Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

2025

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 25471 - 25500 of 25516

Full-Text Articles in Entire DC Network

Antdroidnet Cybersecurity Model: A Hybrid Integration Of Ant Colony Optimization And Deep Neural Networks For Android Malware Detection, Riyadh Rahef Nuiaa Al Ogaili, Osamah Adil Raheem, Mohamed H Ghaleb Abdkhaleq, Zaid Abdi Alkareem Alyasseri, Zaid Abdi Alkareem Alyasseri, Ali Hakem Alsaeedi, Yousif Raad Muhsen, Selvakumar Manickam Jan 2025

Antdroidnet Cybersecurity Model: A Hybrid Integration Of Ant Colony Optimization And Deep Neural Networks For Android Malware Detection, Riyadh Rahef Nuiaa Al Ogaili, Osamah Adil Raheem, Mohamed H Ghaleb Abdkhaleq, Zaid Abdi Alkareem Alyasseri, Zaid Abdi Alkareem Alyasseri, Ali Hakem Alsaeedi, Yousif Raad Muhsen, Selvakumar Manickam

Mesopotamian Journal of CyberSecurity

Malware detection is a vital problem, and efficient methods that can efficiently detect malware are needed. The increasing use of mobile computers makes malware detection a vital part of security in an era where smartphones have come to play a key role in many of our daily lives. Earlier approaches, however, suffer from high false positive rates; they are not scalable for larger databases, or they are not amenable to adapt well to novel zero-day malware. For these reasons, the demand for more sensitive and flexible detection models is high. In this study, we develop a hybrid mobile malware detection …

Go to article

Enhancing Crime Detection In Video Surveillance Via A Lightweight Blockchain And Homomorphic Encryption-Based Computer Vision System, Tanya Abdulsattar Jaber Jan 2025

Enhancing Crime Detection In Video Surveillance Via A Lightweight Blockchain And Homomorphic Encryption-Based Computer Vision System, Tanya Abdulsattar Jaber

Mesopotamian Journal of CyberSecurity

Blockchain technology consists of distributed ledgers or database systems, regarded as immutable, secure, and innovative, characterized by unsupervised internal maintenance with a special security protocol used to prevent inference from malicious or third parties. The widespread use of this technology has led to deep research into the problems posed by this technology, which can be summarized in terms of computational cost and latency time. The crime detection process in video surveillance has made great progress with the use of technologies such as the Internet of Things and blockchain technologies. However, to reach high levels of security in the physical crime …

Go to article

Improved Blockchain Technique Based On Modified Slim Algorithm For Cyber Security, Sarah Mohammed Shareef, Rehab Flaih Hassan Jan 2025

Improved Blockchain Technique Based On Modified Slim Algorithm For Cyber Security, Sarah Mohammed Shareef, Rehab Flaih Hassan

Mesopotamian Journal of CyberSecurity

The number of cybersecurity incidents is increasing, and the cost of a security breach has a catastrophic financial effect. The existing real estate information systems require more robust and resilient cybersecurity solutions to secure hardware, software, and databases. Cybersecurity often relies on user behavior. Phishing attacks and social engineering can bypass blockchain security, highlighting the need for robust user education and awareness. Many blockchain networks face challenges in handling a high volume of transactions. Solutions that work well on a small scale may not perform efficiently as the network grows, leading to delays and increased costs. A secure system is …

Go to article

Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi Jan 2025

Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi

Mesopotamian Journal of CyberSecurity

In the current digital landscape, information security has become a critical necessity given the escalating frequency and sophistication of cyberattacks across global computing networks. Cryptography is the science and practice of securing information by transforming it into a format that is unreadable or inaccessible to unauthorized parties. The strength of the cryptography algorithm lies in the strength of used encryption key. Recently, the nonlinear behavior of chaotic maps has been utilized as a random source to generate robust key stream bits for cryptographic purposes. The aim of this paper is to introduce an efficient and robust system for generating strong …

Go to article

Secured Multi-Objective Optimisation-Based Protocol For Reliable Data Transmission In Underwater Wireless Sensor Networks, Mostfa Albdair, Zainab Rustum Mohsin, Ahmed Saihood, Aqeel M. Hamad, Aqeel M. Hamad Jan 2025

Secured Multi-Objective Optimisation-Based Protocol For Reliable Data Transmission In Underwater Wireless Sensor Networks, Mostfa Albdair, Zainab Rustum Mohsin, Ahmed Saihood, Aqeel M. Hamad, Aqeel M. Hamad

Mesopotamian Journal of CyberSecurity

Underwater wireless sensor network (UWSN) requirements have increased beyond applications in environmental monitoring and underwater exploration to military surveillance. The complex underwater environment raises many challenges due to high propagation delays, limited bandwidth, high error rates, and dynamic underwater currents. Most traditional clustering algorithms do not consider the multifaceted requirements of UWSNs. In most cases, a single objective is optimised at the cost of other essential factors, such as energy consumption, network robustness, and data transmission reliability. This paper proposes a new UWSN protocol based on the tiger beetle optimisation (TBO) algorithm for multiobjective K-means clustering (TBO-MOK). The protocol comprises …

Go to article

Smartphone Authentication Based On 3d Touch Sensor And Finger Locations On Touchscreens Via Decision-Making Techniques, Moceheb Lazam Shuwandy, Rawan Adel Fawzi Alsharida, Maytham M. Hammood Jan 2025

Smartphone Authentication Based On 3d Touch Sensor And Finger Locations On Touchscreens Via Decision-Making Techniques, Moceheb Lazam Shuwandy, Rawan Adel Fawzi Alsharida, Maytham M. Hammood

Mesopotamian Journal of CyberSecurity

Smartphone authentication systems must balance security and user convenience, which is a persistent challenge in the digital realm. Traditional biometrics, such as fingerprints and facial recognition, face vulnerabilities to spoofing and environmental conditions, limiting reliability. This study introduces a novel approach by integrating three-dimensional (3D) touch sensors with finger location data for authentication. The goal is to develop a system that improves accuracy while minimizing false positives and negatives, leveraging touch pressure and spatial interaction as unique biometric identifiers. Data from 20 participants, including pressure levels, spatial coordinates, and timestamps, were analysed using Random Forest (RF) and Extreme Gradient Boosting …

Go to article

Enhancing Cybersecurity With Machine Learning: A Hybrid Approach For Anomaly Detection And Threat Prediction, Adil M. Salman, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Hussein Alkattan, Hussein Alkattan Jan 2025

Enhancing Cybersecurity With Machine Learning: A Hybrid Approach For Anomaly Detection And Threat Prediction, Adil M. Salman, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Hussein Alkattan, Hussein Alkattan

Mesopotamian Journal of CyberSecurity

In today's digital era, cybersecurity has become a principal concern because of the increasing frequency and advancement of cyber threats. This study explores machine learning models for detecting and predicting anomalies in cybersecurity datasets. The research evaluates models such as linear regression, decision tree, RF, gradient boosting, KNN, SVR, LSTM, and neural networks utilizing performance metrics such as accuracy, MAE and MSE. A hybrid model that integrates different learning strategies is additionally proposed to improve the predictive accuracy and strength. The results highlight the superiority of ensemble approaches, especially the hybrid model, in improving peculiarity detection capabilities. The comparative analysis …

Go to article

Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie Jan 2025

Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie

Mesopotamian Journal of CyberSecurity

Securing big data in power plants is an important and fundamental step in the infrastructure of smart cities. In addition, it becomes a barrier if it is not controlled from the beginning. Security must be a combination of fast and robust properties. This research presents a traffic security system (TSS) in a smart city (SC). It is a novel paradigm meant to improve data security and integrity by means of a multilayered method. Advanced fault analysis, dual-stage pseudonymizing, quantum key distribution via the BB84 protocol, and Falcon signatures (FS) are combined in the proposed system. TSS enhances data security by …

Go to article

Schistosomiasis Interventions In Africa: Assessment And Systematic Review, Christopher Yaw Dumevi, George Boateng Kyei, Patience B Tetteh-Quarcoo, James-Paul Kretchy, Irene Ayi, Patrick F Ayeh-Kumi Jan 2025

Schistosomiasis Interventions In Africa: Assessment And Systematic Review, Christopher Yaw Dumevi, George Boateng Kyei, Patience B Tetteh-Quarcoo, James-Paul Kretchy, Irene Ayi, Patrick F Ayeh-Kumi

2020-Current year OA Pubs

No abstract provided.

Go to article

Qualitative And Quantitative Analysis Of A Novel Dental Health Education Program To Improve Dental Care Utilization By Bhutanese-, Burmese-, And Swahili-Speaking Refugees In A Midwestern United States City, Chandra Swanson, Katherine Gordon, Kelly Kreisler, Elizabeth Montgomery Collins Jan 2025

Qualitative And Quantitative Analysis Of A Novel Dental Health Education Program To Improve Dental Care Utilization By Bhutanese-, Burmese-, And Swahili-Speaking Refugees In A Midwestern United States City, Chandra Swanson, Katherine Gordon, Kelly Kreisler, Elizabeth Montgomery Collins

2020-Current year OA Pubs

No abstract provided.

Go to article

Advancing Multivariate Time Series Similarity Assessment: An Integrated Computational Approach, Franck B.N. Tonle, Henri E.Z. Tonnang, Milliam M.Z. Ndadji, Maurice Tchoupe Tchendji, Armand Nzeukou, Kennedy Senagi, Saliou Niassy Jan 2025

Advancing Multivariate Time Series Similarity Assessment: An Integrated Computational Approach, Franck B.N. Tonle, Henri E.Z. Tonnang, Milliam M.Z. Ndadji, Maurice Tchoupe Tchendji, Armand Nzeukou, Kennedy Senagi, Saliou Niassy

All Peer-Reviewed Publications

Data mining, particularly multivariate time series data analysis, is crucial in extracting insights from complex systems and supporting informed decision-making across diverse domains. However, assessing the similarity of multivariate time series data presents several challenges, including dealing with large datasets, addressing temporal misalignments, and necessitating efficient and comprehensive analytical frameworks. A novel integrated computational approach, Multivariate Time series Alignment and Similarity Assessment (MTASA) is proposed to address these challenges. MTASA is built upon a hybrid methodology designed to optimise time series alignment, complemented by a multiprocessing engine that enhances the utilisation of computational resources. This integrated approach comprises four key …

Go to article

Annual Diversity Of Honey Bee Pollen Sources In Two Pumpkin Growing Landscapes, Machakos County, Kenya, Marystella W. Nang’Oni, Muo Kasina, Rebecca Karanja, Mary M. Guantai, Rahab N. Kinyanjui, Evanson R. Omuse, Michael H.G. Lattorff, Elfatih M. Abdel-Rahman, Marian Adan, Samira A. Mohamed, Thomas Dubois Jan 2025

Annual Diversity Of Honey Bee Pollen Sources In Two Pumpkin Growing Landscapes, Machakos County, Kenya, Marystella W. Nang’Oni, Muo Kasina, Rebecca Karanja, Mary M. Guantai, Rahab N. Kinyanjui, Evanson R. Omuse, Michael H.G. Lattorff, Elfatih M. Abdel-Rahman, Marian Adan, Samira A. Mohamed, Thomas Dubois

All Peer-Reviewed Publications

Multi-floral foraging sources for honey bee (Apis mellifera L.) have been threatened by landscape changes and unsustainable farming practices. In East Africa, the biodiversity of forage resources that could support honey bees, especially in agricultural lands, remains least explored. This study investigated pollen diversity for honey bees in Yatta and Masinga Sub-counties in Machakos County, Kenya. Honey bee hives were installed on eight pumpkin (Cucurbita maxima Duchesne ex Lam) farms (one hive per farm) in two varying landscape vegetation classes (low and medium) based on normalized difference vegetation index (NDVI). Pollen traps were installed at the hive entrance and pollen …

Go to article

Morphometric Characterization Of Invasive Diaphorina Citri Infesting Citrus And Orange Jasmine In Ghana, Kodwo Dadzie Ninsin, Maxwell Kelvin Billah, Bernard Agyeman Boateng, Jonathan Osei-Owusu, Fred Kormla Ablormeti, Samuel Opuni-Basoa, Aboagye Kwarteng Dofuor, George Edusei, Steve B.S. Baleba, Owusu Fordjour Aidoo Jan 2025

Morphometric Characterization Of Invasive Diaphorina Citri Infesting Citrus And Orange Jasmine In Ghana, Kodwo Dadzie Ninsin, Maxwell Kelvin Billah, Bernard Agyeman Boateng, Jonathan Osei-Owusu, Fred Kormla Ablormeti, Samuel Opuni-Basoa, Aboagye Kwarteng Dofuor, George Edusei, Steve B.S. Baleba, Owusu Fordjour Aidoo

All Peer-Reviewed Publications

Morphometric analysis plays a crucial role in the accurate identification and classification of insect pests, which is essential for implementing effective management strategies. The Asian citrus psyllid (Diaphorina citri Kuwayama; Hemiptera: Liviidae), an invasive species and a known vector of ‘Candidatus Liberibacter asiaticus’ and ‘Ca. Liberibacter americanus,’ the bacterial pathogens associated with Huanglongbing (HLB), has recently emerged as a pest of concern in Ghana. Despite its significance, little is known about the biological traits of field populations in the region. In this study, we examined morphometric variation in D. citri populations infesting citrus and orange jasmine (Murraya paniculata) across different …

Go to article

Contribution Of Different Frass Fertilizer Products On Enhanced Growth, Yield And Nutrient Quality Of Broccoli [Brassica Oleracea], Noella Kagehi, Dennis Beesigamukama, Chrysantus M. Tanga, Mathew P. Ngugi, Sevgan Subramanian, Fathiya M. Khamis Jan 2025

Contribution Of Different Frass Fertilizer Products On Enhanced Growth, Yield And Nutrient Quality Of Broccoli [Brassica Oleracea], Noella Kagehi, Dennis Beesigamukama, Chrysantus M. Tanga, Mathew P. Ngugi, Sevgan Subramanian, Fathiya M. Khamis

All Peer-Reviewed Publications

Vegetables are crucial for food security and income, but in developing countries their production is hindered by low soil fertility. Although the insect frass fertilizer is a potential solution, its use is constrained by limited product choices. Unlike conventional fertilizers, which are available in different forms, the insect frass fertilizer is mostly available in solid form. Here, we evaluated the effects of different black soldier fly frass fertilizer (BSFFF) products on broccoli [Brassica oleracea] growth, yield, and nutritional profiles. Solid, liquid BSFFF, chitin-fortified solid BSFFF, chitin-fortified liquid BSFFF, and commercial organic fertilizer (Safi) were applied at rates equivalent to 250 …

Go to article

A Review On Knowledge And Information Extraction From Pdf Documents And Storage Approaches, Salvador D. Atagong, Henri Tonnang, Kennedy Senagi, Mark Wamalwa, Komi M. Agboka, John Odindi Jan 2025

A Review On Knowledge And Information Extraction From Pdf Documents And Storage Approaches, Salvador D. Atagong, Henri Tonnang, Kennedy Senagi, Mark Wamalwa, Komi M. Agboka, John Odindi

All Peer-Reviewed Publications

Introduction: Automating the extraction of information from Portable Document Format (PDF) documents represents a major advancement in information extraction, with applications in various domains such as healthcare, law, or biochemistry. However, existing solutions face challenges related to accuracy, domain adaptability, and implementation complexity. Methods: A systematic review of the literature was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to examine approaches and trends in PDF information extraction and storage approaches. Results: The review revealed three dominant methodological categories: rule-based systems, statistical learning models, and neural network-based approaches. Key limitations include the rigidity of rule-based …

Go to article

Predicting Food Prices In Kenya Using Machine Learning: A Hybrid Model Approach With Xgboost And Gradient Boosting, Benard O. Ogol, Evans Omondi, John Olukuru, Betsy Muriithi, Kennedy Senagi Jan 2025

Predicting Food Prices In Kenya Using Machine Learning: A Hybrid Model Approach With Xgboost And Gradient Boosting, Benard O. Ogol, Evans Omondi, John Olukuru, Betsy Muriithi, Kennedy Senagi

All Peer-Reviewed Publications

Introduction: Food price volatility continues to be a significant concern in Kenya's economic development, posing challenges to the country's economic stability. Methodology: This study examines the application of machine learning methods, employing a hybrid approach that combines XGBoost and gradient boosting, to predict food prices in Kenya. The food prices data from the World Food Programme, covering the period from January 2006 to September 2024, as well as currency exchange rates data from the Central Bank of Kenya in US dollars (USD) and inflation rates data, were collated and preprocessed to be ready for analytics and machine learning. The augmented …

Go to article

The Effectiveness Of Tech Support Fraud In Damaging Older Individual’S Financial Security, Vanessa Perera Jan 2025

The Effectiveness Of Tech Support Fraud In Damaging Older Individual’S Financial Security, Vanessa Perera

Theses : Honours

This study discovers the tactics employed to create detrimental effects upon older people impacted from fraudulent tech-support incidents. It examines social engineering, and financial confusion of older people. This is significant considering adaptations towards digital banking and payment management. This research looked at online and active over 65s. Using largely qualitative approaches over 65s were interviewed and responses validated against cyber-professionals’ responses. This identified three key findings: older adults feel confused and misunderstand tech support scams; threat actors build trust by pretending to offer technical help but use this to deceive their victims; and older adults face serious social and …

Go to article

Swatting Flies: Biting Insects As Non-Invasive Samplers For Mammalian Population Genomics, Anubhab Khan, Ryan Carter, Chengetai D. Mpamhanga, Daniel Masiga, Manun Channumsin, Marc Ciosi, Oliva Manangwa, Furaha Mramba, Umer Zeeshan Ijaz, Harriet Auty, Barbara K. Mable Jan 2025

Swatting Flies: Biting Insects As Non-Invasive Samplers For Mammalian Population Genomics, Anubhab Khan, Ryan Carter, Chengetai D. Mpamhanga, Daniel Masiga, Manun Channumsin, Marc Ciosi, Oliva Manangwa, Furaha Mramba, Umer Zeeshan Ijaz, Harriet Auty, Barbara K. Mable

All Peer-Reviewed Publications

Advances in next-generation sequencing have allowed the use of DNA obtained from unusual sources for wildlife studies. However, these samples have been used predominantly to sequence mitochondrial DNA for species identification while population genetics analyses have been rare. Since next-generation sequencing allows indiscriminate detection of all DNA fragments in a sample, technically it should be possible to sequence whole genomes of animals from environmental samples. Here we used a blood-feeding insect, tsetse fly, to target whole genome sequences of wild animals. Using pools of flies, we compared the ability to recover genomic data from hosts using the short-read sequencing (Illumina) …

Go to article

Modelling The Impacts Of Recreational Catch-And-Release Variability On Fish Stock Dynamics, Brett Crisafulli Jan 2025

Modelling The Impacts Of Recreational Catch-And-Release Variability On Fish Stock Dynamics, Brett Crisafulli

Theses: Doctorates and Masters

Recreational fisheries often lack sufficient data for robust stock assessments, and post-release mortality (PRM) of discarded fish, particularly demersal species, poses a significant threat to sustainability. Because demersal fish often experience higher PRM (often due to barotrauma and stress), the substantial global interest in their recreational fisheries (e.g., Australia, Gulf of Mexico, Western Baltic Sea) raises conservation concerns. This study employs three distinct modelling approaches, applied to four reef-dwelling demersal species, to support effective recreational fisheries management by addressing data uncertainty, unintended consequences of management changes, and PRM effects. Specifically, this thesis (1) evaluates variability in average weights of recreationally-caught …

Go to article

Marrying Top-K With Skyline Queries: Operators With Relaxed Preference Input And Controllable Output Size, Kyriakos Mouratidis, Keming Li, Bo Tang Jan 2025

Marrying Top-K With Skyline Queries: Operators With Relaxed Preference Input And Controllable Output Size, Kyriakos Mouratidis, Keming Li, Bo Tang

Research Collection School Of Computing and Information Systems

The two most common paradigms to identify records of preference in a multi-objective setting rely either on dominance (e.g., the skyline operator) or on a utility function defined over the records' attributes (typically, using a top-k query). Despite their proliferation, each of them has its own palpable drawbacks. Motivated by these drawbacks, we identify three hard requirements for practical decision support, namely, personalization, controllable output size, and flexibility in preference specification. With these requirements as a guide, we combine elements from both paradigms and propose two new operators, ORD and ORU. We perform a qualitative study to demonstrate how they …

Go to article

Bi-Objective Dynamic Tugboat Scheduling With Speed Optimization Under Stochastic And Time-Varying Service Demands, Xiaoyang Wei, Hoong Chuin Lau, Zhe Xiao, Xiuju Fu, Xiaocai Zhang, Zheng Qin Jan 2025

Bi-Objective Dynamic Tugboat Scheduling With Speed Optimization Under Stochastic And Time-Varying Service Demands, Xiaoyang Wei, Hoong Chuin Lau, Zhe Xiao, Xiuju Fu, Xiaocai Zhang, Zheng Qin

Research Collection School Of Computing and Information Systems

With the growing emphasis on green shipping to reduce the environmental impact of maritime transportation, optimizing fuel consumption with maintaining high service quality has become critical in port operations. Ports are essential nodes in global supply chains, where tugboats play a pivotal role in the safe and efficient maneuvering of ships within constrained environments. However, existing literature lacks approaches that address tugboat scheduling under realistic operational conditions. To fill the research gap, this is the first work to propose the bi-objective dynamic tugboat scheduling problem that optimizes speed under stochastic and time-varying demands, aiming to minimize fuel consumption and manage …

Go to article

Measuring Model Alignment For Code Clone Detection Using Causal Interpretation, Shamsa Abid, Xuemeng Cai, Lingxiao Jiang Jan 2025

Measuring Model Alignment For Code Clone Detection Using Causal Interpretation, Shamsa Abid, Xuemeng Cai, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Deep Neural Network-based models have demonstrated high accuracy for semantic code clone detection. However, the lack of generalization poses a threat to the trustworthiness and reliability of these models. Furthermore, the black-box nature of these models makes interpreting the model’s decisions very challenging. Currently, there is only a limited understanding of the semantic code clone detection behavior of existing models. There is a lack of transparency in understanding how a model identifies semantic code clones and the exact code components influencing its prediction. In this paper, we introduce the use of a causal interpretation framework based on the Neyman-Rubin causal …

Go to article

Weakly-Supervised Semantic Segmentation With Image-Level Labels: From Traditional Models To Foundation Models, Zhaozheng Chen, Qianru Sun Jan 2025

Weakly-Supervised Semantic Segmentation With Image-Level Labels: From Traditional Models To Foundation Models, Zhaozheng Chen, Qianru Sun

Research Collection School Of Computing and Information Systems

The rapid development of deep learning has driven significant progress in image semantic segmentation—a fundamental task in computer vision. Semantic segmentation algorithms often depend on the availability of pixel-level labels (i.e., masks of objects), which are expensive, time consuming, and labor intensive. Weakly supervised semantic segmentation (WSSS) is an effective solution to avoid such labeling. It utilizes only partial or incomplete annotations and provides a cost-effective alternative to fully supervised semantic segmentation. In this article, our focus is on the WSSS with image-level labels, which is the most challenging form of WSSS. Our work has two parts. First, we conduct …

Go to article

Transforming Urban Dynamics: Harnessing Large Language Models For Smarter Mobility, Hao Xue, Ming Jin, Shirui Pan, Flora Salim, Guansong Pang Jan 2025

Transforming Urban Dynamics: Harnessing Large Language Models For Smarter Mobility, Hao Xue, Ming Jin, Shirui Pan, Flora Salim, Guansong Pang

Research Collection School Of Computing and Information Systems

Artificial intelligence (AI) has the potential to analyze mobility data and make mobility systems smarter by leveraging diverse data sources such as geospatial data, transportation logs, and real-time sensor data to optimize traffic flow, enhance public transportation systems, and support the development of autonomous vehicles. With the newly emerged generative AI paradigm, exemplified by large language models (LLMs), there is great potential to transform the current AI applications in mobility, transportation, and urban domains. This article provides an overview of recent efforts and aims to shed light on the challenges and future opportunities to facilitate the adaptation of LLMs for …

Go to article

Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh Jan 2025

Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

This chapter examines the difficult legal characterisation problems that artificially intelligent systems raise and explores how different characterisations of artificial intelligence (AI) shape practical legal outcomes. Three reasons are offered for the legal difficulty with characterising AI. First, answers to characterisation problems are inherently subjective and perspective-driven, particularly when the subject is an intangible technological system. Second, AI technology is especially difficult to define since the field typically proceeds on inexact anthropomorphic metaphors. Third, AI characterisation problems raise difficult sub-problems, particularly in determining how autonomous an AI system is. The chapter thus argues that a range of plausible AI characterisations …

Go to article

Attribute-Based Encryption With Searchable Encryption, Yang Yang Jan 2025

Attribute-Based Encryption With Searchable Encryption, Yang Yang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) with searchable encryption is a notion that inherits the advantages of both ABE (Goyal et al., 2006) and searchable encryption (SE) (Boneh et al., 2004; Boneh and Waters, 2007) mechanisms to realize secure share and search for the outsourced data. ABE creates fine-grained access control system to prevent sensitive data from being accessed by unauthorized user or external attacker (Bethencourt et al., 2007). SE generates encrypted index for outsourced data such that it can be searched by a keyword trapdoor (or token) (Shi et al., 2007; Naveed et al., 2014), where the outsourced content and search keyword(s) …

Go to article

Gnnsynergy: A Multi-View Graph Neural Network For Predicting Anti-Cancer Drug Synergy, Zhifeng Hao, Jianming Zhan, Yuan Fang, Min Wu, Ruichu Cai Jan 2025

Gnnsynergy: A Multi-View Graph Neural Network For Predicting Anti-Cancer Drug Synergy, Zhifeng Hao, Jianming Zhan, Yuan Fang, Min Wu, Ruichu Cai

Research Collection School Of Computing and Information Systems

Drug combinations play very important roles in cancer therapy, as they can enhance curative efficacy and overcome drug resistance. Due to the increasing size of combinatorial space, experimental screening for all the drug combinations becomes infeasible in practice. Therefore, there is a great need to develop accurate computational approaches that can predict potential drug combinations to direct the experimental screening. In this paper, we propose a novel method called GNNSynergy to learn drug embeddings for drug synergy prediction. Given a specific cancer cell line, we propose a multi-view graph neural network framework which considers the current cell line as main …

Go to article

An End-To-End Bi-Objective Approach To Deep Graph Partitioning, Pengcheng Wei, Yuan Fang, Zhihao Wen, Zheng Xiao, Binbin Chen Jan 2025

An End-To-End Bi-Objective Approach To Deep Graph Partitioning, Pengcheng Wei, Yuan Fang, Zhihao Wen, Zheng Xiao, Binbin Chen

Research Collection School Of Computing and Information Systems

Graphs are ubiquitous in real-world applications, such as computation graphs and social networks. Partitioning large graphs into smaller, balanced partitions is often essential, with the biobjective graph partitioning problem aiming to minimize both the“cut” across partitions and the imbalance in partition sizes. However, existing heuristic methods face scalability challenges or overlook partition balance, leading to suboptimal results. Recent deep learning approaches, while promising, typically focus only on node-level features and lack a truly end-to-end framework, resulting in limited performance. In this paper, we introduce a novel method based on graph neural networks (GNNs) that leverages multilevel graph features and addresses …

Go to article

Enhancing Electric Wheelchair Safety Via Battery State Of Charge Estimationwith Pcc–Nssr–Lstm Method, Chi Wing, Alex Tsang, Xiaoying Lu Jan 2025

Enhancing Electric Wheelchair Safety Via Battery State Of Charge Estimationwith Pcc–Nssr–Lstm Method, Chi Wing, Alex Tsang, Xiaoying Lu

Department of Construction, Environment and Engineering

This study explores a novel algorithm created to predict the state of charge (SOC) of batteries in electric wheelchairs (EWs) to improve EW safety by adjusting SOC thresholds and reducing consumer range anxiety. It involves collecting experimental data from lithium iron phosphate (LFP) battery cells over 1500 cycles at 25◦C, encompassing various parameters. With the Pearson correlation coefficient (PCC), a select set of key parameters including voltage, temperature, dQ/dV (capacity increase to voltage increase ratio) are chosen as inputs for non-linear state space reconstruction long short-term memory (NSSR-LSTM) neural networks, facilitating precise SOC predictions. The study showcases the precision of …

Go to article

The Effectiveness Of Local Updates For Decentralized Learning Under Data Heterogeneity, Tongle Wu, Zhize Li, Ying Sun Jan 2025

The Effectiveness Of Local Updates For Decentralized Learning Under Data Heterogeneity, Tongle Wu, Zhize Li, Ying Sun

Research Collection School Of Computing and Information Systems

We revisit two fundamental decentralized optimization methods, Decentralized Gradient Tracking (DGT) and Decentralized Gradient Descent (DGD), with multiple local updates. We consider two settings and demonstrate that incorporating local update steps can reduce communication complexity. Specifically, for  $\mu$-strongly convex and $L$-smooth loss functions, we proved that local DGT  achieves communication complexity {}{$\tilde{\mathcal{O}} \Big(\frac{L}{\mu(K+1)} + \frac{\delta + {}{\mu}}{\mu (1 - \rho)} + \frac{\rho }{(1 - \rho)^2} \cdot \frac{L+ \delta}{\mu}\Big)$}, where $K$ is the number of additional local update}, $\rho$ measures the network connectivity and $\delta$ measures the second-order heterogeneity of the local losses. Our results reveal the tradeoff between communication and …

Go to article

First Prev Next Last