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关键词： Binary   Computer science education   Educational game   Game-based learning   Low-level   Serious games  

摘要： Game-based learning has had promising results for a variety of different topics; however, for computer science education in particular, its applications have mostly focused on high-level concepts such as program flow and the control structures that modify it. Considering that students are known to struggle with low-level topics, the goal of this thesis is to level down game-based learning by applying it to lower-level concepts—this is accomplished by designing, building, and evaluating two original games. The first game is the physical card game Mermaids and Narwhals, which is meant to teach binary manipulations such as shifts and rotations with broader applications in computational thinking; it was evaluated through a gameplay simulation that modelled the game's behaviour under different conditions. The second game is Binary Bubbles, which is a digital bubble shooter game designed to help students practice their Boolean/bitwise logic operations; this game was evaluated through a large two-group, pre-test post-test survey. Overall, this thesis contributes to a promising area of research that has been relatively unexplored in related literature.

关键词： Physics   Artificial intelligence   Computer science   Fluid mechanics   Industrial engineering   Mathematics   Mechanics   Polymer chemistry   Surgery  

摘要： Laser powder bed fusion (L-PBF) additive manufacturing (AM) is capable of producing complex parts near net shape with good mechanical properties. However, undesired residual stress and distortion that lead to build failure and defects such as porosity are preventing broader applications of L-PBF. To realize the full potential of L-PBF, a multiscale modeling methodology is developed to predict residual deformation, melt pool, and porosity formation. To predict the residual deformation and stress in L-PBF at part-scale, a multiscale process modeling framework based on inherent strain method is proposed. Inherent strain vectors are extracted from detailed multi-layer process simulation with high fidelity at micro-scale. Uniform but anisotropic strains are then applied to L-PBF part in a layer-by-layer fashion in a quasi-static equilibrium finite element analysis (FEA) to predict residual distortion and stress. Besides residual distortion and stress prediction at part scale, multiphysics modeling at powder scale is performed to study the melt pool variation and defect formation induced by process parameters, preheating temperature and spattering particles. Melt pool dynamics and porosity formation mechanisms associated with these factors are revealed through simulation and experiments. Based on the proposed part-scale residual stress and distortion model, path planning method is developed to tailor the laser scanning path for a given geometry to prevent large residual deformation and building failures. Gradient based path planning for continuous and island scanning strategy is formulated and full sensitivity analysis for the formulated compliance- and stress-minimization problem is performed. The feasibility and effectiveness of this proposed path planning method is demonstrated experimentally using the AconityONE L-PBF system. In addition, a data-driven framework utilizing machine learning is developed to predict the thermal history at part-scale for L-PBF. In this wor

关键词： Artificial intelligence   Computer science   Energy   Sustainability   Transportation  

摘要： As an attractive transportation mode, rail transit consumes a lot of energy while transporting a large number of passengers annually. Most energy-aimed research in rail transit focuses on optimizing the train timetable and speed trajectory offline. However, some disturbances during travel will cause the train to fail to follow the offline optimized control strategy, thus invalids the offline optimization. In the typical rail transit control framework, the moving authority of trains is calculated by the zone controller based on the moving/fixed block system in the zone. The zone controller is used to ensure safety when the travel plan of trains changes due to disturbance. Safety is guaranteed during the process, but the change of travel plan leads to extra energy costs. The energy-aimed optimization problem in rail transit requires ensuring safety, pursuing punctuality with considering track slope, travel comfort, energy transferring efficiency, and speed limit, etc. The complex constraints lead to high computational pressure. Therefore, it is difficult for the regional controller to re-optimize the travel plan for all affected trains in near real-time. Multi-agent systems are widely used in many other fields, which show decent performance in solving complex problems by coordinating multiple agents. This study proposes a multi-agent system with multiple optimization algorithms to realize energy-aimed re-optimization in rail transit under different disturbances. The system includes three types of agents, train agents, station agents and central agents. Each agent exchanges information by following the time trigger mechanism (periodically) and the event trigger mechanism (occasionally). Trigger mechanism ensures that affected agents receive necessary information when interference occurs, and their embedded algorithms can achieve necessary optimization. Four types of cases 5 / 128 are tested, and each case has plenty of scenarios. The tested results show that the propos

关键词： Correlation   Measurement   Machine learning   Systematics   Biomedical measurement   Licenses   Computer science   Matthews correlation coefficient   diagnostic odds ratio   binary classification   confusion matrix   supervised machine learning   confusion tetrahedron  

摘要： To assess the quality of a binary classification, researchers often take advantage of a four-entry contingency table called confusion matrix, containing true positives, true negatives, false positives, and false negatives. To recap the four values of a confusion matrix in a unique score, researchers and statisticians have developed several rates and metrics. In the past, several scientific studies already showed why the Matthews correlation coefficient (MCC) is more informative and trustworthy than confusion-entropy error, accuracy, F-1 score, bookmaker informedness, markedness, and balanced accuracy. In this study, we compare the MCC with the diagnostic odds ratio (DOR), a statistical rate employed sometimes in biomedical sciences. After examining the properties of the MCC and of the DOR, we describe the relationships between them, by also taking advantage of an innovative geometrical plot called confusion tetrahedron, presented here for the first time. We then report some use cases where the MCC and the DOR produce discordant outcomes, and explain why the Matthews correlation coefficient is more informative and reliable between the two. Our results can have a strong impact in computer science and statistics, because they clearly explain why the trustworthiness of the information provided by the Matthews correlation coefficient is higher than the one generated by the diagnostic odds ratio.

关键词： Robotics   Computer science   Mechanical engineering  

摘要： This work aims to study the nonprehensile planar manipulation of a cubic block using a nonholonomic MuSHR race car equipped with a flat planar bumper/pusher. The underactuated and nonholonomic nature of our setup and the uncertainty of physical parameters like friction coefficients between contact surfaces, the pressure distribution of the cubic block, etc. pose challenges for planning and control. To tackle these challenges and the sliding motion of the block along the pusher, our method uses an analytical model to output a set of stable pushes in velocity space to generate trajectories from the block’s start to it’s goal position using a graph-based planner under a quasi-static assumption. Stable pushes are defined as push actions in velocity space that do not cause sliding motion of the block w.r.t. the pusher. We then deploy an LSTM based MPC with added stochasticity to approximate the pushing dynamics and track the planner trajectories. We conduct pushing experiments and compare our LSTM based MPC against a first-order Markov Gaussian Process and stable pushing-based MPCs for adaptability to different pushing experiments and robustness to initial sliding displacements. Our results suggest that the LSTM based MPC is more robust to initial sliding displacements compared to baseline alternatives and can be used to track planner and non-planner outputted trajectories.

关键词： Health sciences   Software   Diabetes   Computer science   Telemedicine   Endocrinology   Socioeconomic factors   Poverty   African Americans   Minority & ethnic groups   Mortality   Empowerment   Chronic illnesses   Disease control   Drug therapy  

摘要： Introduction. Diabetes mellitus is a condition with a growing morbidity and mortality burden. An estimated 30 million adults currently live with diabetes, with each individual spending over $9500 annually on medical care. The successful management of diabetes is a lifelong endeavor. This involves balancing a variety of factors including diet, medications, and glucose monitoring. It has been well established that successful control of diabetes depends largely upon patients’ daily lifestyle habits and activities. Not all patients, however, have the resources necessary for effective diabetes management. Health disparities lead to a higher rate of diabetes development in minority and poor populations. Since underserved patients have limited access to traditional healthcare avenues, providers should explore other means, like mobile health (mHealth), to help such patients. The rapid adoption of smartphones within the last decade has allowed an opportunity for patients to use mHealth and smartphone applications (apps) as a low-cost way to get health information and services. mHealth has the potential to address such disparities in access to health care. Little is known about the effectiveness of using apps to help underserved patients with their diabetes management. Assessing these patients’ current self-management practices and their interest in using smartphone apps for their diabetes management is the first step in determining how mHealth may benefit this patient population. Purpose. The purpose of this study was to assess how underserved patients with limited access to primary care physicians handled their diabetes on their own at home, to determine what challenges they faced with their self-management, and to examine their willingness to use diabetes mHealth apps on their smartphones to assist with their diabetes management. Methods. This study employed purposive sampling to select patients for individual interviews. Participant selection occurred at a Memphis hospita

关键词： Artificial intelligence   Computer science   Computer engineering  

摘要： Stereo is the estimation of depth from two views of the same scene. There are two types of depth cues in a stereo image pair: matching and occlusion. Matching refers to regions of the scene that are visible to both views, and occlusion refers to regions that are visible in one view but invisible in the other due to a nearby occluder. Vision science has shown that both types of information are used for depth estimation early in the visual cortex, and human observers can perceive depth even when matching cues are absent or very weak, a capability that remains absent from most computer vision stereo systems. It is one of the reasons why state-of-the-art computer vision stereo algorithms still perform poorly near occlusion boundaries and the associated occluded regions. However, occlusion boundaries are important because they often coincide with object boundaries, and localizing them and predicting precise depth near them is vital for many visual tasks like grasping, manipulation and navigation. This dissertation describes a series of works that make progress towards using stereo occlusion information and improving the depth accuracy near occlusion boundaries. We begin by introducing a taxonomy of local occlusion boundary signatures among patterns of stereo matching scores, categorized by the levels of textures in the nearby foreground and background surfaces. This motivates the investigation of detectors for stereo occlusion boundaries in different types of scenes. Based on this motivation, we design a detector using a simple feedforward network with relatively small receptive fields. We show that the local detector produces better boundaries than many other stereo methods, even without incorporating explicit stereo matching, top-down contextual cues, or single-image boundary cues based on texture and intensity. Next, we describe two algorithms that successfully integrate the matching and occlusion cues in stereo systems. In both algorithms, we represent the disparity

关键词： Computer science   Applied mathematics   Neurosciences   Artificial intelligence  

摘要： Deep neural networks are naturally “black boxes”, offering little insight into how or why they make decisions. These limitations diminish the adoption likelihood of such systems for important tasks and as trusted teammates. We employ introspective techniques to abstract machine activation patterns into human-interpretable strategies and identify relationships between environmental conditions (why), strategies (how), and performance (result) on both a deep reinforcement learning two-dimensional pursuit game application and image-based deep supervised learning obstacle recognition application. Pursuit-evasion games have been studied for decades under perfect information and analytically-derived policies for static environments. We incorporate uncertainty in a target’s position via simulated measurements and demonstrate a novel continuous deep reinforcement learning approach against speed-advantaged targets. The resulting approach was tested under many scenarios and performance exceeded that of a baseline course-aligned strategy. We manually observed separation of learned pursuit behaviors into strategy groups and manually hypothesized environmental conditions that affected performance. These manual observations motivated automation and abstraction of conditions, performance and strategy relationships. Next, we found that deep network activation patterns could be abstracted into human-interpretable strategies for two separate deep learning approaches. We characterized machine commitment by the introduction of a novel measure and revealed significant correlations between machine commitment, strategies, environmental conditions, and task performance. As such, we motivated online exploitation of machine behavior estimation for competency-aware intelligent systems. And finally, we realized online prediction capabilities for conditions, strategies, and performance. Our competency-aware machine learning approach is easily portable to new applications due to its Bayesian nonp

关键词： Computer Science   Databases  

摘要： We study the problem of enumerating answers of Conjunctive Queries ranked according to a given ranking function. Our main contribution is a novel algorithm with small preprocessing time, logarithmic delay, and non-trivial space usage during execution. To allow for efficient enumeration, we exploit certain properties of ranking functions that frequently occur in practice. To this end, we introduce the notions of decomposable and compatible (w.r.t. a query decomposition) ranking functions, which allow for partial aggregation of tuple scores in order to efficiently enumerate the output. We complement the algorithmic results with lower bounds that justify why restrictions on the structure of ranking functions are necessary. Our results extend and improve upon a long line of work that has studied ranked enumeration from both a theoretical and practical perspective.

关键词： Computer science   Cryptography   Cybersecurity   Quantum algorithms   Quantum computing  

摘要： This work aims to demonstrate the abilities of modern quantum computers and quantum programming languages through implementations and practical usages of two of the most famous quantum algorithms: Shor's algorithm and Grover's algorithm, as well as through general quantum computing operations. These implementations will further demonstrate a proof-of-concept of relatively few-qubit quantum computers to encode and transmit data in a secure, tamper-proof manner using the Chinese Remainder Theorem. Lastly, this work discusses an implementation of Grover's algorithm requiring fewer qubits, but which may be limited in overall applicability