Physical Sciences and Mathematics Commons^™

Tour: Dynamic Topic And Sentiment Analysis Of User Reviews For Assisting App Release, Tianyi Yang, Cuiyun Gao, Jingya Zang, David Lo, Michael R. Lyu

Research Collection School Of Computing and Information Systems

App reviews deliver user opinions and emerging issues (e.g., new bugs) about the app releases. Due to the dynamic nature of app reviews, topics and sentiment of the reviews would change along with app release versions. Although several studies have focused on summarizing user opinions by analyzing user sentiment towards app features, no practical tool is released. The large quantity of reviews and noise words also necessitates an automated tool for monitoring user reviews. In this paper, we introduce TOUR for dynamic TOpic and sentiment analysis of User Reviews. TOUR is able to (i) detect and summarize emerging app issues …

Escape From An Echo Chamber, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku

Research Collection School Of Computing and Information Systems

An echo chamber effect refers to the phenomena that online users revealed selective exposure and ideological segregation on political issues. Prior studies indicate the connection between the spread of misinformation and online echo chambers. In this paper, to help users escape from an echo chamber, we propose a novel news-analysis platform that provides a panoramic view of stances towards a particular event from different news media sources. Moreover, to help users better recognize the stances of news sources which published these news articles, we adopt a news stance classification model to categorize their stances into “agree”, “disagree”, “discuss”, or “unrelated” …

Homophily Outlier Detection In Non-Iid Categorical Data, Guansong Pang, Longbing Cao, Ling Chen

Research Collection School Of Computing and Information Systems

Most of existing outlier detection methods assume that the outlier factors (i.e., outlierness scoring measures) of data entities (e.g., feature values and data objects) are Independent and Identically Distributed (IID). This assumption does not hold in real-world applications where the outlierness of different entities is dependent on each other and/or taken from different probability distributions (non-IID). This may lead to the failure of detecting important outliers that are too subtle to be identified without considering the non-IID nature. The issue is even intensified in more challenging contexts, e.g., high-dimensional data with many noisy features. This work introduces a novel outlier …

Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples, Alvin Chan, Lei Ma, Felix Juefei-Xu, Yew-Soon Ong, Xiaofei Xie, Minhui Xue, Yang Liu

Research Collection School Of Computing and Information Systems

The ability to read, reason, and infer lies at the heart of neural reasoning architectures. After all, the ability to perform logical reasoning over language remains a coveted goal of Artificial Intelligence. To this end, models such as the Turing-complete differentiable neural computer (DNC) boast of real logical reasoning capabilities, along with the ability to reason beyond simple surface-level matching. In this brief, we propose the first probe into DNC's logical reasoning capabilities with a focus on text-based question answering (QA). More concretely, we propose a conceptually simple but effective adversarial attack based on metamorphic relations. Our proposed adversarial attack …

Dram Failure Prediction In Aiops: Empirical Evaluation, Challenges And Opportunities, Zhiyue Wu, Hongzuo Xu, Guansong Pang, Fengyuan Yu, Yijie Wang, Songlei Jian, Yongjun Wang

Research Collection School Of Computing and Information Systems

DRAM failure prediction is a vital task in AIOps, which is crucial to maintain the reliability and sustainable service of large-scale data centers. However, limited work has been done on DRAM failure prediction mainly due to the lack of public available datasets. This paper presents a comprehensive empirical evaluation of diverse machine learning techniques for DRAM failure prediction using a large-scale multisource dataset, including more than three millions of records of kernel, address, and mcelog data, provided by Alibaba Cloud through PAKDD 2021 competition. Particularly, we first formulate the problem as a multiclass classification task and exhaustively evaluate seven popular/stateof-the-art …

Urban Perception: Sensing Cities Via A Deep Interactive Multi-Task Learning Framework, Weili Guan, Zhaozheng Chen, Fuli Feng, Weifeng Liu, Liqiang Nie

Research Collection School Of Computing and Information Systems

Social scientists have shown evidence that visual perceptions of urban attributes, such as safe, wealthy, and beautiful perspectives of the given cities, are highly correlated to the residents' behaviors and quality of life. Despite their significance, measuring visual perceptions of urban attributes is challenging due to the following facts: (1) Visual perceptions are subjectively contradistinctive rather than absolute. (2) Perception comparisons between image pairs are usually conducted region by region, and highly related to the specific urban attributes. And (3) the urban attributes have both the shared and specific information. To address these problems, in this article, we present a …

Time Period-Based Top-K Semantic Trajectory Pattern Query, Munkh-Erdene Yadamjav, Farhana Murtaza Choudhury, Zhifeng Bao, Baihua Zheng

Research Collection School Of Computing and Information Systems

The sequences of user check-ins form semantic trajectories that represent the movement of users through time, along with the types of POIs visited. Extracting patterns in semantic trajectories can be widely used in applications such as route planning and trip recommendation. Existing studies focus on the entire time duration of the data, which may miss some temporally significant patterns. In addition, they require thresholds to define the interestingness of the patterns. Motivated by the above, we study a new problem of finding top-k semantic trajectory patterns w.r.t. a given time period and categories by considering the spatial closeness of POIs. …

Detection Of Social Identification In Workgroups From A Passively-Sensed Wifi Infrastructure, Camelia Zakaria, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Social identification: how much individuals psychologically associate themselves with a group has been posited as an essential construct to measure individual and group dynamics. Studies have shown that individuals who identify very differently from their workgroup provides critical cues to the lack of social support or work overloads. However, measuring identification is typically achieved through time-consuming and privacy invasive surveys. We hypothesize that the extremitized in-group norm affects individuals' behaviors, thus more likely to give rise to negative appraisals. As a more convenient and less-invasive technique, we propose a method to predict individuals who are increasingly different in identifying themselves …

Spectest: Specification-Based Compiler Testing, Richard Schumi, Jun Sun

Research Collection School Of Computing and Information Systems

Compilers are error-prone due to their high complexity. They are relevant for not only general purpose programming languages, but also for many domain specific languages. Bugs in compilers can potentially render all programs at risk. It is thus crucial that compilers are systematically tested, if not verified. Recently, a number of efforts have been made to formalise and standardise programming language semantics, which can be applied to verify the correctness of the respective compilers. In this work, we present a novel specification-based testing method named SpecTest to better utilise these semantics for testing. By applying an executable semantics as test …

Dbl: Efficient Reachability Queries On Dynamic Graphs, Qiuyi Lyu, Yuchen Li, Bingsheng He, Bin Gong

Research Collection School Of Computing and Information Systems

Reachability query is a fundamental problem on graphs, which has been extensively studied in academia and industry. Since graphs are subject to frequent updates in many applications, it is essential to support efficient graph updates while offering good performance in reachability queries. Existing solutions compress the original graph with the Directed Acyclic Graph (DAG) and propose efficient query processing and index update techniques. However, they focus on optimizing the scenarios where the Strong Connected Components (SCCs) remain unchanged and have overlooked the prohibitively high cost of the DAG maintenance when SCCs are updated. In this paper, we propose DBL, an …

Towards Efficient Motif-Based Graph Partitioning: An Adaptive Sampling Approach, Shixun Huang, Yuchen Li, Zhifeng Bao, Zhao Li

Research Collection School Of Computing and Information Systems

In this paper, we study the problem of efficient motif-based graph partitioning (MGP). We observe that existing methods require to enumerate all motif instances to compute the exact edge weights for partitioning. However, the enumeration is prohibitively expensive against large graphs. We thus propose a sampling-based MGP (SMGP) framework that employs an unbiased sampling mechanism to efficiently estimate the edge weights while trying to preserve the partitioning quality. To further improve the effectiveness, we propose a novel adaptive sampling framework called SMGP+. SMGP+ iteratively partitions the input graph based on up-to-date estimated edge weights, and adaptively adjusts the sampling distribution …

Dycuckoo: Dynamic Hash Tables On Gpus, Yuchen Li, Qiwei Zhu, Zheng Lyu, Zhongdong Huang, Jianling Sun

Research Collection School Of Computing and Information Systems

The hash table is a fundamental structure that has been implemented on graphics processing units (GPUs) to accelerate a wide range of analytics workloads. Most existing works have focused on static scenarios and occupy large GPU memory to maximize the insertion efficiency. In many cases, data stored in hash tables get updated dynamically, and existing approaches use unnecessarily large memory resources. One naïve solution is to rebuild a hash table (known as rehashing) whenever it is either filled or mostly empty. However, this approach renders significant overheads for rehashing. In this paper, we propose a novel dynamic cuckoo hash table …

Boundary Precedence Image Inpainting Method Based On Self-Organizing Maps, Haibo Pen, Quan Wang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

In addition to text data analysis, image analysis is an area that has increasingly gained importance in recent years because more and more image data have spread throughout the internet and real life. As an important segment of image analysis techniques, image restoration has been attracting a lot of researchers’ attention. As one of AI methodologies, Self-organizing Maps (SOMs) have been applied to a great number of useful applications. However, it has rarely been applied to the domain of image restoration. In this paper, we propose a novel image restoration method by leveraging the capability of SOMs, and we name …

Mixed Dish Recognition With Contextual Relation And Domain Alignment, Lixi Deng, Jingjing Chen, Chong-Wah Ngo, Qianru Sun, Sheng Tang, Yongdong Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Mixed dish is a food category that contains different dishes mixed in one plate, and is popular in Eastern and Southeast Asia. Recognizing the individual dishes in a mixed dish image is important for health related applications, e.g. to calculate the nutrition values of the dish. However, most existing methods that focus on single dish classification are not applicable to the recognition of mixed dish images. The main challenge of mixed dish recognition comes from three aspects: a wide range of dish types, the complex dish combination with severe overlap between different dishes and the large visual variances of same …

Looking Back! Using Early Versions Of Android Apps As Attack Vectors, Yue Zhang, Jian Weng, Jia-Si Wneg, Lin Hou, Anjia Yang, Ming Li, Yang Xiang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Android platform is gaining explosive popularity. This leads developers to invest resources to maintain the upward trajectory of the demand. Unfortunately, as the profit potential grows higher, the chances of these Apps getting attacked also get higher. Therefore, developers improved the security of their Apps, which limits attackers ability to compromise upgraded versions of the Apps. However, developers cannot enhance the security of earlier versions that have been released on the Play Store. The earlier versions of the App can be subject to reverse engineering and other attacks. In this paper, we find that attackers can use these earlier versions …

Hierarchical And Adaptive Filter And Refinement Algorithms For Geometric Intersection Computations On Gpu, Yiming Liu

Dissertations (1934 -)

Geometric intersection algorithms are fundamental in spatial analysis in Geographic Information System (GIS). This dissertation explores high performance computing solution for geometric intersection on a huge amount of spatial data using Graphics Processing Unit (GPU). We have developed a hierarchical filter and refinement system for parallel geometric intersection operations involving large polygons and polylines by extending the classical filter and refine algorithm using efficient filters that leverage GPU computing. The inputs are two layers of large polygonal datasets and the computations are spatial intersection on pairs of cross-layer polygons. These intersections are the compute-intensive spatial data analytic kernels in spatial …

Development Of Mqct Method For Calculations Of Collisional Energy Transfer For Astrochemistry And Planetary Atmospheres, Bikramaditya Mandal

Dissertations (1934 -)

A mixed quantum/classical methodology and an efficient computer code, named MQCT, were developed to model molecular energy transfer processes relevant to astrochemical environments and planetary atmospheres and applied to several real systems. In particular, the rotational energy transfer in N2 + Na collisions was studied with the focus on quantum phase, differential cross-sections, and scattering resonances, and excellent agreement with full quantum results was found. For H2O + H2, detailed calculations were carried out with the focus on allowed vs. forbidden transitions between the ortho/para states of both collision partners. Again, excellent agreement with full quantum calculations was achieved. Calculations …

Toward Understanding The Origin Of Mass-Independent Fractionation In Sulfur Allotropes And In Ozone, Igor Gayday

Dissertations (1934 -)

Mysterious isotope effects, found in atmospheric ozone, cannot be explained by the standard mass-dependent statistical model. Similar mass-dependent isotope effects were also uncovered in sulfur deposits older than 2 billion years. In an effort to pinpoint possible reasons of these isotope effects, we build a theoretical description of the recombination reactions in sulfur allotropes and in ozone. No potential energy surface exists for the sulfur allotropes, so electronic structure calculations are also required. Ab initio calculation of two dimensionally reduced (2D and 3D) models of the potential energy surface for the tetrasulfur molecule at CCSD(T)-F12 and MRCI levels of theory …

Design And Synthesis Of Selective Estrogen Receptor Agonists, Edward Edward Wetzel

Dissertations (1934 -)

Estrogens are hormones that regulates many different physiological functions. A decline in estrogen leads to significant issues that decrease the quality of life. Past treatments of menopausal symptoms included the administration of estrogen. However, side effects such as an increased risk of breast cancer, made this an unattractive therapeutic option. When a new estrogen receptor (ERβ) was discovered, it provided new hope for hormone replacement therapy (HRT). ERβ was shown to inhibit tumor growth, whereas ERα regulates breast cancer proliferation in certain types of breast cancer. The therapeutic benefits of targeting ERβ are vast; herein we focus on the benefits …

Functional Singular Spectrum Analysis: Nonparametric Decomposition And Forecasting Approaches For Functional Time Series, Jordan Christopher Trinka

Dissertations (1934 -)

In this dissertation, we develop nonparametric decomposition methods and the subsequent forecasting techniques for functional, time-dependent data known as functional time series (FTS). We use ideas from functional data analysis (FDA) and singular spectrum analysis (SSA) to introduce the nonparametric decomposition method known as functional SSA (FSSA) and its associated forecasting techniques. We also extend these developed methodologies into multivariate FSSA (MFSSA) over different dimensional domains and its subsequent forecasting routines so that we may perform nonparametric decomposition and prediction of multivariate FTS (MFTS). The FSSA algorithm may be viewed as a signal extraction technique and we find that the …

Scope And Mechanistic Studies Of Ruthenium Catalyzed C-N Bond Activation Reactions, Pandula Taepith Kirinde Arachchige

Dissertations (1934 -)

Primary aliphatic amines which are ubiquitous in natural products, traditionally considered as inert to substitution reactions. Recent studies clearly demonstrated that the aliphatic deaminative coupling chemistry can be used to make valuable scaffolds through C–N bond activation on transition metal complexes. The catalytic system generated in situ from the tetranuclear Ru–H complex with a catechol ligand (2-9/2-16) and independently synthesized ruthenium catecholate complex 2-11 was found to be effective for the direct deaminative coupling of primary amines. The catalytic system formed in-situ from the reaction of cationic Ru–H complex 2-10 with 3,4,5,6-tetrachloro-1,2-benzoquinone 2-12 was found to mediate a regioselective deaminative …

Building A Long-Time Series For Weather And Extreme Weather In The Straits Settlements: A Multi-Disciplinary Approach To The Archives Of Societies, Fiona Williamson

Research Collection School of Social Sciences

In comparison to the Northern Hemisphere, especially Europe and North America, there is a scarcity of information regarding the historic weather and climate of Southeast Asia and the Southern Hemisphere in general. The reasons for this are both historic and political, yet that does not mean that such data do not exist. Much of the early instrumental weather records for Southeast Asia stem from the colonial period and, with some countries and regions changing hands between the European powers, surviving information tends to be scattered across the globe making its recovery a long and often arduous task. This paper focuses …

How Successful Are Open Source Contributions From Countries With Different Levels Of Human Development?, Leonardo Furtado, Bruno Cartaxo, Christoph Treude, Gustavo Pinto

Research Collection School Of Computing and Information Systems

In this article we studied whether developers? locations relate to the outcome of a pull request (PR). Our results suggest that developers from countries with low human development indexes perform a small fraction of the overall PRs and are the ones that face rejection the most.

Silver Bow Creek/Butte Area Npl Site Butte Priority Soils Operable Unit, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Epa Region 8 Qa Document Review Crosswalk, Nikia Greene, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) Silver Bow Creek/Butte Area Npl Site, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Epa Region 8 Qa Document Review Crosswalk, Pioneer Technical Services, Inc., Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Concise Synthesis Of A Methyl Ester 2-Resorcinarene: A Chair-Conformation Macrocycle, Michael R. Reynolds, Fraser S. Pick, John J. Hayward, John F. Trant

Chemistry and Biochemistry Publications

Anions are important hydrogen bond acceptors in a range of biological, chemical, environ-mental and medical molecular recognition processes. These interactions have been exploited for the design and synthesis of ditopic resorcinarenes as the hydrogen bond strength can be tuned through the modification of the substituent at the 2-position. However, many potentially useful compounds, especially those incorporating electron-withdrawing functionalities, have not been prepared due to the challenge of their synthesis: their incorporation slows resorcinarene formation that is accessed by electrophilic aromatic substitution. As part of our broader campaign to employ resorcinarenes as selective recognition elements, we need access to these specialized …

Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv

Faculty Publications

We present twisted spatiotemporal optical vortex (STOV) beams, which are partially coherent light sources that possess a coherent optical vortex and a random twist coupling their space and time dimensions. These beams have controllable partial coherence and transverse orbital angular momentum (OAM), which distinguishes them from the more common spatial vortex and twisted beams (known to carry longitudinal OAM) in the literature and should ultimately make them useful in applications such as optical communications and optical tweezing. We present the mathematical analysis of twisted STOV beams, deriving the mutual coherence function and linear and angular momentum densities. We simulate the …

The Impact Of Artificial Intelligence On Dental Care Delivery: A Comprehensive Review, Robert A. Faiella D.M.D., M.M.Sc., M.B.A., Shaju Puthussery M.S.

The Journal of the Michigan Dental Association

This comprehensive review explores the transformative role of Artificial Intelligence (AI) in the evolution of dental care delivery. As oral health specialists, dentists continually seek to enhance their ability to prevent, diagnose, and manage oral diseases while maintaining and improving patient oral health. The integration of AI offers unprecedented opportunities to revolutionize dental practice and patient care.

AI is rapidly advancing in healthcare, including dental care, with a projected global healthcare AI market value of $45.2 billion by 2026. This technology can potentially revolutionize prevention, diagnosis, treatment planning, and treatment outcomes.

Aspects of AI in dentistry include:

· Diagnostic Accuracy …