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摘要： Disability Inclusion and Accessibility in technology and education have today emerged as a necessity of national importance. National Science Foundation(NSF) funded projects like AccessCSforALL, Bootstrap, and CSforAll, are making efforts to make computer science inclusive to the 7.4 million K-12 students with disabilities. Bringing people with disabilities into tech workforce would not only create equal opportunities for all but would also better equip the society to serve its diverse population. Computer Programming is a growing and important field of the present and future. When the tools to learn programming from an early age are inaccessible to people with disabilities, they are denied the opportunity to succeed. This thesis focuses on making computer science concepts accessible to K-12 students who are Deaf/Hard of Hearing, Blind/Low Vision and those with motor disabilities. It attempts to provide technical strategies to break this inaccessibility barrier and make computer science literacy, education, and, ultimately, careers accessible to all.

关键词： Computer Science   Computer Security   Concept Inventory   Cybersecurity   Education   Misconceptions  

摘要： Cybersecurity incidents are on the rise. Tracing these security breaches back, we linked them to people making an error due to a commonsense misconception. There is no one standard tool that gauges a student's understanding of security topics. In this research, we surveyed 75 security experts about security novices' misconceptions, coded the results, and identified 17 top misconceptions. We created open-ended questions and labs/active learning to identify and remediate those misconceptions. After revising the open-ended questions, we gave them to undergraduate students and successfully extracted real-world instances of the misconceptions in practice. We created a ten-question multiple-choice exam by converting the open-ended questions into multiple-choice with many distractors drawn from students' misconceptions. We then conducted "think-aloud interviews" with students to make sure that the questions were clear. After integrating their feedback, we administered multiple-choice exams to two groups of students; 114 CS 1 students with no formal security education and 28 students from a security course. Almost 30% of CS 1 students failed to answer more than one question correctly, and only 3.5% of CS 1 students passed with a score of 60 (a D-). However, only 21.4% of the security students passed, and no individual student got more than seven out of ten correct. Our results show that both groups of students have these common security misconceptions. While security students earned markedly higher scores, our test unequivocally shows that students are leaving the security course retaining significant misconceptions, pointing the way for improvements in teaching.

关键词： Cryptography   Markov processes   Mobile ad hoc networks   Computer science   Routing   Ontologies   Licenses   Internet of Things (IoT)   opportunistic networks security   opportunistic networks privacy protection   Seed OppNet   communication  

摘要： Opportunistic Networks is a new concept that is increasingly gaining ground since it appears as a concrete example of the Internet of Things, Internet of Vehicles, Industrial Internet of Things, and the Internet of Everything with Mobile ad hoc Networks' characteristics. An Opportunistic Network starts with a Seed OppNet that sets up the network;expands from the Seed OppNet to an extended Seed OppNet through devices' discovery. The characteristics of Opportunistic Networks make OppNets more challenging than any other networks. So, a deep understanding of OppNets' characteristics and demands is an unavoidable precondition before proposing any OppNets related scheme. However, under OppNets' constraints, the relevance of the Opportunistic Networks related articles in literature is yet to be established. Also, most surveys tackling Opportunistic Networks do not give a complete insight into what Opportunistic Networks stand for. This work reviews state of the art on Opportunistic Networks providing three main contributions. First, resorting to the primary definition of Opportunistic Networks, it elucidates what OppNets are, pointing out the particularities of an OppNet, its domains of applications, and challenges. Second, it provides a comprehensive review that encompasses most Opportunistic Networks' research areas: routing, intrusion detection, authentication, privacy protection, data aggregation, and the technology for OppNets, organising them in a taxonomy. Third, it evaluates the role of the Seed OppNet in Opportunistic Networks related schemes. Any proposed OppNets related scheme, to be relevant to OppNets' research, should include OppNets' characteristics and demands.

摘要： In recent years, not only has there been a dramatic drop in the number of students enrolling in computer science courses, and attrition from computer science courses continues to be significant. Traditionally, computer programming courses have high failure rates, and as they tend to be core to computer science courses can be a roadblock for many students to their studies. But, is a computer science course really that difficult — or are there other barriers that negatively affect student progression? This work uses qualitative research following three aspects of computer science pedagogy to help students to improve their academic performance. These three aspects include:(1) How to manage students learning behavior --- Pair Programming and Self-Efficacy in CS1; (2) How to assess students learning and performance --- Logarithmic Rubric Scoring; (3) How to manage student behavior in the examination to make sure fairness --- The Geometry of Assessment. Results showed that this work could incrementally predict course performance, and it mediated the relationship between study behavior (self-efficacy or self-assessment) and both academic criteria. The computer science pedagogy behaviors in the research are a promising predictor of educational outcomes, and they may have usefulness in student course performance.

关键词： African American   graduate students   engineering   computer science  

摘要： Engineers and computer scientists with advanced degrees play a critical role in addressing complex societal challenges while serving as role models for undergraduate students pursuing degrees in these areas. However, the results of a literature map, conducted as a part of a larger study, suggest that we tend to focus on undergraduate education when discussing how to diversify the talent pool. This paper presents the findings from a systematic literature review on the barriers to graduate-level participation in engineering as experienced by African Americans, one of the most under-represented groups. Twenty-two articles resulted from the search, 11 passing the quality check. The analysis focused on synthesizing themes surrounding how researchers study the problem, barriers to participation, and recommendations for addressing them. Results highlight that investigators tend to focus on three topic areas: (1) Student Identity, (2) Recruitment and Persistence, and (3) Students' Perceptions of Graduate School. This synthesis presents the current state of the literature on broadening participation of African American engineering graduate students and highlights opportunities for future inquiries.

关键词： Artificial intelligence   Computer science   Computer vision   Machine learning   Neural networks   Robustness  

摘要： We introduce several new datasets namely ImageNet-A/O and ImageNet-R as well as a synthetic environment and testing suite we called CAOS. ImageNet-A/O allow researchers to focus in on the blind spots remaining in ImageNet. ImageNet-R was specifically created with the intention of tracking robust representation as the representations are no longer simply natural but include artistic, and other renditions. The CAOS suite is built off of CARLA simulator which allows for the inclusion of anomalous objects and can create reproducible synthetic environment and scenes for testing robustness. All of the datasets were created for testing robustness and measuring progress in robustness. The datasets have been used in various other works to measure their own progress in robustness and allowing for tangential progress that does not focus exclusively on natural accuracy. Given these datasets, we created several novel methods that aim to advance robustness research. We build off of simple baselines in the form of Maximum Logit, and Typicality Score as well as create a novel data augmentation method in the form of DeepAugment that improves on the aforementioned benchmarks. Maximum Logit considers the logit values instead of the values after the softmax operation, while a small change produces noticeable improvements. The Typicality Score compares the output distribution to a posterior distribution over classes. We show that this improves performance over the baseline in all but the segmentation task. Speculating that perhaps at the pixel level the semantic information of a pixel is less meaningful than that of class level information. Finally the new augmentation technique of DeepAugment utilizes neural networks to create augmentations on images that are radically different than the traditional geometric and camera based transformations used previously. DeepAugment improves SOTA by a significant margin while being able to be used with other augmentation schemes and demonstrates th

关键词： Motion pictures   Location awareness   Feature extraction   Text recognition   Convolutional neural networks   Computer science   Deep learning   Movie title extraction   multi-script   text localization   transfer learning  

摘要： Graphical texts in natural images play an important role in portraying information in multitudinous fields such as communication, education, and entertainment to name a few. Recognizing text in scene images is challenging due to the inherent complexity of the images. Text recognition in natural images involves script identification, which requires text localization. This is not trivial for natural scene images due to the presence of disparate foreground/background components. For scene images like movie posters, the challenge is more dominant. The challenges aggravate due to the presence of composite characteristics of posters like complex graphics background and the presence of different texts like a movie title, names of actors, producers, directors, and tagline. These texts have miscellaneous fonts, variations in colors, size, orientation, and textures. In this work, an M-EAST (modified EAST) model is proposed, which is based on the EAST (efficient and accurate scene text detector) model for text localization. A novel movie title extraction is thereafter used for separating the title from the extracted text pool. Finally, the title script was identified using a shallow convolutional neural network (SCNN)-based architecture to ensure functionality in low-resource environments. Experiments were performed on a dataset of movie-poster images of Tollywood, Bollywood, and Hollywood industries, and a highest accuracy of 99.82% was obtained. The system performed better than the reported techniques.

关键词： Contracts   Wireless communication   Quality of service   Base stations   Uncertainty   Numerical models   Computer science   Contract theory   incentive mechanism design   wireless edge caching   two-layer networks  

摘要： Wireless caching technologies have been proposed to relieve the transmission pressures, especially, the transmission redundancy on back-haul channels. In this paper, we consider a two-layer caching network, consisting of traditional macro-cell base station (MBS) aided back-haul channels and small-cell base stations (SBSs) aided local links. The network service provider (NSP), who is in charge of the two layers, leases its resources of the secondary layer, i.e., coverage of the SBSs, to content providers (CPs) for making extra profits and releasing pressures on the back-haul channels. At the same time, CPs will evaluate whether they are provided with proper incentives to pre-cache their files in the SBSs. Considering different quality of services (QoS) provided by the two layers as well as the economical impact of the traditional layer on the secondary layer, the NSP designs the optimal incentive mechanisms within the framework of contract theory for maximizing its own profits. First, we formulate the utility of the NSP and CPs. Then, the minimum transmission requirement, reserve price and limited resources are considered as constraints in designing the optimal contract. Also, some important properties of these constraints are analyzed to facilitate the optimal contract determination process. At last, an optimal contract determination scheme is proposed, based on which the optimal coverage set is determined first, and then the corresponding optimal prices are derived with the aid of equal cost line. Numerical results are provided to demonstrate the effectiveness of the proposed optimal contract in increasing the NSP's profits and incentivizing CPs to transmit on the secondary layer.

关键词： Computer science   Genetics   Statistics   Schizophrenia   Human genome--Research   Schizophrenia--Etiology  

摘要： Over the past 20 years, Genome-Wide Association Studies (GWAS) have identified thousands of variants in the genome linked to genetic diseases. However, these associations often reveal little about underlying genetic etiology, which for many phenotypes is thought to be highly heterogeneous. This work investigates statistical methods to move beyond conventional GWAS methods to both improve estimation of associations and to extract additional etiological insights from known associations, with a focus on schizophrenia. This thesis addresses the above aim through three primary topics: First, we describe ***, a web platform to crowdsource the collection of genomic data with user consent and active participation, thereby rapidly increasing sample sizes and power required for GWAS. Second, we describe methods to characterize the latent genomic contributors to heterogeneity in GWAS phenotypes. We develop a Z-score test to detect heterogeneity using correlations between variants among affected individuals, and we develop a contrastive tensor decomposition to explicitly characterize subtype-specific SNP effects independently of confounding heterogeneity such as ancestry. Using these methods we provide evidence of significant heterogeneity in GWAS cohorts for schizophrenia. Lastly, a major avenue of investigation beyond GWAS is identifying the genes through which associated SNPs mechanistically affect the presentation of phenotypes. We develop a method to improve estimation of expression quantitative trait loci by joint inference over gene expression reference data and GWAS data, incorporating insights from the liability threshold model. These methods will advance ongoing efforts to explain the complex etiology of genetic diseases as well as improve the accuracy of disease prediction models based on these insights.

关键词： Web services   Quality of service   Predictive models   Prediction algorithms   Computer science   Time factors   Quality of service   quality prediction   matrix factorization   neighborhood information   covering algorithm  

摘要： The number of Web services on the Internet has been growing rapidly. This has made it increasingly difficult for users to find the right services from a large number of functionally equivalent candidate services. Inspecting every Web service for their quality value is impractical because it is very resource consuming. Therefore, the problem of quality prediction for Web services has attracted a lot of attention in the past several years, with a focus on the application of the Matrix Factorization (MF) technique. Recently, researchers have started to employ user similarity to improve MF-based prediction methods for Web services. However, none of the existing methods has properly and systematically addressed two of the major issues: 1) retrieving appropriate neighborhood information, i.e., similar users and services;2) utilizing full neighborhood information, i.e., both users' and services' neighborhood information. In this paper, we propose CNMF, a covering-based quality prediction method for Web services via neighborhood-aware matrix factorization. The novelty of CNMF is twofold. First, it employs a covering-based clustering method to find similar users and services, which does not require the number of clusters and cluster centroids to be prespecified. Second, it utilizes neighborhood information on both users and services to improve the prediction accuracy. The results of experiments conducted on a real-world dataset containing 1,974,675 Web service invocation records demonstrate that CNMF significantly outperforms eight existing quality prediction methods, including two state-of-the-art methods that also utilize neighborhood information with MF.