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关键词： Phase transitions   Lifetime   Energy conservation   Hydrocarbons   Algorithms   Solvents   Polymerization   Equilibrium   Computer science   Energy  

摘要： Metal-mediated organometallic reactions are critical for both catalytic and synthetic chemistry. Density functional theory (DFT) potential-energy calculations are routinely used with a transition-state theory type of approach to understand and predict the reaction mechanisms of organometallic reactions. However, these calculations do not include atomic momentum and thus ignore dynamic effects. Molecular dynamics is a powerful tool for elucidating mechanistic details of chemical reactions. In this dissertation, quasiclassical molecular dynamics studies reveal key mechanistic details about several fundamental organometallic reactions. Chapter 1 provides a brief overview of key molecular dynamics details. Chapters 2-4 provide details on for three classic organometallic reactions involving alkane C-H bonds. These Chapters are from previously published works (J. Am. Chem. Soc. 2018, 140, 11039; Organometallics 2019, 38, 2280; Organometallics, 2021, 40, 1454). Chapter 5 provides details about progress toward performing quasiclassical molecular dynamics simulations of organometallic reactions in explicit organic solvent.

关键词： Immunology   Bioinformatics   Cellular biology   Computer science   Information Technology   Medicine   Surgery   Therapy  

摘要： A tumour-specific neoantigen-based cancer vaccine is a potentially powerful treatment option, which utilises unique mutated peptides from tumour cells to boost the immune response and selectively attack cancer cells. Thus, the characterisation of the specifically targeted peptides that can be selectively recognised by the immune system is essential for this approach. However, a major problem in neoantigen prediction is obtaining false positives, leading to poor outcomes in clinical research and practice. This thesis aims to address some of the computational issues in neoantigen prediction, including developing more reliable statistics for assessing peptide binding to MHC, and using machine learning to predict which peptides will generate an immune response. Specifically, the thesis introduces an approach for parameter estimation using the modified expectation maximisation (EM) framework with the method of moments for a two-component beta mixture model, representing the distribution of true and false scores from peptide binding prediction. The estimated parameters obtaining from the model can be further used for estimating false discovery rate (FDR) or a local peptide-level statistic such as the posterior error probability (PEP) to develop a robust method for MHC binding peptide selection. Next, the thesis introduces a new immunogenicity prediction model to classify immunogenic and non-immunogenic peptides using machine learning. A data set was assembled containing peptides classes as immunogenic and non-immunogenic peptides, and peptide features of physicochemical properties and homology features were used for constructing the Random Forest classifier for immunogenicity prediction. The two innovations were assembled into an end-to-end pipeline that provides the final probability described true MHC binding ability and the potential for immunogenicity. The final probability of MHC binding and T cell recognition provides a statistical framework to guide users in defini

关键词： Computer science  

ISBN: (数字)9781636391694 ISBN: (纸本)9781636391700;9781636391687

摘要： This book is the first to present the state of the art and provide technical focus on the latest advances in the foundations of blockchain systems. It is a collaborative work between specialists in cryptography, distributed systems, formal languages, and economics, and addresses hot topics in blockchains from a theoretical perspective: cryptographic primitives, consensus, formalization of blockchain properties, game theory applied to blockchains, and economical issues. This book reflects the expertise of the various authors, and is intended to benefit researchers, students, and engineers who seek an understanding of the theoretical foundations of blockchains.

关键词： Computer science   Artificial intelligence  

摘要： Density-based clustering algorithms are widely used unsupervised data mining techniques to find the clusters of points in dense regions that are separated by low-density regions. This algorithm is inherently sequential and has limitations in its parallel implementation. There have been several parallel algorithms presented in the literature for multi-core CPUs and many-core GPUs. One such algorithm for the GPU is CUDA-DClust. In this paper, we propose a new GPU-accelerated DBSCAN algorithm with several optimizations. In comparison to prior work, our algorithm, CUDA-DClust+: (i) computes the indexing structure on the GPU, (ii) uses kernel fusion to combine the index search and cluster expansion kernels, which reduces communication and synchronization overhead with the host, and (iii) seed list management control is primarily given to the GPU rather than the CPU, which further decreases CPU-GPU communication overhead. We compare our algorithm to three state-of-the-art parallel algorithms in the literature on six real-world datasets. We find that our algorithm achieves a speedup of up to ~23x over the fastest GPU algorithm.

关键词： Ecology   Computer science   Agriculture  

摘要： Agroecosystems face multiple threats including land degradation and climate change, changing and competing land uses, invasive species and disease spread, and biodiversity loss. While scientists seek to understand rapidly changing ecosystems, land managers are struggling to maintain ecosystem services amid transitions to novel ecosystem states. Understanding agroecosystem drivers and ensuing responses requires quality information about ecosystems that span biomes, trophic scales, ecological processes, spatiotemporal scales, land use, and land ownership. Yet, using multi-scale agroecosystem information can be frustrating for both scientific researchers and land managers as it is difficult to locate data that are trustworthy, easily accessible, standardized, and connected to analytical tools. Consequently, we urgently need new approaches to agroecological data that leverages our current technological capabilities and disrupts conventional informatics practice and wisdom to improve linkages between science and managers as we seek to understand our rapidly changing ecosystems. In this dissertation, I explore how conceptual and cyberinfrastructure frameworks can assist both land managers and researchers in improving data quality and data access for management and modelling applications. I find that a cultural shift is needed in how we prevent and detect issues pertaining to data quality. A question driven approach can facilitate collaborative, iterative improvements in data quality. Collaborative development of frameworks to calculate agroecosystem indicators is necessary to ensure that software tools are relevant to managers and appropriate to describe ecosystem processes. Finally, I demonstrate how a data commons approach to data aggregation can facilitate data integration with models, other datasets, and decision support tools. I conclude the dissertation by addressing both the cultural and technological challenges of data integration and use and highlight how these a

关键词： Library technology   Computer science students   Library employment   Recruitment   Mentorship  

摘要： Academic libraries in the United States often have difficulty recruiting for technology-focused positions. This mixed-methods study examines what technology skills libraries are seeking in entry-level technology positions and explores ways to increase interest in library employment. Utilizing Lent’s (2013) social cognitive career theory (SCCT) framework, this study seeks to understand why students study computer science, how computer science students seek future employment, and explores how a large university in the southeastern United States can facilitate interest in applying for library technology positions. Quantitative data was determined through an examination of library technology positions to explore trends and what skills employers are seeking. Qualitative data was gathered from recorded interviews with current junior and senior level undergraduate computer science majors. Combined with an in-depth look at the literature and recruitment needs of libraries, possible solutions to the problem of practice are offered in the form of practical internships, interdisciplinary collaboration, and a potential graduate certificate with the goal of connecting computer science students to software development positions in libraries.

关键词： Computer science   Artificial intelligence  

摘要： We humans still perceive and reason in a different way than artificial intelligence models. We witness, we listen, we touch, we understand the world via multi-modal sensing, while machine models rely only on a single or a few modalities and ignore abundant information. In this thesis, we explore techniques for reducing the perception gap between machines and humans and focus on two families of tasks, reasoning and detection. First, we incorporate information from text, audio, motion, external knowledge bases, for training computer vision models. We find that data inputs from more extensive channels provide complementary information to improve models. Second, we study how multimodal inputs can be fully utilized. We argue that most existing deep learning methods are prone to pay too large attention to shallow patterns in the input features, which causes the resulting models to be biased. We propose robust training to overcome the issue. Third, we extend the benefits of multi-modal information to the supervision signals instead of the inputs, by learning a weakly supervised detection model from the natural supervision of textual captions or audio narrations. With the help of NLP constituency parsing, it is possible to extract structural knowledges from the captions and narrations, hence determines the entities and relations of visual objects.

关键词： Control algorithms   Bandwidths   Electric vehicles   Sensors   Controllers   Power supply   Powertrain   Climate change   Computer science   Transportation  

摘要： A high bandwidth (> 20 kHz) motor emulator for IPM machine, utilizing FPGA based high fidelity motor model and hybrid model predictive controller (MPC), voltage source power converter, and fast-switching SiC devices, is presented in this dissertation. The bandwidth achieved far exceeds that of existingMotor Emulator (ME) solutions that can only emulate fundamental current and only few orders of harmonic content. The developed ME uses an MPC based control strategy with a unique gate stitching strategy that synchronizes the inverter switching state with the ME switching state for accurate representation of the emulated motor currents in the physical inverter hardware output. The MPC-gate stitching hybrid algorithm avoids the need for excessively high switching frequency of the ME converter. The developed high bandwidth ME can emulate up to the switching ripple current of the Inverter Under Test (IUT) of which the current slope can change up to 6 times within one switching period when using SVM. The FPGA based fast iterating online motor model is another key component which along with the high performance ME current regulation algorithm can accurately emulate the motor current. The high bandwidth also allows the use of a small line inductor which reduces the size and cost of the ME system. The FPGA implementation and control strategy are given in the dissertation. Simulation and experiment results are provided to verify the high bandwidth current emulating capability. To demonstrate the superiority and flexibility of the motor emulator, advanced motor control techniques are also investigated in this dissertation. Moreover, the details of the motor modeling and FPGA system design methodology are discussed in corresponding chapter.

关键词： Robotics   Artificial intelligence   Computer science   Disinfection & disinfectants   Velocity   Active learning   Success   Planning   Graph representations   Trees   Algorithms   Heuristic  

摘要： Mobile manipulators are essentially robotic arms that can move around and hence provide flexibility in the kinds of tasks they can do. This significantly reduces down-time of such robots as compared to fixed manipulators. Moreover, moving the manipulator and mobile base concurrently can make mobile manipulators more efficient as compared to moving them one at a time as done traditionally. In certain scenarios, it may be even be necessary to move the mobile base and the manipulator concurrently. Motion planning for mobile manipulators with concurrent motions of the mobile base and the manipulator especially with a nonholonomic mobile base is a very challenging problem. In this dissertation, specialized techniques for motion planning of mobile manipulators are presented for three inherently important tasks. These tasks are namely object pick-up, transportation, and area coverage. In the first task, the goal is to pick-up objects while the mobile base is in motion. The dissertation individually focuses on mobile base, manipulator and gripper motion planning under object pose uncertainty. If a mobile manipulator is tasked to pick-up an object from a table while the base is still moving, there are several decisions the robot must make. It must figure out how to move the mobile base such that it reaches close to the object since the intermediary point where the manipulator picks up the object is unknown. Moreover, it must determine when on the mobile base path should the manipulator start moving. Furthermore, the robot must figure out how to grasp the object such that it is the easiest to execute the motions. And finally, if there is uncertainty in the pose of the object, how should the gripper move so that the probability of grasping is high. These challenges are addressed in this dissertation by having: (a) a discrete search-based planner for the mobile base with specialized heuristics to guide it towards the object and a cost function for the time-delay caused by the m

关键词： Mathematics   Computer science   Writers   Scientists   Datasets   Schools   Graphs   Experiments   Dissertations & theses   Eigen values   Neurosciences   Algorithms   Clustering   Immunization   Geometry  

摘要： Traditionally, the study of complex networks has employed mathematical tools from graph theory and statistical physics. More recently, topological data analysis has introduced the application of algebraic topology to network science, opening up new possibilities. This dissertation takes a similar direction by drawing on topological and geometrical aspects of graph theory to develop data mining algorithms that provide new scientific insights into complex networks. I consider the geometric structure of networks at many levels. First, I study the intrinsic metric structure of a graph using the theory of length spectrum and its relation to the eigenvalues of the non-backtracking matrix of the graph. I use this relationship to develop a principled algorithm for measuring graph distance. Second, I study the geometric structure of graph embeddings. Graph embedding techniques place a graph in a surrounding metric space. I use the geometry of this space to develop two embedding algorithms that enable the performance of such tasks such as link prediction and anomaly detection in an efficient and interpretable manner. Third, because considering distances between graphs depends on the assumption that graphs with similar structure exhibit similar behavior, I study how certain dynamical properties of graphs change under small perturbations of their structure. In particular, I focus on how small perturbations to the structure of the graph affect the epidemic threshold of certain dynamics. I introduce two algorithms that effectively manipulate the epidemic threshold by exploiting the relationship between the graph structure and its spectral properties. I conclude with a reflection on the current trend in network science to rethink the study of complex systems in terms of polyadic relations. My collaborators and I find that a necessary step in this direction is to focus on the properties of real-world systems that determine which relationships affect the existence of other relations