Engineering Commons^™

Learning Homophily Couplings From Non-Iid Data For Joint Feature Selection And Noise-Resilient Outlier Detection, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu

Research Collection School Of Computing and Information Systems

This paper introduces a novel wrapper-based outlier detection framework (WrapperOD) and its instance (HOUR) for identifying outliers in noisy data (i.e., data with noisy features) with strong couplings between outlying behaviors. Existing subspace or feature selection-based methods are significantly challenged by such data, as their search of feature subset(s) is independent of outlier scoring and thus can be misled by noisy features. In contrast, HOUR takes a wrapper approach to iteratively optimize the feature subset selection and outlier scoring using a top-k outlier ranking evaluation measure as its objective function. HOUR learns homophily couplings between outlying behaviors (i.e., abnormal behaviors …

Well-Tuned Algorithms For The Team Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen, Kun Lu

Research Collection School Of Computing and Information Systems

The Team Orienteering Problem with Time Windows (TOPTW) is the extension of the Orienteering Problem (OP) where each node is limited by a predefined time window during which the service has to start. The objective of the TOPTW is to maximize the total collected score by visiting a set of nodes with a limited number of paths. We propose two algorithms, Iterated Local Search and a hybridization of Simulated Annealing and Iterated Local Search (SAILS), to solve the TOPTW. As indicated in multiple research works on algorithms for the OP and its variants, determining appropriate parameter values in a statistical …

Time-Aware Conversion Prediction, Wendi Ji, Xiaoling Wang, Feida Zhu

Research Collection School Of Computing and Information Systems

The importance of product recommendation has been well recognized as a central task in business intelligence for e-commerce websites. Interestingly, what has been less aware of is the fact that different products take different time periods for conversion. The “conversion” here refers to actually a more general set of pre-defined actions, including for example purchases or registrations in recommendation and advertising systems. The mismatch between the product’s actual conversion period and the application’s target conversion period has been the subtle culprit compromising many existing recommendation algorithms.The challenging question: what products should be recommended for a given time period to maximize …

Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu

Research Collection School Of Computing and Information Systems

Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …

Proactive And Reactive Coordination Of Non-Dedicated Agent Teams Operating In Uncertain Environments, Pritee Agrawal, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Domains such as disaster rescue, security patrolling etc. often feature dynamic environments where allocations of tasks to agents become ineffective due to unforeseen conditions that may require agents to leave the team. Agents leave the team either due to arrival of high priority tasks (e.g., emergency, accident or violation) or due to some damage to the agent. Existing research in task allocation has only considered fixed number of agents and in some instances arrival of new agents on the team. However, there is little or no literature that considers situations where agents leave the team after task allocation. To that …

Indexing Metric Uncertain Data For Range Queries And Range Joins, Lu Chen, Yunjun Gao, Aoxiao Zhong, Christian S. Jensen, Gang Chen, Baihua Zheng

Research Collection School Of Computing and Information Systems

Range queries and range joins in metric spaces have applications in many areas, including GIS, computational biology, and data integration, where metric uncertain data exist in different forms, resulting from circumstances such as equipment limitations, high-throughput sequencing technologies, and privacy preservation. We represent metric uncertain data by using an object-level model and a bi-level model, respectively. Two novel indexes, the uncertain pivot B+-tree (UPB-tree) and the uncertain pivot B+-forest (UPB-forest), are proposed in order to support probabilistic range queries and range joins for a wide range of uncertain data types and similarity metrics. Both index structures use a small set …

Pivot-Based Metric Indexing, Lu Chen, Yunjun Gao, Baihua Zheng, Christian S. Jensen, Hanyu Yang, Keyu Yang

Research Collection School Of Computing and Information Systems

The general notion of a metric space encompasses a diverse range of data types and accompanying similarity measures. Hence, metric search plays an important role in a wide range of settings, including multimedia retrieval, data mining, and data integration. With the aim of accelerating metric search, a collection of pivot-based indexing techniques for metric data has been proposed, which reduces the number of potentially expensive similarity comparisons by exploiting the triangle inequality for pruning and validation. However, no comprehensive empirical study of those techniques exists. Existing studies each offers only a narrower coverage, and they use different pivot selection strategies …

Geometric Approaches For Top-K Queries [Tutorial], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Top-k processing is a well-studied problem with numerous applications that is becoming increasingly relevant with the growing availability of recommendation systems and decision-making software. The objective of this tutorial is twofold. First, we will delve into the geometric aspects of top-k processing. Second, we will cover complementary features to top-k queries, with strong practical relevance and important applications, that have a computational geometric nature. The tutorial will close with insights in the effect of dimensionality on the meaningfulness of top-k queries, and interesting similarities to nearest neighbor search.

Semantic Visualization For Short Texts With Word Embeddings, Van Minh Tuan Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Semantic visualization integrates topic modeling and visualization, such that every document is associated with a topic distribution as well as visualization coordinates on a low-dimensional Euclidean space. We address the problem of semantic visualization for short texts. Such documents are increasingly common, including tweets, search snippets, news headlines, or status updates. Due to their short lengths, it is difficult to model semantics as the word co-occurrences in such a corpus are very sparse. Our approach is to incorporate auxiliary information, such as word embeddings from a larger corpus, to supplement the lack of co-occurrences. This requires the development of a …

Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok

Research Collection School Of Computing and Information Systems

Measuring and understanding the performance of mobile networks is becoming very important for end users and operators. Despite the availability of many measurement apps, their measurement accuracy has not received sufficient scrutiny. In this paper, we appraise the accuracy of smartphone-based network performance measurement using the Android platform and the network round-trip time (RTT) as the metric. We show that two of the most popular measurement apps-Ookla Speedtest and MobiPerf-have their RTT measurements inflated. We build three test apps that cover three common measurement methods and evaluate them in a testbed. We overcome the main challenge of obtaining a complete …

Hibs-Ksharing: Hierarchical Identity-Based Signature Key Sharing For Automotive, Zhuo Wei, Yanjiang Yang, Yongdong Wu, Jian Weng, Robert H. Deng

Research Collection School Of Computing and Information Systems

Equipped with various sensors and intelligent systems, modern cars turn into entities with connectivity, autonomy, and safety. Car rental/car sharing is an innovative transportation concept and integral in today's urban living. It enables users to access a fleet of vehicles located throughout cities. Complementing public transportation, the car-sharing service helps people to meet their transportation needs economically and in an environmentally responsible manner. When a customer wants to rent a car from a rental company or an owner wants to share a private car with his/her friends or family members, the customer or the user should gain admission to the …

Smartphone Sensing Meets Transport Data: A Collaborative Framework For Transportation Service Analytics, Yu Lu, Archan Misra, Wen Sun, Huayu Wu

Research Collection School Of Computing and Information Systems

We advocate for and introduce TRANSense, a framework for urban transportation service analytics that combines participatory smartphone sensing data with city-scale transportation-related transactional data (taxis, trains etc.). Our work is driven by the observed limitations of using each data type in isolation: (a) commonly-used anonymous city-scale datasets (such as taxi bookings and GPS trajectories) provide insights into the aggregate behavior of transport infrastructure, but fail to reveal individual-specific transport experiences (e.g., wait times in taxi queues); while (b) mobile sensing data can capture individual-specific commuting-related activities, but suffers from accuracy and energy overhead challenges due to usage artefacts and lack …

Embedding-Based Representation Of Categorical Data By Hierarchical Value Coupling Learning, Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao

Research Collection School Of Computing and Information Systems

Learning the representation of categorical data with hierarchical value coupling relationships is very challenging but critical for the effective analysis and learning of such data. This paper proposes a novel coupled unsupervised categorical data representation (CURE) framework and its instantiation, i.e., a coupled data embedding (CDE) method, for representing categorical data by hierarchical value-to-value cluster coupling learning. Unlike existing embedding- and similarity-based representation methods which can capture only a part or none of these complex couplings, CDE explicitly incorporates the hierarchical couplings into its embedding representation. CDE first learns two complementary feature value couplings which are then used to cluster …

Decoupling Information And Connectivity In Information-Centric Networking, Hila Ben Abraham, Jyoti Parwatikar, John Dehart, Adam Drescher, Patrick Crowley

All Computer Science and Engineering Research

This paper introduces and demonstrates the concept of Information-Centric Transport as a mechanism for cleanly decoupling the information plane from the connectivity plane in Information-Centric Networking (ICN) architectures, such as NDN and CICN. These are coupled in today's incarnations of NDN and CICN through the use of forwarding strategy, which is the architectural component for deciding how to forward packets in the presence of either multiple next-hop options or dynamic feedback. As presently designed, forwarding strategy is not sustainable: application developers can only confidently specify strategy if they understand connectivity details, while network node operators can only confidently assign strategies …

Data Extraction From Web Tables: The Devil Is In The Details, George Nagy, Sharad C. Seth, Dongpu Jin, David W. Embley, Spencer Machado, Mukkai Krishnamoorthy

School of Computing: Conference and Workshop Papers

We present a method based on header paths for efficient and complete extraction of labeled data from tables meant for humans. Although many table configurations yield to the proposed syntactic analysis, some require access to semantic knowledge. Clicking on one or two critical cells per table, through a simple interface, is sufficient to resolve most of these problem tables. Header paths, a purely syntactic representation of visual tables, can be transformed (“factored”) into existing representations of structured data such as category trees, relational tables, and RDF triples. From a random sample of 200 web tables from ten large statistical web …

End-To-End Conversion Of Html Tables For Populating A Relational Database, George Nagy, David W. Embley, Sharad C. Seth

School of Computing: Conference and Workshop Papers

Automating the conversion of human-readable HTML tables into machine-readable relational tables will enable end-user query processing of the millions of data tables found on the web. Theoretically sound and experimentally successful methods for index-based segmentation, extraction of category hierarchies, and construction of a canonical table suitable for direct input to a relational database are demonstrated on 200 heterogeneous web tables. The methods are scalable: the program generates the 198 Access compatible CSV files in ~0.1s per table (two tables could not be indexed).

Explaining Trained Neural Networks With Semantic Web Technologies: First Steps, Md Kamruzzaman Sarker, Ning Xie, Derek Doran, Michael L. Raymer, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The ever increasing prevalence of publicly available struc-tured data on the World Wide Web enables new applications in a varietyof domains. In this paper, we provide a conceptual approach that lever-ages such data in order to explain the input-output behavior of trainedartificial neural networks. We apply existing Semantic Web technologiesin order to provide an experimental proof of concept.

Modeling De Novo Granulation Of Anaerobic Sludge, Anna Doloman, Honey Varghese, Charles D. Miller, Nicholas Flann

Computer Science Faculty and Staff Publications

Background: A unique combination of mechanical, physiochemical and biological forces influences granulation during processes of anaerobic digestion. Understanding this process requires a systems biology approach due to the need to consider not just single-cell metabolic processes, but also the multicellular organization and development of the granule.

Results: In this computational experiment, we address the role that physiochemical and biological processes play in granulation and provide a literature-validated working model of anaerobic granule de novo formation. The agent-based model developed in a cDynoMiCs simulation environment successfully demonstrated a de novo granulation in a glucose fed system, with the average specific methanogenic …

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …

Harmonic Distortion Minimization In Power Grids With Wind And Electric Vehicles, Ritam Misra, Sumit Paudyal, Oguzhan Ceylan, Paras Mandal

Michigan Tech Publications, Part 1

Power-electronic interfacing based devices such as wind generators (WGs) and electrical vehicles (EVs) cause harmonic distortions on the power grid. Higher penetration and uncoordinated operation of WGs and EVs can lead to voltage and current harmonic distortions, which may exceed IEEE limits. It is interesting to note that WGs and EVs have some common harmonic profiles. Therefore, when EVs are connected to the grid, the harmonic pollution EVs impart onto the grid can be reduced to some extent by the amount of wind power injecting into the grid and vice versa. In this context, this work studies the impact of …

Multiple Attributes Decision Fusion For Wireless Sensor Networks Based On Intuitionistic Fuzzy Set, Zhenjiang Zhang, Ziqi Hao, Sherali Zeadally, Jing Zhang, Bowen Han, Han-Chieh Chao

Information Science Faculty Publications

Decision fusion is an important issue in wireless sensor networks (WSN), and intuitionistic fuzzy set (IFS) is a novel method for dealing with uncertain data. We propose a multi-attribute decision fusion model based on IFS, which includes two aspects: data distribution-based IFS construction algorithm (DDBIFCA) and the category similarity weight-based TOPSIS intuitionistic fuzzy decision algorithm (CSWBT-IFS). The DDBIFCA is an IFS construction algorithm that transforms the original attribute values into intuitionistic fuzzy measures, and the CSWBT-IFS is an intuitionistic fuzzy aggregation algorithm improved by the traditional TOPSIS algorithm, which combines intuitionistic fuzzy values of different attributes and obtains a final …

How Technology Is Reshaping Financial Services: Essays On Consumer Behavior In Card, Channel And Cryptocurrency Services, Dan Geng

Dissertations and Theses Collection

The financial services sector has seen dramatic technological innovations in the last several years associated with the “fintech revolution.” Major changes have taken place in channel management, credit card rewards marketing, cryptocurren-cy, and wealth management, and have influenced consumers’ banking behavior in different ways. As a consequence, there has been a growing demand for banks to rethink their business models and operations to adapt to changing consumer be-havior and counter the competitive pressure from other banks and non-bank play-ers. In this dissertation, I study consumer behavior related to different aspects of financial innovation by addressing research questions that are motivated …

Full Simulation For The Qweak Experiment At 1.16 And 0.877 Gev And Their Impact On Extracting The Pv Asymmetry In The N→Δ A Transition, Hend Abdullah Nuhait

Doctoral Dissertations

The Qweak project is seeking to find new physics beyond the Standard Model. It is aimed to measure the weak charge of the proton, which has never been measured, at 4% precision at low momentum transfer. The experiment is performed by scattering electrons from protons and exploiting parity violation in the weak interaction at low four-momentum transfer.

In this experiment, two measurements were considered: which are elastic and inelastic. The elastic is to measure the proton's weak charge. In addition, the inelastic asymmetry measurement, which will extract the low energy constant dΔ. That measurement works in the neutral current …

Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam

School of Computing: Dissertations, Theses, and Student Research

Good querying and visualization of moving objects and their trajectories is still an open problem. This thesis investigates three types of moving objects. First, projectiles, whose parabolic motion is difficult to represent. Second, moving objects that slide down a slope. The representation of these objects is challenging because of their accelerating motion. Third, the motion of migrating animals. The motion of migrating animals is challenging because it also involves some spatio-temporal interpolation. The thesis shows a solution to these problems using ideas from physics and an implementation in the MLPQ constraint databases system. The MLPQ implementation enables several complex spatio-temporal …

Attribute-Based Encryption With Expressive And Authorized Keyword Search, Hui Cui, Robert H. Deng, Joseph K. Liu, Yingjiu Li

Research Collection School Of Computing and Information Systems

To protect data security and privacy in cloud storage systems, a common solution is to outsource data in encrypted forms so that the data will remain secure and private even if storage systems are compromised. The encrypted data, however, must be pliable to search and access control. In this paper, we introduce a notion of attribute-based encryption with expressive and authorized keyword search (ABE-EAKS) to support both expressive keyword search and fine-grained access control over encrypted data in the cloud. In ABE-EAKS, every data user is associated with a set of attributes and is issued a private attribute-key corresponding to …

A Unified Framework For Vehicle Rerouting And Traffic Light Control To Reduce Traffic Congestion, Zhiguang Cao, Siwei Jiang, Jie Zhang, Hongliang Guo

Research Collection School Of Computing and Information Systems

As the number of vehicles grows rapidly each year, more and more traffic congestion occurs, becoming a big issue for civil engineers in almost all metropolitan cities. In this paper, we propose a novel pheromone-based traffic management framework for reducing traffic congestion, which unifies the strategies of both dynamic vehicle rerouting and traffic light control. Specifically, each vehicle, represented as an agent, deposits digital pheromones over its route, while roadside infrastructure agents collect the pheromones and fuse them to evaluate real-time traffic conditions as well as to predict expected road congestion levels in near future. Once road congestion is predicted, …

Algorithms For Constructing Vehicle Trajectories In Urban Networks Using Inertial Sensors Data From Mobile Devices, Umana Ahmed

Computational Modeling & Simulation Engineering Theses & Dissertations

Vehicle trajectories are an important source of information for estimating traffic flow characteristics. Lately, several studies have focused on identifying a vehicle’s trajectory in traffic network using data from mobile devices. However, these studies predominantly employed GPS coordinate information for tracking a vehicle’s speed and position in the transportation network. Considering the known limitations of GPS, such as, connectivity issues at urban canyons and underpasses, low precision of localization, high power consumption of device while GPS is in use, this research focuses on developing alternate methods for identifying a vehicle’s trajectory at an intersection and at a urban grid network …

Homogenization Of Plastic Deformation In Heterogeneous Lamella Structures, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou

Materials Science and Engineering Faculty Research & Creative Works

It has been shown that unlike its constituent nanocrystalline (NC) phase, a heterogeneous lamella (HL) composite comprising NC and coarse-grain layers exhibits greatly improved ductility. To understand the origin of this enhancement, we present a 3D discrete dislocation, crystal plasticity finite element model to study the development of strains across this microstructure. Here we show that the HL structure homogenizes the plastic strains in the NC layer, weakening the effect of strain concentrations. These findings can provide valuable insight into the effects of material length scales on material instabilities, which is needed to design heterogeneous structures with superior properties.

Multi-Material Mesh Representation Of Anatomical Structures For Deep Brain Stimulation Planning, Tanweer Rashid

Computational Modeling & Simulation Engineering Theses & Dissertations

The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. The proposed method decomposes an ambiguous grid cube into a set of tetrahedral cells and uses novel polygon generation rules that produce 2-manifold and watertight surface meshes with good-quality triangles. These meshes, being watertight and 2-manifold, are geometrically correct, and therefore can be used to …

Mining Capstone Project Wikis For Knowledge Discovery, Swapna Gottipati, Venky Shankararaman, Melvrivk Goh

Research Collection School Of Computing and Information Systems

Wikis are widely used collaborative environments as sources of information and knowledge. The facilitate students to engage in collaboration and share information among members and enable collaborative learning. In particular, Wikis play an important role in capstone projects. Wikis aid in various project related tasks and aid to organize information and share. Mining project Wikis is critical to understand the students learning and latest trends in industry. Mining Wikis is useful to educationists and academicians for decision-making about how to modify the educational environment to improve student's learning. The main challenge is that the content or data in project Wikis …