Computer Sciences Commons^™

Random Forest Algorithm For Land Cover Classification, Arun D. Kulkarni, Barrett Lowe

Computer Science Faculty Publications and Presentations

Since the launch of the first land observation satellite Landsat-1 in 1972, many machine learning algorithms have been used to classify pixels in Thematic Mapper (TM) imagery. Classification methods range from parametric supervised classification algorithms such as maximum likelihood, unsupervised algorithms such as ISODAT and k-means clustering to machine learning algorithms such as artificial neural, decision trees, support vector machines, and ensembles classifiers. Various ensemble classification algorithms have been proposed in recent years. Most widely used ensemble classification algorithm is Random Forest. The Random Forest classifier uses bootstrap aggregating for form an ensemble of classification and induction tree like tree …

Incorporating Priors For Medical Image Segmentation Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell, James A. Tanyi, Arthur Y. Hung

Computer Science Faculty Publications and Presentations

Medical image segmentation is typically performed manually by a physician to delineate gross tumor volumes for treatment planning and diagnosis. Manual segmentation is performed by medical experts using prior knowledge of organ shapes and locations but is prone to reader subjectivity and inconsistency. Automating the process is challenging due to poor tissue contrast and ill-defined organ/tissue boundaries in medical images. This paper presents a genetic algorithm for combining representations of learned information such as known shapes, regional properties and relative position of objects into a single framework to perform automated three-dimensional segmentation. The algorithm has been tested for prostate segmentation …

Multi-Sorted Inverse Frequent Itemsets Mining: On-Going Research, Domenico Saccà, Edoardo Serra, Antonio Piccolo

Computer Science Faculty Publications and Presentations

Inverse frequent itemset mining (IFM) consists of generating artificial transactional databases reflecting patterns of real ones, in particular, satisfying given frequency constraints on the itemsets. An extension of IFM called many-sorted IFM, is introduced where the schemes for the datasets to be generated are those typical of Big Tables, as required in emerging big data applications, e.g., social network analytics.

Rvlbpnn: A Workload Forecasting Model For Smart Cloud Computing, Yao Lu, John Panneerselvam, Lu Liu, Yan Wu

Computer Science Faculty Publications and Presentations

Given the increasing deployments of Cloud datacentres and the excessive usage of server resources, their associated energy and environmental implications are also increasing at an alarming rate. Cloud service providers are under immense pressure to significantly reduce both such implications for promoting green computing. Maintaining the desired level of Quality of Service (QoS) without violating the Service Level Agreement (SLA), whilst attempting to reduce the usage of the datacentre resources is an obvious challenge for the Cloud service providers. Scaling the level of active server resources in accordance with the predicted incoming workloads is one possible way of reducing the …

Genre Prediction To Inform The Recommendation Process, Nevena Dragovic, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

In this paper we present a time-based genre prediction strategy that can inform the book recommendation process. To explicitly consider time in predicting genres of interest, we rely on a popular time series forecasting model as well as reading patterns of each individual reader or group of readers (in case of libraries or publishing companies). Based on a conducted initial assessment using the Amazon dataset, we demonstrate our strategy outperforms its baseline counter-part.

Hyperlink: Virtual Machine Introspection And Memory Forensic Analysis Without Kernel Source Code, Jidong Xiao, Lei Lu, Haining Wang, Xiaoyun Zhu

Computer Science Faculty Publications and Presentations

Virtual Machine Introspection (VMI) is an approach to inspecting and analyzing the software running inside a virtual machine from the hypervisor. Similarly, memory forensics analyzes the memory snapshots or dumps to understand the runtime state of a physical or virtual machine. The existing VMI and memory forensic tools rely on up-to-date kernel information of the target operating system (OS) to work properly, which often requires the availability of the kernel source code. This requirement prevents these tools from being widely deployed in real cloud environments. In this paper, we present a VMI tool called HyperLink that partially retrieves running process …

Behaviorism Is Not Enough: Better Recommendations Through Listening To Users, Michael D. Ekstrand, Martijn C. Willemsen

Computer Science Faculty Publications and Presentations

Behaviorism is the currently-dominant paradigm for building and evaluating recommender systems. Both the operation and the evaluation of recommender system applications are most often driven by analyzing the behavior of users. In this paper, we argue that listening to what users say — about the items and recommendations they like, the control they wish to exert on the output, and the ways in which they perceive the system — and not just observing what they do will enable important developments in the future of recommender systems. We provide both philosophical and pragmatic motivations for this idea, describe the various points …

Finding, Understanding And Learning: Making Information Discovery Tasks Useful For Children And Teachers, Ion Madrazo Azpiazu, Nevena Dragovic, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

We present our ongoing efforts on the development of a search environment tailored to 6-15 year-olds that can foster learning though retrieval of materials that not only satisfy the information needs of users but also match their reading abilities. YouUnderstood.me is an enhanced environment based on a popular search engine specifically designed to help students deal with search for learning tasks, and allow teachers to track their progress. An initial assessment conducted on YouUnderstood.me and well-known (children-oriented) search engines based on queries generated by K-9 students, showcases the need for this type of environment.

“One Size Doesn’T Fit All": Helping Users Find Events From Multiple Perspectives, Sean Maclachlan, Stacey Donohue, Nevena Dragovic, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

In this demo, we showcase a novel mobile application that offers various ways to present recommendations to users. While the majority of the existing applications in the tourism domain either focus on event recommendation or event browsing, our mobile application acknowledges the fact that users have diffrent interests at different times and for different occasions. Consequently, while suggested events are filtered and ranked by proximity and date ranges to ensure they suit users' needs, each user is allowed to choose how to access these suggestions in one of four ways: search, categorized browsing, following, and traditional recommendations.

Anything Fun Going On?: A Simple Wizard To Avoid The Cold-Start Problem For Event Recommenders, Stacey Donohue, Nevena Dragovic, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

In this demo, we showcase a set up wizard designed to bypass the cold start problem that often affects recommendation systems in the event domain. We have developed a mobile application for tourists, RelEVENT, which allows them to quickly and non-intrusively set up preferences and/or interests related to events. This will directly affect the degree to which they can receive personalized recommendations on-the-fly and become aware of events happening around town that might be appealing to them.

Identifying And Scheduling Loop Chains Using Directives, Ian J. Bertolacci, Michelle Mills Strout, Stephen Guzik, Jordan Riley, Catherine Olschanowsky

Computer Science Faculty Publications and Presentations

Exposing opportunities for parallelization while explicitly managing data locality is the primary challenge to porting and optimizing existing computational science simulation codes to improve performance and accuracy. OpenMP provides many mechanisms for expressing parallelism, but it primarily remains the programmer’s responsibility to group computations to improve data locality. The loopchain abstraction, where data access patterns are included with the specification of parallel loops, provides compilers with sufficient information to automate the parallelism versus data locality tradeoff. In this paper, we present a loop chain pragma and an extension to the omp for to enable the specification of loop chains and …

Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees, Christopher Taylor, Arun D. Kulkarni, Kouider Mokhtari

Computer Science Faculty Publications and Presentations

The assessment of students’ metacognitive knowledge and skills about reading is critical in determining their ability to read academic texts and do so with comprehension. In this paper, we used induction trees to extract metacognitive knowledge about reading from a reading strategies dataset obtained from a group of 1636 undergraduate college students. Using a C4.5 algorithm, we constructed decision trees, which helped us classify participants into three groups based on their metacognitive strategy awareness levels consisting of global, problem-solving and support reading strategies. We extracted rules from these decision trees, and in order to evaluate accuracy of the extracted rules, …

From Boolean Equalities To Constraints, Sergio Antoy, Michael Hanus

Computer Science Faculty Publications and Presentations

Although functional as well as logic languages use equality to discriminate between logically different cases, the operational meaning of equality is different in such languages. Functional languages reduce equational expressions to their Boolean values, True or False, logic languages use unification to check the validity only and fail otherwise. Consequently, the language Curry, which amalgamates functional and logic programming features, offers two kinds of equational expressions so that the programmer has to distinguish between these uses. We show that this distinction can be avoided by providing an analysis and transformation method that automatically selects the appropriate operation. Without this distinction …

Building An Islamic Financial Information System Based On Policy Managements, Izzat Alsmadi, Mohammad Zarour

Computer Science Faculty Publications and Presentations

For many banks and customers in the Middle East and Islamic world, the availability and the ability to apply Islamic Shariah rules on financial activities is very important. In some cases, business and technical barriers can limit the ability to apply and offer financial services that are implemented according to Shariah rules.

In this paper, we discuss enforcing Shariah rules from information technology viewpoint and show how such rules can be implemented and enforced in a financial establishment. Security authorization standard XACML is extended to consider Shariah rules. In this research XACML architecture, that is used and applied in many …

A Constraint Language For Static Semantic Analysis Based On Scope Graphs, Hendrik Van Antwerpen, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth

Computer Science Faculty Publications and Presentations

In previous work, we introduced scope graphs as a formalism for describing program binding structure and performing name resolution in an AST-independent way. In this paper, we show how to use scope graphs to build static semantic analyzers. We use constraints extracted from the AST to specify facts about binding, typing, and initialization. We treat name and type resolution as separate building blocks, but our approach can handle language constructs—such as record field access—for which binding and typing are mutually dependent.We also refine and extend our previous scope graph theory to address practical concerns including ambiguity checking and support for …

Reinforced Imitative Graph Learning For Mobile User Profiling, Dongjie Wang, Pengyang Wang, Yanjie Fu, Kunpeng Liu, Hui Xiong, Charles Hughes

Computer Science Faculty Publications and Presentations

Mobile user profiling refers to the efforts of extracting users’ characteristics from mobile activities. In order to capture the dynamic varying of user characteristics for generating effective user profiling, we propose an imitation-based mobile user profiling framework. Considering the objective of teaching an autonomous agent to imitate user mobility based on the user’s profile, the user profile is the most accurate when the agent can perfectly mimic the user behavior patterns. The profiling framework is formulated into a reinforcement learning task, where an agent is a next-visit planner, an action is a POI that a user will visit next, and …

A Scaffolded, Metamorphic Ctf For Reverse Engineering, Wu-Chang Feng

Computer Science Faculty Publications and Presentations

Hands-on Capture-the-Flag (CTF) challenges tap into and cultivate the intrinsic motivation within people to solve puzzles, much in the same way Sudoku and crossword puzzles do. While the format has been successful in security competitions, there have been a limited number of attempts to integrate them into a classroom environment. This paper describes MetaCTF, a metamorphic set of CTF challenges for teaching reverse code engineering. MetaCTF is 1) scaffolded in a way that allows students to make incremental progress, 2) integrated with the course material so that students can immediately apply knowledge gained in class, 3) polymorphic and metamorphic so …

Compiling Collapsing Rules In Certain Constructor Systems, Sergio Antoy, Andy Jost

Computer Science Faculty Publications and Presentations

The implementation of functional logic languages by means of graph rewriting requires a special handling of collapsing rules. Recent advances about the notion of a needed step in some constructor systems offer a new approach to this problem. We present two results: a transformation of a certain class of constructor-based rewrite systems that eliminates collapsing rules, and a rewrite-like relation that takes advantage of the absence of collapsing rules. We formally state and prove the correctness of these results. When used together, these results simplify without any loss of efficiency an implementation of graph rewriting and consequently of functional logic …

Automatic Fault Injection For Driver Robustness Testing, Kai Cong, Li Lei, Zhenkun Yang, Fei Xie

Computer Science Faculty Publications and Presentations

Robustness testing is a crucial stage in the device driver development cycle. To accelerate driver robustness testing, effective fault scenarios need to be generated and injected without requiring much time and human effort. In this pa- per, we present a practical approach to automatic runtime generation and injection of fault scenarios for driver robust- ness testing. We identify target functions that can fail from runtime execution traces, generate effective fault scenarios on these target functions using a bounded trace-based it- erative strategy, and inject the generated fault scenarios at runtime to test driver robustness using a permutation-based injection mechanism. We …

Naturalized Communication And Testing, Marly Roncken, Swetha Mettala Gilla, Hoon Park, Navaneeth Prasannakumar Jamadagni, Christopher Cowan, Ivan Sutherland

Computer Science Faculty Publications and Presentations

We ”naturalize” the handshake communication links of a self-timed system by assigning the capabilities of filling and draining a link and of storing its full or empty status to the link itself. This contrasts with assigning these capabilities to the joints, the modules connected by the links, as was previously done. Under naturalized communication, the differences between Micropipeline, GasP, Mousetrap, and Click circuits are seen only in the links — the joints become identical; past, present, and future link and joint designs become interchangeable. We also “naturalize” the actions of a self-timed system, giving actions status equal to states — …

Micro-Policies: Formally Verified, Tag-Based Security Monitors, Arthur Azevedo De Amorim, Maxime Denes, Nick Giannarakis, Cătălin Hriţcu, Benjamin C. Pierce, Antal Spector-Zabusky, Andrew Tolmach

Computer Science Faculty Publications and Presentations

Recent advances in hardware design have demonstrated mechanisms allowing a wide range of low-level security policies (or micro-policies) to be expressed using rules on metadata tags. We propose a methodology for defining and reasoning about such tag-based reference monitors in terms of a high-level “symbolic machine,” and we use this methodology to define and formally verify micro-policies for dynamic sealing, compartmentalization, control-flow integrity, and memory safety; in addition, we show how to use the tagging mechanism to protect its own integrity. For each micro-policy, we prove by refinement that the symbolic machine instantiated with the policy’s rules embodies a high-level …

A Novel Root Based Arabic Stemmer, Mohammed N. Al-Kabi, Saif A. Kazakzeh, Belal M. Abu Ata, Saif A. Al-Rababah, Izzat M. Alsmadi

Computer Science Faculty Publications and Presentations

Stemming algorithms are used in information retrieval systems, indexers, text mining, text classifiers etc., to extract stems or roots of different words, so that words derived from the same stem or root are grouped together. Many stemming algorithms were built in different natural languages. Khoja stemmer is one of the known and widely used Arabic stemmers. In this paper, we introduced a new light and heavy Arabic stemmer. This new stemmer is presented in this study and compared with two well-known Arabic stemmers. Results showed that accuracy of our stemmer is slightly better than the accuracy yielded by each one …

Evaluation Of Spam Impact On Arabic Websites Popularity, Mohammed N. Al-Kabi, Izzat M. Alsmadi, Heider A. Wahsheh

Computer Science Faculty Publications and Presentations

The expansion of the Web and its information in all aspects of life raises the concern of how to trust information published on the Web especially in cases where publisher may not be known. Websites strive to be more popular and make themselves visible to search engines and eventually to users. Website popularity can be measured using several metrics such as the Web traffic (e.g. Website: visitors’ number and visited page number). A link or page popularity refers to the total number of hyperlinks referring to a certain Web page. In this study, several top ranked Arabic Websites are selected …

Delay Line As A Chemical Reaction Network, Josh Moles, Peter Banda, Christof Teuscher

Computer Science Faculty Publications and Presentations

Chemistry as an unconventional computing medium presently lacks a systematic approach to gather, store, and sort data over time. To build more complicated systems in chemistries, the ability to look at data in the past would be a valuable tool to perform complex calculations. In this paper we present the first implementation of a chemical delay line providing information storage in a chemistry that can reliably capture information over an extended period of time. The delay line is capable of parallel operations in a single instruction, multiple data (SIMD) fashion.

Using Michaelis-Menten kinetics, we describe the chemical delay line implementation …

Multispectral Image Analysis Using Random Forest, Barrett Lowe, Arun Kulkarni

Computer Science Faculty Publications and Presentations

Classical methods for classification of pixels in multispectral images include supervised classifiers such as the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a method that generates many classifiers and aggregates their results. Breiman proposed Random Forestin 2001 for classification and clustering. Random Forest grows many decision trees for classification. To classify a new object, the input vector is run through each decision tree in the forest. Each tree gives a classification. The forest chooses the classification having the most votes. Random …

Static Conflict Detection For A Policy Language, Alix Trou, Robert Dockins, Andrew Tolmach

Computer Science Faculty Publications and Presentations

We present a static control flow analysis used in the Simple Unified Policy Programming Language (SUPPL) compiler to detect internally inconsistent policies. For example, an access control policy can decide to both “allow” and “deny” access for a user; such an inconsistency is called a conflict. Policies in Suppl. follow the Event-Condition-Action paradigm; predicates are used to model conditions and event handlers are written in an imperative way. The analysis is twofold; it first computes a superset of all conflicts by looking for a combination of actions in the event handlers that might violate a user-supplied definition of conflicts. SMT …

A Demonstration Of The Bigdawg Polystore System, Aaron J. Elmore, Jennie Duggan, Michael Stonebraker, Magdalena Balazinska, Ugur Cetintemel, Vijay Gadepally, J. Heer, Bill Howe, Jeremy Kepner, Tim Kraska, Samuel Madden, David Maier, Timothy G. Mattson, S. Papadopoulos, J. Parkhurst, Nesime Tatbul, Manasi Vartak, Stan Zdonik

Computer Science Faculty Publications and Presentations

This paper presents BigDAWG, a reference implementation of a new architecture for “Big Data” applications. Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-storage-system queries. Guided by the principle that “one size does not fit all”, we build on top of a variety of storage engines, each designed for a specialized use case. To illustrate the promise of this approach, we demonstrate its effectiveness on a hospital application using data from an intensive care unit (ICU). This complex application serves the needs of doctors and researchers …

Needed Computations Shortcutting Needed Steps, Sergio Antoy, Jacob Johannsen, Steven Libby

Computer Science Faculty Publications and Presentations

We define a compilation scheme for a constructor-based, strongly-sequential, graph rewriting system which shortcuts some needed steps. The object code is another constructor-based graph rewriting system. This system is normalizing for the original system when using an innermost strategy. Consequently, the object code can be easily implemented by eager functions in a variety of programming languages. We modify this object code in a way that avoids total or partial construction of the contracta of some needed steps of a computation. When computing normal forms in this way, both memory consumption and execution time are reduced compared to ordinary rewriting computations …

The Expression Problem, Gracefully, Andrew P. Black

Computer Science Faculty Publications and Presentations

The “Expression Problem” was brought to prominence by Wadler in 1998. It is widely regarded as illustrating that the two mainstream approaches to data abstraction — procedural abstraction and type abstraction— are complementary, with the strengths of one being the weaknesses of the other. Despite an extensive literature, the origin of the problem remains ill-understood. I show that the core problem is in fact the use of global constants, and demonstrate that an important aspect of the problem goes away when Java is replaced by a language like Grace, which eliminates them.

The Grace Programming Language Draft Specification Version 0.5. 2025, Andrew P. Black, Kim B. Bruce, James Noble

Computer Science Faculty Publications and Presentations

This is a specification of the Grace Programming Language. This specification is notably incomplete, and everything is subject to change. For discussion and rationale, see http://gracelang.org.