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International Conference on Innovations in Pharmaceutical and Critical Care Diagnostics (IC-IPCCD)

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Articles

An efficient method for predicting a consumer behavior using Logistic Regression algorithm and Apriori algorithm.

LEKSHMI MOHAN, MONISHA DEVARAJAN , Dr. Firas Jamil ALotoum, Dr.Majdi Alsaaideh, KDV PRASAD , Dr. Natrayan L ,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Predicting consumer behavior is a crucial step in the process of doing a business analysis and developing a strategy. Machine learning has being used to forecast customer behavior as AI technology has advanced. This paper introduced novel method for consumer prediction using Logistic algorithm and Apriorist Algorithm. We use Machine learning algorithms for best ac- curacy and prediction. This research paper aims to identify the most efficient algorithm in terms of for consumer prediction. The performance was analyzed for large data set.  

A comparative analysis of AI techniques for fraud detection in financial transactions using Logistic Regression algorithm and Random forest algorithm.

Gunawanwidjaja, Radha T, Dr.RupamSoni, Kuldip Sharma, MS.M.E Devashree, Dr. Natrayan L,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Abstract:With annual costs in the billions of dollars, fraud is a significant issue in the banking sector. Artificial intelligence (AI) systems may identify fraud in financial transactions by identifying patterns that point to it. Two popular techniques for AI fraud detection are random forests and logistic regression. This study compares the efficacy of random forests with logistic regression for the identification of financial transaction fraud. We assess the performance of the two techniques using a collection of real-world financial transactions that have been categorized as either legitimate or fraudulent using a variety of criteria, such as recall, accuracy, precision, and F1 score. Our results show that random forests outperform logistic regression in the detection of fraud in financial transactions. Random Forest accuracy was reached. Our results show that random forests outperform logistic regression for financial transaction fraud detection. Random forests had a 99.5% accuracy rate compared to 98.5% for logistic regression. Random forests also showed better recall and accuracy than logistic regression. These results suggest that random forests are a better option than logistic regression for financial transaction fraud detection. Index Terms: data analytics, random forest algorithms, logistic recursion algorithms, machine learning, and fraud detection

Investigating Magneto-Resistive Effects in Compensated Silicone Materials: An AI-Enhanced Exploration of Techniques

Isroilov Fakhriddin Muradkasimovich , Shertailakov Gayrat Murodovich, Rakhmonov Furkat Abdukhakimovich , Abdurakhmanov Aziz Abdukhalikovich ,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Due to their high temperature sensitivity, our composite temperature sensors make the job much easier when used as an accessory. In our case, the signal can be sent directly to the device registrar or enforcement authority. This increases reliability and reduces the cost of the temperature sensor. An analogue of the composite temperature sensors developed by us is VZ SENSOR Ltd. at the Institute of Management Problems of the Uzbekistan Academy of Sciences. together with can be smart (functional) thermistors developed on the basis of semiconductor structures. The L-shaped current-voltage characteristic is able to solve the problem of selecting certain temperature values without using additional electronic circuits.

Photocatalytic Degradation of Congo Red Dye Using Graphene-BiFeO3 Nano Composite: Enhancing Secure Communication with Blockchain Technology.

Pappu Kumar, Raj kumar gupta,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Abstract-In present report, we have synthesized graphene-BiFeO3 by sol-gel cum ultrasonication technique. X- ray diffraction, transmission electron microscopy, and UV-visible spectroscopy were used to verify crystallographic analysis, particle microstructure, and optical properties, respectively. The production of a pure phase of BiFeO3 and its nano composite has been established using X-ray diffraction. Under UV- vis irradiation, the produced materials demonstrated excellent photocatalytic activity. We have found that the composite version of material has better photo catalytic dye degradation in comparison of pristine.

Applicability of Machine Learning in Process Industry: A Review

Suchita Walke, Jagdish W .Bakal,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Nanomaterials made of cobalt ferrite (CoFe2O4) have drawn a lot of interest because of its potential uses in a number of industries, including energy storage, catalysis, and spintronics. By adjusting the annealing temperature, CoFe2O4 nanoparticles' structural and magnetic characteristics can be customized. To investigate how annealing temperatures, affect the structural and magnetic characteristics of CoFe2O4 nanoparticles, however, can be quite computationally intensive. This problem can be solved via cloud computing. High-performance computing resources are accessible on demand thanks to cloud computing. This eliminates the need for researchers to invest in their own high-performance computing infrastructure in order to explore the impact of annealing temperatures on the structural and magnetic properties of CoFe2O4 nanoparticles. We provide a cloud-based framework for investigating the impact of annealing temperatures in this paper. In this article, we provide a cloud-based platform for researching how CoFe2O4 nanoparticles' structural and magnetic characteristics are affected by annealing temperatures. The platform analyzes the data produced by the simulations using a range of machine learning methods.

Integrating Machine Learning in Teaching and Education

Dr Baig Muntajeeb Ali,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Recently, machine learning has become popular in education and classroom teaching. This study examines machine learning's usefulness in academic settings and its barriers to wider adoption. A comprehensive literature review was undertaken to furnish a synopsis of machine learning, an understanding of education and instruction, and previous studies concerning the implementation of machine learning in this domain. Student learning outcomes may be improved through the integration of machine learning into instruction and learning, according to the study's findings. Nevertheless, the integration of machine learning into educational settings presents several challenges, encompassing technological, pedagogical, ethical, and implementation-related concerns. In order to effectively integrate machine learning into the realm of education, it is imperative that these challenges be duly acknowledged and suitable resolutions be sought. Educators, educational organizations, and policymakers interested in the integration of machine learning into the learning process may find the findings of this study to be a supply of insightful information. Despite the potential benefits, the study finds that incorporating machine learning into teaching and learning is valuable despite the many challenges.

Detecting Driver Somnolence with Deep Learning: Advancements in Driver Safety and Alertness Monitoring

Peddinti. Neeraja, Dr. R G KUMAR, Dr.M. Sunil Kumar, Dr KaziKutubuddin Sayyad Liyakat, Ms. M. Sowmya Vani,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract explores the utilization of deep learning for detecting driver somnolence, aiming to enhance driver safety and alertness monitoring. It investigates the integration of computer vision, physiological signals, and machine learning algorithms. Key considerations include real-time detection, accuracy, scalability, and driver intervention mechanisms. By leveraging deep learning techniques, effective driver somnolence detection systems can contribute to preventing accidents and promoting safer roads.

Enhancing Accessibility: Image Captioning for Visually Impaired Individuals in the Realm of ECE Advancements

Qazi Mohd Iqbal Hussain Anwar, Ch V S Satyamurty, Rakesh Kumar Godi,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

In the world we are living in the most important means of taking information and making sense from it is vision. According to the research made by the scientist’s vision is described as our dominant sense. It is challenging for the person who doesn’t have this crucial ability and such people are called blind. Blind people do lead regular lives and have unique ways of carrying out tasks, but they undoubtedly struggle, so to overcome the challenges faced by them there have been several solutions proposed and one of them is Image Captioning i.e. using deep learning models to create captions for images which shows surrounding of the blind person. The traditional architecture for generating captions is using CNN-LSTM encoder-decoder model. The proposed method utilizes the novel Image Captioning approaches for Visually Impaired People data set containing several use cases (pedestrian crossing, currency detection, bus stops, stair case. . . etc) to train and test through modern approach for Image captioning. The suggested method makes use of a data set with multiple use cases (pedestrian crossings, money detection, bus stops, staircases, etc.) from the innovative Image Captioning for Visually Impaired Dataset in order to train and evaluate a contemporary strategy for Image captioning. By training it on the aforementioned dataset, we examine the effectiveness of two contemporary techniques to picture captioning (YOLO - LSTM) and (CLIP - GPT). Using a common metric (BLEU), the suggested method’s effectiveness is assessed.

Philosophical and Legal Analysis of Law in the Context of Advanced Antenna Systems for Beamforming and Massive MIMO.

Shayakubov Shomansur, Sultanova Aziza,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

With the staggering advancement of informational technologies, researchers all over the world are endeavoring to closely integrate IT in the field of their profession. Constituting a part of this modernity linguists trying to focus on the benefits of IT in the terms of advancement of foreign language teaching/learning. This article regards on the potential benefits as well as approaches of corpora database in the teaching vocabulary in foreign classes. It is believed that general language ability highly relies on the Competency in knowing and using words in true contexts (Carter & McCarthy, 1988). However, nearly all learners whether English as a second or foreign language (ESL / EFL) learners face some difficulties with vocabulary, and it becomes one of the leading difficulties of language instruction (Cobb, 2003). On the other hand, it cannot be ignored that vocabulary is an indispensable element of a language and of critical importance to the EFL learners (Zhang & Liu, 2014).

SYNERGY OF CURRENT KNOWLEDGE IN PHYSICS, AGROMETEOROLOGY AND MODERN TECHNOLOGIES IN AGRICULTURE

A.B.Kamalov, S.U.Ashirbekova, M.P.Serimbetova, Sh.J.Baymuratov, B.Sh.Aytmuratov, M.Eshbaeva,

Year: 2023 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract presents an Online Voting System that leverages Python algorithms along with a range of technologies and frameworks including Django, face recognition, OpenCV, Pillow, Scikit-learn, Tesseract, Mkdocs, Django REST API, SQLite3 database, Jinja tags, HTML, and CSS. The proposed Online Voting System aims to provide a secure, efficient, and accessible platform for conducting elections or voting processes. It incorporates robust security measures to ensure the integrity and confidentiality of votes. Face recognition, implemented using OpenCV and face recognition algorithms, allows for biometric authentication, minimizing the risks of fraudulent activities and impersonation. To ensure accurate vote counting and analysis, the system employs Python algorithms and Scikit-learn for data processing and classification tasks. Additionally, Tesseract, an optical character recognition (OCR) engine, enables the system to handle scanned documents or images containing text-based information. The Django framework is utilized to develop the web application, providing a user-friendly interface for voters to cast their votes securely. Django' s built-in authentication and authorization mechanisms, along with SQLite3 database, ensure data integrity and prevent unauthorized access. Mkdocs is employed to generate comprehensive documentation for the system, enabling easy maintenance and understanding of the codebase. Additionally, Django REST API is utilized to facilitate seamless integration with external services or applications. Jinja tags, HTML, and CSS are used for front-end development, allowing for a visually appealing and responsive user interface. This combination of technologies ensures an intuitive and accessible voting experience across various devices and platforms. The Online Voting System presented in this abstract offers a secure, efficient, and user-friendly solution for conducting elections. By leveraging Python algorithms and an array of cutting-edge technologies, the system provides robust security, accurate vote counting, and a seamless user experience, thereby addressing the challenges faced by traditional voting systems.


International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

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