教学课程资源库 更多>>

关键词： Computer science  

摘要： “Social communication is the use of language in social contexts. It encompasses social interaction, social cognition, pragmatics, and language processing” [3]. One presumed prerequisite of social communication is visual attention–the focus of this work. “Visual attention is a process that directs a tiny fraction of the information arriving at primary visual cortex to high-level centers involved in visual working memory and pattern recognition” [7]. This process involves the integration of two streams: the global and local streams; the global stream rapidly processes the scene, and the local stream processes details. This integration is important to social communication in that attending to both the global and local features of a scene are necessary to grasp the overall meaning. For people with autism spectrum disorder (ASD), the integration of these two streams can be disrupted by the tendency to privilege details (local processing) over seeing the big picture (global processing) [66]. Consequently, people with ASD may have challenges integrating visual attention, which may disrupt their social communication. This doctoral work explores the hypothesis that visual attention can be redirected to the features of an image that contain holistic information about a scene, which when highlighted might enable people with ASD to see the forest as well as the trees (i.e., seeing a scene as a whole rather than parts). The focuses are on 1) designing a global filter that can shift visual attention from local details to global features, and 2) evaluating the performance of a global filter by leveraging eye-tracking technology. This doctoral work manipulates visual stimuli in an effort to shift the visual attention of people with ASD. This doctoral work includes two development life cycles (i.e., design, develop, evaluate): 1) low-fidelity filter, and 2) high-fidelity filter. The low-fidelity filter life cycle includes the design of four low-fidelity filters for an initial experi

关键词： Computer science  

摘要： As our world continues to become more interconnected through the Internet, cybersecurity incidents are correspondingly increasing in number, severity, and complexity. The consequences of these attacks include data loss, financial damages, and are steadily moving from the digital to the physical world, impacting everything from public infrastructure to our own homes. The existing mechanisms in responding to cybersecurity incidents have three problems: they promote a security monoculture, are too centralized, and are too slow. In this thesis, we show that improving one's network security strongly benefits from a combination of personalized, local detection, coupled with the controlled exchange of previously-private network information with collaborators. We address the problem of a security monoculture with personalized detection, introducing diversity by tailoring to the individual's browsing behavior, for example. We approach the problem of too much centralization by localizing detection, emphasizing detection techniques that can be used on the client device or local network without reliance on external services. We counter slow mechanisms by coupling controlled sharing of information with collaborators to reactive techniques, enabling a more efficient response to security events. We prove that we can improve network security by demonstrating our thesis with four studies and their respective research contributions in malicious activity detection and cybersecurity data sharing. In our first study, we develop Content Reuse Detection, an approach to locally discover and detect duplication in large corpora and apply our approach to improve network security by detecting "bad neighborhoods" of suspicious activity on the web. Our second study is AuntieTuna, an anti-phishing browser tool that implements personalized, local detection of phish with user-personalization and improves network security by reducing successful web phishing attacks. In our third study, we develop Re

关键词： Computer engineering   System science   Computer science  

摘要： Small Satellites, especially those at or below the 50kg weight limit for micro-satellite classification, provide low cost alternatives to space exploration and spacecraft innovation. These missions allow programs to achieve higher throughput for repeatability, iteration, and higher permissible risk levels. Whether used as a standalone platform or to facilitate technology demonstrations for future missions, the innovative practice of developing Small Satellite technology is improving the aerospace industry. The University of Georgia Small Satellite Research Lab is currently developing a 6U Earth Observation CubeSat utilizing an off the shelf NVIDIA GPU SoC for onboard computer vision processing. The work laid out in this thesis shows how the mission will utilize this new computational technology on a small satellite platform that increases computational abilities and autonomy at an unprecedented low mission price.

关键词： Information technology   Computer science  

摘要： Given the rising trend in security breaches among organization’s worldwide, cybersecurity has increasingly become an important role in the public and private industry sectors. In addition, the cybersecurity workforce gap has left many organizations without qualified professionals to secure their data. There is a growing need to educate and employ cybersecurity professionals in both commercial organizations and government. The main barriers to beginning a career in cybersecurity are gaining advanced and relevant knowledge and experience in cybersecurity. Knowledge can be difficult and time consuming to obtain, and training can cost money. Because of the barriers to beginning a career in cybersecurity, a single source of information that leads to knowledge and experience in cybersecurity is valuable. The purpose of this research was to develop a cybersecurity penetration testing methodology template for use by aspiring cybersecurity professionals to practice penetration testing and develop a personalized methodology. What are the common penetration testing tools and methods for attacking a network or environment from the Internet? What are the common penetration testing tools and methods for attacking a network or environment from the Intranet? What are the common penetration testing tools and methods for attacking web applications? This research is important because penetration testing experience leads to advanced knowledge in cybersecurity, which is an advantage when beginning a career in cybersecurity. Understanding cybersecurity concepts through a security analysis provides a tester with conceptual knowledge and hands-on experience. Through the process of developing a penetration testing methodology, an aspiring cybersecurity professional will learn about cybersecurity tools, technologies and procedures.

关键词： Indexes   Optimization   Computer science   Query processing   Information filters   Skyline queries   incomplete database   dynamic database   pairwise comparisons  

摘要： Skyline queries rely on the notion of Pareto dominance, filter the data items by keeping only those data items that are the best, most preferred, also known as skylines, from a database to meet the user's preferences. Skyline query has been studied extensively and a significant number of skyline algorithms have been proposed, mostly attempt to resolve the optimisation problem that is mainly associated with a reduction in the processing time of skyline computations. In today's era, the presence of incomplete data in a database is inevitable. Furthermore, databases are dynamic in nature in which their states change throughout the time to reflect the current and latest information of the applications. The skylines derived before changes are made towards the initial database are no longer valid in the new state of the database. Blindly examining the entire database to identify the new set of skylines is unwise as not all data items are affected by the changes made towards the database. Hence, in this paper we propose a solution, named DyIn-Skyline, which is capable of deriving skylines over a dynamic and incomplete database, by exploiting only those data items that are affected by the changes. Several experiments have been conducted and the results show that our proposed solution outperforms the previous works with regard to the number of pairwise comparisons and processing time.

摘要： The article focuses on the role of computer science education in primary schools. Topics include addressing how and why a computer with the binary system net or like errors in transmitted data can be recognized and corrected, creating the artifacts by children as they are actively engaged in constructing something, curriculum development of computer science, and instructing the teachers fundamental understanding of computer science.

关键词： Computer science  

摘要： With recent technological advancements, the amount of personal user data that is being generated is immense. Due to the large volume of data, machine learning algorithms such as neural networks are serving as the backbone to derive patterns from this data quickly. This need for big data analytics comes at the cost of the privacy of user data. The second challenge that must be solved relates to the scalability of the machine learning algorithm. Neural networks are known to deteriorate as the volume of the data increases due to complex sum and sigmoid calculations. Therefore in this thesis, an attempt to parallelize the neural network while also maintaining the privacy of user data is made. This model would provide a viable option for big data analytics without sacrificing the privacy of individual users while also maintaining precision and the classification accuracy of the model. The implementation of the parallelized privacy preserving neural network will be based on the MapReduce computing model which provides advanced features such as fault tolerance, data replication, and load balancing.

关键词： Computer science  

摘要： Topological Data Analysis denotes the set of algorithms and methods to define and retrieve the underlying structure of the shapes in the data. Utilizing topological inference in data mining and generally data science is recent, while computational geometry and computational topology have been examined in the area of applied mathematics for many years. Some recent studies have shown the strength of topological data analysis when dealing with high-dimensional data sets. Dealing with the noisy data, the most common goal in TDA is to refine the underlying shapes as the most important property of the data. Then what remains may be considered irrelevant information or simply the noise. Topological inference has been applied to many sub-areas of pattern recognition and data mining, but it is not widely used in natural language processing and text mining. A simple reason is that defining shapes in the text is not easy. In this dissertation document, we introduce three different algorithms of extracting topological features from textual documents, using as the underlying representations of text the two most popular methods, namely term frequency vectors and word embeddings, and also without using any conventional features: (1) To extract topological features without using conventional features, we analyze the graph of appearance/co-appearance of different entities through long documents. We show how these topological structures in a text may effectively act as the signature or identifier of the topic, writer, writing, etc. (2) Then we introduce a new algorithm of extracting topological features from text, namely by converting a sequence of word embeddings into a time series, and analyzing the dimensions of the resulting series for topological persistence. (3) We also provide a topological method to analyze the geometry of the term frequency space. In all three algorithms, we apply homological persistence to reveal the geometric structures under different distance resolutions

关键词： Computer science  

摘要： Conversational agents, popularly called chatbots, received significant attention in the last few years. The major reason behind the success of these systems is that chatbots use the already familiar conversational interface. However, chatbots are still in their nascent stage: They have a low penetration rate as 84% of the Internet users have not used a chatbot yet. First, we conducted a study with 16 first-time chatbot users interacting with eight chatbots over multiple sessions on the Facebook Messenger platform. Analysis of chat logs and user interviews revealed several major problems with the current chatbots, including (a) mismatch between the chatbot's state of understanding (also called context) and the user's perception of the chatbot's understanding, (b) limitations in natural language understanding technologies leading to dialog failures, and (c) targeting chatbots specifically towards the Internet-savvy technically-advanced users. Second, we focused on these three problems and developed solutions, respectively: (a) Convey: stands for CONtext View, is a window added to the chatbot interface, displaying the conversational context and providing interactions with the context values, which we evaluated with 16 participants; (b) Resilient Chatbot: explores user preferences for eight repair strategies taken from commercially-deployed chatbots (e.g., confirmation, providing options) as well as novel strategies explaining characteristics of the underlying machine learning algorithms, was evaluated with 216 MTurkers; and (c) FarmChat: is a multi-modal multi-lingual conversational agent, to meet the information needs of rural low literate farmers, and evaluated with 34 farmers in Ranchi, India. To summarize, we propose ways to make chatbots more transparent, and extend its applicability to new demographics.

关键词： Computer science  

摘要： Smart home assistants are becoming a norm due to their ease-of-use. They employ spoken language as an interface, facilitating easy interaction with their users. Even with their obvious advantages, natural-language based interfaces are not prevalent outside the domain of home assistants. It is hard to adopt them for computer-controlled systems due to the numerous complexities involved with their implementation in varying fields. The main challenge is the grounding of natural language base terms into the underlying system's primitives. The existing systems that do use natural language interfaces are specific to one problem domain only. In this thesis, a domain-agnostic framework that creates natural language interfaces for computer-controlled systems has been developed by making the mapping between the language constructs and the system primitives customizable. The framework employs ontologies built using OWL (Web Ontology Language) for knowledge representation purposes and machine learning models for language processing tasks. It has been evaluated within a simulation environment consisting of objects and a robot. This environment has been deployed as a web application, providing anonymous user testing for evaluation, and generating training data for machine learning components. Performance evaluation has been done on metrics such as time taken for a task or the number of instructions given by the user to the robot to accomplish a task. Additionally, the framework has been used to create a natural language interface for a database system to demonstrate its domain independence.