Physical Sciences and Mathematics Commons^™

An Efficient Strategy For Deploying Deception Technology, Noora Abdulla Alhosani

Theses

Implementations of deception technology is crucial in discovering attacks by creating a controlled and monitored environment for detecting malicious activity. This technology involves the deployment of decoys, traps, and honeypots that mimic natural systems and network assets to attract and identify attackers. The use of deception technology provides an early warning system for detecting cyber-attacks, allowing organizations to respond quickly and mitigate damage. This article proposed a framework that focuses on maximizing the efficiency of deception technology in detecting sophisticated attacks. The framework employs multi-layered deception techniques at various levels of the network, system, and application to provide comprehensive coverage …

Cloud Tracking Winds On Mars Using Emm-Exi Imaging, Shaimaa Ahmed Alblooki

Theses

The Martian atmospheric wind structure is a major unknown in our understanding of Mars’ climate because it is difficult to measure wind remotely. The Emirates eXploration Imager (EXI) instrument on board the Emirates Mars Mission (EMM) takes visible and ultraviolet images of the whole hemisphere of the planet at a time, and can capture complete weather systems at once, along with their evolution over time. This project uses EXI 320 nm observations to measure winds on Mars using Correlation Imaging Velocimetry (CIV), a cloud tracking method based on software developed for laboratory fluid dynamics experiments, and with significant heritage in …

Fog Harvesting Using Chemically Functionalized Porous Membranes, Afra Saif Alhumaidi

Theses

This work explores the use of chemically functionalized porous membranes for fog harvesting. Fog water has emerged as a valuable alternative water source in regions where traditional freshwater resources are scarce. However, conventional fog harvesting techniques often suffer from low collection efficiency and limited scalability. To address these challenges, this research investigates the potential of chemically functionalized porous membranes for enhanced fog water collection. The study focuses on the development and characterization of specialized membranes with surface properties optimized for efficient fog droplet capture.
/="/">The current study proposes the use of aluminum mesh for fog collection, as it stands …

Using The Hirota Method To Investigate The Integrability And New Exact Solutions Of The Non-Autonomous Nonlinear Schrodinger Equation, Islam Majed Albazlamit

Theses

In this thesis research, we investigate the existence of Hirota bilinear systems for the non-autonomous nonlinear Schrodinger equation (NLSE) with position- and time-dependent coefficients and external potentials. To that end, we employ a semi-analytical systematic method that employs some exact solutions. The Hirota bilinear system is then employed to derive new solutions to the same nonlinear differential equation. We have applied this approach to a number of different versions of NLSEs to find that each family of solutions shares the same Hirota bilinear system. Furthermore, properties of solutions such as stability are investigated.

Fabrication, Characterization And Analytical Applications Of Planar Solid Metal And Planar Cavity Electrodes, Fatima Salmeen Alnuaimi

Theses

The present thesis describes the design, construction, and applications of a versatile flow cell (VFC) for used with different types of planar working electrodes. These included the commercially available planar 3-electrode screen-printed electrode chips (SPECs), custom planar metallic electrodes (PMEs), and cavity-type electrodes (CTEs). The PMEs are fabricated from platinum, titanium, stainless steel and copper rods inserted in a rectangular-PEEK housing, respectively. The dimensions of the PEEK blocks were 13.5 mm width x 39 mm length x 12.5 mm height. The VFC was constructed from a cell cover and base machined from acrylic sheets. The cover incorporated a built-in Ag/AgCl/Cl …

Preparation Of Copper Oxide Nano-Architectures For Fog Harvesting Applications, Ola M. Abu Draz

Theses

The issue of limited freshwater resources is a significant problem for humans, especially in desert areas where water scarcity poses a serious risk to human survival. In nature, there are several species that harvest fog based on their tuned surface structure, e.g.., Cactus, desert beetles, etc. In addition to surface hydrophilic/hydrophobic architecture, another key factor in effective water collection is the porosity of the surface, which helps droplets to form, grow, and be removed. To address the challenge of water scarcity, we inspired, from nature, to design surfaces that have features that favor water collection. In this aspect, we introduced …

Synthesis, Characterization, And Photocatalytic Activity Of Photoactive Mofs And M-Hof Under Simulated Visible Light Irradiation, Lamia Ali Siddig

Dissertations

The increasing global energy demand has resulted in environmental issues, leading to a shift in research towards sustainable and renewable energy sources. Among these, solar energy is the most abundant natural resource available. One of the most profitable ways to utilize sunlight is through chemical transformation using photocatalysts. In this regard, we reported the synthesis of different stable porous materials, such as metal-organic frameworks (MOFs) and metal hydrogen-bonded organic frameworks (M-HOFs). The MOF photocatalysts are bismuth-gallate (Bi-gallate), a mixed ligand manganese-based MOF (Mn^II₃(tp)_6/2(bpy)₂. (dmf)) and a new hexagonal layer manganese MOF compound named …

Unraveling The Origins Of Grb190114c: An Investigation Of Progenitor Models Through Observational Analysis, Nusrin Habeeb

Dissertations

Gamma-ray bursts (GRBs) are among the most energetic and violent events in the universe, characterized by sudden and intense emission of gamma rays lasting from a fraction of a second to several minutes. The primary focus of this thesis is to study gamma-ray bursts (GRBs), with a specific emphasis on GRB190114C. GRB190114C is a long-duration GRB that was detected on January 14, 2019, by the Fermi Gamma-ray Burst Monitor (GBM) and the Swift Burst Alert Telescope (BAT). It had a T₉₀ duration of 116 s and a redshift of z = 0.4245, which corresponds to a luminosity distance of …

Bismuth And Lanthanides In Mixed Metal Oxides To Metal– Organic Frameworks: Synthesis, Cherectarization, And Photocatalytic Performance, Reem H. Alzard

Dissertations

Known as rare–earth elements (REE), lanthanides (Ln) found in f–blocks of the periodic table, have gained much interest because of their unique characteristics including magnetism, photoluminescence and catalysis. Having a diverse range of coordination geometries, lanthanides can result in different complexes and materials. Herein, three classes of materials containing selected lanthanides such as lanthanide bismuth mixed metal oxides (Ln–Bi oxides), 1D lanthanide coordination polymers (Ln–CPs) and lanthanide metal–organic frameworks (Ln–MOFs) were investigated. Simple route sol– gel method was used to prepare Ln–Bi oxides while Ln–CPs and MOFs were prepared by solvothermal condition. The materials were characterized using multiple analytical, spectroscopic …

Digital Transformation In Local Governments: A Case Study Of Abu Dhabi Municipality Transport Department, Alia Sahmi Al Ahbabi

Theses

The new generation is rapidly adapting to the digital era, where government and private services are being transformed into electronic services, commonly known as Eservices. Cities are leveraging digitalization to streamline their business processes and business services. This digitalization has improved service delivery time and quality for individuals. With digitalization, business processes align with technology, enhancing performance and customer satisfaction. However, there are challenges associated with digitalization, particularly people working in various municipality departments who find it challenging to adapt to digitization. Employees may take time to adjust to the new techniques and technologies, which may hamper the actions of …

Invalidator: Automated Patch Correctness Assessment Via Semantic And Syntactic Reasoning, Tranh Le-Cong, Duc Minh Luong, Xuan Bach D. Le, David Lo, Nhat-Hoa Tran, Bui Quang-Huy, Quyet-Thang Huynh

Research Collection School Of Computing and Information Systems

Automated program repair (APR) has been gaining ground recently. However, a significant challenge that still remains is test overfitting, in which APR-generated patches plausibly pass the validation test suite but fail to generalize. A common practice to assess the correctness of APR-generated patches is to judge whether they are equivalent to ground truth, i.e., developer-written patches, by either generating additional test cases or employing human manual inspections. The former often requires the generation of at least one test that shows behavioral differences between the APR-patched and developer-patched programs. Searching for this test, however, can be difficult as the search space …

Lessons Learned From The Hospital To Home Community Care Program In Singapore And The Supporting Ai Multiple Readmissions Prediction Model, John Abisheganaden, Kheng Hock Lee, Lian Leng Low, Eugene Shum, Han Leong Goh, Christine Gia Lee Ang, Adny An Ta Wee, Steven M. Miller

Research Collection School Of Computing and Information Systems

In a prior practice and policy article published in Healthcare Science, we introduced the deployed application of an artificial intelligence (AI) model to predict longer-term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home (H2H) program that has been operating since 2017. In this follow on practice and policy article, we further elaborate on Singapore's H2H program and care model, and its supporting AI model for multiple readmission prediction, in the following ways: (1) by providing updates on the AI and supporting information systems, (2) by reporting on customer …

Tracing The Twenty-Year Evolution Of Developing Ai For Eye Screening In Singapore: A Master Chronology Of Sidrp, Selena+ And Eyris, Steven M. Miller

Research Collection School Of Computing and Information Systems

This working paper is entirely comprised of a timeline table that begins in 2002 and runs through mid-2023. Across these two decades, this timeline traces the evolutionary development of the following:

• The early Singapore R&D efforts to apply software-based image analysis algorithms and methods to analyse eye retina images for diabetic retinopathy and other eye diseases. This was based on a collaboration between the Singapore Eye Research Institute (SERI) and its parent organization, the Singapore National Eye Centre (SNEC), with faculty from the School of Computing at National University of Singapore.
• The establishment and operation of the Singapore Integrated Diabetic …

Mosaic: Spatially-Multiplexed Edge Ai Optimization Over Multiple Concurrent Video Sensing Streams, Ila Gokarn, Hemanth Sabbella, Yigong Hu, Tarek Abdelzaher, Archan Misra

Research Collection School Of Computing and Information Systems

Sustaining high fidelity and high throughput of perception tasks over vision sensor streams on edge devices remains a formidable challenge, especially given the continuing increase in image sizes (e.g., generated by 4K cameras) and complexity of DNN models. One promising approach involves criticality-aware processing, where the computation is directed selectively to "critical" portions of individual image frames. We introduce MOSAIC, a novel system for such criticality-aware concurrent processing of multiple vision sensing streams that provides a multiplicative increase in the achievable throughput with negligible loss in perception fidelity. MOSAIC determines critical regions from images received from multiple vision …

Catching The Fast Payments Trend: Optimal Designs And Leadership Strategies Of Retail Payment And Settlement Systems, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

Recent financial technologies have enabled fast payments and are reshaping retail payment and settlement systems globally. We developed an analytical model to study the optimal design of a new retail payment system in terms of settlement speed and system capability under both bank and fintech firm heterogeneous participation incentives. We found that three types of payment systems emerge as equilibrium outcomes: batch retail (BR), expedited retail (ER), and real-time retail (RR) payment systems. Although the base value of the payment service positively affects both settlement speed and system capability, the expected liquidity cost negatively impacts settlement speed, and total transaction …

Ldptrace: Locally Differentially Private Trajectory Synthesis, Yuntao Du, Yujia Hu, Zhikun Zhang, Ziquan Fang, Lu Chen, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Trajectory data has the potential to greatly benefit a wide-range of real-world applications, such as tracking the spread of the disease through people's movement patterns and providing personalized location-based services based on travel preference. However, privacy concerns and data protection regulations have limited the extent to which this data is shared and utilized. To overcome this challenge, local differential privacy provides a solution by allowing people to share a perturbed version of their data, ensuring privacy as only the data owners have access to the original information. Despite its potential, existing point-based perturbation mechanisms are not suitable for real-world scenarios …

How Does Credit Risk Affect Cost Management Strategies? Evidence On The Initiation Of Credit Default Swap And Sticky Cost Behavior, Jing Dai, Nan Hu, Rong Huang, Yan Yan

Research Collection School Of Computing and Information Systems

In this paper, we examine the effect of credit defaults swaps (CDS) initiation on reference firms' cost management strategies. CDS contracts provide insurance protection for creditors, inducing a shift in bargaining power from borrowers to creditors and an excessive incidence of bankruptcy. Anticipating more intransigent creditors in debt renegotiations and higher bankruptcy risk, CDS firms are incentivized to mitigate risk through decreasing cost stickiness after CDS initiation, as cost stickiness lowers liquidity and triggers early covenant violations. We find that, on average, CDS initiation is associated with a decline in reference firms' cost stickiness. This association is more pronounced for …

Glocal Energy-Based Learning For Few-Shot Open-Set Recognition, Haoyu Wang, Guansong Pang, Peng Wang, Lei Zhang, Wei Wei, Yanning Zhang

Research Collection School Of Computing and Information Systems

Few-shot open-set recognition (FSOR) is a challenging task of great practical value. It aims to categorize a sample to one of the pre-defined, closed-set classes illustrated by few examples while being able to reject the sample from unknown classes. In this work, we approach the FSOR task by proposing a novel energy-based hybrid model. The model is composed of two branches, where a classification branch learns a metric to classify a sample to one of closedset classes and the energy branch explicitly estimates the open-set probability. To achieve holistic detection of openset samples, our model leverages both class-wise and pixelwise …

Class-Incremental Exemplar Compression For Class-Incremental Learning, Zilin Luo, Yaoyao Liu, Bernt Schiele, Qianru Sun

Research Collection School Of Computing and Information Systems

Exemplar-based class-incremental learning (CIL) finetunes the model with all samples of new classes but few-shot exemplars of old classes in each incremental phase, where the "few-shot" abides by the limited memory budget. In this paper, we break this "few-shot" limit based on a simple yet surprisingly effective idea: compressing exemplars by downsampling non-discriminative pixels and saving "many-shot" compressed exemplars in the memory. Without needing any manual annotation, we achieve this compression by generating 0-1 masks on discriminative pixels from class activation maps (CAM). We propose an adaptive mask generation model called class-incremental masking (CIM) to explicitly resolve two difficulties of …

Extracting Class Activation Maps From Non-Discriminative Features As Well, Zhaozheng Chen, Qianru Sun

Research Collection School Of Computing and Information Systems

Extracting class activation maps (CAM) from a classification model often results in poor coverage on foreground objects, i.e., only the discriminative region (e.g., the “head” of “sheep”) is recognized and the rest (e.g., the “leg” of “sheep”) mistakenly as background. The crux behind is that the weight of the classifier (used to compute CAM) captures only the discriminative features of objects. We tackle this by introducing a new computation method for CAM that explicitly captures non-discriminative features as well, thereby expanding CAM to cover whole objects. Specifically, we omit the last pooling layer of the classification model, and perform clustering …

Freestyle Layout-To-Image Synthesis, Han Xue, Zhiwu Huang, Qianru Sun, Li Song, Wenjun Zhang

Research Collection School Of Computing and Information Systems

Typical layout-to-image synthesis (LIS) models generate images for a close set of semantic classes, e.g., 182 common objects in COCO-Stuff. In this work, we explore the freestyle capability of the model, i.e., how far can it generate unseen semantics (e.g., classes, attributes, and styles) onto a given layout, and call the task Freestyle LIS (FLIS). Thanks to the development of large-scale pre-trained language-image models, a number of discriminative models (e.g., image classification and object detection) trained on limited base classes are empowered with the ability of unseen class prediction. Inspired by this, we opt to leverage large-scale pre-trained text-to-image diffusion …

3d Dental Biometrics: Transformer-Based Dental Arch Extraction And Matching, Zhiyuan Zhang, Zhong Xin

Research Collection School Of Computing and Information Systems

The dental arch is a significant anatomical feature that is crucial in assessing tooth arrangement and configuration and has a potential for human identification in biometrics and digital forensic dentistry. In a previous study, we proposed an auto pose-invariant arch feature extraction Radial Ray Algorithm (RRA) and a matching framework [1] based solely on 3D dental geometry. To enhance the identification accuracy and speed of our previous work, we propose in this study a transformer architecture that can extract dental keypoints by encoding both local and global features. The dental arch is then constructed through robust interpolation of the dental …

Preference-Aware Delivery Planning For Last-Mile Logistics, Qian Shao, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

Optimizing delivery routes for last-mile logistics service is challenging and has attracted the attention of many researchers. These problems are usually modeled and solved as variants of vehicle routing problems (VRPs) with challenging real-world constraints (e.g., time windows, precedence). However, despite many decades of solid research on solving these VRP instances, we still see significant gaps between optimized routes and the routes that are actually preferred by the practitioners. Most of these gaps are due to the difference between what's being optimized, and what the practitioners actually care about, which is hard to be defined exactly in many instances. In …

A Mixed-Integer Linear Programming Reduction Of Disjoint Bilinear Programs Via Symbolic Variable Elimination, Jihwan Jeong, Scott Sanner, Akshat Kumar

Research Collection School Of Computing and Information Systems

A disjointly constrained bilinear program (DBLP) has various practical and industrial applications, e.g., in game theory, facility location, supply chain management, and multi-agent planning problems. Although earlier work has noted the equivalence of DBLP and mixed-integer linear programming (MILP) from an abstract theoretical perspective, a practical and exact closed-form reduction of a DBLP to a MILP has remained elusive. Such explicit reduction would allow us to leverage modern MILP solvers and techniques along with their solution optimality and anytime approximation guarantees. To this end, we provide the first constructive closed-form MILP reduction of a DBLP by extending the technique of …

Scanet: Self-Paced Semi-Curricular Attention Network For Non-Homogeneous Image Dehazing, Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu, Jingxiang Qu, Shengfeng He, Ren Wenqi

Research Collection School Of Computing and Information Systems

The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details. Existing homogeneous dehazing methods struggle to handle the non-uniform distribution of haze in a robust manner. The crucial challenge of non-homogeneous dehazing is to effectively extract the non-uniform distribution features and reconstruct the details of hazy areas with high quality. In this paper, we propose a novel self-paced semi-curricular attention network, called SCANet, for non-homogeneous image dehazing that focuses on enhancing haze-occluded regions. Our approach consists of an attention generator network and a scene re-construction network. We use the luminance …

How To Resuscitate A Sick Vm In The Cloud, Xuhua Ding

Research Collection School Of Computing and Information Systems

A guest virtual machine in a cloud platform may fall “sick” when its kernel encounters a fatal low-level bug or is subverted by an adversary. The VM owner is hence likely to lose her control over it due to a kernel hang or being denied of remote accesses. While the VM can be rebooted with the assistance from the cloud server, the owner not only faces service disruption but also is left with no opportunity to make an in-depth diagnosis and forensics on the spot, not to mention a live rectification. Currently, the cloud service provider has neither incentive nor …

Semantic Scene Completion With Cleaner Self, Fengyun Wang, Dong Zhang, Hanwang Zhang, Jinhui Tang, Qianru Sun

Research Collection School Of Computing and Information Systems

Semantic Scene Completion (SSC) transforms an image of single-view depth and/or RGB 2D pixels into 3D voxels, each of whose semantic labels are predicted. SSC is a well-known ill-posed problem as the prediction model has to “imagine” what is behind the visible surface, which is usually represented by Truncated Signed Distance Function (TSDF). Due to the sensory imperfection of the depth camera, most existing methods based on the noisy TSDF estimated from depth values suffer from 1) incomplete volumetric predictions and 2) confused semantic labels. To this end, we use the ground-truth 3D voxels to generate a perfect visible surface, …

Livoauth: Liveness Detection In Voiceprint Authentication With Random Challenges And Detection Modes, Rui Zhang, Zheng Yan, Xueru Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Voiceprint authentication provides great convenience to users in many application scenarios. However, it easily suffers from spoofing attacks including speech synthesis, speech conversion, and speech replay. Liveness detection is an effective way to resist these attacks. But existing methods suffer from many disadvantages, such as extra deployment costs due to precise data collection, environmental disturbance, high computational overhead, and operational complexity. A uniform platform that can offer voiceprint authentication as a service (VAaS) over the cloud is also lacked. Hence, it is imperative to design an economic and effective method for liveness detection in voiceprint authentication. In this article, we …

The Bemi Stardust: A Structured Ensemble Of Binarized Neural Networks, Ambrogio Maria Bernardelli, Stefano Gualandi, Hoong Chuin Lau, Simone Milanesi

Research Collection School Of Computing and Information Systems

Binarized Neural Networks (BNNs) are receiving increasing attention due to their lightweight architecture and ability to run on low-power devices, given the fact that they can be implemented using Boolean operations. The state-of-the-art for training classification BNNs restricted to few-shot learning is based on a Mixed Integer Programming (MIP) approach. This paper proposes the BeMi ensemble, a structured architecture of classification-designed BNNs based on training a single BNN for each possible pair of classes and applying a majority voting scheme to predict the final output. The training of a single BNN discriminating between two classes is achieved by a MIP …

Imitating Opponent To Win: Adversarial Policy Imitation Learning In Two-Player Competitive Games, The Viet Bui, Tien Mai, Thanh H. Nguyen

Research Collection School Of Computing and Information Systems

Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim agent) to perform poorly in a multi-agent environment. In existing studies, adversarial policies are directly trained based on experiences of interacting with the victim agent. There is a key shortcoming of this approach --- knowledge derived from historical interactions may not be properly generalized to unexplored policy regions of the victim agent, making the trained adversarial policy significantly less effective. In this work, we design a new effective adversarial policy learning algorithm that overcomes …