermal imaging to the problem of pothole detection is, hence, the goal of this effort. We have collected enough data with pictures of potholes in different weather conditions and used augmentation techniques to it. After this, a novel technique to this problem area that utilises thermal imaging the convolutional neural networks (CNN) method of deep learning was implemented. Also included is a comparison of the researcher's own convolutional neural model to pretrained models. Positive outcomes will follow from this investigation, and it will aid in directing future studies into this novel use of thermal imaging for pothole detection.
Using the Capabilities of the AutoCAD Program to Solve Metric and Position Issues Zhabbarov, Anvar E.; Akhmedov, Nurali O.
International Journal on Human-Computing Studies Vol. 6 No. 2 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i2.5247

Abstract

The article proposes to “compare” the solution of metric and positional problems in engineering graphics, that is, to perform it in practice with the help of computer programs after doing it manually based on theoretical knowledge. Theoretical knowledge teaches how to read drawings, how to imagine objects spatially depending on their representation, what operations are necessary to solve the problem, and introduces the laws and rules. Computer graphic programs, on the other hand, ensure that the drawings are done quickly, cleanly and accurately.
Human Stress Detection Through Sleep by Using Machine Learning Rajasekaran G; P.Velavan; B. Vaidianathan
International Journal on Human-Computing Studies Vol. 6 No. 2 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i2.5266

Abstract

An individual's capacity to learn, concentrate, make sound decisions, and solve problems is all profoundly affected by stress. Recently, researchers in the fields of computer science and psychology have begun to focus on stress detection and modelling. Affective states, the sensation of the underlying emotional state, are used by psychologists to quantify stress. Human stress classification has mostly relied on user-dependent models, which can't adapt to different users' needs. This necessitates a substantial amount of effort from new users as they train the model to anticipate their emotional states. Urgent action is required to address prevalent childhood mental health concerns, which, if left untreated, can progress to more complex forms. Analysis of medical data and problem diagnosis are now areas where machine learning approaches shine. After running Features on the complete set of characteristics, we were able to minimise the number of attributes. We compared the accuracy of the chosen set of attributes on several ML methods.
The Subject of This Study is the Multiphase Flow of a Compressible Liquid in a Porous Medium, Specifically Focusing on Classification Bustanov A. Khudaykul
International Journal on Human-Computing Studies Vol. 6 No. 2 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i2.5272

Abstract

Modeling the flow of two-phase compressible fluids through porous media is very pertinent to a broad spectrum of physical and technical applications. The study focuses on reservoir modeling and oil and gas production, which require the use of advanced numerical methods to ensure efficiency. The objective is to achieve a numerical solution to this model by integrating finite element and finite volume approaches. This involves generating velocity values at the boundary of the finite volume grid cells based on point pressure values at KE nodes.
Cloud Technology as a New Approach for Effective Education Aminov I.B.; Sharapova N.A.
International Journal on Human-Computing Studies Vol. 6 No. 2 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i2.5273

Abstract

One of the tasks of the education system in modern society is to provide each person with free and open access to education throughout his life, taking into account his interests, abilities and needs. The article considers the possibilities of using cloud technologies in education, and also presents the main examples of modern services built on the basis of cloud computing technology for education.
Analysis of Real-Time Video for the Detection of Fire Using OpenCV M. Gandhi, M. Gandhi; S. Manikandan, S. Manikandan; B. Vaidianathan, B. Vaidianathan
International Journal on Human-Computing Studies Vol. 6 No. 2 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i2.5280

Abstract

Because of the wide range of colours and textures present in visual landscapes, fire detection is a challenging undertaking. To get over this issue, several fire image categorization methods have been suggested; nevertheless, the majority of these systems depend on rule-based methods or characteristics that are manually created. Develop and propose an innovative technique for fire picture detection using deep convolution neural networks. Adaptive piece-wise linear units are utilised in the network's hidden layers in place of conventional rectified linear units or tangent functions. In addition, we will generate a fresh, compact dataset of fire photos to use for model training and evaluation. Increasing the amount of training images available through the use of conventional data augmentation methods and generative adversarial networks helps alleviate the overfitting issue that arises from training the network on a small dataset. In this study, we compare and contrast two methods for measuring the geometrical features of wildland fires: one that uses image processing to identify colours, and the other that uses Mk2ethods. Presented here are two novel rules and two novel detection methods that make use of an intelligent combination of the rules; their respective performances are then evaluated. About 270 million non-fire pixels and 200 million fire pixels taken from 500 wild terrain photos taken under different imaging conditions are used to run the benchmark. Color and presence of fire are used to classify pixels as fire, whereas average intensity of the associated image is used to classify pixels as non-fire. Because of this, the future of Metrologic systems for detecting fires in unstructured environments looks bright thanks to this technology.
SwiftTrip: Your Smart Travel Companion for Effortless Planning and Memorable Journeys R. Regin; Rajest , S. Suman
International Journal on Human-Computing Studies Vol. 6 No. 3 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i3.5316

Abstract

This paper presents "SwiftTrip," an innovative tool designed to enhance travel planning by integrating location, activity, weather, and packing considerations. As travel becomes increasingly spontaneous, there is a need for comprehensive solutions that cater to dynamic travel environments. "SwiftTrip" addresses this gap by offering detailed vacation itineraries, weather forecasts, and customized packing lists. The system utilizes climate patterns to suggest optimal travel routes and weather-sensitive recommendations for attractions and activities. Advanced algorithms analyze meteorological data to generate personalized packing lists, ensuring travelers are prepared for varying weather conditions. By providing current and forecasted weather data, including temperature, precipitation, and wind speed, "SwiftTrip" aims to make travel planning more informed and enjoyable, ultimately enhancing the travel experience in a rapidly changing environment.
Innovative Principles for Managing the Use of Mobile Software Tools Ilhom Isxokovich Juraev
International Journal on Human-Computing Studies Vol. 6 No. 3 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i3.5347

Abstract

Mobile software tools (MSTs) are increasingly significant in modern life, influencing various sectors such as education, business, healthcare, and entertainment. Effective management of MSTs is crucial for maximizing their benefits while mitigating potential risks. The insurance industry, in particular, has been transformed by the rapid adoption of digital technologies, allowing companies to deliver services through mobile applications and online platforms. Despite the growing trend of online insurance sales, disparities in accessibility and the efficiency of policy acquisition remain prevalent due to the absence of mobile applications in some cases. This chapter delves into strategies for integrating corporate applications, with a focus on architectural methodologies, integration approaches, and systems available for streamlining insurance policy sales.
Interval Potential Method for Solving Transportation Problems Using Mathematical Programming Khamroeva, Dilafruz
International Journal on Human-Computing Studies Vol. 7 No. 1 (2025): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v7i1.5355

Abstract

This study explores the interval variant of the potential method as an innovative approach for solving transportation problems within mathematical programming. Traditional methods often fail to address the complexities arising from parameter uncertainties, creating a knowledge gap in deriving reliable solutions under varying conditions. To bridge this gap, the interval potential method is proposed, utilizing interval matrices to define constraints and feasible solutions. The methodology involves constructing the initial transportation plan using the northwest corner method and applying interval analysis to account for data variability. A structured algorithm calculates directional potentials and checks the plan's acceptability, iteratively adjusting for optimal results. Numerical simulations demonstrate the robustness of the proposed method in solving transportation problems with uncertain parameters. Results confirm that this approach identifies optimal interval solutions while maintaining computational efficiency. The implications extend to various fields requiring reliable transportation and logistics optimization under uncertain conditions, such as supply chain management and resource allocation. This work contributes to the broader application of interval analysis in mathematical programming, providing a scalable solution for real-world challenges.

Page 40 of 42 | Total Record : 417

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