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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： Alternative Energy   Computer science   Energy   Mathematics   Transportation  

摘要： This work will present a Medium Voltage Distribution Network that is operated as a Smart Grid. As the distribution infrastructure for electric energy ages and the share of EV’s and renewables increases, changes will have to be made to support the increasing power flows in the network. A more long-term solution than reinforcing the network with heavier cables is constructing an intelligent network that reacts to changing power flows inside the network and adapts accordingly to guarantee optimal functionality. External data from an optimisation algorithm is used to determine the switching behaviour. The network was modeled and analysed using a simulation software. If done correctly, a simulation can offer a lot of insight for only a fraction of the cost of constructing and testing the network in reality. MATLAB Simulink was used for the virtual modeling and analysis of the network. The main objective is to construct a model of the MVDN and use it to generate and analyse the power flows in the network to determine the plausibility of exploiting a similar network in an existing city. The models for each of the network components were developed and picked to combine them into a functioning network model based on the smart city’s topology. Simulating a smart grid is in essence not novel, but has not been done in Simulink before in this context. The hardest obstacle to overcome during the construction of the network model was finding a way to achieve the making and breaking of network connections in a way that Simulink could compute the network parameters correctly and in a timely manner. A whole section is dedicated to resolving these development issues. Following this, the results of the simulation regarding power flows and losses in the network are discussed. When it comes to the renewable generation implementation, the results showed promising results, even on days with low wind velocity the renewables aided in reducing the power demanded from the substation. The total

关键词： Mathematics   Operations research   Design optimization   Simulation   Computer science   Regression analysis   Random variables   Equilibrium   Roads & highways   Approximation   Probability   Prices   Algorithms   Dynamical systems   Servers  

摘要： Stochastic modeling plays an important role in estimating potential outcomes where randomness or uncertainty is present. This type of modeling forecasts the probability distributions of potential outcomes by allowing for random variation in one or more inputs over time under different conditions. One of the classic topics of stochastic modeling is queueing theory. Hence, the first part of the dissertation is about a stylized queueing model motivated by paid express lanes on highways. There are two parallel, observable queues with finitely many servers: one queue has a faster service rate, but charges a fee to join, and the other is free but slow. Upon arrival, customers see the state of each queue and choose between them by comparing the respective disutility of time spent waiting, subject to random shocks. This framework encompasses both the multinomial logit and exponomial customer choice models. Using a fluid limit analysis, we give a detailed characterization of the equilibrium in this system. We show that social welfare is optimized when the express queue is exactly at (but not over) full capacity; however, in some cases, revenue is maximized by artificially creating congestion in the free queue. The latter behaviour is caused by changes in the price elasticity of demand as the service capacity of the free queue fills up. The second part of the dissertation is about a new optimal experimental design for linear regression models with continuous covariates, where the expected response is interpreted as the value of the covariate vector, and an “error” occurs if a lower-valued vector is falsely identified as being better than a higher-valued one. Our design optimizes the rate at which the probability of error converges to zero using a large deviations theoretic characterization. This is the first large deviations-based optimal design for continuous decision spaces, and it turns out to be considerably simpler and easier to implement than designs that use discretiza

关键词： Robotics   Artificial intelligence   Computer science   Algorithms   Behavior   Deep learning   Coffee   Knowledge   Robots   Adaptation   Preferences   Walking   Objectives   Semantics  

摘要： Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensi

关键词： Computer science   Oncology   Bioinformatics   Artificial intelligence   Genetics  

摘要： The introduction of genetic testing has profoundly enhanced the prospects of early detection of diseases and techniques to suggest precision medicines. The subtyping of critical diseases has proven to be an essential part of the development of individualized therapies and has led to deeper insights into the heterogeneity of the disease. Studies suggest that variants in particular genes have significant effects on certain types of immune system cells and are also involved in the risk of certain critical illnesses like cancer. By analyzing the genetic sequence of a patient, disease types and subtypes can be predicted. Recent research work has shown that the CNN's prediction quality within this context using gene intensity features could be improved when the input is structured into 2D images. Constructed from chromosome locations or from transformations involving kPCA, t-SNE, etc., these two-dimensional images express certain types of relationships among the intensity features. While this approach extends the success of convolutional neural networks to non-image data, getting a precise mapping of features on the images to reflect the relationship among the features is hard, if not impossible. To this end, we propose an enhancement to the approach by providing the CNN training procedure with not only the samples of the structured image data but also the samples from the unstructured raw gene expression data in its original form. While the former is fed into the convolutional layers in the network, the latter is input only to the fully connected layers of the network. The proposed method is applied to The Cancer Genome Atlas (TCGA) dataset for cancer subtypes with the median values of the expression level of all expressed genes in an RNA sequence. According to the experiments, our proposed approach can improve the classification accuracy by 2.7% when it is applied to the state-of-the-art method with 2D CNN architecture trained using images that are constructed based on

关键词： Mathematics   Computer science   Artificial intelligence  

关键词： Computer science   Artificial intelligence  

摘要： Recent advances in mobile devices, having embedded sensors and high-performance processors, enable the users to collect sensor data and utilize them more easily. These improvements in accessibility have led to beneficial developments in many areas. In this paper, we present Deep-Scanner, which finds the stud only by knocking with a smartphone. Deep-Scanner utilizes a microphone and accelerometer sensor to collect the knocking sounds and exploit 1D-Convolution Neural Network to identify the stud's existence. In our experiment, our model achieved high accuracy up to 97% with samples of 4-inch intervals. It also can find the stud with an accuracy of less than 0.75-inches.

关键词： Computer science   Computer engineering   Information technology   Artificial intelligence   Accuracy   Datasets   Sensors   Traffic control   Support vector machines   Classification   Noise   Methods   Algorithms  

摘要： Despite the breakthroughs in machine learning, most classifiers are not robust against adversarial attacks. They can be easily fooled by adversarial examples. These examples can be created in a variety of ways. In this thesis, the ideas of detecting edges or critical pixels in an image are investigated that could be used for fooling classifiers. Identifying those critical pixels in an image can lead the way to fix the vulnerabilities and thus making it robust against cyber-attacks. For testing, a Support Vector Machine (SVM) is used to see the success of the adversarial examples generated.

关键词： Transportation   Computer science   Environmental justice  

摘要： Transportation equity plays an important role in modern communities, and a fair distribution of transportation infrastructures is vital as an integral part of transportation planning process. The In-Service Performance Evaluation (ISPE) satisfies transportation safety requirements by identifying the problems of roadside safety devices during installation and maintenance process with proper solutions, and the performance results reveal the current statue of target devices in specific areas. Although several studies have been conducted to emphasize transportation equity, there is still a lack of equity research specifically focusing on the deploying of roadside safety devices associated with ISPE results. With proper comparison of in-service performance results in different areas, the importance of ensuring transportation equity of all communities and areas in the decision-making process is able to be demonstrated. This thesis utilizes Machine Learning models to analyze linked crash and roadway data related to major roadside safety devices implemented in Texas. Three typical roadside safety devices are selected to be assessed, including: (1) guardrail, (2) median barrier, and (3) bridge rail. By comparing both statistical and Machine Learning based modeling analysis with rural and metropolitan areas in specific counties, it is demonstrated that distributions of crashes that end up causing heavy property damage or serious injuries is higher in rural communities regardless of its lower crash frequency. The data analysis result suggests that parameters related to roadway conditions and transportation infrastructures tend to have higher influence over the performances of rural safety devices. Additional one year of crash data analysis also addresses the importance of transportation equity under the COVID-19 pandemic period. Recommendations on improving overall equity and Environmental Justice (EJ) within all regions are conducted with stated findings.