Physical Sciences and Mathematics Commons^™

The 4th International Workshop On Talent And Management Computing (Tmc'2023): Editorial, Hengshu Zhu, Hui Xiong, Yong Ge, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In today's competitive and fast-evolving business environment, it is a critical time for organizations to rethink how to deal with the talent and management related tasks in a quantitative manner. Indeed, thanks to the era of big data, the availability of large-scale talent data provides unparalleled opportunities for business leaders to understand the rules of talent and management, which in turn deliver intelligence for effective decision making and management for their organizations. In the past few years, talent and management computing have increasingly attracted attentions from KDD communities, and a number of research/applied data science efforts have been devoted. To …

Extraction, Purification, And Characterization Of Potential Bioactive Compounds Produced By Janthinobacterium Lividum Tajx1901, Andy Elorm Agbakpo

Electronic Theses and Dissertations

Underexplored environments such as soil samples continue to be an untapped source of bacterial strains with great potential to produce secondary metabolites for medicinal applications. As a result, these microorganisms represent a broad and yet unknown reservoir of new strains capable of producing these novel compounds. The current research primarily seeks to perform the isolation, purification, and characterization of secondary metabolites from a soil bacterium (Janthinobacterium lividum TAJX1901). The isolated soil bacterium was successfully cultured on rich media agar plates, followed by extraction using methanol and chloroform. The purification methods utilized include flash column chromatography, preparative thin-layer chromatography, and …

The Analysis Of Extended Producer Responsibility (Epr) For E-Waste Management Policy Drivers And Challenges In Singapore, Aldy Gunawan, Tasaporn Visawameteekul, Aidan Marc Wong, Linh Chi Tran

Research Collection School Of Computing and Information Systems

This paper examines Singapore’s Extended Producer Responsibility (EPR) scheme for managing e-waste, focusing on policy drivers, challenges, and young consumers’ attitudes through an online survey. Using the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB), it models the relationships between awareness, norms, and perceived convenience. Findings emphasize the need for tailored policies, formal recycling promotion, and analysis of disposal factors, cost preferences, and incentives. Text analysis also highlights concerns from respondents’ recommendations.

Deep Weakly-Supervised Anomaly Detection, Guansong Pang, Chunhua Shen, Huidong Jin, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Recent semi-supervised anomaly detection methods that are trained using small labeled anomaly examples and large unlabeled data (mostly normal data) have shown largely improved performance over unsupervised methods. However, these methods often focus on fitting abnormalities illustrated by the given anomaly examples only (i.e., seen anomalies), and consequently they fail to generalize to those that are not, i.e., new types/classes of anomaly unseen during training. To detect both seen and unseen anomalies, we introduce a novel deep weakly-supervised approach, namely Pairwise Relation prediction Network (PReNet), that learns pairwise relation features and anomaly scores by predicting the relation of any two …

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 …

Single-View View Synthesis With Self-Rectified Pseudo-Stereo, Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view view synthesis problem to a multi-view setting. Specifically, we leverage the reliable and explicit stereo prior to generate a pseudo-stereo viewpoint, which serves as an auxiliary input to construct the 3D space. In this way, the challenging novel view synthesis process is decoupled into two simpler problems of stereo synthesis and 3D reconstruction. In order to synthesize a structurally correct and detail-preserved stereo image, we propose a self-rectified stereo synthesis to amend erroneous …

Balancing Utility And Fairness In Submodular Maximization, Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang

Research Collection School Of Computing and Information Systems

Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications – including data summarization, influence maximization, and recommendation. In many of these problems, the goal is to find a solution that maximizes the average utility over all users, for each of whom the utility is defined by a monotone submodular function. However, when the population of users is composed of several demographic groups, another critical problem is whether the utility is fairly distributed across different groups. Although the utility and fairness objectives are both desirable, they might contradict each other, and, to the best of our knowledge, …

Ai For Connectivism Learning: Undergraduate Students’ Experiences Of Chatgpt In Advanced Programming Courses, Swapna Gottipati, Kyong Jin Shim, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Advanced programming skills are required for computing courses on merging topics, and students often struggle to develop these skills to solve complex problems. To address this challenge, faculty members provide additional lectures, practice sessions, and educational technology tools. This paper discusses the challenges faced by computer science students in developing advanced programming skills and explores the use of AI chatbots, specifically ChatGPT, as a support tool for learning. We study the engagement and effectiveness of ChatGPT in helping students learn advanced programming skills using two engagement learning frameworks (CIE and MELT) for evaluation. The study involves designing a computing lab …

Multi-Granularity Detector For Vulnerability Fixes, Truong Giang Nguyen, Cong, Thanh Le, Hong Jin Kang, Ratnadira Widyasari, Chengran Yang, Zhipeng Zhao, Bowen Xu, Jiayuan Zhou, Xin Xia, Ahmed E. Hassan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulnerability-fixing commits. Prior works have proposed methods that can automatically identify such vulnerability-fixing commits. However, identifying such commits is highly challenging, as only a very small minority of commits are vulnerability fixing. Moreover, code changes can be noisy and difficult to analyze. We observe that noise can occur at different levels of detail, making it challenging to detect vulnerability fixes accurately. To address these challenges and …

Lean Manufacturing Approach To Increase Packaging Efficiency, Lina Gozali, Irsandy Kurniawan, Aldo Salim, Iveline Anne Marie, Benny Tjahjono, Yun Chia Liang, Aldy Gunawan, Nnovia Hardjo Sie, Yuliani Suseno

Research Collection School Of Computing and Information Systems

The company upon which this paper is based engages in flexible packaging production, especially pharmaceutical products with guaranteed quality, trusted by consumers. Its production process includes printing, laminating, and assembling processes. Production activities are done manually and automatically using machines, so various types of waste are often found in these processes, making the level of plant efficiency nonoptimal. This study aims to identify wastes occurring in the production process, especially the production of pollycelonium with three colour variants as the highest demand product, by applying lean manufacturing concepts. The Current Value Stream Mapping (CVSM) used to map the production process …

Knowledge Representation For Conceptual, Motivational, And Affective Processes In Natural Language Communication, Seng Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria

Research Collection School Of Computing and Information Systems

Natural language communication is an intricate and complex process. The speaker usually begins with an intention and motivation of what is to be communicated, and what outcomes are expected from the communication, while taking into consideration the listener’s mental model to concoct an appropriate sentence. Likewise, the listener has to interpret the speaker’s message, and respond accordingly, also with the speaker’s mental model in mind. Doing this successfully entails the appropriate representation of the conceptual, motivational, and affective processes that underlie language generation and understanding. Whereas big-data approaches in language processing (such as chatbots and machine translation) have performed well, …

Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An

Research Collection School Of Computing and Information Systems

Quantitative stock investment is a fundamental financial task that highly relies on accurate prediction of market status and profitable investment decision making. Despite recent advances in deep learning (DL) have shown stellar performance on capturing trading opportunities in the stochastic stock market, the performance of existing DL methods is unstable with sensitivity to network initialization and hyperparameter selection. One major limitation of existing works is that investment decisions are made based on one individual neural network predictor with high uncertainty, which is inconsistent with the workflow in real-world trading firms. To tackle this limitation, we propose AlphaMix, a novel three-stage …

A Survey On Proactive Dialogue Systems: Problems, Methods, And Prospects, Yang Deng, Wenqiang Lei, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side. It is empowered by advanced techniques to progress to more complicated tasks that require strategical and motivational interactions. In this survey, we provide a comprehensive overview of the prominent problems and advanced designs for conversational agent's proactivity in different types of dialogues. Furthermore, we discuss challenges that meet the real-world application needs but require a greater research focus in the future. We hope that …

Corporate Trade War Uncertainty And Patent Bubble, Xu Yang, Nan Hu, Peng Liang

Research Collection School Of Computing and Information Systems

This paper draws upon resource dependence theory and investigates how trade policy uncertainty affects firm strategic innovation management in China. Adopting a machine learning approach called Word2Vec from computational linguistics, we construct and validate a measure of firm-level managers’ perceived trade war uncertainty (TWU). We find that TWU has a positive effect on the number of total patent applications, but this positive effect is totally driven by low-quality patents instead of high-quality patents. Moreover, we document that firms have stronger incentives for such strategic innovation behavior when the underlying firms are more financially constrained, and/or when the management is more …

Generative Artificial Intelligence And Metaverse: Future Of Work, Future Of Society, And Future Of Humanity, Yuxin Liu, Keng Siau

Research Collection School Of Computing and Information Systems

The rapid development of Generative Artificial Intelligence (GenAI) and the emergence of the Metaverse are dynamically reshaping our lives and societies. GenAI can enhance the development of Metaverse and empower the applications in Metaverse. Metaverse is also an excellent environment for GenAI to demonstrate its power and usefulness. This interwoven relationship fuels the potential of integrating GenAI and Metaverse. The paper discusses the integration potential of GenAI and Metaverse from four aspects. We further investigate how GenAI, Metaverse, and the integration of GenAI and Metaverse can reshape our future across the realms of work, society, and humanity. This paper offers …

Using Ai And Chatgpt In Brand Storytelling, Runyu Wang, Keng Siau, Zili Zhang

Research Collection School Of Computing and Information Systems

AI Chatbots, like ChatGPT, have attracted widespread attention for their powerful natural languageprocessing capabilities. Artificial intelligence (AI) chatbots, such as Auto-GPT and ChatGPT, canhelpcompanies create brand stories and communicate with stakeholders to enhance corporate communicationand brand equity. In this extended abstract, we discuss our plan to generate brand messages withvaryinglanguage formality and investigate the effect of informed communicators (i.e., human and AI chatbots) and the language formality of brand stories on individuals' attitudes to the brand and examine the roleof psychological distance. Our findings are expected to contribute to the theoretical fundamentals of usingchatbots like ChatGPT in brand storytelling.

Flood: A Flexible Invariant Learning Framework For Out-Of-Distribution Generalization On Graphs, Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat‑Seng Chua, Qing He

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have achieved remarkable success in various domains but most of them are developed under the in-distribution assumption. Under out-of-distribution (OOD) settings, they suffer from the distribution shift between the training set and the test set and may not generalize well to the test distribution. Several methods have tried the invariance principle to improve the generalization of GNNs in OOD settings. However, in previous solutions, the graph encoder is immutable after the invariant learning and cannot be adapted to the target distribution flexibly. Confronting the distribution shift, a flexible encoder with refinement to the target distribution can …

Diffusion Variational Autoencoder For Tackling Stochasticity In Multi-Step Regression Stock Price Prediction, Kelvin J.L. Koa, Yunshan Ma, Ritchie Ng, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Multi-step stock price prediction over a long-term horizon is crucial for forecasting its volatility, allowing financial institutions to price and hedge derivatives, and banks to quantify the risk in their trading books. Additionally, most financial regulators also require a liquidity horizon of several days for institutional investors to exit their risky assets, in order to not materially affect market prices. However, the task of multi-step stock price prediction is challenging, given the highly stochastic nature of stock data. Current solutions to tackle this problem are mostly designed for single-step, classification-based predictions, and are limited to low representation expressiveness. The problem …

Epbc 2010/5491: Weaber Plain Development Project Compliance Report - 1st May 2022 To 30th April 2023, Department Of Primary Industries And Regional Development, Western Australia

Irrigated Agricultural Development in the North

The Weaber Plain Development Project (Goomig Project) was approved on 13 September 2011. The approval reference is EPBC 2010/5491 (the Approval).

The Goomig Project comprises irrigated farmland, associated infrastructure, and a buffer area on the Weaber Plain located about 30km north-northeast of Kununurra in Western Australia. Figure 1 shows the location and layout of the Goomig Project and interface with other projects including the Knox Creek Plain Irrigation Development (EPBC 2014/7143), Sorby Hills Silver Lead Zinc mining project, and Ord River Irrigation Area (ORIA) Stage 1 'Cave Springs' farms.

The Department of Primary Industries and Regional Development is the Goomig …

Two Low-Complexity Efficient Beamformers For An Irs- And Uav-Aided Directional Modulation Network, Yeqing Lin, Feng Shu, Yuxiang Zheng, Jing Liu, Rongen Dong, Xun Chen, Yue Wu, Shihao Yan, Jiangzhou Wang

Research outputs 2022 to 2026

As excellent tools for aiding communication, an intelligent reflecting surface (IRS) and an unmanned aerial vehicle (UAV) can extend the coverage area, remove the blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance of directional modulation (DM) networks using an IRS and UAV in combination. To fully explore the benefits of the IRS and UAV, two efficient methods are proposed to enhance the SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS …

Bayesian Optimization With Switching Cost: Regret Analysis And Lookahead Variants, Peng Liu, Haowei Wang, Wei Qiyu

Research Collection Lee Kong Chian School Of Business

Bayesian Optimization (BO) has recently received increasing attention due to its efficiency in optimizing expensive-to-evaluate functions. For some practical problems, it is essential to consider the path-dependent switching cost between consecutive sampling locations given a total traveling budget. For example, when using a drone to locate cracks in a building wall or search for lost survivors in the wild, the search path needs to be efficiently planned given the limited battery power of the drone. Tackling such problems requires a careful cost-benefit analysis of candidate locations and balancing exploration and exploitation. In this work, we formulate such a problem as …

Ultrasonic Study Of Water Adsorbed In Nanoporous Glasses, Jason Ogbebor, John J. Valenza, Peter I. Ravikovitch, Ashoka Karunarathne, Giovanni Muraro, Maxim Lebedev, Boris Gurevich, Alexei F. Khalizov, Gennady Y. Gor

Research outputs 2022 to 2026

Thermodynamic properties of fluids confined in nanopores differ from those observed in the bulk. To investigate the effect of nanoconfinement on water compressibility, we perform water sorption experiments on two nanoporous glass samples while concomitantly measuring the speed of longitudinal and shear ultrasonic waves in these samples. These measurements yield the longitudinal and shear moduli of the water-laden nanoporous glass as a function of relative humidity that we utilize in the Gassmann theory to infer the bulk modulus of the confined water. This analysis shows that the bulk modulus (inverse of compressibility) of confined water is noticeably higher than that …

People's Preferences And Perceptions Toward Low-Input Versus Conventional Park Design Approaches Using 3d Images And Interview-Based Questionnaires, Fatemeh Kazemi, Nazanin Hosseinpour, Mahsa Ebrahimian

Research outputs 2022 to 2026

Future urban planning and public satisfaction will be significantly impacted by understanding people's preferences and perceptions of urban landscape design scenarios, particularly innovative sustainable development approaches. This study examined residents' preferences in Mashhad, Iran, for low-input park design versus conventional park design techniques. The research method integrated questionnaire-based interviews with 3D-simulated images of a site designed with the two approaches. Ninety-three respondents answered validated questions regarding their preference towards the planting and architecture of the parks, their perceptions about social sustainability, psychological feelings, and their perceptions of low-input and maintenance of the spaces. T-test analyses showed that people preferred the …

Open Data From The Third Observing Run Of Ligo, Virgo, Kagra, And Geo, R. Abbott, H. Abe, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series …

Fem Simulations Of Plasmon Field Enhancement In Gold Nanoparticle Dimers And Gold Nanoparticle-Nanorod Dimers, Edward J. Lipchus

Graduate Masters Theses

Plasmon resonance refers to the collective oscillation of free electrons in a nanomaterial in response to an incident electromagnetic field. When two plasmonic nanoparticles are placed close together, their localized surface plasmon resonances can couple and interact. The resulting plasmonic coupling leads to the formation of new plasmonic modes in the dimer system, significantly enhancing the electromagnetic fields in the vicinity of the nanoparticles, with various interesting and potentially useful applications. This thesis investigates the optical field enhancement arising from gold nanoparticle dimers in an aqueous dielectric medium, using the Finite Element Method simulation software COMSOL Multiphysics. The simulations provide …

Addressing Health Crises Through Courts? Climate Litigation In Latin America, The Right To Health And Vulnerable Populations, Thalia Viveros Uehara

Graduate Doctoral Dissertations

As Latin America faces increasing climate-related health crises that disproportionately affect populations experiencing poverty and social exclusion, it becomes increasingly urgent to realize the most vulnerable's right to health. While the region's new constitutionalism (NLAC) has made progress in protecting this right, it has only recently begun to intersect with climate change law through rights-based climate litigation. This dissertation takes a transdisciplinary multi-methods research approach to answer the following question: How do health crises emerge within, and how are they addressed by courts through, domestic climate litigation in Latin America? Specifically, it examines how health concerns for vulnerable populations are …

Dataset Of Optical And Electronic Properties For Mos2-Graphene Vertical Heterostructures And Mos2-Graphene-Au Heterointerfaces, Sanju Gupta, Panagiota Pimenidou, Miguel Garcia, Shivanshi Das, Nicholas Dimakis

Physics & Astronomy Faculty Publications

The computational and experimental data presented in this paper refer to the research article "First-Principles Calculations Integrated with Experimental Optical and Electronic Properties for MoS2-graphene Heterostructures and MoS2-graphene-Au Heterointerfaces". The computational data includes structural information, electronic and optical properties, and data to calculate the work functions for various molybdenum disulfide and graphene heterostructures and their heterointerfaces with gold. The optical properties calculations include the frequency-dependent dielectric function, the refractive index, the reflectivity, the extinction coefficient, and the energy loss function. These properties were calculated using the independent particle approximation (IPA). As for the experimental optoelectronic properties, we measured photoluminescence spectra …

Spectral Broadening Effects On Pulsed-Source Digital Holography, Steven A. Owens, Mark F. Spencer, Glen P. Perram

Faculty Publications

Using a pulsed configuration, a digital-holographic system is setup in the off-axis image plane recording geometry, and spectral broadening via pseudo-random bit sequence is used to degrade the temporal coherence of the master-oscillator laser. The associated effects on the signal-to-noise ratio are then measured in terms of the ambiguity and coherence efficiencies. It is found that the ambiguity efficiency, which is a function of signal-reference pulse overlap, is not affected by the effects of spectral broadening. The coherence efficiency, on the other hand, is affected. As a result, the coherence efficiency, which is a function of effective fringe visibility, is …

Exploring And Testing Wildfire Risk Decision-Making In The Face Of Deep Uncertainty, Bart R. Johnson, Alan A. Ager, Cody Evers, David Hulse, Max Nielsen-Pincus, John P. Bolte

Environmental Science and Management Faculty Publications and Presentations

We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire. Our goal was to develop an adaptable simulation platform for anticipating risk-mitigation tradeoffs in a fire-prone wildland– urban interface (WUI) facing conditions outside the bounds of experience. We describe how five social and ecological system (SES) submodels interact over time and space to generate highly variable alternative futures even within the same scenario as stochastic elements in simulated wildfire, succession, and landowner decisions create large sets of unique, path-dependent futures for …

Portuguese Society Of Pastures And Forages, J. Potes, E. V. Lourenço, T. Carita

IGC Proceedings (1977-2023)

The Portuguese Society of Pastures and Forages (SPPF) was born from a course on pastures and forages held in the National Plant Breeding Station of Elvas (where the headquarters of SPPF are located) in 1979. It was organised by the head of the Pastures and Forages Department, David Gomes Crespo, who was the first and founder member. According to Abreu et al. (1999), the structure established was that of a Scientific Society and was considered by the Government as a Service of Public Interest. It gathered inspiration from the British Grassland Society, the Association Francaise pour la Production Fourragére, …