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Articles 1 - 30 of 44
Full-Text Articles in Engineering
Understanding Sleep In Pediatric Patients With Sickle Cell Disease Admitted For Vaso-Occlusive Pain Crisis Through Objective Data, Kalindi Narine, Fan Yang, Tanvi Banerjee, Jude Jonassaint, Nirmish Shah
Understanding Sleep In Pediatric Patients With Sickle Cell Disease Admitted For Vaso-Occlusive Pain Crisis Through Objective Data, Kalindi Narine, Fan Yang, Tanvi Banerjee, Jude Jonassaint, Nirmish Shah
Computer Science and Engineering Faculty Publications
Sickle cell disease (SCD) is an inherited red cell disorder that leads to sickling of red blood cells, anemia and vaso-occlusion. The most common reason for hospitalization and morbidity in children is pain due to vaso-occlusive crisis (VOC). Importantly, poor sleep quality can lead to increased pain the subsequent day and nocturnal pain leads to reduced deep sleep, both which can then modify pain sensitivity. Studies using sleep diaries have shown this cyclical relationship between sleep and pain. Frequent occurrences of restless sleep are therefore believed to contribute to an increased severity and intensity of pain episodes. There is very …
Teaching Image Processing And Visualization Principles To Medicine Students, Christina Gillmann, Thomas Wischgoll, Jose T. Hernandez, Hans Hagen
Teaching Image Processing And Visualization Principles To Medicine Students, Christina Gillmann, Thomas Wischgoll, Jose T. Hernandez, Hans Hagen
Computer Science and Engineering Faculty Publications
Although image processing becomes increasingly important in most applications such as medicine, image processing and visualization is usually not a part of the medical education and therefore not widely spread in clinical daily routine. Contrary to students from computer science, medical students are usually not familiar to computational models or algorithms and require a different view of the algorithms instead of knowing each computational detail. To solve this problem this paper presents the concept of a lecture that aims to impart image processing and visualization principals for students in medicine in order to pioneer a higher acceptance and propagation of …
What Does Explainable Ai Really Mean? A New Conceptualization Of Perspectives, Derek Doran, Sarah Schulz, Tarek R. Besold
What Does Explainable Ai Really Mean? A New Conceptualization Of Perspectives, Derek Doran, Sarah Schulz, Tarek R. Besold
Computer Science and Engineering Faculty Publications
We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached. The paper is motivated by a corpus analysis of NIPS, ACL, COGSCI, and ICCV/ECCV paper titles showing differences in how work on explainable AI is positioned in various fields. We close by introducing a fourth notion: truly explainable systems, where automated reasoning is central to output crafted explanations without requiring human …
Explaining Trained Neural Networks With Semantic Web Technologies: First Steps, Md Kamruzzaman Sarker, Ning Xie, Derek Doran, Michael L. Raymer, Pascal Hitzler
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.
Intuitive Error Space Exploration Of Medical Image Data In Clinical Daily Routine, Christina Gillmann, Pablo Arbeláez, José Tiberio Hernández Peñaloza, Hans Hagen, Thomas Wischgoll
Intuitive Error Space Exploration Of Medical Image Data In Clinical Daily Routine, Christina Gillmann, Pablo Arbeláez, José Tiberio Hernández Peñaloza, Hans Hagen, Thomas Wischgoll
Computer Science and Engineering Faculty Publications
Medical image data can be affected by several image errors. These errors can lead to uncertain or wrong diagnosis in clinical daily routine. A large variety of image error metrics are available that target different aspects of image quality forming a highdimensional error space, which cannot be reviewed trivially. To solve this problem, this paper presents a novel error space exploration technique that is suitable for clinical daily routine. Therefore, the clinical workflow for reviewing medical data is extended by error space cluster information, that can be explored by user-defined selections. The presented tool was applied to two real-world datasets …
Data-Driven Network-Centric Threat Assessment, Dae Wook Kim
Data-Driven Network-Centric Threat Assessment, Dae Wook Kim
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As the Internet has grown increasingly popular as a communication and information sharing platform, it has given rise to two major types of Internet security threats related to two primary entities: end-users and network services. First, information leakages from networks can reveal sensitive information about end-users. Second, end-users systems can be compromised through attacks on network services, such as scanning-and-exploit attacks, spamming, drive-by downloads, and fake anti-virus software. Designing threat assessments to detect these threats is, therefore, of great importance, and a number of the detection systems have been proposed. However, these existing threat assessment systems face significant challenges in …
Deep Learning Approach For Intrusion Detection System (Ids) In The Internet Of Things (Iot) Network Using Gated Recurrent Neural Networks (Gru), Manoj Kumar Putchala
Deep Learning Approach For Intrusion Detection System (Ids) In The Internet Of Things (Iot) Network Using Gated Recurrent Neural Networks (Gru), Manoj Kumar Putchala
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The Internet of Things (IoT) is a complex paradigm where billions of devices are connected to a network. These connected devices form an intelligent system of systems that share the data without human-to-computer or human-to-human interaction. These systems extract meaningful data that can transform human lives, businesses, and the world in significant ways. However, the reality of IoT is prone to countless cyber-attacks in the extremely hostile environment like the internet. The recent hack of 2014 Jeep Cherokee, iStan pacemaker, and a German steel plant are a few notable security breaches. To secure an IoT system, the traditional high-end security …
Panel: Teaching To Increase Diversity And Equity In Stem, Helen H. Hu, Douglas Blank, Albert Chan, Travis E. Doom
Panel: Teaching To Increase Diversity And Equity In Stem, Helen H. Hu, Douglas Blank, Albert Chan, Travis E. Doom
Computer Science and Engineering Faculty Publications
TIDES (Teaching to Increase Diversity and Equity in STEM) is a three-year initiative to transform colleges and universities by changing what STEM faculty, especially CS instructors, are doing in the classroom to encourage the success of their students, particularly those that have been traditionally underrepresented in computer science.Each of the twenty projects selected proposed new inter-disciplinary curricula and adopted culturally sensitive pedagogies, with an eye towards departmental and institutional change. The four panelists will each speak about their TIDES projects, which all involved educating faculty about cultural competency. Three of the panelists infused introductory CS courses with applications from other …
Semi-Supervised Approach To Monitoring Clinical Depressive Symptoms In Social Media, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Monireh Ebrahimi, Goonmeet Bajaj, Tanvi Banerjee, Krishnaprasad Thirunarayan, Jyotishman Pathak, Amit Sheth
Semi-Supervised Approach To Monitoring Clinical Depressive Symptoms In Social Media, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Monireh Ebrahimi, Goonmeet Bajaj, Tanvi Banerjee, Krishnaprasad Thirunarayan, Jyotishman Pathak, Amit Sheth
Computer Science and Engineering Faculty Publications
With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of clinical depression from tweets obtained unobtrusively. Based on the analysis of tweets crawled from users with self-reported depressive symptoms in their Twitter profiles, we demonstrate the potential for detecting clinical depression symptoms which emulate the PHQ-9 questionnaire clinicians use today. Our study uses a semi-supervised statistical model to evaluate how the duration of these symptoms …
An Industrial Vision System To Analyze The Wear Of Cutting Tools, Christina Gillmann, Tobias Post, Benjamin Kirsch, Thomas Wischgoll, Jörg Hartig, Bernd Hamann, Hans Hagen, Jan C. Aurich
An Industrial Vision System To Analyze The Wear Of Cutting Tools, Christina Gillmann, Tobias Post, Benjamin Kirsch, Thomas Wischgoll, Jörg Hartig, Bernd Hamann, Hans Hagen, Jan C. Aurich
Computer Science and Engineering Faculty Publications
The wear behavior of cutting tools directly affects the quality of the machined part. The measurement and evaluation of wear is a time consuming process and is subjective. Therefore, an image-based wear measurement that can be computed automatically based on given image series of cutting tools and an objective way to review the resulting wear is presented in this paper. The presented method follows the industrial vision system pipeline where images of cutting tools are used as input which are then transformed through suitable image processing methods to prepare them for the computation of a novel image based wear measurement. …
A High-Dimensional Data Quality Metric Using Pareto Optimality, Tobias Post, Thomas Wischgoll, Bernd Hamann, Hans Hagen
A High-Dimensional Data Quality Metric Using Pareto Optimality, Tobias Post, Thomas Wischgoll, Bernd Hamann, Hans Hagen
Computer Science and Engineering Faculty Publications
The representation of data quality within established high-dimensional data visualization techniques such as scatterplots and parallel coordinates is still an open problem. This work offers a scale-invariant measure based on Pareto optimality that is able to indicate the quality of data points with respect to the Pareto front. In cases where datasets contain noise or parameters that cannot easily be expressed or evaluated mathematically, the presented measure provides a visual encoding of the environment of a Pareto front to enable an enhanced visual inspection.
Virtuo-Its: An Interactive Tutoring System To Teach Virtual Memory Concepts Of An Operating System, Venkata Krishna Kanth Musunuru
Virtuo-Its: An Interactive Tutoring System To Teach Virtual Memory Concepts Of An Operating System, Venkata Krishna Kanth Musunuru
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Interactive tutoring systems are software applications that help individuals to learn difficult concepts. They can allow students to interact with ideas from essential mathematics to more complicated subjects like software engineering. This thesis concentrates on one such interactive tutoring system (ITS) designed for teaching concepts related to operating system virtual memory. Operating system concepts can be troublesome to learn without having someone or something to explain them. Even when an instructor is able to provide detailed explanations, it is still exceptionally difficult for students without a computer science foundation to comprehend these concepts. Students require a sophisticated set of mental …
Gait Analysis From Wearable Devices Using Image And Signal Processing, Bradley A. Schneider
Gait Analysis From Wearable Devices Using Image And Signal Processing, Bradley A. Schneider
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We present the results of analyzing gait motion in-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera and are validated using the ground truth dataset. We perform an additional data collection with both the camera and a body-worn accelerometer …
Characterizing Concepts In Taxonomy For Entity Recommendations, Siva Kumar Cheekula
Characterizing Concepts In Taxonomy For Entity Recommendations, Siva Kumar Cheekula
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Entity recommendation systems are enormously popular on the Web. These systems harness manually crafted taxonomies for improving recommendations. For example, Yahoo created the Open Directory Project for search and recommendation, and Amazon utilizes its own product taxonomy. While these taxonomies are of high quality, it is a labor and time-intensive process to manually create and keep them up to date. Instead, in this era ofWeb 2.0 where users collaboratively create large amounts of information on the Web, it is possible to utilize user-generated content to automatically generate good quality taxonomies. However, harnessing such taxonomies for entity recommendations has not been …
Multi-Class Classification Of Textual Data: Detection And Mitigation Of Cheating In Massively Multiplayer Online Role Playing Games, Naga Sai Nikhil Maguluri
Multi-Class Classification Of Textual Data: Detection And Mitigation Of Cheating In Massively Multiplayer Online Role Playing Games, Naga Sai Nikhil Maguluri
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The success of any multiplayer game depends on the player’s experience. Cheating/Hacking undermines the player’s experience and thus the success of that game. Cheaters, who use hacks, bots or trainers are ruining the gaming experience of a player and are making him leave the game. As the video game industry is a constantly increasing multibillion dollar economy, it is crucial to assure and maintain a state of security. Players reflect their gaming experience in one of the following places: multiplayer chat, game reviews, and social media. This thesis is an exploratory study where our goal is to experiment and propose …
Sched-Its: An Interactive Tutoring System To Teach Cpu Scheduling Concepts In An Operating Systems Course, Bharath Kumar Koya
Sched-Its: An Interactive Tutoring System To Teach Cpu Scheduling Concepts In An Operating Systems Course, Bharath Kumar Koya
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Operating systems is an essential course in computer science curriculum, which helps students to develop a mental model of how computer operating systems work. The internal mechanisms and processes of an operating system (OS) are often complex, non-deterministic and intangible which makes them difficult for students to understand. One such concept is central processing unit (CPU) scheduling. CPU scheduling forms the basis of the multiprogramming in an OS. In practice, OS courses involve classroom lectures describing high-level abstractions of the concepts, and students complete programming assignments to apply the material in a more concrete way. Depending on the programming assignments, …
Detection Of Ddos Attacks Against The Sdn Controller Using Statistical Approaches, Basheer Husham Ali Al-Mafrachi
Detection Of Ddos Attacks Against The Sdn Controller Using Statistical Approaches, Basheer Husham Ali Al-Mafrachi
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In traditional networks, switches and routers are very expensive, complex, and inflexible because forwarding and handling of packets are in the same device. However, Software Defined Networking (SDN) makes networks design more flexible, cheaper, and programmable because it separates the control plane from the data plane. SDN gives administrators of networks more flexibility to handle the whole network by using one device which is the controller. Unfortunately, SDN faces a lot of security problems that may severely affect the network operations if not properly addressed. Threat vectors may target main components of SDN such as the control plane, the data …
Detecting Information Leakage In Android Malware Using Static Taint Analysis, Soham P. Kelkar
Detecting Information Leakage In Android Malware Using Static Taint Analysis, Soham P. Kelkar
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According to Google, Android now runs on 1.4 billion devices. The growing popularity has attracted attackers to use Android as a platform to conduct malicious activities. To achieve these malicious activities some attacker choose to develop malicious Apps to steal information from the Android users. As the modern day smartphones process, a lot of sensitive information, information security, and privacy becoming a potential target for the attacker. The malicious Apps steal information from the infected phone and send this information to the attacker-controlled URLs using various Android sink functions. Therefore, it necessary to protect data as it can prove detrimental …
Automated Rendering Of Schema Diagram For Ontologies, Nazifa Karima
Automated Rendering Of Schema Diagram For Ontologies, Nazifa Karima
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Semantic Web extends the current web, using ontologies, metadata and other technologies to establish links between terms and concepts. This enables machines to automatically integrate information across different platforms utilizing the standard definitions. Furthermore, reasoning agents can infer new knowledge by gathering existing information and these additional connections between them. As a result of being designed and maintained independently, data sources exhibit highly heterogeneous nature. This increases the complexity of data integration and hinders interoperability. However, if we can align the overlapping concepts among different domains of knowledge, the prospect of achieving interoperability and integration without having any intermediate reasoning …
Harassment Detection On Twitter Using Conversations, Venkatesh Edupuganti
Harassment Detection On Twitter Using Conversations, Venkatesh Edupuganti
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Social media has brought people closer than ever before, but the use of social media has also brought with it a risk of online harassment. Such harassment can have a serious impact on a person such as causing low self-esteem and depression. The past research on detecting harassment on social media is primarily based on the content of messages exchanged on social media. The lack of context when relying on a single social media post can result in a high degree of false alarms. In this study, I focus on the reliable detection of harassment on Twitter by better understanding …
Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu
Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu
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Motivational Interviewing (MI) has been proved to be an effective Screening, Brief Intervention, and Referral to Treatment (SBIRT) technique. It is an evidence-based practice used to identify, reduce, and prevent problematic use, abuse, and dependence on alcohol and illicit drugs. It emphasizes on patient-centered counseling approach that can help resolve their ambivalence through a non-confrontational, goal-oriented style for eliciting behavior change from the patient, almost like patients talk themselves into change. This approach provokes less resistance and stimulates the progress of patients at their own pace towards deciding about planning, making and sustaining positive behavioral change. Thus, training medical professionals …
Development Of An Ultra-Portable Non-Contact Wound Measurement System, Anka Babu Billa
Development Of An Ultra-Portable Non-Contact Wound Measurement System, Anka Babu Billa
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Continuous monitoring of changes in wound size is key to correctly predict whether wounds will heal readily with conventional treatment or require more aggressive treatment strategies. Unfortunately, existing wound measurement solutions don't meet the clinical demand due to their limitations in accuracy, operating complexity and time, acquisition and operation cost, or reproducibility, resulting in unnecessarily lengthy recovery or extra treatment procedures, incurring an excessively high financial cost, and in many cases extended usage of addictive painkillers. In this thesis, we proposed and developed a low cost, a portable non-contact solution that combines multi-spectral imaging and a portfolio of imaging processing …
Efficient Reasoning Algorithms For Fragments Of Horn Description Logics, David Carral
Efficient Reasoning Algorithms For Fragments Of Horn Description Logics, David Carral
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We characterize two fragments of Horn Description Logics and we define two specialized reasoning algorithms that effectively solve the standard reasoning tasks over each of such fragments. We believe our work to be of general interest since (1) a rather large proportion of real-world Horn ontologies belong to some of these two fragments and (2) the implementations based on our reasoning approach significantly outperform state-of-the-art reasoners. Claims (1) and (2) are extensively proven via empirically evaluation.
Settings Protection Add-On: A User-Interactive Browser Extension To Prevent The Exploitation Of Preferences, Venkata Naga Siva Seelam
Settings Protection Add-On: A User-Interactive Browser Extension To Prevent The Exploitation Of Preferences, Venkata Naga Siva Seelam
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The abuse of browser preferences is a significant application security issue, despite numerous protections against automated software changing these preferences. Browser hijackers modify user’s desired preferences by injecting malicious software into the browser. Users are not aware of these modifications, and the unwanted changes can annoy the user and circumvent security preferences. Reverting these changes is not easy, and users often have to go through complicated sequences of steps to restore their preferences to the previous values. Tasks to resolve this issue include uninstalling and re-installing the browser, resetting browser preferences, and installing malware removal tools. This thesis describes a …
Distance Learning And Attribute Importance Analysis By Linear Regression On Idealized Distance Functions, Rupesh Kumar Singh
Distance Learning And Attribute Importance Analysis By Linear Regression On Idealized Distance Functions, Rupesh Kumar Singh
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A good distance metric is instrumental on the performance of many tasks including classification and data retrieval. However, designing an optimal distance function is very challenging, especially when the data has high dimensions.Recently, a number of algorithms have been proposed to learn an optimal distance function in a supervised manner, using data with class labels. In this thesis we proposed methods to learn an optimal distance function that can also indicate the importance of attributes. Specifically, we present several ways to define idealized distance functions, two of which involving distance error correction involving KNN classification, and another involving a two-constant …
Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna
Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna
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The processing of structured and semi-structured content on the Web has been gaining attention with the rapid progress in the Linking Open Data project and the development of commercial knowledge graphs. Knowledge graphs capture domain-specific or encyclopedic knowledge in the form of a data layer and add rich and explicit semantics on top of the data layer to infer additional knowledge. The data layer of a knowledge graph represents entities and their descriptions. The semantic layer on top of the data layer is called the schema (ontology), where relationships of the entity descriptions, their classes, and the hierarchy of the …
An Optimization Compiler Framework Based On Polyhedron Model For Gpgpus, Lifeng Liu
An Optimization Compiler Framework Based On Polyhedron Model For Gpgpus, Lifeng Liu
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General purpose GPU (GPGPU) is an effective many-core architecture that can yield high throughput for many scientific applications with thread-level parallelism. However, several challenges still limit further performance improvements and make GPU programming challenging for programmers who lack the knowledge of GPU hardware architecture. In this dissertation, we describe an Optimization Compiler Framework Based on Polyhedron Model for GPGPUs to bridge the speed gap between the GPU cores and the off-chip memory and improve the overall performance of the GPU systems. The optimization compiler framework includes a detailed data reuse analyzer based on the extended polyhedron model for GPU kernels, …
Oclep+: One-Class Intrusion Detection Using Length Of Patterns, Sai Kiran Pentukar
Oclep+: One-Class Intrusion Detection Using Length Of Patterns, Sai Kiran Pentukar
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In an earlier paper, a method called One-class Classification using Length statistics of (jumping) Emerging Patterns (OCLEP) was introduced for masquerader detection. Jumping emerging patterns (JEPs) for a test instance are minimal patterns that match the test instance but they do not match any normal instances. OCLEP was based on the observation that one needs long JEPs to differentiate an instance of one class from instances of the same class, but needs short JEPs to differentiate an instance of one class from instances of a different class. In this thesis, we present OCLEP+, One-class Classification using Length statistics of Emerging …
Smart Ev Charging For Improved Sustainable Mobility, Ashutosh Shivakumar
Smart Ev Charging For Improved Sustainable Mobility, Ashutosh Shivakumar
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The landscape of energy generation and utilization is witnessing an unprecedented change. We are at the threshold of a major shift in electricity generation from utilization of conventional sources of energy like coal to sustainable and renewable sources of energy like solar and wind. On the other hand, electricity consumption, especially in the field of transportation, due to advancements in the field of battery research and exponential technologies like vehicle telematics, is seeing a shift from carbon based to Lithium based fuel. Encouraged by 1. Decrease in the cost of Li – ion based batteries 2. Breakthroughs in battery chemistry …
Exploiting Alignments In Linked Data For Compression And Query Answering, Amit Krishna Joshi
Exploiting Alignments In Linked Data For Compression And Query Answering, Amit Krishna Joshi
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Linked data has experienced accelerated growth in recent years due to its interlinking ability across disparate sources, made possible via machine-processable RDF data. Today, a large number of organizations, including governments and news providers, publish data in RDF format, inviting developers to build useful applications through reuse and integration of structured data. This has led to tremendous increase in the amount of RDF data on the web. Although the growth of RDF data can be viewed as a positive sign for semantic web initiatives, it causes performance bottlenecks for RDF data management systems that store and provide access to data. …