Computer Sciences Commons^™

Lagrangian Analysis Of Vector And Tensor Fields: Algorithmic Foundations And Applications In Medical Imaging And Computational Fluid Dynamics, Zi'ang Ding

Open Access Dissertations

Both vector and tensor fields are important mathematical tools used to describe the physics of many phenomena in science and engineering. Effective vector and tensor field visualization techniques are therefore needed to interpret and analyze the corresponding data and achieve new insight into the considered problem. This dissertation is concerned with the extraction of important structural properties from vector and tensor datasets. Specifically, we present a unified approach for the characterization of distinguished manifolds that form the skeleton of vector and tensor fields and play a key role in understanding their properties.

This dissertation makes several important contributions in this …

Fine-Tuning An Algorithm For Semantic Document Clustering Using A Similarity Graph, Lubomir Stanchev

Computer Science and Software Engineering

In this article, we examine an algorithm for document clustering using a similarity graph. The graph stores words and common phrases from the English language as nodes and it can be used to compute the degree of semantic similarity between any two phrases. One application of the similarity graph is semantic document clustering, that is, grouping documents based on the meaning of the words in them. Since our algorithm for semantic document clustering relies on multiple parameters, we examine how fine-tuning these values affects the quality of the result. Specifically, we use the Reuters-21578 benchmark, which contains 11,362 newswire stories …

The History Of Algorithmic Complexity, Audrey A. Nasar

Publications and Research

This paper provides a historical account of the development of algorithmic complexity in a form that is suitable to instructors of mathematics at the high school or undergraduate level. The study of algorithmic complexity, despite being deeply rooted in mathematics, is usually restricted to the computer science curriculum. By providing a historical account of algorithmic complexity through a mathematical lens, this paper aims to equip mathematics educators with the necessary background and framework for incorporating the analysis of algorithmic complexity into mathematics courses as early on as algebra or pre-calculus.

The R Journal (December 2016) 8(2): Complete Issue, The R Foundation

The R Journal

Editorial, Michael Lawrence

Contributed Research Articles

multipleNCC: Inverse Probability Weighting of Nested Case-Control Data, Nathalie C. Støer and Sven Ove Samuelsen

QPot: An R Package for Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, and Karen C. Abbott

Design of the TRONCO BioConductor Package for TRanslational ONCOlogy, Marco Antoniotti, Giulio Caravagna, Luca De Sano, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, and Daniele Ramazzotti

diverse: An R Package to Analyze Diversity in Complex Systems, Miguel R. Guevara, Dominik Hartmann, and Marcelo Mendoza

Simulating Correlated Binary and Multinomial Responses under Marginal Model Specification: …

Non Markovian Queue With Two Types Service Optional Re-Service And General Vacation Distribution, K. Sathiya, G. Ayyappan

Applications and Applied Mathematics: An International Journal (AAM)

We consider a single server batch arrival queueing system, where the server provides two types of heterogeneous service. A customer has the option of choosing either type 1 service with probability p1 or type 2 service with probability p2 with the service times follow general distribution. After the completion of either type 1 or type 2 service a customer has the option to repeat or not to repeat the type 1 or type 2 service. As soon as the customer service is completed, the server will take a vacation with probability θ or may continue staying in the system with …

Grading That Takes Into Account The Need To Learn From Mistakes, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

It is well known that the best way to learn the new material is to try it, to make mistakes, and to learn from these mistakes. However, the current grading scheme, in which the overall grade is a weighted average of the grades for all the assignments, exams, etc., does not encourage mistakes: any mistake decreases the grade on the corresponding assignment and thus, decreases the overall grade for the class. It is therefore desirable to modify the usual grading scheme, so that it will take into account -- and encourage -- learning by mistakes. Such a modification is proposed …

Structure Of Filled Functions: Why Gaussian And Cauchy Templates Are Most Efficient, Vyacheslav Kalashnikov, Vladik Kreinovich, José Guadalupe Flores Muñiz, Nataliya Kalashnykova

Departmental Technical Reports (CS)

One of the main problems of optimization algorithms is that they often end up in a local optimum. It is, therefore, necessary to make sure that the algorithm gets out of the local optimum and eventually reaches the global optimum. One of the promising ways guiding one from the local optimum is prompted by the filled function method. It turns out that empirically, the best smoothing functions to use in this method are the Gaussian and Cauchy functions. In this paper, we provide a possible theoretical explanation of this empirical effect.

The Transition Experiences Of International Graduate Students In Clark University School Of Professional Studies, Xuesong Huang, Mingyang Lian, Dang Trung, Jay Sheth, Yuwei Yang, Irina Klimenko

School of Professional Studies

In the last decade, the School of Professional Studies at Clark University has witnessed a sharp increase in international students. More and more international students in the millennial generation have entered the School of Professional Studies pursuing one of the two-year graduate programs: Master of Science in Professional Studies, Master of Science in Public Administration, and Master of Science in Information Technology. In the past, working adult student dominant the program. These students already had a career outside the classrooms before them came to study. The millennial international students have generated new adjustment problems. Some of the transition issues of …

A Heuristic Solution Of The Toll Optimal Problem With Congestion Affected Costs, Vyacheslav Kalashnikov, José Guadalupe Flores Muñiz, Nataliya Kalashnykova

Departmental Technical Reports (CS)

An important problem concerning the toll roads is the setting of appropriate costs for driving along paid arcs of a transportation network. Our paper treats this problem as a bilevel programming model. At the upper level, decisions are made by a public regulator/private company that administers the toll roads endeavoring to elevate their benefits. At the lower level, several transportation companies/individual users appease the existing demand for transportation of goods or passengers while selecting the routes that would minimize their total travel costs. In contrast to the previous models, here the lower level problem assumes quadratic costs implied by the …

On The Vulnerabilities Of Voronoi-Based Approaches To Mobile Sensor Deployment, Novella Bartolini, Stefano Ciavarella, Simone Silvestri, Thomas La Porta

Computer Science Faculty Research & Creative Works

Mobile sensor networks are the most promising solution to cover an Area of Interest (AoI) in safety critical scenarios. Mobile devices can coordinate with each other according to a distributed deployment algorithm, without resorting to human supervision for device positioning and network configuration. In this paper, we focus on the vulnerabilities of the deployment algorithms based on Voronoi diagrams to coordinate mobile sensors and guide their movements. We give a geometric characterization of possible attack configurations, proving that a simple attack consisting of a barrier of few compromised sensors can severely reduce network coverage. On the basis of the above …

Cloud-Enhanced Robotic System For Smart City Crowd Control, Akhlaqur Rahman, Jiong Jin, Antonio Cricenti, Ashfaqur Rahman, Marimuthu Palaniswami, Tony Tie Luo

Computer Science Faculty Research & Creative Works

Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS). However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a …

Why Growth Of Cancerous Tumors Is Gompertzian: A Symmetry-Based Explanation, Pedro Barragan Olague, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that the growth of a cancerous tumor is well described by the Gompertz's equation. The existing explanations for this equation rely on specifics of cell dynamics. However, the fact that for many different types of tumors, with different cell dynamics, we observe the same growth pattern, make us believe that there should be a more fundamental explanation for this equation. In this paper, we show that a symmetry-based approach indeed leads to such an explanation: indeed, out of all scale-invariant growth dynamics, the Gompertzian growth is the closest to the linear-approximation exponential growth model.

Fuzzy Data Processing Beyond Min T-Norm, Andrzej Pownuk, Vladik Kreinovich, Songsak Sriboonchitta

Departmental Technical Reports (CS)

Usual algorithms for fuzzy data processing -- based on the usual form of Zadeh's extension principle -- implicitly assume that we use the min "and"-operation (t-norm). It is known, however, that in many practical situations, other t-norms more adequately describe human reasoning. It is therefore desirable to extend the usual algorithms to situations when we use t-norms different from min. Such an extension is provided in this paper.

What Is The Best Way To Add Large Number Of Integers: Number-By-Number As Computers Do Or Lowest-Digits-Than-Next-Digits-Etc As We Humans Do?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

When we need to add several integers, computers add them one by one, while we usually add them digit by digit: first, we add all the lowest digits, then we add all next lowest digits, etc. Which way is faster? Should we learn from computers or should we teach computers to add several integers our way?

In this paper, we show that the computer way is faster. This adds one more example to the list of cases when computer-based arithmetic algorithms are much more efficient than the algorithms that we humans normally use.

Fuzzy Pareto Solution In Multi-Criteria Group Decision Making With Intuitionistic Linguistic Preference Relation, Bui Cong Cuong, Vladik Kreinovich, Le Hoang Son, Nilanjan Dey

Departmental Technical Reports (CS)

In this paper, we investigate the multi criteria group decision making with intuitionistic linguistic preference relation. The concept of Fuzzy Collective Solution (FCS) is used to evaluate and rank the candidate solution sets for modeling under linguistic assessments. Intuitionistic linguistic preference relation and associated aggregation procedures are then defined in a new concept of Fuzzy Pareto Solution. Numerical examples are presented to demonstrate computing procedures. The results affirm efficiency of the proposed method.

Predicting Human Behavior Based On Survey Response Patterns Using Markov And Hidden Markov Models, Arun Kumar Pokharna

Computer Science and Engineering Theses - Archive

With technological advancements in World Wide Web (www), connecting with people for gathering information has become common. Among several ways, surveys are one of the most commonly used way of collecting information from people. Given a specific objective, multiple surveys are conducted to collect various pieces of information. This collected information, in the form of survey responses, can be categorical values or a descriptive text that represents information regarding the survey question. If additional details regarding the response behavior, scenario in which survey is being responded, or survey outcomes is available, machine learning and prediction modeling can be used to …

Linchpin: A Yaml Template Based Cross Cloud Resource Provisioning Tool, Samvaran Kashyap Rallabandi

Computer Science and Engineering Theses - Archive

A cloud application developed, will have a specific requirement of particular cloud resources and software stack to be deployed to make it run. Resource templates enable the environment design and deployment required for an application. A template describes the infrastructure of the cloud application in a text file which includes servers, floating/public IP, storage volumes, etc. This approach is termed “Infrastructure as a code.” In Amazon public cloud, OpenStack private cloud, Google cloud these templates are called as cloud formation templates, HOT (Heat orchestration templates), Google cloud templates respectively. Though the existing template systems give a flexibility for the end …

Cloud Hopper: A Unified Cloud Solution To Manage Heterogeneous Clouds, Shraddha Jain

Computer Science and Engineering Theses - Archive

Cloud environments are built on virtualization platforms which offer scalability, on-demand pricing, high performance, elasticity, easy accessibility of the resources and cost efficient services. Most of the small and large businesses use cloud computing to take advantage of these features. The usage of the cloud resources depends on the requirements of the organizations. With the advent of cloud computing, the traditional way of handling machines by the IT professionals has decreased. However, it leads to wastage of resources due to inadequate monitoring and improper management of resources. Often it happens that the cloud resources once deployed are forgotten, and they …

Machine Learning Based Datacenter Monitoring Framework, Ravneet Singh Sidhu

Computer Science and Engineering Theses - Archive

Monitoring the health of large data centers is a major concern with the ever-increasing demand of grid/cloud computing and the higher need of computational power. In a High Performance Computing (HPC) environment, the need to maintain high availability makes monitoring tasks and hardware more daunting and demanding. As data centers grow it becomes hard to manage the complex interactions between different systems. Many open source systems have been implemented which give specific state of any individual machine using Nagios, Ganglia or Torque monitoring software. In this work we focus on the detection and prediction of data center anomalies by using …

Mavroomie: An End-To-End Architecture For Finding Compatible Roommates Based On User Preferences, Vijendra Bhogadi

Computer Science and Engineering Theses - Archive

Team Formation is widely studied in literature as a method for forming teams or groups under certain constraints. However, very few works address the aspect of collaboration while forming groups under certain constraints. Motivated by the collaborative team formation, we try to extend the problem of team formation to a general problem in the real world scenario of finding compatible roommates to share a place. There are numerous applications like “roommates.com" ,”roomiematch.com" , “Roomi” which try to find roommates based on geographical and cost factors and ignore the important human factors which can play a substantial role in finding a …

Evaluation Of Html Tag Susceptibility To Statistical Fingerprinting For Use In Censorship Evasion, Kelly Scott French

Computer Science and Engineering Theses - Archive

The ability to speak freely has always been a source of conflict between rulers and the people over which they exert power. This conflict usually takes the form of State-sponsored censorship with occasional instances of commercial efforts typically to silence criticism or squelch dissent, and people's efforts to evade such censorship. This is even more so evident in the current environment with its ever-growing number of communication technologies and platforms available to individuals around the world. If the face of efforts to control communication before it is posted or to prevent the discovery of information that exists outside of the …

Remote Patient Monitoring Using Health Bands With Activity Level Prescription, Pranay Shirolkar

Computer Science and Engineering Theses - Archive

With the advent of new commercially available consumer grade fitness and health devices, it is now possible and very common for users to obtain, store, share and learn about some of their important physiological metrics such as steps taken, heart rate, quality of sleep and skin temperature. For devices with this wearable technology, it is common to find these sensors embedded in a smart watch, or dedicated wearable wrist bands such that among other functionalities of a wearable device, it is capable of smartly assisting users about their activity levels by leveraging the fact that these devices can be, and …

Searching And Classifying Mobile Application Screenshots, Adis Kovacevic

Computer Science and Engineering Theses - Archive

Searching for a particular application layout image is a challenging task. No search provider gives an adequate method to filter the query results to the look of a mobile application. Searching for a particular style of application requires lots of manual time sifting through the results returned. Search engines such as Google are too broad and return too many unrelated results without providing sufficient filters on things like category or layout type. This paper proposes a technique that would allow the searching and classifying of mobile application screenshots based on the layout of the content, the category of the application, …

Integration Of Apache Mrql Query Language With Apache Storm Realtime Computational System, Achyut Paudel

Computer Science and Engineering Theses - Archive

The use of real time processing of data has increased in recent years with the increase of data captured by social media platforms, IOT and other big data applications. The processing of data in real time has been an important aspect of the day from finding the trends over the internet to fraud detection of in the banking transactions. Finding relevant information from large amount of data has always been a difficult problem to solve. MRQL is a query language that can be used on top of different big data platform such as Apache Hadoop, Flink, Hama, and Spark that …

Extracting And Modeling Useful Information From Videos For Supporting Continuous Queries, Manish Kumar Annappa

Computer Science and Engineering Theses - Archive

Automating video stream processing for inferring situations of interest has been an ongoing challenge. This problem is currently exacerbated by the volume of surveillance/monitoring videos generated. Currently, manual or context-based customized techniques are used for this purpose. To the best to our knowledge the attempted work in this area use a custom query language to extract data and infer simple situations from the video streams, thus adding an additional overhead to learn their query language. Objective of the work in this thesis is to develop a framework that extracts data from video streams generating a data representation such that simple …

Cell Segmentation In Cancer Histopathology Images Using Convolutional Neural Networks, Viswanathan Kavassery Rajalingam

Computer Science and Engineering Theses - Archive

Cancer, the second most dreadful disease causing large scale deaths in humans is characterized by uncontrolled growth of cells in the human body and the ability of those cells to migrate from the original site and spread to distant sites. The major proportion of deaths in cancer is due to improper primary diagnosis that raises the need for Computer Aided Diagnosis (CAD). Digital Pathology is a technique that acts as second set of eyes to radiologists in delivering expert level preliminary diagnosis for cancer patients. Cell segmentation is a challenging step in digital pathology that identifies cell regions from micro-slide …

Convolutional And Recurrent Neural Networks For Pedestrian Detection, Vivek Arvind Balaji

Computer Science and Engineering Theses - Archive

Pedestrian Detection in real time has become an interesting and a challenging problem lately. With the advent of autonomous vehicles and intelligent traffic monitoring systems, more time and money are being invested into detecting and locating pedestrians for their safety and towards achieving complete autonomy in vehicles. For the task of pedestrian detection, Convolutional Neural Networks (ConvNets) have been very promising over the past decade. ConvNets have a typical feed-forward structure and they share many properties with the visual system of the human brain. On the other hand, Recurrent Neural Networks (RNNs) are emerging as an important technique for image …

Learning Perception To Action Mapping For Functional Imitation, Bhupender Singh

Computer Science and Engineering Theses - Archive

Imitation leaning is the learning of advanced behavior whereby an agent acquires a skill by observing another's behavior while performing the same skill. The main objective of imitation learning is to make robots usable for a variety of tasks without programming them but by simply demonstrating new tasks. The power of this approach arises since end users of such robots will frequently not know how to program the robot, might not understand the dynamics and behavioral capabilities of the system, and might not know how to program these robots to get different/new tasks done. Some challenges in achieving imitation capabilities …

Cloud Merge: Heterogeneous Cloud Application Migration Using Platform As A Service, Mayank Jain

Computer Science and Engineering Theses - Archive

With the evolution of cloud service providers offering numerous services such as SaaS, IaaS, PaaS, options for enterprises to choose the best set of services under optimal costs have also increased. The migration of web applications across these heterogeneous platforms comes with ample of options to choose from, providing users the flexibility to choose the best options suiting their requirements. This process of migration must be automated to ensure the security, performance and availability, keeping the cost to be optimal while moving the application from one platform to another. A multi-tier web application will have many dependencies such as the …

Improving Memorization And Long Term Recall Of System Assigned Passwords, Jayesh Doolani

Computer Science and Engineering Theses - Archive

Systems assigned password have guaranteed robustness against guessing attacks, but they are hard to memorize. To make system assigned passwords more usable, it is of prime importance that systems that assign random password also assist users with memorization and recall. In this work, we have designed a novel technique that employs rote memorization inform of an engaging game, which is played during the account registration process. Based on prior work on chunking, we break a password into three equal chunks, and then the game helps plant those chunks in memory. We present the findings of 17 participant user-study, where we …