Other Computer Sciences Commons^™

Building Cyber Resilience: Key Factors For Enhancing Organizational Cyber Security, Thavaselvi Munusamy, Touraj Khodadi

Journal of Informatics and Web Engineering

The increasingly pervasive influence of technology on a global scale, coupled with the accelerating pace of organizations operating in cyberspace, has intensified the need for adequate protection against the risks posed by cyber threats. This paper aims to identify cyber resilience management attributes that can enable organizations to sustain and continually adapt in the face of evolving cyber risks and threats. The researcher explores the intersections between cybersecurity and resilience by reviewing existing frameworks, models, studies, and surveys. This study establishes the attributes of resilience with the integration of resilience theory and security theory, along with their position in the …

Aira: An Intelligent Recommendation Agent Application For Movies, Ayesha Anees Zaveri, Ramsha Mashood, Sarama Shehmir, Misbah Parveen, Naveera Sami, Mobeen Nazar

Journal of Informatics and Web Engineering

An intelligent Recommendation App has been developed to assist caregivers. This project's primary objective is to assist parents in determining whether a particular movie/cartoon/drama is adequate for their children by providing ratings that will assist them in identifying age-appropriate content. This application will provide reliable evaluations, reviews, and recommendations to parents. Each rating and review are based on fundamental, essential child development principles. Intelligent Recommendation Agent aids families in making intelligent media selections. It provides the most extensive and reliable database of learning ratings, age recommendations, and content evaluations for films, television series, and dramas. In addition, there will be …

The Assistance Of Eye Blink Detection For Two- Factor Authentication, Wei-Hoong Chuah, Siew-Chin Chong, Lee-Ying Chong

Journal of Informatics and Web Engineering

This paper discusses the implementation of a blink detection method using 68 facial markers and the eye aspect ratio (EAR) to provide strong protection for access systems. It investigates the importance of 68 facial markers and explores how to use eye landmarks to calculate the eye aspect ratio. Access systems, which should have good security measures and be difficult to decipher, are typically safeguarded by passwords or multi-factor verification, such as passwords combined with facial recognition. However, these methods have inherent weaknesses, including the risk of shoulder surfing with passwords and the potential to be deceived by fake face images …

Genregait: Gender Recognition Using Gait Features, Yue Fong Ti, Tee Connie, Michael Kah Ong Goh

Journal of Informatics and Web Engineering

Gender recognition based on gait features has gained significant interest due to its wide range of applications in various fields. This paper proposes GenReGait, a robust method for gender recognition utilizing gait features. Gait, the unique walking pattern of individuals, contains distinct gender-specific characteristics, such as stride length, step frequency, and body posture, making it a promising modality for gender estimation. The proposed GenReGait method begins by extracting landmark positions on the human body using a human keypoint estimation technique. These landmarks serve as informative cues for estimating gender based on their spatial and temporal characteristics. However, environmental factors can …

Analysing Gamma Frequency Components In Eeg Signals: A Comprehensive Extraction Approach, Tanvir Hasib, Vijayakumar Vengadasalam

Journal of Informatics and Web Engineering

Gamma band activity is a high-frequency (30-100 Hz) oscillation of the electroencephalogram (EEG) that has been linked to a variety of cognitive processes including attention, memory and learning. However, extracting gamma band activity from EEG data can be challenging due to the relatively low signal-to-noise ratio of gamma band signals and the presence of other frequency bands such as beta and alpha. In this paper, we present a method for extracting gamma band activity from EEG data. We evaluated our method on a dataset of EEG data recorded from dyslexic patients. We found that our method was able to successfully …

Ensuring Privacy And Security On Banking Websites In Malaysia: A Cookies Scanner Solution, Yi Hong Tay, Shih Yin Ooi, Ying Han Pang, Ying Huey Gan, Sook Ling Lew

Journal of Informatics and Web Engineering

In this new era of science and technology, data can be said to be an extremely valuable asset for individuals, corporations, and even countries. Different parties attempt to obtain users' data occasionally, and the collection of web cookies is a prominent example. When users use a computer network, their data will be saved by the web server as cookies, including their private information. As people with bad intentions obtain this information, they can use it to commit cybercrimes and cause losses to the information owners. Thus, cookies management is vital for web users to protect their data. This paper proposes …

Traffic Impact Assessment System Using Yolov5 And Bytetrack, Jin Jie Ng, Kah Ong Michael Goh, Connie Tee

Journal of Informatics and Web Engineering

Monitoring software for traffic is not too much in this era of digital. Even cheaper is decent traffic monitoring software. You can gauge the quality of the software. It should be possible to assess the code's performance outside of a test environment. The most useful metrics are frequently those that support the program's ability to fulfil business requirements. Therefore, this project is planning to develop a traffic assessment system. The main purpose of development is to improve heavy traffic in this country – Malaysia. This system includes function vehicle detection using YOLOv5, vehicle counting with a different type (such as …

Enhancing Migraine Management System Through Weather Forecasting For A Better Daily Life, Wen-Xuan Ong, Sin-Ban Ho, Chuie-Hong Tan

Journal of Informatics and Web Engineering

A migraine is a severe, throbbing, or pulsing headache that typically affects one side of the head. A migraine attack can be so painful that it interferes with daily activities and can last for hours or even days. Migraine is a common health issue that affects approximately 1 in every 5 women and 1 in every 15 men. Additionally, millions of people worldwide suffer from migraine attacks due to the inability to anticipate or adapt to their environment. In today's globalized world, mobile phones have become a necessity for the general public, enabling communication, internet shopping, food purchases, and even …

Multi-Label Classification With Deep Learning For Retail Recommendation, Zhi Yuan Poo, Choo Yee Ting, Yuen Peng Loh, Khairil Imran Ghauth

Journal of Informatics and Web Engineering

Selecting the right retail business for a location is crucial for the success of a business because it determines the likelihood of favourable return on investment. One common approach used in retail recommendation is multi-class classification, where retail businesses are categorized into different classes or categories based on various features or attributes. Existing research in the field of retail recommendation has extensively proposed and evaluated different algorithms, techniques, and approaches for multi-class classification in the context of retail recommendation, however, limited work has been focusing on formulating retail recommendation as a multi-label problem. This is because in retail recommendation, one …

Utilizing Fuzzy Algorithm For Understanding Emotional Intelligence On Individual Feedback, Elham Abdulwahab Anaam, Su-Cheng Haw, Kok-Why Ng, Palanichamy Naveen, Rasha Thabit

Journal of Informatics and Web Engineering

Although previous studies looked at how employees should seek assistance, the issue is the researchinvestigation into how behavioral intelligence affects employee satisfaction is limited. This study examines several significant usages and developments of fuzzy mental modelling. The primary objective of the current section is to provide an innovative technique for modelling an emotion-based acceleration of the compressor for individuals. Methodologies of experiential thinking postulate that our comprehension of facial emotional reactions depends significantly on facial behavior imitation and the reactions as opportunities. Considering the theoretical foundations of combined logical reasoning. In addition, the hypothesis of probability, it additionally is not …

Face And Facial Expressions Recognition System For Blind People Using Resnet50 Architecture And Cnn, Jia-Rou Lee, Kok-Why Ng, Yih-Jian Yoong

Journal of Informatics and Web Engineering

Many blind individuals have difficulties in recognizing people’s facial expression which may impact their social interaction. With the recognition, the blind individuals can accurately interpret and respond to the emotions. There is a lack in the existing application with the combination of face and facial expressions recognition. The blind individuals have to rely on multiple applications to accomplish the same task, making it difficult and time-consuming for them to use. The paper aims to recognize faces and facial expressions for blind individuals and provides feedback in real-time. Three face detection algorithms of Haar Cascade Classifier, Dlib, and RetinaFace are compared. …

Impact Of Green Building Certification On The Rent Of Commercial Properties: A Review, Thebuwena Arachchige Chandana Hemantha Jayakody, Anthony Vaz

Journal of Informatics and Web Engineering

The world is currently facing two major problems, namely, increasing energy costs and global warming. As a result, it is crucial to take proactive measures to effectively address and mitigate the detrimental impacts arising from elevated energy costs, the pressing issue of global warming, and various types of environmental degradation. As a reaction, international organizations are advocating for the development of eco-friendly, sustainable, or green buildings as a strategy to reduce the harmful effects of the construction sector on the environment. While green development may entail higher costs for developers, it is imperative to evaluate the return on investment from …

A Cost-Based Dual Convnet-Attention Transfer Learning Model For Ecg Heartbeat Classification, Johnson Olanrewaju Victor, Xinying Chew, Khai Wah Khaw, Ming Ha Lee

Journal of Informatics and Web Engineering

The heart is a very crucial organ of the body. Concerted efforts are constantly put forward to provide adequate monitoring of the heart. A heart disorder is reported to cause a lot of hidden ailments resulting in numerous deaths. Early heart monitoring using an electrocardiogram (ECG) through the advancement of computer-aided diagnostic (CAD) systems is widely used. Meanwhile, the use of human reading of ECG results are faced with many challenges of inaccurate and unreliable interpretations. Over two decades, studies provided artificial intelligence (AI) technique using machine learning (ML) algorithms as a fast and reliable technique for ECG heartbeat classification. …

A Marker Free Visual-Based Home Rehabilitation Framework, Roy Kwang Yang Chang, Kok Swee Sim, Siong Hoe Lau

Journal of Informatics and Web Engineering

Adhesive capsulitis or more commonly known as frozen shoulder, is a familiar occurrence for adults aged above 40 caused by the inflammation of the connective tissues surrounding the shoulder joint. There are different severity of adhesive capsulitis but patients afflicted with frozen shoulder typically will experience stiffness, severe pain, and reduced range of motion (ROM) for the shoulder. No matter the course of treatment being non-steroidal anti-inflammatory drugs (NSAIDs) or steroid injections, which can help reduce the inflammation and reduce pain, in order to restore ROM for the afflicted shoulder joint, rehabilitation exercises need to be performed. Even without the …

Engaging Learning Experience: Enhancing Productivity Software Lessons With Screencast Videos, Usha Vellappan, Lim Liyen, Lim Su Yin

Journal of Informatics and Web Engineering

The use of screencast videos can improve the effectiveness of the teaching and learning process, whether it is face-to-face or online. Screencast videos are digital resources that capture the computer screen and create an audio-visual experience, and they can be shared online to aid the learning process. It eliminates the need for educators to repeat information multiple times and creates an uninterrupted personalised learning environment for the students. This method of learning gives students a more personalised sense, as if they were given one-on-one guidance from the educator, with students having access to the educator and receiving immediate feedback during …

Workplace Preference Analytics Among Graduates, Sin-Yin Ong, Choo-Yee Ting, Hui-Ngo Goh, Albert Quek, Chin-Leei Cham

Journal of Informatics and Web Engineering

Graduates often find themselves difficult to secure a job after completing their education at universities or colleges. In this light, researchers have proposed various solutions to address this challenge. However, most of the work has largely focused on academic profile and personality traits; very few have highlighted the importance of workplace location characteristics. To address this challenge, this study has employed feature selection and machine learning approach to help graduates identify desired company type and sector based on their preferences and preferred location. The data used in this study was obtained from the Ministry of Higher Education Graduates Tracer Study's …

Qr Food Ordering System With Data Analytics, Chee-Chun Wong, Lee- Ying Chong, Siew-Chin Chong, Check-Yee Law

Journal of Informatics and Web Engineering

As the epidemic starts to slow down and Malaysians are more confident about containing the outbreak with the norm of vaccination, diners have been aching to return to dining rooms, with many restaurants functioning at full capacity, but staffing is an entirely different story. As restaurateurs try to keep their businesses running at full speed and solve limited staff issues, there is only one solution: process automation. This paper aims to design a food ordering system that covers the benefits of automating the ordering process using the QR code and provides visualised insightful information based on the business data. Customers …

Diversification And Fairness In Top-K Ranking Algorithms, Mahsa Asadi

Dissertations

Given a user query, the typical user interfaces, such as search engines and recommender systems, only allow a small number of results to be returned to the user. Hence, figuring out what would be the top-k results is an important task in information retrieval, as it helps to ensure that the most relevant results are presented to the user. There exists an extensive body of research that studies how to score the records and return top-k to the user. Moreover, there exists an extensive set of criteria that researchers identify to present the user with top-k results, and result diversification …

Integrating Traditional Cs Class Activities With Computing For Social Good, Ethics, And Communications And Leadership Skills, Renato Cortinovis, Devender Goyal, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Software and information technologies are becoming increasingly integrated and pervasive in human society and range from automated decision making and social media and entertainment, to running critical social and physical infrastructures like government programs, utilities, and financial institutions. As a result, there is a growing awareness of the need to develop professionals who will harness these technologies in fair and inclusive ways and use them to address global issues like health, water management, poverty, and human rights. In this regard, many academic researchers have expressed the need to complement traditional teaching of CS technical skills with computer and information ethics …

Intrusion Detection: Machine Learning Techniques For Software Defined Networks, Jacob S. Rodriguez

Masters Theses

In recent years, software defined networking (SDN) has gained popularity as a novel approach towards network management and architecture. Compared to traditional network architectures, this software-based approach offers greater flexibility, programmability, and automation. However, despite the advantages of this system, there still remains the possibility that it could be compromised. As we continue to explore new approaches to network management, we must also develop new ways of protecting those systems from threats. Throughout this paper, I will describe and test a network intrusion detection system (NIDS), and how it can be implemented within a software defined network. This system will …

Verifying Empirical Predictive Modeling Of Societal Vulnerability To Hazardous Events: A Monte Carlo Experimental Approach, Yi Victor Wang, Seung Hee Kim, Menas C. Kafatos

Institute for ECHO Articles and Research

With the emergence of large amounts of historical records on adverse impacts of hazardous events, empirical predictive modeling has been revived as a foundational paradigm for quantifying disaster vulnerability of societal systems. This paradigm models societal vulnerability to hazardous events as a vulnerability curve indicating an expected loss rate of a societal system with respect to a possible spectrum of intensity measure (IM) of an event. Although the empirical predictive models (EPMs) of societal vulnerability are calibrated on historical data, they should not be experimentally tested with data derived from field experiments on any societal system. Alternatively, in this paper, …

Self-Supervised Pretraining And Transfer Learning On Fmri Data With Transformers, Sean Paulsen

Dartmouth College Ph.D Dissertations

Transfer learning is a machine learning technique founded on the idea that knowledge acquired by a model during “pretraining” on a source task can be transferred to the learning of a target task. Successful transfer learning can result in improved performance, faster convergence, and reduced demand for data. This technique is particularly desirable for the task of brain decoding in the domain of functional magnetic resonance imaging (fMRI), wherein even the most modern machine learning methods can struggle to decode labelled features of brain images. This challenge is due to the highly complex underlying signal, physical and neurological differences between …

Proposing A Measure Of Ethicality For Humans And Ai, Alejandro Jorge Napolitano Jawerbaum

Electronic Theses and Dissertations

Smarter people or intelligent machines are able to make more accurate inferences about their environment and other agents more efficiently than less intelligent agents. Formally: ‘Intelligence measures an agent’s ability to achieve goals in a wide range of environments.’ (Legg, 2008)

In this dissertation we extend this definition to include ethical behaviour and we will offer a mathematical formalism and a way to estimate how ethical an action is or will be, both for a human and for a computer, by calculating the expected values of random variables. Formally, we propose the following measure of ethicality, which is computable, or …

A Data-Driven Multi-Regime Approach For Predicting Real-Time Energy Consumption Of Industrial Machines., Abdulgani Kahraman

Electronic Theses and Dissertations

This thesis focuses on methods for improving energy consumption prediction performance in complex industrial machines. Working with real-world industrial machines brings several challenges, including data access, algorithmic bias, data privacy, and the interpretation of machine learning algorithms. To effectively manage energy consumption in the industrial sector, it is essential to develop a framework that enhances prediction performance, reduces energy costs, and mitigates air pollution in heavy industrial machine operations. This study aims to assist managers in making informed decisions and driving the transition towards green manufacturing. The energy consumption of industrial machinery is substantial, and the recent increase in CO2 …

Understanding The Role Of Interactivity And Explanation In Adaptive Experiences, Lijie Guo

All Dissertations

Adaptive experiences have been an active area of research in the past few decades, accompanied by advances in technology such as machine learning and artificial intelligence. Whether the currently ongoing research on adaptive experiences has focused on personalization algorithms, explainability, user engagement, or privacy and security, there is growing interest and resources in developing and improving these research focuses. Even though the research on adaptive experiences has been dynamic and rapidly evolving, achieving a high level of user engagement in adaptive experiences remains a challenge. %????? This dissertation aims to uncover ways to engage users in adaptive experiences by incorporating …

All Hands On Deck: Choosing Virtual End Effector Representations To Improve Near Field Object Manipulation Interactions In Extended Reality, Roshan Venkatakrishnan

All Dissertations

Extended reality, or "XR", is the adopted umbrella term that is heavily gaining traction to collectively describe Virtual reality (VR), Augmented reality (AR), and Mixed reality (MR) technologies. Together, these technologies extend the reality that we experience either by creating a fully immersive experience like in VR or by blending in the virtual and "real" worlds like in AR and MR.

The sustained success of XR in the workplace largely hinges on its ability to facilitate efficient user interactions. Similar to interacting with objects in the real world, users in XR typically interact with virtual integrants like objects, menus, windows, …

The Effects Of Primary And Secondary Task Workloads On Cybersickness In Immersive Virtual Active Exploration Experiences, Rohith Venkatakrishnan

All Dissertations

Virtual reality (VR) technology promises to transform humanity. The technology enables users to explore and interact with computer-generated environments that can be simulated to approximate or deviate from reality. This creates an endless number of ways to propitiously apply the technology in our lives. It follows that large technological conglomerates are pushing for the widespread adoption of VR, financing the creation of the Metaverse - a hypothetical representation of the next iteration of the internet.

Even with VR technology's continuous growth, its widespread adoption remains long overdue. This can largely be attributed to an affliction called cybersickness, an analog to …

Epileptic Seizure Classification Using Image-Based Data Representation, Amber Surles

Graduate Theses and Dissertations (2019 - present)

Epilepsy is a recurrence of seizures caused by a disorder of the brain in over 3.4 million people nationwide. Some people are able to predict their seizures based off prodrome, which is an early sign or symptom that usually resembles mood changes or a euphoric feeling even days to an hour before occurrence. Consequently, the natural instincts of the body to react to an upcoming attack lends credence to the existence of a pre-ictal state that precedes seizure episodes. Physicians and researchers have thus sought for an automated approach for predicting or detecting seizures.

In this research, we evaluate the …

Heterochiral Dna Nanotechnology For Biomedical Applications, Tracy L. Mallette

Biomedical Engineering ETDs

In the past 30 years, there have been major advancements on how to treat and diagnose disease because of the improvement and increase in accessibility of sequencing technology. Nucleic acid-based therapeutics can manipulate protein expression. Likewise, pathogens can be identified and detected with single nucleotide specificity. However, the underlying oligonucleotide technology requires protection against natural defense systems that have evolved to destroy foreign nucleic acids. Many chemical modifications that can protect nucleotides also have significant cytotoxic side effects and must be carefully designed into the strands. A novel way to protect against nuclease-mediated degradation is through the use of mirror-image, …

Multi-Scale Attention Networks For Pavement Defect Detection, Junde Chen, Yuxin Wen, Yaser Ahangari Nanehkaran, Defu Zhang, Adan Zeb

Engineering Faculty Articles and Research

Pavement defects such as cracks, net cracks, and pit slots can cause potential traffic safety problems. The timely detection and identification play a key role in reducing the harm of various pavement defects. Particularly, the recent development in deep learning-based CNNs has shown competitive performance in image detection and classification. To detect pavement defects automatically and improve effects, a multi-scale mobile attention-based network, which we termed MANet, is proposed to perform the detection of pavement defects. The architecture of the encoder-decoder is used in MANet, where the encoder adopts the MobileNet as the backbone network to extract pavement defect features. …