Software Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

Generative Model-Based Testing On Decision-Making Policies, Zhuo Li, Xiongfei Wu, Derui Zhu, Mingfei Cheng, Siyuan Chen, Fuyuan Zhang, Xiaofei Xie, Lei Ma, Jianjun Zhao

Research Collection School Of Computing and Information Systems

The reliability of decision-making policies is urgently important today as they have established the fundamentals of many critical applications, such as autonomous driving and robotics. To ensure reliability, there have been a number of research efforts on testing decision-making policies that solve Markov decision processes (MDPs). However, due to the deep neural network (DNN)-based inherit and infinite state space, developing scalable and effective testing frameworks for decision-making policies still remains open and challenging.In this paper, we present an effective testing framework for decision-making policies. The framework adopts a generative diffusion model-based test case generator that can easily adapt to different …

The Devil Is In The Tails: How Long-Tailed Code Distributions Impact Large Language Models, Xin Zhou, Kisub Kim, Bowen Xu, Jiakun Liu, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE) tasks. However, most existing works focus on designing better learning-based models and pay less attention to the properties of datasets. Learning-based models, including popular LLMs for code, heavily rely on data, and the data's properties (e.g., data distribution) could significantly affect their behavior. We conducted an exploratory study on the distribution of SE data and found that such data usually follows a skewed distribution (i.e., long-tailed distribution) where a small number of classes have an extensive collection of samples, while a …

Sparsity Brings Vulnerabilities: Exploring New Metrics In Backdoor Attacks, Jianwen Tian, Kefan Qiu, Debin Gao, Zhi Wang, Xiaohui Kuang, Gang Zhao

Research Collection School Of Computing and Information Systems

Nowadays, using AI-based detectors to keep pace with the fast iterating of malware has attracted a great attention. However, most AI-based malware detectors use features with vast sparse subspaces to characterize applications, which brings significant vulnerabilities to the model. To exploit this sparsityrelated vulnerability, we propose a clean-label backdoor attack consisting of a dissimilarity metric-based candidate selection and a variation ratio-based trigger construction. The proposed backdoor is verified on different datasets, including a Windows PE dataset, an Android dataset with numerical and boolean feature values, and a PDF dataset. The experimental results show that the attack can slash the accuracy …

Synthesizing Speech Test Cases With Text-To-Speech? An Empirical Study On The False Alarms In Automated Speech Recognition Testing, Julia Kaiwen Lau, Kelvin Kai Wen Kong, Julian Hao Yong, Per Hoong Tan, Zhou Yang, Zi Qian Yong, Joshua Chern Wey Low, Chun Yong Chong, Mei Kuan Lim, David Lo

Research Collection School Of Computing and Information Systems

Recent studies have proposed the use of Text-To-Speech (TTS) systems to automatically synthesise speech test cases on a scale and uncover a large number of failures in ASR systems. However, the failures uncovered by synthetic test cases may not reflect the actual performance of an ASR system when it transcribes human audio, which we refer to as false alarms. Given a failed test case synthesised from TTS systems, which consists of TTS-generated audio and the corresponding ground truth text, we feed the human audio stating the same text to an ASR system. If human audio can be correctly transcribed, an …

Mitigating Adversarial Attacks On Data-Driven Invariant Checkers For Cyber-Physical Systems, Rajib Ranjan Maiti, Cheah Huei Yoong, Venkata Reddy Palleti, Arlindo Silva, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

The use of invariants in developing security mechanisms has become an attractive research area because of their potential to both prevent attacks and detect attacks in Cyber-Physical Systems (CPS). In general, an invariant is a property that is expressed using design parameters along with Boolean operators and which always holds in normal operation of a system, in particular, a CPS. Invariants can be derived by analysing operational data of various design parameters in a running CPS, or by analysing the system's requirements/design documents, with both of the approaches demonstrating significant potential to detect and prevent cyber-attacks on a CPS. While …

Characterization And Estimation Of Musculoskeletal Pain Using Machine Learning, Boluwatife Faremi

Master's Theses

Traditional scales utilized for recording pain are known to be highly subjective and biased due to inaccuracies in recollecting actual pain intensities. As a result, machine learning (ML) models that are trained using these scores as ground truth are reported to have low performance for objective pain classification because of the huge disparity between what was felt in moments of pain and the scores recorded afterward.

In the present study, two devices were designed for gathering real-time, continuous in-session subjective pain scores and the recording of the autonomic nervous system (ANS) altered endodermal (EDA) activity. 24 participants were recruited to …

Generation-Based Code Review Automation: How Far Are We?, Xin Zhou, Kisub Kim, Bowen Xu, Donggyun Han, Junda He, David Lo

Research Collection School Of Computing and Information Systems

Code review is an effective software quality assurance activity; however, it is labor-intensive and time-consuming. Thus, a number of generation-based automatic code review (ACR) approaches have been proposed recently, which leverage deep learning techniques to automate various activities in the code review process (e.g., code revision generation and review comment generation).We find the previous works carry three main limitations. First, the ACR approaches have been shown to be beneficial in each work, but those methods are not comprehensively compared with each other to show their superiority over their peer ACR approaches. Second, general-purpose pre-trained models such as CodeT5 are proven …

What Do Users Ask In Open-Source Ai Repositories? An Empirical Study Of Github Issues, Zhou Yang, Chenyu Wang, Jieke Shi, Thong Hoang, Pavneet Singh Kochhar, Qinghua Lu, Zhenchang Xing, David Lo

Research Collection School Of Computing and Information Systems

Artificial Intelligence (AI) systems, which benefit from the availability of large-scale datasets and increasing computational power, have become effective solutions to various critical tasks, such as natural language understanding, speech recognition, and image processing. The advancement of these AI systems is inseparable from open-source software (OSS). Specifically, many benchmarks, implementations, and frameworks for constructing AI systems are made open source and accessible to the public, allowing researchers and practitioners to reproduce the reported results and broaden the application of AI systems. The development of AI systems follows a data-driven paradigm and is sensitive to hyperparameter settings and data separation. Developers …

Picaso: Enhancing Api Recommendations With Relevant Stack Overflow Posts, Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, Kisub Kim, David Lo

Research Collection School Of Computing and Information Systems

While having options could be liberating, too many options could lead to the sub-optimal solution being chosen. This is not an exception in the software engineering domain. Nowadays, API has become imperative in making software developers' life easier. APIs help developers implement a function faster and more efficiently. However, given the large number of open-source libraries to choose from, choosing the right APIs is not a simple task. Previous studies on API recommendation leverage natural language (query) to identify which API would be suitable for the given task. However, these studies only consider one source of input, i.e., GitHub or …

Niche: A Curated Dataset Of Engineered Machine Learning Projects In Python, Ratnadira Widyasari, Zhou Yang, Ferdian Thung, Sheng Qin Sim, Fiona Wee, Camellia Lok, Jack Phan, Haodi Qi, Constance Tan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Machine learning (ML) has gained much attention and has been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such a high-quality dataset poses an obstacle to understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on the evidence of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. This …

Arkavalley Liquor: Simplifying Restaurant Alcohol Orders, Isaiah A. Kitts, Dayton Drilling, Bradlee Treece, Cameron Lumpkin

ATU Scholars Symposium

The ArkaValley Liquor system is a web-based ordering platform designed to simplify the process of ordering alcohol for local restaurants. Currently, restaurants place orders by emailing the store, which makes it difficult to maintain a paper trail and track order details. With the ArkaValley Liquor system, the ordering process is automated, and all order details are saved in one central location. Each restaurant will have a login, ensuring only authorized individuals can place orders. The system will also provide a record of each restaurant's most recent order, making it easy to reorder if necessary. By using the ArkaValley Liquor system, …

A Study Of A Collaborative Task Management Application Built On React Native Using The Basic Ux Framework, Andrei Modiga

Campus Research Month

Many times it can be difficult to accomplish all this is proposed in a meeting. This project aimed to build a simple planner application using React Native that allows groups of people to collaborate and stay organized. The application was built using the BASIC Framework as a guide, and featured a collaboration feature that enabled users to share tasks, projects, and communicate with one another in order to stay coordinated and productive. The user interface was designed for easy use, allowing for quick and efficient task management within a group. The goal of the application was to provide a useful …

Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu

Research Collection School Of Computing and Information Systems

Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs such as (on GitHub or Stack Overflow), identifying and localizing the precise code is critical for the software developers. In addition, Deep learning has recently been widely applied to different code-related scenarios, ., vulnerability detection, source code summarization. However, automated deep code search is still challenging since it requires a high-level semantic mapping between code and natural language queries. Most existing deep learning-based approaches for code search rely on the sequential text ., …

Dsdnet: Toward Single Image Deraining With Self-Paced Curricular Dual Stimulations, Yong Du, Junjie Deng, Yulong Zheng, Junyu Dong, Shengfeng He

Research Collection School Of Computing and Information Systems

A crucial challenge regarding the single image deraining task is to completely remove rain streaks while still preserving explicit image details. Due to the inherent overlapping between rain streaks and background scenes, the texture details could be inevitably lost when clearing rain away from the degraded image, making the two purposes contradictory. Existing deep learning based approaches endeavor to resolve the two issues successively in a cascaded framework or to treat them as independent tasks in a parallel structure. However, none of the models explores a proper interaction between rain distributions and hidden feature responses, which intuitively would provide more …

Code Will Tell: Visual Identification Of Ponzi Schemes On Ethereum, Xiaolin Wen, Kim Siang Yeo, Yong Wang, Ling Cheng, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

Ethereum has become a popular blockchain with smart contracts for investors nowadays. Due to the decentralization and anonymity of Ethereum, Ponzi schemes have been easily deployed and caused significant losses to investors. However, there are still no explainable and effective methods to help investors easily identify Ponzi schemes and validate whether a smart contract is actually a Ponzi scheme. To fill the research gap, we propose PonziLens, a novel visualization approach to help investors achieve early identification of Ponzi schemes by investigating the operation codes of smart contracts. Specifically, we conduct symbolic execution of opcode and extract the control flow …

Ureca – The Research Ethics And Data Protection Online Review Platform Used By The University Of Malta, Joel Azzopardi

The Journal of Electronic Theses and Dissertations

Nowadays, research ethics and data protection are given very high importance, and research organizations, including universities, need to safeguard their level of professionalism and integrity by providing the necessary guidelines. Moreover, they need to ensure that these guidelines are being adhered to by their affiliated researchers, including students. This is needed for protection of the research subjects, researchers, and the organization (university) itself. However, care must be taken so that the research ethics review process is streamlined as much as possible to minimize bureaucracy, as such guidelines would then be viewed as a research barrier. This study describes URECA, the …

A Data Augmented Method For Plant Disease Leaf Image Recognition Based On Enhanced Gan Model Network, Mingyuan Xin, Ling Weay Ang, Sellappan Palaniappan

Journal of Informatics and Web Engineering

The identification of plant disease leaves based on deep learning is the key to control the development and spread of plant diseases. In this paper, the existing problems of traditional classification and recognition of plant disease leaves and the limitations of deep learning-based plant disease leaf training are analysed. An enhanced GAN model network based on the Wasserstein GAN loss function has been developed to address the limited training images of plant disease leaves. The self-attention layer is added into the self-encoding structure of the generating network. The effectiveness of data generated by the encoder is increased after the self-attention …

Elderly And Smartphone Apps: Case Study With Lightweight Mysejahtera, Ciu Yung Seek, Shih Yin Ooi, Ying Han Pang, Sook Ling Lew, Xin Yun Heng

Journal of Informatics and Web Engineering

The outbreak of Covid-19 in the past 2 years has made the usage of contact-tracing app almost mandatory in Malaysia. Though the usage is seeming to be simple, but one interesting phenomenon can be observed in Malaysia is that most of the senior citizen are found not using smartphones regularly. While check-in through MySejahtera (the primary contract-tracing app used in Malaysia) for business, premises, and transports has made compulsory, it does bring a lot of inconveniences to the elderly. Many elderlies start to learn how to use smartphone and government has also taking initiative by providing free or low-cost smartphone …

The Impact Of The Telecommunication Industry As A Moderator On Poverty Alleviation And Educational Programmes To Achieve Sustainable Development Goals In Developing Countries, S.K.C Ruklani Wickramasinghe, Kamal Abd Razak

Journal of Informatics and Web Engineering

The purpose of this study is to investigate the influence of the telecommunications industry's contribution to sustainable development in developing nations. A detailed literature study is conducted for this purpose, and a conceptual framework is offered. To validate the proposed conceptual framework, we conducted multiple case studies involving companies in the telecommunications industry from various countries. These findings improved the suggested conceptual framework produced for this study. However, despite the contributions of the telecommunications industry to the Sustainable Development Goals, no study has been conducted to examine how they have benefited poverty reduction and educational programmes in Sri Lanka. The …

A Swot Analysis With A Digital Transformation: A Case Study For Hospitals In The Pharmaceutical Supply Chain, Nguyen Huu Khanh Quan, Harwindar Singh, Thai Hong Thuy Khanh, Premkumar Rajagopal

Journal of Informatics and Web Engineering

The pharmaceutical business meets all requirements for a complicated and tightly regulated sector, including multi-stakeholder participation. The objective is to study digital transformation strategies in hospitals to improve the safety and convenience of pharmaceutical services when providing healthcare services. In this study, a SWOT analysis is performed to identify strengths, weaknesses, opportunities, and threats with a digital transformation case study for hospitals in the pharmaceutical supply chain in Ho Chi Minh City, Vietnam. Information source for SWOT analysis of published articles and reports in the following aspects: Digital transformation environment of hospitals in the global pharmaceutical supply chain; new technology …

Enhancing Mimo Capacity Through Space-Time Coding: Analysis And Design Framework, Lijun Han, Ling Weay Ang, Sellappan Palaniappan, Jing Wang

Journal of Informatics and Web Engineering

Space-time coding combines time and space to generate codewords, transmitting signals in both time and space domains. This leads to not only diversity and coding gains but also reduces the impact of multipath fading, resulting in high spectral efficiency. This paper examines the challenges in implementing space-time coding to enhance the capacity of MIMO systems. It analyzes the principle, design objectives, and criteria of space-time coding, providing a basic design framework, based on the space-time coding (STC) system model. .STC and MIMO have proven to be effective in improving system capacity, reliability, and overall performance in wireless communication. They have …

Robust Image Watermarking With Quaternion Fractional-Order Polar Harmonic-Fourier Moments Based On Wavelet Transformation: Resistance Against Rotation Attacks, Wang Jing, Ling Weay Ang, Sellappan Palaniappan, Bing He

Journal of Informatics and Web Engineering

This study presents a zero-watermarking algorithm that can resist rotation attacks. The algorithm uses quaternion fractional-order polar harmonic-Fourier moments (QFr-PHFMs) based on wavelet-transformation. First, the wavelet-transformation is applied to each component of the host image, which is in RGB three-channel color. The low-frequency sub-bands of each component are then extracted and represented using quaternion algebra. Multiple QFr-PHFMs are calculated, and the invariants of the QFr-PHFMs are utilized to establish the watermark system. The watermark extraction process is also simplified. The detection of the image requires a two-level wavelet transformation, followed by the calculation of multiple invariant moments of the low-frequency …