Physical Sciences and Mathematics Commons^™

Exploring And Evaluating Attributes, Values, And Structures For Entity Alignment, Zhiyuan Liu, Yixin Cao, Liangming Pan, Juanzi Li, Zhiyuan Liu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of rich content by linking the equivalent entities from various KGs. GNN-based EA methods present promising performance by modeling the KG structure defined by relation triples. However, attribute triples can also provide crucial alignment signal but have not been well explored yet. In this paper, we propose to utilize an attributed value encoder and partition the KG into subgraphs to model the various types of attribute triples efficiently. Besides, the performances of current EA methods are overestimated because of the name-bias of existing EA datasets. To make an objective …

Security Analysis Of Permission Re-Delegation Vulnerabilities In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

The Android platform facilitates reuse of app func- tionalities by allowing an app to request an action from another app through inter-process communication mechanism. This fea- ture is one of the reasons for the popularity of Android, but it also poses security risks to end users because malicious, unprivileged apps could exploit this feature to make privileged apps perform privileged actions on behalf of them.

In our journal paper [4], we investigate the hybrid use of program analysis, genetic algorithm based test generation, natu- ral language processing, machine learning techniques for precise detection of permission re-delegation vulnerabilities in Android apps. …

Semi-Analytical Model For Design And Analysis Of On-Orbit Servicing Architecture, Koki Ho, Hai Wang, Paul A. De Trempe, Tristan Sarton Du Jonchay, Kento Tomita

Research Collection School Of Computing and Information Systems

Robotic on-orbit servicing (OOS) is expected to be a key technology and concept for future sustainable space exploration. This paper develops a novel semi-analytical model for OOS system analysis, responding to the growing needs and ongoing trend of robotic OOS. An OOS infrastructure system is considered whose goal is to provide responsive services to the random failures of a set of customer modular satellites distributed in space (e.g., at the geosynchronous orbit). The considered OOS architecture comprises a servicer that travels and provides module-replacement services to the customer satellites, an on-orbit depot to store the spares, and a series of …

A Geospatial Analytics Approach To Delineate Trade Areas For Quick Service Restaurants (Qsr) In Singapore, Hui Ting Lim

Research Collection School Of Computing and Information Systems

According to Huff, trade area is defined as “a geographically delineated region containing potential customers for whom there exists a probability greater than zero of their purchasing a given class of products or services offered for sale by a particular firm or by a particular agglomeration of firms”. Several methods to delineate a store trade area have been proposed over the years. For drive-time or travel distance analysis method, the trade area is delineated according to how far or how long the customers are willing to travel to patronise the store. Another commonly used method is the Huff Model which …

Boosting Privately: Federated Extreme Gradient Boosting For Mobile Crowdsensing, Yang Liu, Zhuo Ma, Ximeng Liu, Siqi Ma, Surya Nepal, Robert H. Deng, Kui Ren

Research Collection School Of Computing and Information Systems

Recently, Google and other 24 institutions proposed a series of open challenges towards federated learning (FL), which include application expansion and homomorphic encryption (HE). The former aims to expand the applicable machine learning models of FL. The latter focuses on who holds the secret key when applying HE to FL. For the naive HE scheme, the server is set to master the secret key. Such a setting causes a serious problem that if the server does not conduct aggregation before decryption, a chance is left for the server to access the user’s update. Inspired by the two challenges, we propose …

An Empirical Study Of Release Note Production And Usage In Practice, Tingting Bi, Xin Xia, David Lo, John Grundy, Thomas Zimmermann

Research Collection School Of Computing and Information Systems

The release note is one of the most important software artifacts that serves as a bridge for communication among stakeholders. Release notes contain a set of crucial information, such as descriptions of enhancements, improvements, potential issues, development, evolution, testing, and maintenance of projects throughout the whole development lifestyle. A comprehensive understanding of what makes a good release note and how to write one for different stakeholders would be highly beneficial. However, in practice, the release note is often neglected by stakeholders and has not to date been systematically investigated by researchers. In this paper, we conduct a mixed methods study …

Using Data Analytics To Predict Students Score, Nang Laik Ma, Gim Hong Chua

Research Collection School Of Computing and Information Systems

Education is very important to Singapore, and the government has continued to invest heavily in our education system to become one of the world-class systems today. A strong foundation of Science, Technology, Engineering, and Mathematics (STEM) was what underpinned Singapore's development over the past 50 years. PISA is a triennial international survey that evaluates education systems worldwide by testing the skills and knowledge of 15-year-old students who are nearing the end of compulsory education. In this paper, the authors used the PISA data from 2012 and 2015 and developed machine learning techniques to predictive the students' scores and understand the …

A Secure Flexible And Tampering-Resistant Data Sharing System For Vehicular Social Networks, Jianfei Sun, Hu Xiong, Shufan Zhang, Ximeng Liu, Jiaming Yuan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Vehicular social networks (VSNs) have emerged as the promising paradigm of vehicular networks that can improve traffic safety, relieve traffic congestion and even provide comprehensive social services by sharing vehicular sensory data. To selectively share the sensory data with other vehicles in the vicinity and reduce the local storage burden of vehicles, the vehicular sensory data are usually outsourced to vehicle cloud server for sharing and searching. However, existing data sharing systems for VSNs can neither provide secure selective one-to-many data sharing and verifiable data retrieval over encrypted data nor ensure that the integrity of retrieved data. In this paper, …

Capitalising Product Associations In A Supermarket Retail Environment, Michelle L. F. Cheong, Yong Qing Chia

Research Collection School Of Computing and Information Systems

This paper explores methods to capitalise on retail companies’ transactional databases, to mine meaningful product associations, and to design product placement strategies as a means to drive sales. We implemented three in-store initiatives based on our hypotheses – placing products with high associations together will induce an increase in sales of consequent; introducing an antecedent that is new to store will bring about a similar impact on sales of consequent based on established product association rules uncovered from other stores. Sales tracking over twelve weeks revealed that there were improvements in sales of consequents across all three initiatives performed in-store.

Jito: A Tool For Just-In-Time Defect Identification And Localization, Fangcheng Qiu, Meng Yan, Xin Xia, Xinyu Wang, Yuanrui Fan, Ahmed E. Hassan, David Lo

Research Collection School Of Computing and Information Systems

In software development and maintenance, defect localization is necessary for software quality assurance. Current defect localization techniques mainly rely on defect symptoms (e.g., bug reports or program spectrum) when the defect has been exposed. One challenge task is: can we locate buggy program prior to the appearance of the defect symptom. Such kind of localization is conducted at an early stage (e.g., when buggy program elements are being checkedin) which can be an early step of continuous quality control.In this paper, we propose a Just-In-Time defect identification and lOcalization tool, named JITO, which can help developers to locate defective lines …

Cross-Thought For Sentence Encoder Pre-Training, Shuohang Wang, Yuwei Fang, Siqi Sun, Zhe Gan, Yu Cheng, Jingjing Liu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we propose Cross-Thought, a novel approach to pre-training sequence encoder, which is instrumental in building reusable sequence embeddings for large-scale NLP tasks such as question answering. Instead of using the original signals of full sentences, we train a Transformer-based sequence encoder over a large set of short sequences, which allows the model to automatically select the most useful information for predicting masked words. Experiments on question answering and textual entailment tasks demonstrate that our pre-trained encoder can outperform state-of-the-art encoders trained with continuous sentence signals as well as traditional masked language modeling baselines. Our proposed approach also …

Effort-Aware Just-In-Time Defect Identification In Practice: A Case Study At Alibaba, Meng Yan, Xin Xia, Yuanrui Fan, David Lo, Ahmed E. Hassan, Xindong Zhang

Research Collection School Of Computing and Information Systems

Effort-aware Just-in-Time (JIT) defect identification aims at identifying defect-introducing changes just-in-time with limited code inspection effort. Such identification has two benefits compared with traditional module-level defect identification, i.e., identifying defects in a more cost-effective and efficient manner. Recently, researchers have proposed various effort-aware JIT defect identification approaches, including supervised (e.g., CBS+, OneWay) and unsupervised approaches (e.g., LT and Code Churn). The comparison of the effectiveness between such supervised and unsupervised approaches has attracted a large amount of research interest. However, the effectiveness of the recently proposed approaches and the comparison among them have never been investigated in an industrial setting.In …

Leveraging Profanity For Insincere Content Detection: A Neural Network Approach, Swapna Gottipati, Annabel Tan, David Jing Shan Chow, Joel Wee Kiat Lim

Research Collection School Of Computing and Information Systems

Community driven social media sites are rich sources of knowledge and entertainment and at the same vulnerable to the flames or toxic content that can be dangerous to various users of these platforms as well as to the society. Therefore, it is crucial to identify and remove such content to have a better and safe online experience. Manually eliminating flames is tedious and hence many research works focus on machine learning or deep learning models for automated methods. In this paper, we primarily focus on detecting the insincere content using neural network-based learning methods. We also integrated the profanity features …

A Theory Of The Engagement In Open Source Projects Via Summer Of Code Programs, Jefferson Silva, Igor Wiese, Daniel M. German, Christoph Treude, Marco A. Gerosa, Igor Steinmacher

Research Collection School Of Computing and Information Systems

Summer of code programs connect students to open source software (OSS) projects, typically during the summer break from school. Analyzing consolidated summer of code programs can reveal how college students, who these programs usually target, can be motivated to participate in OSS, and what onboarding strategies OSS communities adopt to receive these students. In this paper, we study the well-established Google Summer of Code (GSoC) and devise an integrated engagement theory grounded in multiple data sources to explain motivation and onboarding in this context. Our analysis shows that OSS communities employ several strategies for planning and executing student participation, socially …

Answerfact: Fact Checking In Product Question Answering, Wenxuan Zhang, Yang Deng, Jing Ma, Wai Lam

Research Collection School Of Computing and Information Systems

Product-related question answering platforms nowadays are widely employed in many E-commerce sites, providing a convenient way for potential customers to address their concerns during online shopping. However, the misinformation in the answers on those platforms poses unprecedented challenges for users to obtain reliable and truthful product information, which may even cause a commercial loss in E-commerce business. To tackle this issue, we investigate to predict the veracity of answers in this paper and introduce AnswerFact, a large scale fact checking dataset from product question answering forums. Each answer is accompanied by its veracity label and associated evidence sentences, providing a …

An Integrated Assessment Of The Global Virtual Water Trade Network Of Energy, Rebecca A. M. Peer, Christopher M. Chini

Faculty Publications

The global trade of energy allows for the distribution of the world's collective energy resources and, therefore, an increase in energy access. However, this network of trade also generates a network of virtually traded resources that have been used to produce energy commodities. An integrated database of energy trade water footprints is necessary to capture interrelated energy and water concerns of a globalized economy,and is also motivated by current climate and population trends. Here, we quantify and present the virtual water embedded in energy trade across the globe from 2012 to 2018, building on previous water footprinting and energy virtual …

Stochastic Delay Differential Equations With Applications In Ecology And Epidemics, Hebatallah Jamil Alsakaji

Dissertations

Mathematical modeling with delay differential equations (DDEs) is widely used for analysis and predictions in various areas of life sciences, such as population dynamics, epidemiology, immunology, physiology, and neural networks. The memory or time-delays, in these models, are related to the duration of certain hidden processes like the stages of the life cycle, the time between infection of a cell and the production of new viruses, the duration of the infectious period, the immune period, and so on. In ordinary differential equations (ODEs), the unknown state and its derivatives are evaluated at the same time instant. In DDEs, however, the …

Efficient Filters For Geometric Intersection Computations Using Gpu, Yiming Liu, Satish Puri

Computer Science Faculty Research and Publications

Geometric intersection algorithms are fundamental in spatial analysis in Geographic Information System (GIS). Applying high performance computing to perform geometric intersection on huge amount of spatial data to get real-time results is necessary. Given two input geometries (polygon or polyline) of a candidate pair, we introduce a new two-step geospatial filter that first creates sketches of the geometries and uses it to detect workload and then refines the sketches by the common areas of sketches to decrease the overall computations in the refine phase. We call this filter PolySketch-based CMBR (PSCMBR) filter. We show the application of this filter in …

Groundwater Withdrawal Prediction Using Integrated Multitemporal Remote Sensing Data Sets And Machine Learning, S. Majumdar, Ryan G. Smith, J. J. Butler, V. Lakshmi

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Effective monitoring of groundwater withdrawals is necessary to help mitigate the negative impacts of aquifer depletion. In this study, we develop a holistic approach that combines water balance components with a machine learning model to estimate groundwater withdrawals. We use both multitemporal satellite and modeled data from sensors that measure different components of the water balance and land use at varying spatial and temporal resolutions. These remote sensing products include evapotranspiration, precipitation, and land cover. Due to the inherent complexity of integrating these data sets and subsequently relating them to groundwater withdrawals using physical models, we apply random forests -- …

The Cycle Structure Of Unicritical Polynomials, Andrew Bridy, Derek Garton

Mathematics and Statistics Faculty Publications and Presentations

A polynomial with integer coefficients yields a family of dynamical systems indexed by primes as follows: for any prime p" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; border: 0px; font-variant: inherit; font-stretch: inherit; line-height: normal; font-family: inherit; vertical-align: baseline; display: inline; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; position: relative;">pp⁠, reduce its coefficients mod p" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; border: 0px; font-variant: inherit; font-stretch: inherit; line-height: normal; font-family: inherit; vertical-align: baseline; display: inline; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; …

Significance Statements Communicate Our Science More Widely, Rezaul Mahmood

School of Natural Resources: Faculty Publications

The American Meteorological Society (AMS) mission statement specifically calls for advancing ‘‘the atmospheric and related sciences . . . for the benefit of society.’’ To further the goal of communicating the importance of the science in our journals more widely, AMS is encouraging the inclusion in submitted papers of a ‘‘significance statement,’’ written in plain language and aimed at an educated layperson without formal training or education in the atmospheric and related sciences. As of 6 November 2020, Earth Interactions authors now have the option to include a significance statement with their submitted papers. A significance statement is an explanation …

Data Availability Principles And Practice, Rezaul Mahmood, Joseph A. Santanello, Xiaoyang Zhang

School of Natural Resources: Faculty Publications

Science requires evidence. Making data available lets other scientists confirm results, uncover errors, or find new insights. Moreover, gathering data can be expensive and time consuming. Since the same data can be used for a range of purposes, making data available can be an efficient use of limited research resources. Doing so can also improve traceability and, thus, accountability, when it comes to research findings. These reasons and more lie behind recent efforts to promote data availability. The American Meteorological Society (AMS) recently updated its data policy guidelines (https://www.ametsoc.org/ index.cfm/ams/publications/ethical-guidelines-and-ams-policies/data-policy-and-guidelines/) to require, among other things, that papers in its journals …

Using Current-Voltage Characteristics To Probe The Transport Mechanism In Carbon Nanotube Networks, Alejandro Jimenez

Physics

Carbon nanotube (CNT) random networks have shown great promise in electronic applications. For example, they have been used as the active layer in thin film transistor biosensors and as electrodes in supercapacitors (Hu, 2010). Although CNT networks applications are numerous, some of the key details of their electrical behavior are not fully understood. In particular, it is known that the junctions between tubes in CNT networks play a key role in determining the sensing properties of the network (Thanihaichelvana, et al., 2018), however, the mechanism by which metallic-semiconducting (m-s) tube junctions affect the electrical sensing properties of the network is …

Under-Ice Phytoplankton Blooms: Shedding Light On The "Invisible" Part Of Arctic Primary Production, Mathieu Ardyna, C. J. Mundy, Nicolas Mayot, Lisa C. Matthes, Laurent Oziel, Christopher Horvat, Eva Leu, Philipp Assmy, Victoria Hill, Patricia A. Matrai, Matthew Gale, Igor A. Melnikov, Kevin R. Arrigo

OES Faculty Publications

The growth of phytoplankton at high latitudes was generally thought to begin in open waters of the marginal ice zone once the highly reflective sea ice retreats in spring, solar elevation increases, and surface waters become stratified by the addition of sea-ice melt water. In fact, virtually all recent large-scale estimates of primary production in the Arctic Ocean (AO) assume that phytoplankton production in the water column under sea ice is negligible. However, over the past two decades, an emerging literature showing significant under-ice phytoplankton production on a pan-Arctic scale has challenged our paradigms of Arctic phytoplankton ecology and phenology. …

Drastic Vegetation Change In The Guajira Peninsula (Colombia) During The Neogene, Carlos Jaramillo, Pierre Sepulchre, Damian Cardenas, Francisca Oboh-Ikuenobe, For Full List Of Authors, See Publisher's Website.

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Dry biomes occupy ~35% of the landscape in the Neotropics, but these are heavily human-disturbed. In spite of their importance, we still do not fully understand their origins and how they are sustained. The Guajira Peninsula in northern Colombia is dominated by dry biomes and has a rich Neogene fossil record. Here, we have analyzed its changes in vegetation and precipitation during the Neogene using a fossil pollen and spore dataset of 20 samples taken from a well and we also dated the stratigraphic sequence using microfossils. In addition, we analyzed the pollen and spore contents of 10 Holocene samples …

Lead Complexation By Humic Acids And Their Analogs: A Voltammetric Study, Spencer Steinberg, Vernon Hodge

Chemistry and Biochemistry Faculty Research

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Differential pulse polarography (DPP) was used to assess the interaction of Pb2+ with various humic acid analogs and several humic acids. DPP analysis demonstrated that the reduction peak maximum (Ep) for Pb2+ shifted to more negative values in the presence of humic acids and humic acid analogs. The observed Ep for Pb2+ in the presence of humic acids and humic acid analogs is influenced by ligand concentration, solution pH and Pb2+ concentration. Shifts in the Ep for Pb2+ are related to the reduction potential and can be rationalized using the Lingane …

Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations, Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia

Research Collection School Of Computing and Information Systems

The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV). A number of previous studies focus on leveraging stance classification to enhance RV with multi-task learning (MTL) methods. However, most of these methods failed to employ pre-trained contextualized embeddings such as BERT, and did not exploit inter-task dependencies by using predicted stance labels to improve the RV task. Therefore, in this paper, to extend BERT to obtain thread representations, we first propose a Hierarchical Transformer1 , which divides each long thread into shorter subthreads, …

Bugsinpy: A Database Of Existing Bugs In Python Programs To Enable Controlled Testing And Debugging Studies, Ratnadira Widyasari, Sheng Qin Sim, Camellia Lok, Haodi Qi, Jack Phan, Qijin Tay, Constance Tan, Fiona Wee, Jodie Ethelda Tan, Yuheng Yieh, Brian Goh, Ferdian Thung, Hong Jin Kang, Thong Hoang, David Lo, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

The 2019 edition of Stack Overflow developer survey highlights that, for the first time, Python outperformed Java in terms of popularity. The gap between Python and Java further widened in the 2020 edition of the survey. Unfortunately, despite the rapid increase in Python's popularity, there are not many testing and debugging tools that are designed for Python. This is in stark contrast with the abundance of testing and debugging tools for Java. Thus, there is a need to push research on tools that can help Python developers.One factor that contributed to the rapid growth of Java testing and debugging tools …

Reducing Estimation Bias Via Triplet-Average Deep Deterministic Policy Gradient, Dongming Wu, Xingping Dong, Jianbing Shen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

The overestimation caused by function approximation is a well-known property in Q-learning algorithms, especially in single-critic models, which leads to poor performance in practical tasks. However, the opposite property, underestimation, which often occurs in Q-learning methods with double critics, has been largely left untouched. In this article, we investigate the underestimation phenomenon in the recent twin delay deep deterministic actor-critic algorithm and theoretically demonstrate its existence. We also observe that this underestimation bias does indeed hurt performance in various experiments. Considering the opposite properties of single-critic and double-critic methods, we propose a novel triplet-average deep deterministic policy gradient algorithm that …

Coinwatch: A Clone-Based Approach For Detecting Vulnerabilities In Cryptocurrencies, Qingze Hum, Wei Jin Tan, Shi Ying Tey, Latasha Lenus, Ivan Homoliak, Yun Lin, Jun Sun

Research Collection School Of Computing and Information Systems

Cryptocurrencies have become very popular in recent years. Thousands of new cryptocurrencies have emerged, proposing new and novel techniques that improve on Bitcoin's core innovation of the blockchain data structure and consensus mechanism. However, cryptocurrencies are a major target for cyber-attacks, as they can be sold on exchanges anonymously and most cryptocurrencies have their codebases publicly available. One particular issue is the prevalence of code clones in cryptocurrencies, which may amplify security threats. If a vulnerability is found in one cryptocurrency, it might be propagated into other cloned cryptocurrencies. In this work, we propose a systematic remedy to this problem, …