Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- MMU Press (252)
- San Jose State University (58)
- University of Dayton (15)
- Chapman University (11)
- City University of New York (CUNY) (10)
-
- University of Denver (10)
- California Polytechnic State University, San Luis Obispo (8)
- Southern Methodist University (8)
- Western Kentucky University (8)
- University of Arkansas, Fayetteville (6)
- University of South Alabama (6)
- University of Texas at Arlington (6)
- West Virginia University (6)
- LSU New Orleans (5)
- Clemson University (4)
- East Tennessee State University (4)
- Missouri State University (4)
- Technological University Dublin (4)
- University of Malaya (4)
- University of Nebraska - Lincoln (4)
- Claremont Colleges (3)
- College of Saint Benedict and Saint John's University (3)
- Dakota State University (3)
- Dartmouth College (3)
- Fort Hays State University (3)
- Montclair State University (3)
- Old Dominion University (3)
- University at Albany, State University of New York (3)
- University of Nevada, Las Vegas (3)
- Virginia Commonwealth University (3)
- Keyword
-
- Machine Learning (79)
- Deep Learning (40)
- Artificial Intelligence (34)
- Machine learning (33)
- Deep learning (21)
-
- Classification (16)
- Natural Language Processing (16)
- Computer Vision (13)
- Sentiment Analysis (11)
- AI (9)
- Artificial intelligence (9)
- Convolutional Neural Network (9)
- Natural language processing (9)
- Random Forest (9)
- Cybersecurity (7)
- Data Mining (7)
- Editorial Preview (7)
- Computer Science (6)
- Computer vision (6)
- Cyber Security (6)
- E-Commerce (6)
- Generative AI (6)
- Internet of Things (6)
- LSTM (6)
- Long Short-Term Memory (6)
- Neural networks (6)
- Prediction (6)
- Recommender Systems (6)
- Support Vector Machine (6)
- Automation (5)
- Publication Year
- Publication
-
- Journal of Informatics and Web Engineering (252)
- Master's Projects (57)
- MAICS: The Modern Artificial Intelligence and Cognitive Science Conference (12)
- Electronic Theses and Dissertations (9)
- Mathematics, Physics, and Computer Science Faculty Articles and Research (7)
-
- Moving AI Lab: 2D Maps and Benchmark Problems (7)
- Dissertations, Theses, and Capstone Projects (6)
- Graduate Theses, Dissertations, and Problem Reports (ETD) (6)
- Master's Theses (6)
- SMU Data Science Review (6)
- Theses and Dissertations (6)
- Computer Science Faculty Publications (5)
- LSU New Orleans Theses and Dissertations (5)
- Conference papers (4)
- Graduate Theses/Dissertations (4)
- Computer Science and Computer Engineering Undergraduate Honors Theses (3)
- Computer Science and Engineering Dissertations - Archive (3)
- Department of Computer Science Faculty Scholarship and Creative Works (3)
- Electronic Theses & Dissertations (2024 - present) (3)
- Graduate Theses and Dissertations (2019 - present) (3)
- All College Thesis Program, 2016-2019 (2)
- All Dissertations (2)
- All Theses (2)
- CMC Senior Theses (2)
- Computer Science Theses (2)
- Computer Science Working Papers (2)
- Computer Science and Engineering Theses and Dissertations (2)
- Dartmouth College Ph.D Dissertations (2)
- Dissertations (2)
- Doctoral Dissertations and Master's Theses (2)
- Publication Type
- File Type
Articles 211 - 240 of 530
Full-Text Articles in Other Computer Sciences
Towards Analysable Chaos-Based Cryptosystems: Constructing Difference Distribution Tables For Chaotic Maps, Je Sen Teh, Abubakar Abba
Towards Analysable Chaos-Based Cryptosystems: Constructing Difference Distribution Tables For Chaotic Maps, Je Sen Teh, Abubakar Abba
Journal of Informatics and Web Engineering
Chaos-based cryptography has yet to achieve practical, real-world applications despite extensive research. A major challenge is the difficulty in analysing the security of these cryptosystems, which often appear ad hoc in design. Unlike conventional cryptography, evaluating the security margins of chaos-based encryption against attacks such as differential cryptanalysis is complex. This paper introduces a straightforward approach of using chaotic maps in cryptographic algorithms in a way that facilitates cryptanalysis. We demonstrate how a chaos-based substitution function can be constructed using fixed-point representation, enabling the application of conventional cryptanalysis tools such as the difference distribution table. As a proof-of-concept, we apply …
Mobitest – A Software For Mobile-Based Testing, Ayesha Anees Zaveri, Ramsha Mashood, Nabiha Faisal, Misbah Parveen, Naveera Sami, Mobeen Nazar, Saba Imtiaz
Mobitest – A Software For Mobile-Based Testing, Ayesha Anees Zaveri, Ramsha Mashood, Nabiha Faisal, Misbah Parveen, Naveera Sami, Mobeen Nazar, Saba Imtiaz
Journal of Informatics and Web Engineering
MobiTest is an application that serves as a valuable tool in the fast-growing field of software testing. Efficiency is crucial in this industry, where testers, quality assurance teams, and others must meticulously test each application, avoiding the need to repeat the entire cycle to identify bugs. This application is a breeze thanks to its intuitive features and educational content. Thanks to continuous integration, testers can easily keep up with the fast-paced development cycle and start automating tasks as soon as the user interface development is completed. This saves valuable time and ensures a smoother and more efficient process. During the …
Enhancing Cybersecurity Awareness Through Gamification: Design An Interactive Cybersecurity Learning Platform For Multimedia University Students, Adlil Khaliq Abdul Razack, Mohamad Firdaus Mat Saad
Enhancing Cybersecurity Awareness Through Gamification: Design An Interactive Cybersecurity Learning Platform For Multimedia University Students, Adlil Khaliq Abdul Razack, Mohamad Firdaus Mat Saad
Journal of Informatics and Web Engineering
Cybersecurity has emerged as a critical imperative in contemporary digital landscapes, necessitating heightened awareness and proficiency across all demographic segments. Accordingly, this research has been meticulously crafted to delve into the complexities of cybersecurity awareness, with a specific focus on university students. The study embarks on an exhaustive analysis encompassing the evaluation of cybersecurity awareness levels within the targeted groups, the identification of prevailing issues and practices, and an exploration of novel methodologies, notably gamification, to fortify cybersecurity knowledge and skills among diverse user cohorts. Central to this investigation is the efficacy of gamified learning environments tailored expressly for augmenting …
Comparative Analysis Of Linear And Nonlinear Semg Methods For Detecting Muscle Fatigue During Dynamic Biceps Curls, Tang Ming, Ling Weay Ang, Sellappan Palaniappan
Comparative Analysis Of Linear And Nonlinear Semg Methods For Detecting Muscle Fatigue During Dynamic Biceps Curls, Tang Ming, Ling Weay Ang, Sellappan Palaniappan
Journal of Informatics and Web Engineering
Muscle fatigue, a key concern in sports science, rehabilitation, and occupational health, influences performance, injury risk, and provides insights into muscle functionality and endurance. Surface electromyography (sEMG) has emerged as a vital tool for non-invasively tracking muscle electrical activity and gauging health. As its application for muscle fatigue assessment grows, identifying the most accurate analytical methods is essential. Current sEMG analyses employ both linear and nonlinear metrics to measure fatigue onset and progression, yet research is ongoing to determine which method is most effective in the context of dynamic contractions. The study was aimed to evaluate the efficacy of established …
Pi Class – A Revolutionary Step Forward In Hybrid Class Management System, Qasim Hassan, Nabiha Faisal, Ayesha Anees Zaveri
Pi Class – A Revolutionary Step Forward In Hybrid Class Management System, Qasim Hassan, Nabiha Faisal, Ayesha Anees Zaveri
Journal of Informatics and Web Engineering
The COVID-19 pandemic has caused widespread disruptions globally, resulting in a state of health emergency with numerous deaths reported and an overall implementation of quarantine and isolation. Strict lockdowns have been implemented to curb the spread of the virus, requiring social distancing and limiting physical interactions. These measures had far-reaching impacts on all aspects of life, including education. Education was one of the most affected sectors, with difficulty delivering quality education in schools, colleges, and universities. It was hard to provide quality education, a basic need of humanity. In this research paper, we propose an adequate solution to overcome the …
Comparative Evaluation Of Machine Learning Models For Mobile Phone Price Prediction: Assessing Accuracy, Robustness, And Generalization Performance, Saima Anwar Lashari, Muhammad Muntazir Khan, Abdullah Khan, Sana Salahuddin, Muhammad Noman Ata
Comparative Evaluation Of Machine Learning Models For Mobile Phone Price Prediction: Assessing Accuracy, Robustness, And Generalization Performance, Saima Anwar Lashari, Muhammad Muntazir Khan, Abdullah Khan, Sana Salahuddin, Muhammad Noman Ata
Journal of Informatics and Web Engineering
These days, mobile phones are the most commonly purchased goods. Thousands of new models with improved features, designs, and specifications are released yearly. An autonomous mobile price prediction system is required to assist customers in determining whether or not they can afford these devices. Many machine learning models exhibit varying performance degrees based on their architecture and learning properties. Ten widely used classifiers were assessed in this study: Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Decision Tree (DT), Naïve Bayes (NB), Linear Discriminant Analysis (LDA), AdaBoost, and Light Gradient Boosting …
Investigation On Understanding The Numeracy Capacity Of Intellectual Disabled Students Using Enabling Technology Tools: Web Application, Ar And Ui/Ux, Vishvjit Thakar, Romany Thakar, Pratik Vyas
Investigation On Understanding The Numeracy Capacity Of Intellectual Disabled Students Using Enabling Technology Tools: Web Application, Ar And Ui/Ux, Vishvjit Thakar, Romany Thakar, Pratik Vyas
Journal of Informatics and Web Engineering
The population of individuals with intellectual disabilities (ID) is increasing, necessitating assistance with a wide range of daily activities. Acquiring and assessing numeracy and communication skills are critical for this demographic, requiring tools and techniques tailored to their specific needs. Effective educational tools must employ multi-modal and multi-sensory approaches to cater to diverse learning styles and incorporate assistive technological solutions. Despite the availability of numerous tools, there is a need to enhance their utility and effectiveness. This study aims to identify and refine the requirements for an innovative educational tool that employs Two-dimensional (2D) and Augmented Reality (AR) technologies. To …
Ddos Attack Detection With Machine Learning, Wei-Wu Tay, Siew-Chin Chong, Lee-Ying Chong
Ddos Attack Detection With Machine Learning, Wei-Wu Tay, Siew-Chin Chong, Lee-Ying Chong
Journal of Informatics and Web Engineering
Nowadays, Distributed Denial of Service (DDoS) attacks are a major issue in internet security. These attacks target servers or network infrastructure. Similar to an unanticipated traffic jam on highway (lagging/crash) that prevent normal traffic reach to destination. DDoS may prevent users to access any system services. Researchers and scientists have developed numerous methods and algorithms to improve the performance of DDoS detection. In this paper, a DDoS detection method utilizing machine learning is proposed. There are three type of supervised machine learning classification methods which are K-Nearest Neighbor, Multilayer Perceptron and Random Forest, are applied in the proposed work to …
Editorial: Artificial Intelligence And Cybersecurity In Pervasive Computing, Ji-Jian Chin
Editorial: Artificial Intelligence And Cybersecurity In Pervasive Computing, Ji-Jian Chin
Journal of Informatics and Web Engineering
Pervasive computing, or ubiquitous computing, is rapidly increasing in capacity and capabilities. With the Internet of Things (IoT) becoming an integral part of daily life and the growing availability of edge computing resources, automation guided by data is advancing applications in healthcare, manufacturing, automotive, and other areas. It's natural that pervasive computing will intersect with artificial intelligence (AI) and cybersecurity. AI can improve detection, prediction, and anticipative responses to human needs, while cybersecurity addresses topics like misuse prevention, ethics, policies, and governance. This issue features seven articles on these intersections, including four AI articles exploring natural language processing and computer …
Sibling Discrimination Using Linear Fusion On Deep Learning Face Recognition Models, Rita Goel, Maida Alamgir, Haroon Wahab, Maria Alamgir, Irfan Mehmood, Hassan Ugail, Amit Sinha
Sibling Discrimination Using Linear Fusion On Deep Learning Face Recognition Models, Rita Goel, Maida Alamgir, Haroon Wahab, Maria Alamgir, Irfan Mehmood, Hassan Ugail, Amit Sinha
Journal of Informatics and Web Engineering
Facial recognition technology has revolutionised human identification, providing a non-invasive alternative to traditional biometric methods like signatures and voice recognition. The integration of deep learning has significantly enhanced the accuracy and adaptability of these systems, now widely used in criminal identification, access control, and security. Initial research focused on recognising full-frontal facial features, but recent advancements have tackled the challenge of identifying partially visible faces, a scenario that often reduces recognition accuracy. This study aims to identify siblings based on facial features, particularly in cases where only partial features like eyes, nose, or mouth are visible. Utilising advanced deep learning …
Hybrideval: An Improved Novel Hybrid Metric For Evaluation Of Text Summarization, Raheem Sarwar, Bilal Ahmad, Pin Shen Teh, Suppawong Tuarob, Tipajin Thaipisutikul, Farooq Zaman, Naif R. Aljohani, Jia Zhu, Saeed-Ul Hassan, Raheel Nawaz, Ali R Ansari, Muhammad A B Fayyaz
Hybrideval: An Improved Novel Hybrid Metric For Evaluation Of Text Summarization, Raheem Sarwar, Bilal Ahmad, Pin Shen Teh, Suppawong Tuarob, Tipajin Thaipisutikul, Farooq Zaman, Naif R. Aljohani, Jia Zhu, Saeed-Ul Hassan, Raheel Nawaz, Ali R Ansari, Muhammad A B Fayyaz
Journal of Informatics and Web Engineering
The present work re-evaluates the evaluation method for text summarization tasks. Two state-of-the-art assessment measures e.g., Recall-Oriented Understudy for Gisting Evaluation (ROUGE) and Bilingual Evaluation Understudy (BLEU) are discussed along with their limitations before presenting a novel evaluation metric. The evaluation scores are significantly different because of the length and vocabulary of the sentences, this suggests that the primary restriction is its inability to preserve the semantics and meaning of the sentences and consistent weight distribution over the whole sentence. To address this, the present work organizes the phrases into six different groups and to evaluate “text summarization” problems, a …
Conditional Deployable Biometrics: Matching Periocular And Face In Various Settings, Jihyeon Kim, Tiong-Sik Ng, Andrew Beng Jin Teoh
Conditional Deployable Biometrics: Matching Periocular And Face In Various Settings, Jihyeon Kim, Tiong-Sik Ng, Andrew Beng Jin Teoh
Journal of Informatics and Web Engineering
In this paper, we introduce the concept of Conditional Deployable Biometrics (CDB), designed to deliver consistent performance across various biometric matching scenarios, including intra-modal, multimodal, and cross-modal applications. The CDB framework provides a versatile and deployable biometric authentication system that ensures reliable matching regardless of the biometric modality being used. To realize this framework, we have developed CDB-Net, a specialized deep neural network tailored for handling both periocular and face biometric modalities. CDB-Net is engineered to handle the unique challenges associated with these different modalities while maintaining high accuracy and robustness. Our extensive experimentation with CDB-Net across five diverse and …
In Search Of Suitable Methods For Cost-Benefit Analysis Of Cyber Risk Mitigation In Offshore Wind: A Survey, Yvonne Hwei-Syn Kam, Kevin Jones, Robert Rawlinson-Smith, Kimberly Tam
In Search Of Suitable Methods For Cost-Benefit Analysis Of Cyber Risk Mitigation In Offshore Wind: A Survey, Yvonne Hwei-Syn Kam, Kevin Jones, Robert Rawlinson-Smith, Kimberly Tam
Journal of Informatics and Web Engineering
In recent years, notable incidents have highlighted the vulnerability of wind energy infrastructure, making cybersecurity crucial for the offshore wind industry. However, justifying the costs of cybersecurity measures is essential. A cost benefit analysis (CBA) is commonly utilised to support decision-making for risk mitigation. With a cost benefit analysis, risk mitigation strategies that strike an optimal balance between the costs of mitigation measures and the resulting risk reduction can be identified. This survey of literature was carried out to identify the existing proposed solutions for cost benefit analysis on cyber risk mitigation measures for offshore wind cyber physical systems. After …
Enhancing Place-Based Interaction With Emotion Ai And Augmented Reality, Jake Maier, Ivan Martinez
Enhancing Place-Based Interaction With Emotion Ai And Augmented Reality, Jake Maier, Ivan Martinez
College of Engineering Summer Undergraduate Research Program
This project explores the integration of augmented reality (AR) and Emotion AI technologies to enhance user experiences in physical environments. By seamlessly merging virtual elements with real-world contexts, we aim to deepen individuals’ interactions and perceptions of their surroundings. Leveraging AR technology enables users to access contextual information, engage with interactive content, and navigate spaces with heightened immersion and understanding. Additionally, Emotion AI enhances these experiences by detecting and responding to users’ emotional states, fostering personalized and emotionally resonant interactions. We aim to integrate digital content within physical environments using mixed-reality headsets equipped with eye-tracking capabilities and consumer-grade wireless EEG …
A Guideline For Open-Source Tools To Make Medical Imaging Data Ready For Artificial Intelligence Applications: A Society Of Imaging Informatics In Medicine (Siim) Survey, Sanaz Vahdati, Bardia Khosravi, Elham Mahmoudi, Kuan Zhang, Pouria Rouzrokh, Shahriar Faghani, Mana Moassefi, Aylin Tahmasebi, Katherine Andriole, Peter Chang, Keyvan Farahani, Mona Flores, Les Folio, Sina Houshmand, Maryellen Giger, Judy Gichoya, Bradley Erickson
A Guideline For Open-Source Tools To Make Medical Imaging Data Ready For Artificial Intelligence Applications: A Society Of Imaging Informatics In Medicine (Siim) Survey, Sanaz Vahdati, Bardia Khosravi, Elham Mahmoudi, Kuan Zhang, Pouria Rouzrokh, Shahriar Faghani, Mana Moassefi, Aylin Tahmasebi, Katherine Andriole, Peter Chang, Keyvan Farahani, Mona Flores, Les Folio, Sina Houshmand, Maryellen Giger, Judy Gichoya, Bradley Erickson
Department of Radiology Faculty Papers
In recent years, the role of Artificial Intelligence (AI) in medical imaging has become increasingly prominent, with the majority of AI applications approved by the FDA being in imaging and radiology in 2023. The surge in AI model development to tackle clinical challenges underscores the necessity for preparing high-quality medical imaging data. Proper data preparation is crucial as it fosters the creation of standardized and reproducible AI models while minimizing biases. Data curation transforms raw data into a valuable, organized, and dependable resource and is a fundamental process to the success of machine learning and analytical projects. Considering the plethora …
Rethinking Retrieval Augmented Fine-Tuning In An Evolving Llm Landscape, Nicholas Sager, Timothy Cabaza, Matthew Cusack, Ryan Bass, Joaquin Dominguez
Rethinking Retrieval Augmented Fine-Tuning In An Evolving Llm Landscape, Nicholas Sager, Timothy Cabaza, Matthew Cusack, Ryan Bass, Joaquin Dominguez
SMU Data Science Review
This study explores the utilization of Retrieval Augmented Fine-Tuning (RAFT) to enhance the performance of Large Language Models (LLMs) in domain-specific Retrieval Augmented Generation (RAG) tasks. By integrating domain-specific information during the retrieval process, RAG aims to reduce hallucination and improve the accuracy of LLM outputs. We investigate the use of RAFT, an approach that enhances LLMs by incorporating domain-specific knowledge and effectively handling distractor documents. This paper validates previous work, which found that RAFT can considerably improve the performance of Llama2-7B in specific domains. We also expand upon previous work into new state-of-the-art open-source models and other datasets with …
Advancing Affective Computing: Emotion Recognition And Tracking Across Diverse Contexts (Varied Environments), Shao Liu
Dissertations, Theses, and Capstone Projects
Affective Computing (AC) is an interdisciplinary field that recognizes, interprets, and processes human emotions. Emotions are complex, involving consciousness, physical sensations, and behavioral expressions, and are significant in various domains like mental health, human-computer interaction, and social security. Real-world applications of AC include monitoring drivers’ emotional states to improve road safety and understanding the emotions expressed by artists in visual arts. Traditional methods relying on facial expressions often fall short due to the nuanced nature of emotions, which vary across individuals, cultures, and contexts. Accurate AC systems require sophisticated, multimodal models to handle these variations and external factors like noise …
Offensive Content Detection In Online Social Platforms, Ebuka Okpala
Offensive Content Detection In Online Social Platforms, Ebuka Okpala
All Dissertations
Online social platforms enable users to connect with large, diverse audiences and the ability for a message or content to flow from one user to another user, user to followers, followers to user, and followers to followers. Of course, the advantages of this are apparent, and the dangers are also clearly obvious. The user-generated content could be abusive, offensive, or hateful to other users, possibly leading to adverse health effects or offline harm. As more of society's public discourse and interaction move online and these platforms grow and increase their reach, it is inherently important to protect the safety of …
Bridging Design And Perception: Novel Tools And Technologies For Creating Effective Human-Robot Interactions, Benjamin Dossett
Bridging Design And Perception: Novel Tools And Technologies For Creating Effective Human-Robot Interactions, Benjamin Dossett
Electronic Theses and Dissertations
This thesis explores human perception of robots through the use of novel tools and technologies. First, the impact of Augmented Reality (AR) data presentation on human perception of robots is investigated. A study conducted with the AR human-robot teaming system found that robot performance significantly influenced participants’ perceptions, overshadowing the impact of matching or mismatching robot confidence feedback. Second, the DU Want to Build-A-Bot platform is presented, which enables participatory robot design and opens the door for novel research of how robot design affects human perception. The Build-A-Bot platform enables the collection of diverse robot designs, facilitating machine learning analysis …
Eye Diseases Prediction And Classification Using Deep Learning Techniques., Ahmed M. Fahmy
Eye Diseases Prediction And Classification Using Deep Learning Techniques., Ahmed M. Fahmy
Artificial Intelligence
In human anatomy, the eye is a major sense organ and loss of vision would have an enormous impact on quality of life. In addition, it may also be possible that the eye is showing signs of severe health problems. Eye diseases detection is mainly the problem here. Detecting eye diseases using different advanced AI- based techniques to analyze and predict the type of eye disease from retinal eye images and improve the performance and the accuracy of the proposed system. This proposed system can help ophthalmologists to save their time in manual examination. This paper aims to develop Deep …
Real Time 3d Internal Building Directory Map, Zi Yang Chia, Pey Yun Goh
Real Time 3d Internal Building Directory Map, Zi Yang Chia, Pey Yun Goh
Journal of Informatics and Web Engineering
Global Positioning System (GPS) is a famous technology around the world in identifying the real time precise location of any object with the assistance of satellites. The most common application of GPS is the use of outdoor maps. GPS offers efficient, scalable and cost-effective location services. However, this technology is not reliable when the position is in an indoor environment. The signal is very weak or totally lost due to signal attenuation and multipath effects. Among the indoor positioning technologies, WLAN is the most convenient and cost effective. In recent research, machine learning algorithms have become popular and utilized in …
Development And Validation Of Autotronic Training Module For Automobile Technology Students In Polytechnics In Southern Nigeria, Saue, Baritule Prince, Chukuigwe, Ogbondah Nndameka, Bassey, Imaobong Sunday
Development And Validation Of Autotronic Training Module For Automobile Technology Students In Polytechnics In Southern Nigeria, Saue, Baritule Prince, Chukuigwe, Ogbondah Nndameka, Bassey, Imaobong Sunday
Journal of Informatics and Web Engineering
A research was carried out to create and verify an autotronic training module for students studying vehicle technology at polytechnics located in Southern Nigeria. The design used for the project was Research and Development (R&D). An observation has been made that the curriculum of polytechnics in Nigeria lacks sufficient substance on autotronics technology. As a result, lecturers have challenges in fully imparting the abilities that are essential for the professional world. Undoubtedly, there is now a disparity between the training that craftsmen receive and the skills that are demanded by industries. The research was carried out in the southern region …
Ensemble-Smote: Mitigating Class Imbalance In Graduate On Time Detection, Theng-Jia Law, Choo-Yee Ting, Hu Ng, Hui-Ngo Goh, Albert Quek
Ensemble-Smote: Mitigating Class Imbalance In Graduate On Time Detection, Theng-Jia Law, Choo-Yee Ting, Hu Ng, Hui-Ngo Goh, Albert Quek
Journal of Informatics and Web Engineering
In education, detecting students graduating on time is difficult due to high data complexity. Researchers have employed various approaches in identifying on-time graduation with Machine Learning, but it remains a challenging task due to the class imbalance in the dataset. This study has aimed to (i) compare various class imbalance treatment methods with different sampling ratios, (ii) propose an ensemble class imbalance treatment method in mitigating the problem of class imbalance, and (iii) develop and evaluate predictive models in identifying the likelihood of students graduating on time during their studies in university. The dataset is collected from 4007 graduates of …
Facial Skin Analysis In Malaysians Using Yolov5: A Deep Learning Perspective, Ying Huey Gan, Shih Yin Ooi, Ying Han Pang, Yi Hong Tay, Quan Fong Yeo
Facial Skin Analysis In Malaysians Using Yolov5: A Deep Learning Perspective, Ying Huey Gan, Shih Yin Ooi, Ying Han Pang, Yi Hong Tay, Quan Fong Yeo
Journal of Informatics and Web Engineering
Nowadays, people are more concerned about their skin conditions and are more willing to spend money and time on facial care routines. The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in the market, each is invented and tested abroad. Those skin type readers in the beauty market are not applied well on Malaysian skin. Therefore, this paper proposes a facial skin analysis system tailored primarily for Malaysian skin. This paper integrated object detection and deep learning algorithms in developing skin-type readers. …
Assessing The Efficiency Of Deep Learning Methods For Automated Vehicle Registration Recognition For University Entrance, Muhammad Syaqil Irsyad, Zarina Che Embi, Khairil Imran Bin Ghauth
Assessing The Efficiency Of Deep Learning Methods For Automated Vehicle Registration Recognition For University Entrance, Muhammad Syaqil Irsyad, Zarina Che Embi, Khairil Imran Bin Ghauth
Journal of Informatics and Web Engineering
With the ever-increasing number of vehicles on the road, a faster reliable security system for university entry is needed. This paper presents an approach for Automatic Number Plate Recognition (ANPR) using deep learning and PP-OCRv3. The proposed approach utilizes a pre-trained object detection model to locate license plates, extracts a single frame of the license plate, performs license plate recognition, applies pre-processing techniques, and employs PP-OCRv3 for text extraction in real time. The system was tested with Malaysian vehicle plates, and its accuracy and speed of detection were evaluated. The results show the system's potential to be easily adapted to …
Secure Room-Sharing Decentralized App Development On Ethereum Block Chain Using Smart Contracts, Hasnain Raza, Reqad Ali, Jawaid Iqbal, Muhammad Awais
Secure Room-Sharing Decentralized App Development On Ethereum Block Chain Using Smart Contracts, Hasnain Raza, Reqad Ali, Jawaid Iqbal, Muhammad Awais
Journal of Informatics and Web Engineering
The purpose of this research is to analyze whether Blockchain technology can affect the share-economy. Apart from that, blockchain technology has been innovating the whole of the industries and so the academics are discovering the possibilities and starting to incorporate them in order to provide additional tech possibilities. The sharing economic system is the system which enables to share asset among the one person to the other person. It has seen the remarkable growth in the last few years, Uber, Careem, Airbnb, Zostel, Hostel World are some companies to mention which have fueled this growth. Yet, the majority of the …
Editorial Preview, Su-Cheng Haw
Editorial Preview, Su-Cheng Haw
Journal of Informatics and Web Engineering
This editorial highlights all 18 papers in the June issue that deal with the practical aspects of Machine Learning (ML), Artificial Intelligence (AI), Data Mining (DM), the Internet of Things (IoT), Computer Vision, e-learning, and other topics in Computer Science. This issue also includes suggestions for several worthwhile works that deserve further research. With effective from our third volume first issue, we will be publishing triannually in February, June and October.
Classroom Environment Analysis Via Internet Of Things, Kai-Yuan Tan, Kok-Why Ng, Kanesaraj Ramasamy
Classroom Environment Analysis Via Internet Of Things, Kai-Yuan Tan, Kok-Why Ng, Kanesaraj Ramasamy
Journal of Informatics and Web Engineering
In this era of rapid technological advancement, the potential of the digital age has opened up numerous possibilities for our society. However, despite these advancements, traditional classrooms still lack the necessary technology to create an optimal learning environment for students. Consequently, students may struggle to effectively acquire knowledge within classrooms. This paper aims to conduct a classroom environment analysis using Internet of Things technology to gather data and uncover valuable insights. The proposed solution involves an embedded system for controlling and monitoring the classroom environment, as well as exporting historical data for further research. By ensuring accurate data collection, this …
Temporal Climatic Shifts In Henan Province: A 16-Decades Perspective Through Regression, Sarima, And Nar Modeling, Lin Qing, Ang Ling Weay, Shao Yiyang, Sellappan Palaniappan
Temporal Climatic Shifts In Henan Province: A 16-Decades Perspective Through Regression, Sarima, And Nar Modeling, Lin Qing, Ang Ling Weay, Shao Yiyang, Sellappan Palaniappan
Journal of Informatics and Web Engineering
Global warming is having a significant impact on all aspects of human production and life. This study employs a cross-sectional analysis to investigate the temporal dynamics of average temperature changes in Henan Province, China, from 1851 to 2012. Utilizing the Berkeley Earth Surface Temperature Data and the Daily Meteorological Dataset of China National Surface Weather Station v3.0, we applied regression analysis, Seasonal Autoregressive Integrated Moving Average (SARIMA), and Nonlinear Autoregressive Network (NAR) models to predict temperature trends. Results indicate a significant warming trend over the 160-year period, with the models demonstrating strong predictive performance, albeit with some variability. The study …
Sentiment Analysis In Social Media: A Case Study Of Hike In University School Fees In Selected Nigerian Universities, Abdulahi Olarewaju Aremu, Isah Muhammad
Sentiment Analysis In Social Media: A Case Study Of Hike In University School Fees In Selected Nigerian Universities, Abdulahi Olarewaju Aremu, Isah Muhammad
Journal of Informatics and Web Engineering
Faced with escalating operational costs and government disinvestment, Nigerian public universities are implementing tuition fee increases to maintain institutional functionality. This necessary fiscal measure comes in the wake of 2022 industrial action, which exacerbated pre-existing financial strain through extended work stoppages and potentially higher costs associated with resuming activities, while leaving unaddressed the longstanding demands of academics for improved welfare and working conditions. The court-mandated resumption of academic activities without resolution of these core issues further strained university finances, leading to a significant increase in tuition fees. Using VADER, this study investigated social media sentiments related to the increase in …