Computer Sciences Commons^™

Anticipation In Dynamic Environments: Deciding What To Monitor, Zohreh A. Dannenhauer

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In dynamic environments, external changes may occur that may affect planning decisions and goal choices. We claim that an intelligent agent should actively watch for what can go wrong and anticipate changes in the environment that allows the changing of its plan or changing of a given goal. In this thesis, we focus on the relationship between perception, act, interpretation, and planning. We claim that these components are not independent and need to interact with each other to help the agent succeed in achieving its goals and plans. If newly encountered world information affects the plan, the agent adapts to …

Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov

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Elliptic Curve Cryptography (ECC) is a public-key cryptography system. Elliptic Curve Cryptography (ECC) can achieve the same level of security as the public-key cryptography system, RSA, with a much smaller key size. It is a promising public key cryptography system with regard to time efficiency and resource utilization. This thesis focuses on the software implementations of ECC over finite field GF(p) with two distinct implementations of the Big Integer classes using character arrays, and bit sets in C++ programming language. Our implementation works on the ECC curves of the form y^2 = x^3 + ax + b (mod p). The …

Rules With Right Hand Existential Or Disjunction With Rowltab, Sri Jitendra Satpathy

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One hotly debated research topic is, “What is the best approach for modeling ontologies?”. In the earlier stages of modeling ontologies, researchers have favored the usage of description logic to capture knowledge. One such choice is the Web Ontology Language (OWL) that is based on description logic. Many tools were designed around this principle and are still widely being used to model and explore ontologies. However, not all users find description logic to be intuitive, at least not without an extensive background in formal logics. Due to this, researchers have tried to explore other ways that will enable such users …

Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth

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The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches …

Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi

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In recent years, the research in deep learning and knowledge engineering has made a wide impact on the data and knowledge representations. The research in knowledge engineering has frequently focused on modeling the high level human cognitive abilities, such as reasoning, making inferences, and validation. Semantic Web Technologies and Deep Learning have an interest in creating intelligent artifacts. Deep learning is a set of machine learning algorithms that attempt to model data representations through many layers of non-linear transformations. Deep learning is in- creasingly employed to analyze various knowledge representations mentioned in Semantic Web and provides better results for Semantic …

Leveraging Blockchain To Mitigate The Risk Of Counterfeit Microelectronics In Its Supply Chain, Aman Ali Pogaku

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System on Chip (SoC) is the backbone component of the electronics industry nowadays. ASIC and FPGA-based SoCs are the two most popular methods of manufacturing SoCs. However, both ASIC and FPGA industries are plagued with risks of counterfeits due to the limitations in Security, Accountability, Complexity, and Governance of their supply chain management. As a result, the current practices of these microelectronics supply chain suffer from performance and efficiency bottlenecks. In this research, we are incorporating blockchain technology into the FPGA and ASIC microelectronic supply chain to help mitigate the risk of counterfeit microelectronics through a secure and decentralized solution …

Design And Development Of An Immersive Simulation For Social Determinants Of Health Training, Lahari Surapaneni

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This thesis research project focuses on design and development of an immersion simulation-based training tool that help raise the social determinants of health (SDOH) awareness among the health care providers. Compared to existing classroom lecture and/or role-play based SDOH education approach, our immersion-simulation based approach provides an easy access and highly realistic experience to such training curriculum at anytime and anywhere with an Internet connection. Such an interactive and immersive exposure is critical to raise SDOH awareness and maintain long-lasting empathy towards actual patients in practice, and thus help providers to be better prepared when encountering with those patients. Particularly, …

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

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The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

Assessing The Quality Of Software Development Tutorials Available On The Web, Manziba A. Nishi

Theses and Dissertations

Both expert and novice software developers frequently access software development resources available on the Web in order to lookup or learn new APIs, tools and techniques. Software quality is affected negatively when developers fail to find high-quality information relevant to their problem. While there is a substantial amount of freely available resources that can be accessed online, some of the available resources contain information that suffers from error proneness, copyright infringement, security concerns, and incompatible versions. Use of such toxic information can have a strong negative effect on developer’s efficacy. This dissertation focuses specifically on software tutorials, aiming to automatically …

A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall

Electrical & Computer Engineering and Computer Science Faculty Publications

For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools …

Indirect Relatedness, Evaluation, And Visualization For Literature Based Discovery, Sam Henry

Theses and Dissertations

The exponential growth of scientific literature is creating an increased need for systems to process and assimilate knowledge contained within text. Literature Based Discovery (LBD) is a well established field that seeks to synthesize new knowledge from existing literature, but it has remained primarily in the theoretical realm rather than in real-world application. This lack of real-world adoption is due in part to the difficulty of LBD, but also due to several solvable problems present in LBD today. Of these problems, the ones in most critical need of improvement are: (1) the over-generation of knowledge by LBD systems, (2) a …

Multi-Branch Ensemble Learning Architecture Based On 3d Cnn For False Positive Reduction In Lung Nodule Detection, Haichao Cao, Hong Liu, Enmin Song, Chih-Cheng Hung

Faculty Articles

It is critical to have accurate detection of lung nodules in CT images for the early diagnosis of lung cancer. In order to achieve this, it is necessary to reduce the false positive rate of detection. Due to the heterogeneity of lung nodules and their similarity to the background, it is difficult to distinguish true lung nodules from numerous candidate nodules. In this paper, in order to solve this challenging problem, we propose a Multi-Branch Ensemble Learning architecture based on the three-dimensional (3D) convolutional neural networks (MBEL-3D-CNN). The method combines three key ideas: 1) constructing a 3D-CNN to make the …

Phenogeneranker: A Tool For Gene Prioritization Using Complete Multiplex Heterogeneous Networks, Cagatay Dursun, Naoki Shimoyama, Mary Shimoyama, Michael Schläppi, Serdar Bozdag

Computer Science Faculty Research and Publications

Uncovering genotype-phenotype relationships is a fundamental challenge in genomics. Gene prioritization is an important step for this endeavor to make a short manageable list from a list of thousands of genes coming from high-throughput studies. Network propagation methods are promising and state of the art methods for gene prioritization based on the premise that functionally-related genes tend to be close to each other in the biological networks.

In this study, we present PhenoGeneRanker, an improved version of a recently developed network propagation method called Random Walk with Restart on Multiplex Heterogeneous Networks (RWR-MH). PhenoGeneRanker allows multi-layer gene and disease networks. …

A Novel Methodology For Timely Brain Formations Of 3d Spatial Information With Application To Visually Impaired Navigation, Spyridon Manganas

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Human brain analysis and understanding pose several challenges due to the great complexity of the structural organization and the functional connectivity that characterizes the human brain. The ability of the brain to adapt in dynamic changes over time such as normal aging, neurodegenerative diseases or congenital brain malformations renders the brain’s exploration a particularly demanding and difficult task. In recent years, advances in brain imaging modalities and lately the multimodal fusion, combined with improvements in related technologies have greatly assisted the development of brain maps by providing insights regarding the overall brain structure and functionality. Even though the existence of …

Exploring The Impact Of (Not) Changing Default Settings In Algorithmic Crime Mapping - A Case Study Of Milwaukee, Wisconsin, Md Romael Haque, Katy Weathington, Shion Guha

Computer Science Faculty Research and Publications

Policing decisions, allocations and outcomes are determined by mapping historical crime data geo-spatially using popular algorithms. In this extended abstract, we present early results from a mixed-methods study of the practices, policies, and perceptions of algorithmic crime mapping in the city of Milwaukee, Wisconsin. We investigate this differential by visualizing potential demographic biases from publicly available crime data over 12 years (2005-2016) and conducting semi-structured interviews of 19 city stakeholders and provide future research directions from this study.

Two-Sided Value-Based Music Artist Recommendation In Streaming Music Services, J. Ren, Robert John Kauffman, D. King

Research Collection School Of Computing and Information Systems

Most work on music recommendations has focused on the consumer side not the provider side. We develop a two-sided value-based approach to music artist recommendation for a streaming music scenario. It combines the value yielded for the music industry and consumers in an integrated model. For the industry, the approach aims to increase the conversion rate of potential listeners to adopters, which produces new revenue. For consumers, it aims to improve their utility related to recommendations they receive. We use one year of listening records for 15,000+ Last.fm users to train and test the proposed recommendation model on 143 artists. …

A Compiler Target Model For Line Associative Registers, Paul S. Eberhart

Theses and Dissertations--Electrical and Computer Engineering

LARs (Line Associative Registers) are very wide tagged registers, used for both register-wide SWAR (SIMD Within a Register )operations and scalar operations on arbitrary fields. LARs include a large data field, type tags, source addresses, and a dirty bit, which allow them to not only replace both caches and registers in the conventional memory hierarchy, but improve on both their functions. This thesis details a LAR-based architecture, and describes the design of a compiler which can generate code for a LAR-based design. In particular, type conversion, alignment, and register allocation are discussed in detail.

Agent-Based Modeling And Simulation Approaches In Stem Education Research, Shanna R. Simpson-Singleton, Xiangdong Che

Journal of International Technology and Information Management

The development of best practices that deliver quality STEM education to all students, while minimizing achievement gaps, have been solicited by several national agencies. ABMS is a feasible approach to provide insight into global behavior based upon the interactions amongst agents and environments. In this review, we systematically surveyed several modeling and simulation approaches and discussed their applications to the evaluation of relevant theories in STEM education. It was found that ABMS is optimal to simulate STEM education hypotheses, as ABMS will sensibly present emergent theories and causation in STEM education phenomena if the model is properly validated and calibrated.

Mpa-Ibm Project Safer: Sense-Making Analytics For Maritime Event Recognition, Gavin Yeo, Shiau Hong Lim, Laura Wynter, Hifaz Hassan

Research Collection School Of Computing and Information Systems

Project SAFER, a collaboration between the Singapore Maritime and PortAuthority and the IBM Research Singapore Laboratory, was established to conceptualize,develop, and test new analytics-based technologies to enhance port operations and cater tothe increasing growth in vessel traffic in Singapore. The SAFER system addresses areas inmaritime management that have historically required significant human effort. Through acommon set of machine learning–based models, the SAFER system is able to forecast vesselarrival timings and potential traffic hot spots within port waters as well as to detectunusual behavior of vessels, from illegal bunkering (i.e., transfer of marine fuel) to shipsflouting Singapore regulations. The SAFER project …

Comparing Procedural Content Generation Algorithms For Creating Levels In Video Games, Zina Monaghan

Dissertations

Procedural Content Generation (PCG) is used frequently in games to increase replayability by introducing variety to playghrough of a game and reduce development time by allowing complex game worlds to be developed by a smaller team over a more limited amount of time.

Detection Of Offensive Youtube Comments, A Performance Comparison Of Deep Learning Approaches, Priyam Bansal

Dissertations

Social media data is open, free and available in massive quantities. However, there is a significant limitation in making sense of this data because of its high volume, variety, uncertain veracity, velocity, value and variability. This work provides a comprehensive framework of text processing and analysis performed on YouTube comments having offensive and non-offensive contents.

YouTube is a platform where every age group of people logs in and finds the type of content that most appeals to them. Apart from this, a massive increase in the use of offensive language has been apparent. As there are massive volume of new …

A First Look At Unfollowing Behavior On Github, Jing Jiang, David Lo, Yun Yang, Jianfeng Li, Li Zhang

Research Collection School Of Computing and Information Systems

Many open source software projects rely on contributors to fix bugs and contribute new features. On GitHub, developers often broadcast their activities to followers, which may entice followers to be project contributors. It is important to understand unfollowing behavior, maintain current followers, and attract some followers to become contributors in OSS projects.Our objective in this paper is to provide a comprehensive analysis of unfollowing behavior on GitHub. To the best of our knowledge, we present a first look at unfollowing behavior on GitHub. We collect a dataset containing 701,364 developers and their 4,602,440 following relationships in March 2016. We also …

Big Data Investment And Knowledge Integration In Academic Libraries, Saher Manaseer, Afnan R. Alawneh, Dua Asoudi

Copyright, Fair Use, Scholarly Communication, etc.

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges.

One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage …

การเตือนการพลิกคว่ำแบบทริปเเละแบบอันทริปด้วยโครงข่ายประสาทเเบบเวลาจริง, ไกรฤกษ์ ตรีทิพสุนทร

Chulalongkorn University Theses and Dissertations (Chula ETD)

ระบบป้องกันการพลิกคว่ำสำคัญมากสำหรับความปลอดภัยของผู้ขับขี่ การพัฒนาระบบป้องกันการพลิกคว่ำต้องการการประเมินความเสี่ยงในการพลิกคว่ำ ความยากของการประเมินความเสี่ยงคือ การที่ไม่รู้ความสูงจุดศูนย์ถ่วงของรถ หรือน้ำหนักของรถในขณะนั้น เป็นต้น งานวิจัยนี้จะพัฒนาการคาดเดาการพลิกคว่ำโดยที่ไม่รู้ตัวแปรข้างต้น โดยโครงข่ายประสาทใช้ค่าจากเซนเซอร์ที่ติดตั้งบนรถ การทดลองจะใช้โมเดลของรถยนต์ SUV เนื่องจากมีจุดศูนย์ถ่วงที่สูงกว่ารถยนต์ประเภทอื่น การทดสอบใช้รถทดสอบอัตราส่วน 1:5 โดยใช้ทฤษฎีบักกิงแฮมพาย และรถทดสอบได้ติดตั้งเซนเซอร์วัดความเร่ง 5 จุด และไจโรสโกป 1 จุด การเตือนการพลิกคว่ำ แบ่งเป็น 3 ระดับ ได้แก่ ปลอดภัย, มีความเสี่ยง และมีความเสี่ยงสูง โดยระบบสามารถเตือนการพลิกคว่ำได้ทั้งแบบทริป และอันทริป ทริป คือการเข้าโค้งและสะดุดหลุม หรือสิ่งกีดขวาง อันทริปคือการเข้าโค้งด้วยความเร็วสูง การเตือนการพลิกคว่ำใกล้เคียงกับค่าดัชนีการพลิกคว่ำที่วัดได้จริง การทดลองด้วยข้อมูลจากโปรแกรมจำลอง “CarSim” งานวิจัยนี้ใช้โครงข่ายประสาทแบบวนกลับ โดยใช้ข้อมูลจากเซนเซอร์ที่ติดตั้งบนตัวรถ ผู้วิจัยทดสอบ และเปรียบเทียบ ชนิดของโครงข่ายประสาท โครงสร้างของโครงข่ายประสาท และข้อมูลรับเข้าที่แตกต่างกัน โดยโครงข่ายประสาทที่เหมาะสมกับการคาดเดาแบบทริปคือแทนเจนต์มีรากที่สองของค่าเฉลี่ยความผิดพลาดกำลังสอง (RMSE) อยู่ที่ 3.66x10-4 และ GRU เหมาะสำหรับการคาดเดาแบบอันทริป โดยมีรากที่สองของค่าเฉลี่ยความผิดพลาดกำลังสองอยู่ที่ 0.131x10-2

The Role Of Previous Discourse In Identifying Public Textual Cyberbullying, Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill

Articles

In this paper we investigate the contribution of previous discourse in identifying elements that are key to detecting public textual cyberbullying. Based on the analysis of our dataset, we first discuss the missing cyberbullying elements and the grammatical structures representative of discourse-dependent cyberbullying discourse. Then we identify four types of discourse dependent cyberbullying constructions: (1) fully inferable constructions, (2) personal marker and cyberbullying link inferable constructions, (3) dysphemistic element and cyberbullying link inferable constructions, and (4) dysphemistic element inferable constructions. Finally, we formalise a framework to resolve the missing cyberbullying elements that proposes several resolution algorithms. The resolution algorithms target …

Maia: A Language For Mandatory Integrity Controls Of Structured Data, Wassnaa Al-Mawee, Paul Bonamy, Steven Carr, Jean Mayo

Michigan Tech Publications, Part 1

The integrity of systems files is necessary for the secure functioning of an operating system. Integrity is not generally discussed in terms of complete computer systems. Instead, integrity issues tend to be either tightly coupled to a particular domain (e.g. database constraints), or else so broad as to be useless except after the fact (e.g. backups). Often, file integrity is determined by who modifies the file or by a checksum. This paper focuses on a general model of the internal integrity of a file. Even if a file is modified by a subject with trust or has a valid checksum, …

Automated Essay Evaluation Using Natural Language Processing And Machine Learning, Harshanthi Ghanta

Theses and Dissertations

The goal of automated essay evaluation is to assign grades to essays and provide feedback using computers. Automated evaluation is increasingly being used in classrooms and online exams. The aim of this project is to develop machine learning models for performing automated essay scoring and evaluate their performance. In this research, a publicly available essay data set was used to train and test the efficacy of the adopted techniques. Natural language processing techniques were used to extract features from essays in the dataset. Three different existing machine learning algorithms were used on the chosen dataset. The data was divided into …

Studying Geometric Optical Illusions Through The Lens Of A Convolutional Neural Network, Nick Laberge

CMC Senior Theses

Geometrical optical illusions such as the Muller Lyer illusion and the Ponzo illusion have been widely researched over the past 100+ years, yet researchers have not reached a consensus on why human perception is deceived by these illusions or which illusions are the results of the same effects. In this paper, I study these illusions through the lens of a convolutional neural network. First, I successfully train the network to correctly classify how a human would perceive a particular class of illusion (such as the Muller Lyer illusion), then I test the network’s ability to generalize to illusions that it …

@Yourlocation: A Spatial Analysis Of Geotagged Tweets In The Us, Ocean Mckinney

CMC Senior Theses

This project examines the spatial network properties observable from geo-located tweet data. Conventional exploration examines characteristics of a variety of network attributes, but few employ spatial edge correlations in their analysis. Recent studies have demonstrated the improvements that these correlations contribute to drawing conclusions about network structure. This thesis expands upon social network research utilizing spatial edge correlations and presents processing and formatting techniques for JSON (JavaScript Object Notation) data.

Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk

CMC Senior Theses

With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption.

To accelerate the growth of the creation of these research talks, I propose an alternative to video: …