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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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Application of the Multiplicative Method to Eliminate the Singularity in Integrals Oblokulov S; Pardayev M.
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.v5i12.5019

Abstract

In such cases it is necessary to construct exact quadratic formulas, as there are some errors in the approximate calculation of specific or non-specific integrals whose first-order derivatives become infinity in a given interval. In this work, the multiplicative method of loss of specificity under the integral of integral or non-specific integrals in which the first-order derivatives become infinity in a given interval is considered.
Features Changes Hemodinamic Liver Easy Preeclampsia Zaripova D.Ya
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.v5i12.5023

Abstract

Examine the systemic circulation of the liver and its role in the predicting of preeclampsia. We studied 100 pregnant women with mild preeclampsia (II group), and 50 pregnant women with physiological pregnancy control group (I group), 50 pregnant women with severe PE (III group). Comprehensive ultrasound and Doppler blood flow study was performed, ultrasound scanner Sono-scape SSI 5000 (China model) equipped with Convex probe (3.5 MHz) provided with a pulsed Doppler unit and wave function of the DRC. Examined blood flow in arteries and veins of the liver (liv A, liv V, Col V). Blood flow in the same hepatic portal vein and a tendency towards a certain decrease in pregnant women with PE. LMS and R & D in the hepatic artery, these values were increased by 13.3 and 26.4, respectively, in severe PE. Study features of hepatic arterial blood flow with the emergence of hypertension in pregnancy can be a predictor of the development of PE and its progress with the transition to severe.
University Students' Perception and Use of ChatGPT: Generative Artificial Intelligence (AI) in Higher Education Obenza, Brandon Nacua; Salvahan, Alexa; Rios, Alexandra Nicole; Solo, Althea; Alburo, Rea Ashlee; Gabila, Rey Jose
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.v5i12.5033

Abstract

This quantitative study examined how university students perceive and use generative AI technology, specifically ChatGPT, in higher education. The main objective is to explore and describe university students' perception and use of generative AI, particularly ChatGPT, in the context of higher education. A 5-point Likert scale questionnaire was adopted and used in the study. Five hundred students from various universities in Region XI were surveyed using a stratified random sampling technique. Further, the validity and reliability of the scale used in the study were assessed using Cronbach's Alpha and Factor Analysis and demonstrated acceptable construct validity and reliability indices. The findings revealed that university students demonstrated high levels of understanding, knowledge, perception of the advantages and disadvantages, positive attitude, and strong intention to use generative AI technologies in the context of higher education. Moreover, the respondents showed a moderate level of concern about generative AI.
Energy Efficient Cloud Computing Using Artificial Neural Networks Al-Mudhafar, Haneen Saeed; Ibrahim, Abdullahi Abdu
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5049

Abstract

This effort focuses on building an intelligent, energy-efficient cloud architecture to improve cloud computing infrastructures. The rate at which cloud data gets modernized has increased, leading to more reviews comparing the various modernization methodologies and models. Several wealthy nations, including Turkey, have upgraded to more complicated and energy-efficient cloud infrastructure. We designed a Python application that uses an AI framework to maximize cloud computing's usage of computing resources and clean, renewable energy. This plan outlines concepts for a future neural network-trained digital ecosystem (ANN). The ANN model details energy forecasting tasks within a constrained system. Prominent corporations use AI to design policies to secure their cloud infrastructures and digital assets. Cloud computing systems were modernized by acquiring, normalizing, and transforming their file formats. Most cloud-based infrastructures were updated successfully. This was expected, given digital implementations dominate these systems. We'll investigate the energy consumption of AWS, AZURE, GCP, and Digital Ocean. Since most files were still on paper in 2015, the number of upgrades was modest. By 2020, a large part of cloud computing systems will be converted to digital format, with 98.68% accuracy for all cloud computing systems when trained on 80% of the data and evaluated on 20% of the data. Smart energy-efficient cloud solutions are replacing traditional data centers year by year. Smart energy-efficient cloud systems help preserve cloud computing systems and understand how cloud platforms are modernized and perform in energy prediction.
The Relationship "Parents and Child" In Russian and German Siddikova Nargiza Badirovna
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5054

Abstract

In line with comparative linguistics (based on the proverbial fund of the Russian and German languages), “parents – children” is described. Features indicated representations of the relationship between parents and children in both linguistic cultures, similarities and differences due to mentality and cultural identity are identified representatives of the described language communities.
Recording Student Attendance and Recognizing Their Faces Using Deep Learning Al-Inizi, Hayder Hamid Hammodi; Kurnaz, Dr. Sefer
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5075

Abstract

There are several methods available to monitor student attendance in classes, such as biometric, radiofrequency, face recognition, and paper-based systems. However, the face recognition-based approach has been found to be both efficient and secure. In this study, a threshold to confi-dence has been implemented through Euclidean distance values to en-hance the identification process. The Local Binary Pattern Histogram (LBPH) algorithm has been utilized for this purpose, as it has been demonstrated to be more effective than other methods such as Eigenfaces and Fisher faces. The Haar cascade method has been used for facial de-tection due to its robustness. The system's performance has been assessed in various scenarios, including recognition rates, false-positive rates, and detecting unknown individuals with or without a threshold. The system has demonstrated an impressive 79% recognition rate for students, with a 24% false-positive rate, and can identify students wearing glasses or a beard. The LBPH algorithm and Haar Cascade method contribute to the system's exceptional performance. The recognition rate for unregistered individuals in facial recognition technology is noteworthy even without the use of a threshold value, sitting at a commendable 64%. Moreover, the rate of false positives is impressively low, remaining at approximate-ly 15% and 31%.
An Approach Based on Machine Learning for Conducting Sentiment Analysis on Twitter Data S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5122

Abstract

Using Twitter's primary goals as a guide, we built a real-time sentiment analysis system that labels tweets according to the emotions they convey. One more way Twitter facilitates social networking is through microblogging, which allows users to record brief status updates. The analysis of the emotions conveyed at intervals between tweets allows us to get a reflection of public attitude, which is made possible by this massive amount of usage. The goal is to find the most accurate way to examine the information by primarily applying approaches based on machine learning. Data validation, cleaning, and preparation for visual representation will be performed on the entire provided dataset after the controlled AI technique (SMLT) has been used to capture various pieces of information, such as variable ID, amount and factual strategy, missing worth medicines, and univariate examination. Through the discovery of the optimal exactness computation, our inquiry provides a comprehensive guide to sensitivity analysis of model parameters in relation to performance in sentiment analysis prediction. All of the algorithms' performance metrics, including exactness recall, f1score, sensitivity, and specificity, are also computed and compared.
Planning the Most Effective Itinerary for Tourists through the use of Data Analysis R. Regin; S. Suman Rajest; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5124

Abstract

In order to provide the most effective scheduling alternatives, data analysis of the information that the customer has provided is performed. The mobile application provides further recommendations, such as a list of all the appropriate sites or areas to visit inside the destination that has been picked, once the intended destination has been specified. In addition, the other significant recommendations concerning the method of transportation, the most efficient routes, the most desirable times, and the expenses associated with them will be automatically offered. Additionally, the Android Studio toolkit and the Google Maps interface are utilised in the process of application creation. Hadoop is used for the analysis of weather data. Hadoop is a Java programming platform and open-source Apache software that is utilised in the distributed world for the purpose of managing the management of enormous data volumes. One of the most significant benefits is the utilisation of the machine learning approach to cost estimation in the budget planning process. Travel plans that are efficient are provided by the intelligent local route as well as the form of transportation. The online application offers a platform that functions as a digital assistant that is intelligent and tailored to the tourists' areas of interest.
Constructing Ellipse Points as an Isometry of a Circle Using the Graphical Method Akhmedov Nurali Odilovich
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.v6i1.5176

Abstract

Creating ellipses dots from graphic method is offered in this article. In this case, the graphical method for constructing an ellipse is described in detail, and it is recommended to use it in modern architecture of buildings, since ellipsoids provide structural strength and have an excellent appearance.
Automation System for Kiosk Ordering Processes for Tourists Nazarov F.; Salimova M.
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.v6i1.5182

Abstract

In this research work, the system of automating kiosk ordering processes for tourists and its possibilities are mentioned. In this, the service functions of kiosks, better and faster customer service, adequate satisfaction of customer needs, prevention of disagreements between customers and employees, ordering kiosks for tourists and their capabilities are fully covered.

Page 39 of 42 | Total Record : 417

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