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A Multi-Model Approach to Aspect-Based Sentiment Analysis of Car Reviews
This study presents an application of Aspect-Based Sentiment Analysis (ABSA) on a dataset of car reviews collected from the CarDekho website. The dataset comprises reviews for four distinct car models of four popular brands. Our objective was to extract ...
Employing Deep Convolutional Neural Networks for Microstructure Image Classification
The aim of this study is to employ deep learning models for microstructural image classification. The microstructures provide valuable insights into material's history and properties, but manual classification is time consuming, labor-intensive and ...
Bio-inspired Intrusion Detection System for Internet of Things Networks Security
The contemporary era has witnessed substantial growth in the Internet of Things (IoT), accompanied by an escalation in data volume due to the proliferation of Internet-connected devices. Unfortunately, this surge has attracted the attention of ...
Jointly Preserving Subject and Object Anonymity in Nearby Friends Querying for Curious Service Providers
This work studies the urban area location privacy preserving location updates and nearby friends (NF) querying for the centralized proximity based services (PBSs). The urban area constraint forces the user mobility to be on the city road network, ...
Mathematical Support for The Study of Three-Layer Rods Under Spatial Loads
This article is devoted to the development of mathematical support (software) for the study of three-layer rods under spatial loads. Variations in kinetic and potential energy and the work of external volumetric and surface forces of a three-layer rod ...
Enhancing Lane Detection Performance A Comprehensive Analysis of YOLOPv2 under Adverse Conditions
With the growing global interest in autonomous driving from big car companies and the research community, road lane detection has become a hot topic. In this paper, You Only Look Once for Panoptic Driving (YOLOPv2), which is a deep learning network that ...
The use of ChatGPT to generate Summative Feedback in Programming Assessments that is Consistent, Prompt, without Bias and Scalable
ABSTRACT
This paper explores the automated integration of ChatGPT into the feedback process for a large-scale and complex university programming assignment. It aims to explore the feasibility of using ChatGPT to facilitate prompt, efficient, and valued ...
Childhood Obesity Prediction: Algorithms, Datasets, and Taxonomies
Childhood obesity is a significant health concern impacting children and adolescents. The excess weight often initiates health issues such as diabetes, high blood pressure, and elevated cholesterol levels. Moreover, childhood obesity can contribute to ...
Assessing the Impact of Virtual Reality on Enhancing Consumer Satisfaction in the Context of Streaming Services: The Case of Netflix
Virtual Reality has revolutionized user experience in various domains. The integration of Virtual Reality into e-commerce platforms is rapidly advancing, offering an immersive experience beyond traditional interactions. This study examines several ...
Fractal Measurement of Images Human Brain from MRI
This article is devoted to the determination of the fractal size of the damaged part of the human brain on the basis of images obtained from MRI (magnetic resonance imaging). There are various mathematical methods for determining the size of fractal ...
Optimizing MIMO-OFDM Communication Systems: A Comparative Analysis of LMMSE and LZF Equalizers under Varying Antenna Configurations
Orthogonal Frequency Division Multiplexing (OFDM) has emerged as a fundamental modulation technique in modern broadband wireless communication systems, effectively addressing challenges arising from dispersive channels and random fading phenomena. By ...
Speed Control of Brushless DC Motor based on Online Neural-PID Controller
DC brushless motors have exceptional characteristics in terms of their speed and torque capabilities. But this outstanding performance comes at the price of potential disturbances that arise during loading. These disturbances can be attributed to the ...
Underwater image processing based on CNN applications: A review
In recent years, due to the natural resources contained in the vast underwater world and the diversity of organisms present in it, including microscopic organisms, coral reefs, seaweed, many types of fish and marine animals, and the presence of ...
Analyzing Methods for Classification of Electronic Word-of-Mouth: A Review
This paper explores the evolving landscape of electronic word-of-mouth (eWOM) and its impact on consumer behavior. With the transition from traditional word-of-mouth to online platforms (users’ reviews), businesses now have access to vast amounts of user-...
Velocity Analysis of the Inverted Slider-Crank Mechanism using Artificial Neural Network Approach
In this study, velocity analysis of the inverted slider-crank mechanism using a supervised learning algorithm is introduced. Although velocity analysis of a slider-crank mechanism is simple and very well-established, there has been not been an ...
Solving Secluded Path Problem by Heuristics and Local Search
Wireless Sensor Networks (WSNs) play a crucial role in various domains, from commercial to military, enabling precise monitoring of environmental and other conditions. However, the transmission of sensitive data in WSNs poses security challenges, ...
Exploring the Role of Explainable Artificial Intelligence(XAI) in Adaptive learning systems
Explainable Artificial Intelligence (XAI) plays a pivotal role in enhancing adaptive learning systems by fostering an environment where transparency is key to developing students' critical thinking skills. In such systems, each learner's experience is ...
Comparative Performance of Advanced NLP Models and LLMs in Multilingual Geo-Entity Detection
The integration of advanced Natural Language Processing (NLP) methodologies and Large Language Models (LLMs) has significantly enhanced the extraction and analysis of geospatial data from multilingual texts, impacting sectors such as national and ...
Advancing Cyber Threat Intelligence through Machine Learning Algorithms
In the domain of Cyber Threat Intelligence (CTI) the enigmatic depths of the Dark Web are pivotal for the early identification of nascent cyber threats. Yet, the voluminous and sprawling data across hacker forums and illicit marketplaces pose a ...
Hybridizing Computational Intelligence and Computer Vision Techniques for Efficient Navigation and Marker Detection and Identification by a Swarm of Minirobotic Units
Swarm intelligence is a a branch of artificial intelligence grounded in the observation that swarms of simple individuals or agents with very limited intelligence can achieve remarkably intricate collective behaviors through decentralized low-level ...
Intelligent Food Recommendation Framework Based on Social Media Behavioral Data
This research introduces an Intelligent Food Recommendation Framework leveraging social media Behavioral Data, explicitly focusing on Instagram. It posits that users' engagements with food-related content on Instagram offer insights into their food ...
Breast Cancer Segmentation and Detection Using U-net With Ultrasound Dataset
Breast cancer is a significant health issue for women, being one of the most common types of cancer and the second leading cause of death among them. Detecting breast cancer early is crucial for effective treatment. While ultrasound is often used for ...
Binding Text, Images, Graphs, and Audio for Music Representation Learning
Abstract In the field of Information Retrieval and Natural Language Processing, text embeddings play a significant role in tasks such as classification, clustering, and topic modeling. However, extending these embeddings to abstract concepts such as ...
Assessing the Effect of Model Poisoning Attacks on Federated Learning in Android Malware Detection
Android devices are central to our daily lives, which leads to an increase in mobile security threats. Attackers try to exploit vulnerabilities and steal personal information from the installed applications on these devices. Because of their widespread ...
Deep Learning-Based Feature Extraction from Children's Facial Images for Autism Spectrum Disorder Detection
Autism spectrum disorder (ASD) is a complex neurological developmental disease that appears in a variety of ways[8]. Most autistic children are not diagnosed until they are at least three years old [6] [13]. Abnormal facial traits caused by development ...
The Role of Artificial Intelligence in Idea Management Systems and Innovation Processes: An Integrative Review
The role of artificial intelligence (AI) in idea management systems (IMS) and innovation processes has recently been a topic of significant research interest. AI has been acknowledged for its potential to enhance innovation activities by providing ...
An Investigation into the Exponential T-X Family Distributions to Simulation study
In this article, we introduce the T-X exponential (ETX) group of distributions. An updated expansion of the Frechet model is presented using the proposed methodology. The suggested technique for modeling heavy-tailed data is highly flexible. Several ...
Geometric Modelling of Fractal Structured Objects based on Integration of R-Function And L-System Methods
- Shahzoda Anarova,
- Shakhlo Sadullaeva Azimbayevna,
- Golib Berdiev,
- Adhamjon Toxtasinov Ilhomjon Ogli,
- Maftuna Ismoilova Ilxom Kizi
The article offers suggestions about mathematical modeling of architectural objects based on the functional image using the constructive operations of the theory of R-functions. Given in 2D format 3D surface from the data equations work exit according to ...
Numerical Modelling of The System of Doubly Nonlinear Diffusion Equations with Convective Transfer and Damping
- Shakhlo Azimbaevna Sadullaeva,
- Shahzoda Anarova,
- Abdugaffor Khaydarov,
- Zarnigor Fayzullayeva,
- Dilorom Nazirova,
- Nazhiba Mirkhodzhaeva
Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are nonlinear, degenerate, and have ...
Strategic Approaches to Eco-Efficient Computing in Institutional Environments
This study underscores the critical importance of computer energy efficiency within institutions, using advanced tools to passively gather information for a rigorous analysis of computing devices' energy consumption. By examining a diverse array of over ...
Index Terms
- Proceedings of the Cognitive Models and Artificial Intelligence Conference