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2017

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Articles 3301 - 3330 of 12522

Full-Text Articles in Physical Sciences and Mathematics

Flexible Online Task Assignment In Real-Time Spatial Data, Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, Ke Xu Aug 2017

Flexible Online Task Assignment In Real-Time Spatial Data, Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, Ke Xu

Research Collection School Of Computing and Information Systems

The popularity of Online To Offline (O2O) service platforms has spurred the need for online task assignment in real-time spatial data, where streams of spatially distributed tasks and workers are matched in real time such that the total number of assigned pairs is maximized. Existing online task assignment models assume that each worker is either assigned a task immediately or waits for a subsequent task at a fixed location once she/he appears on the platform. Yet in practice a worker may actively move around rather than passively wait in place if no task is assigned. In this paper, we define …

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Recommendation Vs Sentiment Analysis: A Text-Driven Latent Factor Model For Rating Prediction With Cold-Start Awareness, Kaisong Song, Wei Gao, Shi Feng Feng, Daling Wang, Kam-Fai Wong, Chengqi Zhang Aug 2017

Recommendation Vs Sentiment Analysis: A Text-Driven Latent Factor Model For Rating Prediction With Cold-Start Awareness, Kaisong Song, Wei Gao, Shi Feng Feng, Daling Wang, Kam-Fai Wong, Chengqi Zhang

Research Collection School Of Computing and Information Systems

Review rating prediction is an important research topic. The problem was approached from either the perspective of recommender systems (RS) or that of sentiment analysis (SA). Recent SA research using deep neural networks (DNNs) has realized the importance of user and product interaction for better interpreting the sentiment of reviews. However, the complexity of DNN models in terms of the scale of parameters is very high, and the performance is not always satisfying especially when user-product interaction is sparse. In this paper, we propose a simple, extensible RS-based model, called Text-driven Latent Factor Model (TLFM), to capture the semantics of …

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Large-Scale Online Feature Selection For Ultra-High Dimensional Sparse Data, Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu Aug 2017

Large-Scale Online Feature Selection For Ultra-High Dimensional Sparse Data, Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu

Research Collection School Of Computing and Information Systems

Feature selection (FS) is an important technique in machine learning and data mining, especially for large scale high-dimensional data. Most existing studies have been restricted to batch learning, which is often inefficient and poorly scalable when handling big data in real world. As real data may arrive sequentially and continuously, batch learning has to retrain the model for the new coming data, which is very computationally intensive. Online feature selection (OFS) is a promising new paradigm that is more efficient and scalable than batch learning algorithms. However, existing online algorithms usually fall short in their inferior efficacy. In this article, …

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Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok Aug 2017

Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok

Research Collection School Of Computing and Information Systems

Measuring and understanding the performance of mobile networks is becoming very important for end users and operators. Despite the availability of many measurement apps, their measurement accuracy has not received sufficient scrutiny. In this paper, we appraise the accuracy of smartphone-based network performance measurement using the Android platform and the network round-trip time (RTT) as the metric. We show that two of the most popular measurement apps-Ookla Speedtest and MobiPerf-have their RTT measurements inflated. We build three test apps that cover three common measurement methods and evaluate them in a testbed. We overcome the main challenge of obtaining a complete …

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Sparse Online Learning Of Image Similarity, Xingyu Gao, Steven C. H. Hoi, Yongdong Zhang, Jianshe Zhou, Ji Wan, Zhenyu Chen, Jintao Li, Jianke Zhu Aug 2017

Sparse Online Learning Of Image Similarity, Xingyu Gao, Steven C. H. Hoi, Yongdong Zhang, Jianshe Zhou, Ji Wan, Zhenyu Chen, Jintao Li, Jianke Zhu

Research Collection School Of Computing and Information Systems

Learning image similarity plays a critical role in real-world multimedia information retrieval applications, especially in Content-Based Image Retrieval (CBIR) tasks, in which an accurate retrieval of visually similar objects largely relies on an effective image similarity function. Crafting a good similarity function is very challenging because visual contents of images are often represented as feature vectors in high-dimensional spaces, for example, via bag-of-words (BoW) representations, and traditional rigid similarity functions, for example, cosine similarity, are often suboptimal for CBIR tasks. In this article, we address this fundamental problem, that is, learning to optimize image similarity with sparse and high-dimensional representations …

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Modeling Trajectories With Recurrent Neural Networks, Hao Wu, Ziyang Chen, Weiwei Sun, Baihua Zheng, Wei Wang Aug 2017

Modeling Trajectories With Recurrent Neural Networks, Hao Wu, Ziyang Chen, Weiwei Sun, Baihua Zheng, Wei Wang

Research Collection School Of Computing and Information Systems

Modeling trajectory data is a building block for many smart-mobility initiatives. Existing approaches apply shallow models such as Markov chain and inverse reinforcement learning to model trajectories, which cannot capture the long-term dependencies. On the other hand, deep models such as Recurrent Neura lNetwork (RNN) have demonstrated their strength of modeling variable length sequences. However, directly adopting RNN to model trajectories is not appropriate because of the unique topological constraints faced by trajectories. Motivated by these findings, we design two RNN-based models which can make full advantage of the strength of RNN to capture variable length sequence and meanwhile to …

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Multiplex Media Attention And Disregard Network Among 129 Countries, Haewoon Kwak, Jisun An Aug 2017

Multiplex Media Attention And Disregard Network Among 129 Countries, Haewoon Kwak, Jisun An

Research Collection School Of Computing and Information Systems

We built a multiplex media attention and disregard network (MADN) among 129 countries over 212 days. By characterizing the MADN from multiple levels, we found that it is formed primarily by skewed, hierarchical, and asymmetric relationships. Also, we found strong evidence that our news world is becoming a "global village." However, at the same time, unique attention blocks of the Middle East and North Africa (MENA) region, as well as Russia and its neighbors, still exist.

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Personas For Content Creators Via Decomposed Aggregate Audience Statistics, Jisun An, Haewoon Kwak, Bernard J. Jansen Aug 2017

Personas For Content Creators Via Decomposed Aggregate Audience Statistics, Jisun An, Haewoon Kwak, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We propose a novel method for generating personas based on online user data for the increasingly common situation of content creators distributing products via online platforms. We use non-negative matrix factorization to identify user segments and develop personas by adding personality such as names and photos. Our approach can develop accurate personas representing real groups of people using online user data, versus relying on manually gathered data.

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Formresnet: Formatted Residual Learning For Image Restoration, Jianbo Jiao, Wei-Chih Tu, Shengfeng He Aug 2017

Formresnet: Formatted Residual Learning For Image Restoration, Jianbo Jiao, Wei-Chih Tu, Shengfeng He

Research Collection School Of Computing and Information Systems

In this paper, we propose a deep CNN to tackle the image restoration problem by learning the structured residual. Previous deep learning based methods directly learn the mapping from corrupted images to clean images, and may suffer from the gradient exploding/vanishing problems of deep neural networks. We propose to address the image restoration problem by learning the structured details and recovering the latent clean image together, from the shared information between the corrupted image and the latent image. In addition, instead of learning the pure difference (corruption), we propose to add a 'residual formatting layer' to format the residual to …

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Basket-Sensitive Personalized Item Recommendation, Duc Trong Le, Hady W. Lauw, Yuan Fang Aug 2017

Basket-Sensitive Personalized Item Recommendation, Duc Trong Le, Hady W. Lauw, Yuan Fang

Research Collection School Of Computing and Information Systems

Personalized item recommendation is useful in narrowing down the list of options provided to a user. In this paper, we address the problem scenario where the user is currently holding a basket of items, and the task is to recommend an item to be added to the basket. Here, we assume that items currently in a basket share some association based on an underlying latent need, e.g., ingredients to prepare some dish, spare parts of some device. Thus, it is important that a recommended item is relevant not only to the user, but also to the existing items in the …

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Predicting Potential Alzheimer Medical Condition In Elderly Using Iot Sensors - Case Study, Zhi Hao Kevin Chong, Yu Xuan Tee, Ling Jing Toh, Shi Jia Phang, Jie Ying Liew, Bertran Queck, Swapna Gottipati Aug 2017

Predicting Potential Alzheimer Medical Condition In Elderly Using Iot Sensors - Case Study, Zhi Hao Kevin Chong, Yu Xuan Tee, Ling Jing Toh, Shi Jia Phang, Jie Ying Liew, Bertran Queck, Swapna Gottipati

Research Collection School Of Computing and Information Systems

Ageing population would cause profound problems and the impact is already being felt today in many developed countries such as Singapore. The main concern for the Government is to help the citizens with active ageing through home ownership and good healthcare. With Internet of Things (IoT) gaining traction globally, Singapore is set to take advantage of this technology and leverage it to extend its capabilities towards a graceful Ageing-In-Place for the elderly. This ties in nicely with the expertise of SHINE Seniors project by SMU-iCity Lab, which integrates IT with healthcare in ways that creates innovative IT health solutions that …

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Electron Paramagnetic Resonance Study Of Neutral Mg Acceptors In Β-Ga2O3 Crystals, Brant E. Kananen [*], Larry E. Halliburton, Elizabeth M. Scherrer [*], K. T. Stevens, G. K. Foundos, K. B. Chang, Nancy C. Giles Aug 2017

Electron Paramagnetic Resonance Study Of Neutral Mg Acceptors In Β-Ga2O3 Crystals, Brant E. Kananen [*], Larry E. Halliburton, Elizabeth M. Scherrer [*], K. T. Stevens, G. K. Foundos, K. B. Chang, Nancy C. Giles

Faculty Publications

Electron paramagnetic resonance (EPR) is used to directly observe and characterize neutral Mg acceptors (Mg0Ga) in a β-Ga2O3 crystal. These acceptors, best considered as small polarons, are produced when the Mg-doped crystal is irradiated at or near 77 K with x rays. During the irradiation, neutral acceptors are formed when holes are trapped at singly ionized Mg acceptors (Mg−Ga). Unintentionally present Fe3+ (3d5) and Cr3+ (3d3) transition-metal ions serve as the corresponding electron traps. The hole is localized in a nonbonding p orbital on a threefold-coordinated oxygen ion …

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The Mechanism Of Plasma Plume Termination For Pulse Excited Plasmas In A Quartz Tube, Mingzhe Rong, Wenjie Xia, Xiaohua Wang, Zhijie Liu, Dingxin Liu, Zhihu Liang, Xiaoning Zhang, Michael G. Kong Aug 2017

The Mechanism Of Plasma Plume Termination For Pulse Excited Plasmas In A Quartz Tube, Mingzhe Rong, Wenjie Xia, Xiaohua Wang, Zhijie Liu, Dingxin Liu, Zhihu Liang, Xiaoning Zhang, Michael G. Kong

Bioelectrics Publications

Although the formation and propagation of plasma plume for atmospheric pressure plasmas have been intensively studied, how does the plasma plume terminate is still little known. In this letter, helium plasma plumes are generated in a long quartz tube by pulsed voltages and a constant gas flow. The voltages have a variable pulse width (PW) from 0.5 μs to 200 μs. It is found that the plasma plume terminates right after the falling edge of each voltage pulse when PW < 20 μs, whereas it terminates before the falling edge. When PW is larger than 30 μs, the …

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Novel Bayesian Adaptive Clinical Trial Designs In Early Phases, Haitao Pan Aug 2017

Novel Bayesian Adaptive Clinical Trial Designs In Early Phases, Haitao Pan

Dissertations & Theses (Open Access)

Early phase, or phase I and phase II, trials are the first step in testing new medicines that have been developed in the lab. The main goal of phase I clinical trials is to establish the recommended dose of new drugs for phase II trials. For the cytotoxic drugs, the goal is to find maximum tolerated dose (MTD). The guiding principle for dose escalation in phase I trials is to avoid exposing too many patients to subtherapeutic doses while preserving safety and maintaining rapid accrual. Therefore, dose escalation methods, especially Bayesian designs, are recommended to be used in phase I …

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A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener Aug 2017

A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener

Electronic Theses and Dissertations

This thesis presents an applied data science methodology on a set of University of Louisville, Speed School of Engineering student data. We used data mining and classic statistical techniques to help educational researchers quickly see the data trends and peculiarities. Our data includes scores and information about two Engineering Fundamental Class. The format of these classes is called an inverted classroom model or flipped class. The purpose of this study is to analyze the data in order to uncover potentially hidden information, tell interesting stories about the data, examine student learning behavior and learning performance in an active learning environment, …

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Likelihood-Based Methods For Analysis Of Copy Number Variation Using Next Generation Sequencing Data., Udika Iroshini Bandara Aug 2017

Likelihood-Based Methods For Analysis Of Copy Number Variation Using Next Generation Sequencing Data., Udika Iroshini Bandara

Electronic Theses and Dissertations

A Copy Number Variation (CNV) detection problem is considered using Circular Binary Segmentation (CBS) procedures, including newly developed procedures based on likelihood ratio tests with the parametric bootstrap for models based on discrete distributions for count data (Poisson and negative binomial) and a widely-used DNAcopy package. Results from the literature concerning maximum likelihood estimation for the negative binomial distribution are reviewed. The Newton-Raphson method is used to find the root of the derivative of the profile log likelihood function when applicable, and it is proven that this method converges to the true Maximum Likeihood Estimate (MLE), if the starting point …

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Some Problems Arising From Mathematical Model Of Ductal Carcinoma In Situ., Heng Li Aug 2017

Some Problems Arising From Mathematical Model Of Ductal Carcinoma In Situ., Heng Li

Electronic Theses and Dissertations

Ductal carcinoma in situ (DCIS) is the earliest form of breast cancer. Three mathematical models in the one dimensional case arising from DCIS are proposed. The first two models are in the form of parabolic equation with initial and known moving boundaries. Direct and inverse problems are considered in model 1, existence and uniqueness are proved by using tool from heat potential theory and Volterra integral equations. Also, we discuss the direct problem and nonlocal problem of model 2, existence and uniqueness are proved. And approximation solution of these problems are implemented by Ritz-Galerkin method, which is the first attempt …

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Extending Difference Of Votes Rules On Three Voting Models., Sarah Schulz King Aug 2017

Extending Difference Of Votes Rules On Three Voting Models., Sarah Schulz King

Electronic Theses and Dissertations

In a voting situation where there are only two competing alternatives, simple majority rule outputs the alternatives with the most votes or declares a tie if both alternatives receive the same number of votes. For any non-negative integer k, the difference of votes rule Mk outputs the alternative that beats the competing alternative by more than k votes. Llamazares (2006) gives a characterization of the difference of votes rules in terms of five axioms. In this thesis, we extend Llamazares' result by completely describing the class of voting rules that satisfy only two out of his five axioms. …

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Controlled Electrochemical Synthesis Of Single One-Dimensional Metal Nanochains Across Microgap Electrodes., Amareshwari Konutham Aug 2017

Controlled Electrochemical Synthesis Of Single One-Dimensional Metal Nanochains Across Microgap Electrodes., Amareshwari Konutham

Electronic Theses and Dissertations

This study mainly focuses on the fabrication of single one dimensional (1D) NP chains across the 5-micron gap of Au two electrode devices (TED). This has been achieved by electrochemical deposition of Ag onto the two electrodes, soaking the TED in 0.1 M Cetyltrimethyl ammonium bromide for 2-3 hours, and then close monitoring of the current as a function of time while a voltage across the two Ag coated Au electrodes in air. One dimensional Ag nanoparticle chain formation occurred by oxidation of Ag to Ag+ at the positive electrode followed by movement of Ag+ ions to the …

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Deep Learning Based Multi-Label Classification For Surgical Tool Presence Detection In Laparoscopic Videos, Ashwin Raju Aug 2017

Deep Learning Based Multi-Label Classification For Surgical Tool Presence Detection In Laparoscopic Videos, Ashwin Raju

Computer Science and Engineering Theses

Laparoscopic surgery, Modern surgery, where the surgery is performed far away from the patient by inserting small incisions on the patient's body and the surgery is performed with a help of a video recorder and through which the doctor performs the surgery. The computer assisted intervention are increasing exponentially and the need for accurate and reliable intervention is very important because of the domain which is very critical. Efforts have made to develop a system that is both fast and accurate approach but it is still an active area of research due its importance. Some applications which involve identifying the …

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An Intelligent Multimodal Upper-Limb Rehabilitation Robotic System, Alexandros Lioulemes Aug 2017

An Intelligent Multimodal Upper-Limb Rehabilitation Robotic System, Alexandros Lioulemes

Computer Science and Engineering Dissertations

A traffic accident, a battlefield injury, or a stroke can lead to brain or musculoskeletal injuries that impact motor and cognitive functions and can drastically change a person's life. In such situations, rehabilitation plays a critical role in the ability of the patient to partially or totally regain motor function, but the optimal training approach remains unclear. Robotic technologies are recognized as powerful tools to promote neuroplasticity and stimulate motor re-learning. Moreover, they deliver high-intensity, repetitive, active and task-oriented training; in addition, they provide objective measurements for patient evaluation. The primary focus of this research is to investigate the development …

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Evaluation Of A Factual Claim Classifier With And Without Using Entities As Features, Abu Ayub Ansari Syed Aug 2017

Evaluation Of A Factual Claim Classifier With And Without Using Entities As Features, Abu Ayub Ansari Syed

Computer Science and Engineering Theses

Fact-checking in real-time for events such as presidential debates is a challenging task. These fact-checking processes have a difficult and rigorous task in having the best accuracy in classifying facts, finding topics, etc. The first and foremost task in fact-checking is to find out whether a sentence is factually check-worthy. The UTA IDIR Lab has deployed an automated fact-checking system named ClaimBuster. ClaimBuster has a core functionality of identifying check-worthy factual sentences. Named entities are essentially an important component of any textual data. To use these named entities, it is required to link them to labels such as a person, …

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Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi Aug 2017

Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi

Electronic Theses and Dissertations

While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …

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Residuated Maps, The Way-Below Relation, And Contractions On Probabilistic Metric Spaces., M. Ryan Luke Aug 2017

Residuated Maps, The Way-Below Relation, And Contractions On Probabilistic Metric Spaces., M. Ryan Luke

Electronic Theses and Dissertations

In this dissertation, we will examine residuated mappings on a function lattice and how they behave with respect to the way-below relation. In particular, which residuated $\phi$ has the property that $F$ is way-below $\phi(F)$ for $F$ in appropriate sets. We show the way-below relation describes the separation of two functions and how this corresponds to contraction mappings on probabilistic metric spaces. A new definition for contractions is considered using the way-below relation.

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Water-Soluble Pd And Pd-Alloy Nanoparticles As Catalysts In Biphasic Solvent., Shekhar Bhama Aug 2017

Water-Soluble Pd And Pd-Alloy Nanoparticles As Catalysts In Biphasic Solvent., Shekhar Bhama

Electronic Theses and Dissertations

This dissertation shows the chemical synthesis of Pd and Pd-alloy nanoparticles (NPs) and their hydrogen and thermal stabilities for applications in the homogeneous and pseudo-homogeneous catalysis of organic reactions. Mainly, this dissertation describes 1) the chemical synthesis of Pd, PdPt, PdAu and Cu-Pd core-shell NPs coated with various organic ligands (thiols, amines and citrate), with different metal compositions in different synthetic environment, 2) the stability of solutions containing various NPs in the presence of hydrogen or varying temperatures, 3) the evaluation of the catalytic activity of Pd, PdPt, PdAu and CuPd NPs for hydrogenation/isomerization of allylic alcohols, and 4) the …

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Bayesian Approach On Short Time-Course Data Of Protein Phosphorylation, Casual Inference For Ordinal Outcome And Causal Analysis Of Dietary And Physical Activity In T2dm Using Nhanes Data., You Wu Aug 2017

Bayesian Approach On Short Time-Course Data Of Protein Phosphorylation, Casual Inference For Ordinal Outcome And Causal Analysis Of Dietary And Physical Activity In T2dm Using Nhanes Data., You Wu

Electronic Theses and Dissertations

This dissertation contains three different projects in proteomics and causal inferences. In the first project, I apply a Bayesian hierarchical model to assess the stability of phosphorylated proteins under short-time cold ischemia. This study provides inference on the stability of these phosphorylated proteins, which is valuable when using these proteins as biomarkers for a disease. in the second project, I perform a comparative study of different confounding-adjusted to estimate the treatment effect when the outcome variable is ordinal using observational data. The adjusted U-statistics method is compared with other methods such as ordinal logistic regression, propensity score based stratification and …

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Transient Absorption Studies Of Cdse Nanocluster Passivated With Phenyldithiocarbamate Ligands., Yizhou Xie Aug 2017

Transient Absorption Studies Of Cdse Nanocluster Passivated With Phenyldithiocarbamate Ligands., Yizhou Xie

Electronic Theses and Dissertations

Semiconductor nanocluster (SCNC) research is a rapidly growing field driven by the promising fact that properties of such materials can be tailored by modifying their size, shape, and structure. Combination of nanocluster and organic ligands provides even wider possibilities of design and development of effective and task-specific nanostructures. Understanding of and, eventually, control of energetics, interfacial interaction, and photoinduced processes in such highly heterogeneous structures is critical to invention of novel materials including those in photovoltaic devices. In the newly established Ultrafast Laser Facility (ULF), transient absorption pump-probe spectroscopy (TAPPS) has been employed to investigate the electron transfer (ET) and …

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A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro Aug 2017

A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro

Electronic Theses and Dissertations

As stigmatized persons, registered sex offenders betoken instability in communities. Depressed home sale values are associated with the presence of registered sex offenders even though the public is largely unaware of the presence of registered sex offenders. Using a spatial multilevel approach, the current study examines the role registered sex offenders influence sale values of homes sold in 2015 for three U.S. counties (rural, suburban, and urban) located in Illinois and Kentucky within the social disorganization framework. Homebuyers were surveyed to examine whether awareness of local registered sex offenders and the homebuyer’s community type operate as moderators between home selling …

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Fabrication And Functionalization Of Carbon Nanocages For Use In Cfx Batteries., Nathan Smith Aug 2017

Fabrication And Functionalization Of Carbon Nanocages For Use In Cfx Batteries., Nathan Smith

Electronic Theses and Dissertations

A relatively inexpensive method for obtaining high quality lithium-CFx batteries is reported. Nickel acetate and citric acid are used to synthesize a precursor which is then annealed and subsequently etched to fabricate highly uniform 3 nm radius pristine CNCs. These CNCs are then functionalized with fluorine using an RF plasma system. The resulting fluorinated CNCs are then combined with a carbon binder and pressed onto a stainless steel mesh to form a CFx cathode. This cathode is then tested in a coin cell primary battery with a lithium anode. Results indicate that a specific capacity of 660 mAh/g …

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Novel Half-Metallic And Spin-Gapless Heusler Compounds, Yunlong Jin Aug 2017

Novel Half-Metallic And Spin-Gapless Heusler Compounds, Yunlong Jin

Department of Physics and Astronomy: Dissertations, Theses, and Student Research

This thesis is devoted to experimental studies of Heusler compounds CoFeCrAl, CoFeCrX (X = Si, Ge) and Mn2PtSn. These Heusler alloys present an interesting class of ferromagnetic materials for spintronic applications since they are predicted to be spin gapless semiconductors and have half-metallic properties with 100 % spin polarization at the Fermi level. In this thesis, the structural, magnetic, spin-polarization and electron- transport properties of the fabricated alloys were studied. CoFeCrAl thin films deposited on MgO exhibit nearly perfect epitaxy and a high degree of L21 Heusler order. All considered types of chemical disorder destroy the spin-gapless …

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