Optimal Strategy For Handling Unbalanced Medical Datasets: Performance Evaluation Of K-Nn Algorithm Using Sampling Techniques,
2024
Universitas Muslim Indonesia, Indonesia
Optimal Strategy For Handling Unbalanced Medical Datasets: Performance Evaluation Of K-Nn Algorithm Using Sampling Techniques, Yulita Salim, Aulia Putri Utami, Abdul Rachman Manga, Huzain Azis, Fadhila Tangguh Admojo
Knowledge Engineering and Data Science
This study addresses the critical role of medical image classification in enhancing healthcare effectiveness and tackling the challenges of imbalanced medical datasets. It focuses on optimizing classification performance by integrating Canny edge detection for segmentation and Hu-moment feature extraction and applying oversampling and undersampling techniques. Five diverse medical datasets were utilized, covering Alzheimer’s and Parkinson’s diseases, COVID-19, brain tumours, and lung cancer. The K-Nearest Neighbors (K-NN) algorithm was implemented to enhance classification accuracy, aiming to develop a more robust framework for medical image analysis. The evaluation, conducted using cross-validation, demonstrated notable improvements in key metrics. Specifically, oversampling significantly enhanced lung …
A Hierarchical Density-Based Spatial Clustering Of Applications With Noise (Hdbscan) Approach For Identifying Potential Villages In Buleleng Regency,
2024
Universitas Islam Indonesia, Indnonesia
A Hierarchical Density-Based Spatial Clustering Of Applications With Noise (Hdbscan) Approach For Identifying Potential Villages In Buleleng Regency, Dina Nur Amalina, Achmad Fauzan
Knowledge Engineering and Data Science
Buleleng Regency, located in Bali Province, possesses diverse village potential, including agricultural production and tourist attractions. However, this potential has not been fully optimized. Therefore, it is important to enhance village potential by clustering villages based on their specific characteristics to identify and prioritize those requiring special attention. This approach aims to promote equitable village development and reduce poverty levels. This study clusters villages in Buleleng Regency based on their potential using the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) method. The data utilized in this study comprises village potential data obtained from the Buleleng Regency Statistics Office …
Manifold Learning And Undersampling Approaches For Imbalanced Class Sentiment Classification,
2024
IPB University, Indonesia
Manifold Learning And Undersampling Approaches For Imbalanced Class Sentiment Classification, L.M. Risman Dwi Jumansyah, Agus Mohamad Soleh, Utami Dyah Syafitri
Knowledge Engineering and Data Science
Movie reviews are crucial in determining a film's success by influencing audience decisions. Automating sentiment classification is essential for efficient public opinion analysis. However, it faces challenges such as high-dimensional data and imbalanced class distributions. This study addresses these issues by applying manifold learning techniques, Principal Component Analysis (PCA) and Laplacian Eigenmaps (LE) to reduce data complexity and undersampling strategies (Random Undersampling (RUS) and EasyEnsemble) to balance data and improve predictions for both sentiment classes. On reviews of The Raid 2: Berandal, EasyEnsemble achieved the highest average G-Mean of 0.694 using Term Frequency-Inverse Document Frequency (TF IDF) features with a …
Constructing Qur’An Recitation Classification Using Alexnet Algorithm,
2024
Universitas Negeri Malang,Indonesia
Constructing Qur’An Recitation Classification Using Alexnet Algorithm, Harits Ar Rosyid, Dzulkifli Abdullah, Mohammed S. Alqahtani
Knowledge Engineering and Data Science
The growing demands for accurate and efficient methods in the Qur'an recitation classification highlight the limitations of existing models, particularly in assisting the memorization process. This study aims to address these challenges by implementing the AlexNet Convolutional Neural Network architecture, widely recognized for its effectiveness in image classification, to classify the Qur'an recitations using the Mel Frequency Cepstral Coefficient (MFCC) as the feature extraction method. The research involves several stages, including data collection, preprocessing (audio segmentation by verse), data augmentation, feature extraction, and classification using the AlexNet architecture, followed by performance evaluation. Key results demonstrate that the combination of MFCC …
Deep Learning Approach For Dental Anomalies X-Ray Imaging Using Yolov8,
2024
University Malaysia, Malaysia
Deep Learning Approach For Dental Anomalies X-Ray Imaging Using Yolov8, Amelia Ritahani Ismail, Md Salim Sadman Taseen
Knowledge Engineering and Data Science
Dental X-ray imaging is a critical diagnostic tool for identifying various dental anomalies. However, manual interpretation is time-consuming, prone to human error, and requires specialized expertise. Deep learning models, particularly object detection frameworks like YOLO, have demonstrated promising results in automating medical image analysis. This study aims to develop and evaluate a YOLOv8-based deep learning model for automated detection and classification of 14 dental anomaly categories, including Caries, Crowns, Fillings, Implants, and Periapical lesions. The proposed approach addresses limitations in previous YOLO versions by leveraging anchor-free detection and enhanced feature extraction for improved accuracy. The model was trained on a …
Classification Of Anxiety Levels Entering The World Of Work In Final Year Students Using The Neighbor Weighted K-Nearest Neighbor Method,
2024
Universitas Pembangunan Nasional Veteran Yogyakarta, Indonesia
Classification Of Anxiety Levels Entering The World Of Work In Final Year Students Using The Neighbor Weighted K-Nearest Neighbor Method, Awang Hendrianto Pratomo, Muhammad Fahmi Adam, Dessyanto Boedi Prasetyo
Knowledge Engineering and Data Science
This study evaluates the accuracy of the Neighbor Weighted K-Nearest Neighbor (NWKNN) method in classifying the anxiety levels of final-year students as they prepare to enter the workforce, particularly in cases of unbalanced data distribution. The system was developed using the prototype method, and NWKNN was applied to classify anxiety levels into low, medium, and high categories. Testing using the Confusion Matrix demonstrated strong performance, achieving an accuracy of 94% based on a dataset of 1009 students, with a 90:10 ratio of training to test data. The results indicate that NWKNN effectively provides classification input values, making it a reliable …
Comparative Analysis Of Bpnn And Lvq For Sundanese Character Recognition,
2024
Universitas Mulawarman, Indonesia
Comparative Analysis Of Bpnn And Lvq For Sundanese Character Recognition, Haviluddin Haviluddin, Herman Santoso Pakpahan, Dinda Izmya Nurpadillah, Hario Jati Setyadi, Medi Taruk, Rayner Alfred
Knowledge Engineering and Data Science
The Sundanese script (Aksara Sunda), an essential part of Sundanese cultural heritage, has been used since the 14th century AD. However, recognizing handwritten Sundanese characters remains challenging due to variations in individual writing styles. This study compares the performance of Backpropagation Neural Network (BPNN) and Learning Vector Quantization (LVQ) for recognizing handwritten Sundanese vowel (Swara) characters. A dataset was collected from 15 individuals, each writing seven Sundanese vowel characters, which were then used for training and testing the recognition models. Experimental results show that BPNN outperforms LVQ, achieving a higher classification accuracy (95.23%), lower Mean Squared Error (MSE), and faster …
Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications.,
2024
University of Louisville
Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications., Bhaskara Venkata Raju Garuda
Electronic Theses and Dissertations
The convergence of robotics and 5G wireless communication technologies has opened new avenues for real-time, dynamic robotic applications. This dissertation introduces a novel framework that integrates the Robot Operating System (ROS), Software-Defined Radios (SDRs), and 5G wireless networks to achieve seamless coemulation of robotic systems. The research emphasizes the unique features of 5G, such as ultra-low latency and high throughput, which enable critical applications like remote surgery, industrial automation, and autonomous vehicles. The methodology combines ROS for robotic control, SDRs for programmable communication channels, and 5G testbeds for high-speed, reliable data transmission. The experimental evaluation focuses on both position-based and …
Data Security In The Apple Ecosystem: An Evaluation,
2024
Old Dominion University
Data Security In The Apple Ecosystem: An Evaluation, Kayrene Woods
Cybersecurity Undergraduate Research Showcase
This study provides a comprehensive evaluation of data security within the Apple ecosystem, focusing on the company’s privacy policies, user perceptions, and the effectiveness of its App Store review processes. Employing an interdisciplinary methodology, the research examines Apple’s commitment to data protection, emphasizing transparency and user trust. A survey of user experiences revealed varying levels of engagement and understanding of Apple’s privacy practices, with only 32.8% of respondents having read the Privacy Policy and mixed opinions on its clarity. Additionally, concerns persist about third-party app security, with 39.7% of users expressing apprehension and skepticism about Apple’s App Store review process. …
Motivating Sustainability Through The State Of Biologically Inspired Design,
2024
Embry-Riddle Aeronautical University
Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson
Sustainability Conference
There are multiple arguements for sustainability, but one that resonates with environmentalists and the public alike is the need for preservation to all us to discovery natural solutions to our problems. Common examples often given include medical discoveries, unique mechanisms, and new materials. This presentation focuses on two ideas to motivate sustainability. First, what is the current state of biologically inspired design? Is there more to learn from nature? To answer these questions, recent research is presented which examined 660 Biologically Inspired Design samples from three data sources: Google Scholar, Google News, and the Asknature.org “Innovations” database. The data were …
It's Not As Bad As You Think: Detecting Ai-Generated Voices,
2024
University of Nevada, Las Vegas
It's Not As Bad As You Think: Detecting Ai-Generated Voices, Yong Qin Xu
Undergraduate Research Symposium Lightning Talks
Advances in machine learning have opened up the world to a brand new frontier of fraudulent phone calls which the average person may not be in any way prepared for. From imitations of a loved one's voice to lifelike mimicry of human callers, telephone scams may become harder than ever to anticipate or prevent now that criminals have the help of AI on their side. This is why in my research paper, I aim to analyze and compare two existing methods of detecting the authenticity of human voice recordings in order to demonstrate and explain currently available technology that's capable …
Modeling W/V-Band Satellite Communications In The Presence Of Noise Jamming,
2024
University of New Mexico
Modeling W/V-Band Satellite Communications In The Presence Of Noise Jamming, Ryan Michael Eckman
Electrical and Computer Engineering ETDs
Understanding the performance of wideband modulated signals under noise jamming conditions is important for advancing W/V-band military satellite communications. This research developed and validated models to predict performance degradation of a communication channel in the presence of wideband noise jamming. Channel models were developed that included both modulated communication signals and jammer signals. Integrated models included environmental link factors and practical implementation factors. Integrated models were verified and validated using outdoor radio frequency environments utilizing two W/V-band transceivers, a portable W-band jammer, and software defined radios. Experimental results demonstrated excellent agreement with integrated model predictions. Channel degradation due to the …
Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin,
2024
Technological University Dublin
Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr
Articles
Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …
Remote Operated Amateur Radio Using Raspberry Pi And Limesdr,
2024
California Polytechnic State University, San Luis Obispo
Remote Operated Amateur Radio Using Raspberry Pi And Limesdr, Esteban I. Perez
College of Engineering Summer Undergraduate Research Program
This project presents the design and implementation of a portable, remotely programmable amateur radio system operating on the 2-meter and 70-cm bands. The system utilizes Raspberry Pi 5 and LimeSDR hardware to facilitate communication between aerial and ground units, allowing for efficient transmission and reception of synchronization and calibration waveforms. A custom communication protocol incorporating BPSK modulation and a two-tone signaling mechanism enables time-of-flight measurements for calculating distances between nodes. This low-cost solution has potential applications in civilian sectors, such as search and rescue operations, where accurate direction finding and target localization are critical. Full-duplex operation enhances the system's capability …
Measurement Automation & Measurement System Research Endowment,
2024
California Polytechnic State University, San Luis Obispo
Measurement Automation & Measurement System Research Endowment, Brian Bivinetto, Beneda Loya, Shiron Bendrihem
College of Engineering Summer Undergraduate Research Program
Road travel safety is always the most important issue in transportation systems. In general, several factors cause road accidents, such as human error, vehicle mechanical failure, roadway limitations (e.g. pavement, lane geometry, etc.), and inclement weather conditions. The major focus of today’s transportation developments is related to making highway transportation safer, smarter, and greener to enhance livability. Many accidents are caused when drivers lack a better understanding of the surrounding traffic conditions because the driver not only needs to control his/her vehicle but also needs to be aware of the movements of the vehicles around him/her. A driver cannot be …
Sal-E: Responsive Space Pathfinder Mission,
2024
California Polytechnic State University, San Luis Obispo
Sal-E: Responsive Space Pathfinder Mission, Liam Duckworth, Berfredd Quezon
College of Engineering Summer Undergraduate Research Program
The main objective of the SAL-E mission is to grow the Cal Poly CubeSat Lab’s (PolySat) capabilities in rapid spacecraft design, as well as to provide the current generation of students with the opportunity to design, test, integrate, and communicate with a satellite. This summer we will be focusing on a few aspects of the spacecraft design and preparing our test facilities for Fall. Specifically, we will be ordering electronics boards that were designed in Spring, testing the boards as they arrive, developing software to interface with the payloads, begin integrated testing, updating the control system in our thermal vacuum …
Exploring Social Networks: An Analysis Of Intra-Organizational Networks,
2024
Sacred Heart University
Exploring Social Networks: An Analysis Of Intra-Organizational Networks, Ximeng Chen, Yiding Cao, Jiachen Liu, Danushka Bandara, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
This research investigates intra-organizational social networks by employing network science methods, aiming to provide actionable insights for both managers and employees. Using datasets from the Colorado Index of Complex Networks (ICON), this study examines four intra-organizational networks from a consulting firm and a research team, focusing on advice requests and skill awareness. The analysis includes network topology, degree distribution, community detection, correlation between communities and node attributes, maximal clique detection, and multilayer network analysis. The findings reveal that intra-organizational networks are intricate and significantly impact organizational efficiency and individual career development. Key insights include the importance of mid-level employees in …
Evaluation Of Business-Driven Reference Architecture For Big Data Analytics Implementation By Public Sector Organizations In Resource-Constrained Setting: A Case Study Of Uganda,
2024
Department of Information Systems and Technology, The University of Dodoma, Tanzania
Evaluation Of Business-Driven Reference Architecture For Big Data Analytics Implementation By Public Sector Organizations In Resource-Constrained Setting: A Case Study Of Uganda, Matendo Didas
Tanzania Journal of Engineering and Technology (TJET)
Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) …
Assessment Of The Factors Affecting The National Ict Broadband Backbone (Nictbb) Systems Restoration Time,
2024
Mechanical and Industrial Engineering Department, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania
Assessment Of The Factors Affecting The National Ict Broadband Backbone (Nictbb) Systems Restoration Time, Victoria Mahabi
Tanzania Journal of Engineering and Technology (TJET)
This study investigates the factors affecting the prolonged system restoration time when national ICT broadband backbone (NICTBB) services are affected by breakdown incidents. NICTBB is the government-owned backbone infrastructure constructed nationally by the Republic of Tanzania to increase the usage of ICT for equitable and sustainable socio-economic development and accelerate poverty reduction. This study utilised a mixture of exploratory and descriptive study approaches. The sample size determination was executed using purposing and simple random sampling, thus involving 289 respondents. The data reliability test was undertaken. It was followed by factor analysis, analysis of variances (ANOVA), linear regression analysis, and confirmed …
Data Communication Over Power-Lines: A Review On Technical, And Applications Challenges,
2024
University of Dar es salaam
Data Communication Over Power-Lines: A Review On Technical, And Applications Challenges, Abdi Abdalla
Tanzania Journal of Engineering and Technology (TJET)
This paper presents a review study on the data communication over power-lines, commonly referred to as power-line carrier, power-line communication (PLC), mains communications, or power-line digital subscriber line (PDSL). This study examines the technical and application advantages and challenges associated with adopting PLC as a preferred alternative technology for wideband or broadband data communication. The broader coverage area of the PLC network gives it a distinct advantage over other communication network technologies. Additionally, implementing a communication system using the existing power-line network is more cost-effective and less time-consuming compared to constructing a new network from scratch. However, the primary challenge …
