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Full-Text Articles in Other Computer Engineering

Blockchain Design For A Secure Pharmaceutical Supply Chain, Zhe Xu Mar 2024

Blockchain Design For A Secure Pharmaceutical Supply Chain, Zhe Xu

Masters Theses

In the realm of pharmaceuticals, particularly during the challenging times of the COVID-19 pandemic, the supply chain for drugs has faced significant strains. The increased demand for vaccines and therapeutics has revealed critical weaknesses in the current drug supply chain management systems. If not addressed, these challenges could lead to severe societal impacts, including the rise of counterfeit medications and diminishing trust in government authorities.

The study identified that more than the current strategies, such as the Drug Supply Chain Security Act (DSCSA) in the U.S., which focuses on unique authentication and traceability codes for prescription drugs, is needed to …


Design And Fabrication Of A Trapped Ion Quantum Computing Testbed, Christopher A. Caron Aug 2023

Design And Fabrication Of A Trapped Ion Quantum Computing Testbed, Christopher A. Caron

Masters Theses

Here we present the design, assembly and successful ion trapping of a room-temperature ion trap system with a custom designed and fabricated surface electrode ion trap, which allows for rapid prototyping of novel trap designs such that new chips can be installed and reach UHV in under 2 days. The system has demonstrated success at trapping and maintaining both single ions and cold crystals of ions. We achieve this by fabricating our own custom surface Paul traps in the UMass Amherst cleanroom facilities, which are then argon ion milled, diced, mounted and wire bonded to an interposer which is placed …


Learning To Rig Characters, Zhan Xu Aug 2023

Learning To Rig Characters, Zhan Xu

Doctoral Dissertations

With the emergence of 3D virtual worlds, 3D social media, and massive online games, the need for diverse, high-quality, animation-ready characters and avatars is greater than ever. To animate characters, artists hand-craft articulation structures, such as animation skeletons and part deformers, which require significant amount of manual and laborious interaction with 2D/3D modeling interfaces. This thesis presents deep learning methods that are able to significantly automate the process of character rigging. First, the thesis introduces RigNet, a method capable of predicting an animation skeleton for an input static 3D shape in the form of a polygon mesh. The predicted skeletons …


Improving The Programmability Of Networked Energy Systems, Noman Bashir Jun 2022

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …


Ticknet: A Lightweight Deep Classifier For Tick Recognition, Li Wang Feb 2021

Ticknet: A Lightweight Deep Classifier For Tick Recognition, Li Wang

Masters Theses

The world is increasingly controlled by machine learning and deep learning. Deep neural networks are becoming powerful, encroaching on many tasks in computer vision system areas previously seen as the unique domain of humans, such as image classification, object detection, semantic segmentation, and instance segmentation. The success of a deep learning model at a specific application is determined by a sequence of choices, like what kind of deep neural network will be used, what data to be fed into the deep model, and what manners will be adopted to train a deep model.

The goal of this work is to …


Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan Mar 2020

Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan

Doctoral Dissertations

Content delivery networks (CDNs) deploy hundreds of thousands of servers around the world to cache and serve trillions of user requests every day for a diverse set of content such as web pages, videos, software downloads and images. In this dissertation, we propose algorithms to provision traffic across cache servers and manage the content they host to achieve performance objectives such as maximizing the cache hit rate, minimizing the bandwidth cost of the network and minimizing the energy consumption of the servers. Traffic provisioning is the process of determining the set of content domains hosted on the servers. We propose …


Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh Oct 2019

Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh

Doctoral Dissertations

Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …


Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng Jul 2019

Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng

Doctoral Dissertations

Today we are living in a world awash with data. Large volumes of data are acquired, analyzed and applied to tasks through machine learning algorithms in nearly every area of science, business, and industry. For example, medical scientists analyze the gene expression data from a single specimen to learn the underlying causes of disease (e.g. cancer) and choose the best treatment; retailers can know more about customers' shopping habits from retail data to adjust their business strategies to better appeal to customers; suppliers can enhance supply chain success through supply chain systems built on knowledge sharing. However, it is also …


Modeling Temporal Structures In Time-Varying Networks, Kun Tu Mar 2019

Modeling Temporal Structures In Time-Varying Networks, Kun Tu

Doctoral Dissertations

A dynamic network is a network whose structure changes because of the emergence and disappearance of node or edges. It can be used to study complex systems where individuals in a system are represented as nodes and their relations/interactions are represented as edges. Studying dynamic network structures helps to better understand changes in relationships. Considerable work has been conducted on learning network structure. However, due to the complexity of dynamic networks, there is considerable room for improvement to obtain better analysis results. This thesis studies different aspects of characteristic and dynamics of a network, focusing on their application in link …


Multi-Sensor Localization And Tracking In Disaster Management And Indoor Wayfinding For Visually Impaired Users, Zhuorui Yang Oct 2018

Multi-Sensor Localization And Tracking In Disaster Management And Indoor Wayfinding For Visually Impaired Users, Zhuorui Yang

Doctoral Dissertations

This dissertation proposes a series of multi-sensor localization and tracking algorithms particularly developed for two important application domains, which are disaster management and indoor wayfinding for blind and visually impaired (BVI) users. For disaster management, we developed two different localization algorithms, one each for Radio Frequency Identification (RFID) and Bluetooth Low Energy (BLE) technology, which enable the disaster management system to track patients in real-time. Both algorithms work in the absence of any pre-deployed infrastructure along with smartphones and wearable devices. Regarding indoor wayfinding for BVI users, we have explored several types of indoor positioning techniques including BLE-based, inertial, visual …


Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma Oct 2018

Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma

Doctoral Dissertations

Modern distributed server applications are hosted on enterprise or cloud data centers that provide computing, storage, and networking capabilities to these applications. These applications are built using the implicit assumption that the underlying servers will be stable and normally available, barring for occasional faults. In many emerging scenarios, however, data centers and clouds only provide transient, rather than continuous, availability of their servers. Transiency in modern distributed systems arises in many contexts, such as green data centers powered using renewable intermittent sources, and cloud platforms that provide lower-cost transient servers which can be unilaterally revoked by the cloud operator. Transient …


Power Laws In Complex Graphs: Parsimonious Generative Models, Similarity Testing Algorithms, And The Origins, Shan Lu Jul 2018

Power Laws In Complex Graphs: Parsimonious Generative Models, Similarity Testing Algorithms, And The Origins, Shan Lu

Doctoral Dissertations

This dissertation mainly discussed topics related to power law graphs, including graph similarity testing algorithms and power law generative models. For graph similarity testing, we proposed a method based on the mathematical theory of diffusion over manifolds using random walks over graphs. We show that our method not only distinguishes between graphs with different degree distributions, but also graphs with the same degree distributions. We compare the undirected power law graphs generated by Barabasi-Albert model and directed power law graphs generated by Krapivsky's model to the random graphs generated by Erdos-Renyi model. We also compare power law graphs generated by …


Navigation Instruction Validation Tool And Indoor Wayfinding Training System For People With Disabilities, Linlin Ding Oct 2017

Navigation Instruction Validation Tool And Indoor Wayfinding Training System For People With Disabilities, Linlin Ding

Masters Theses

According to World Health Survey, there are 785 million (15.6%) people in the world that live with a disability. It is a well-known fact that lack of access to public transportation is a barrier for people with disabilities in seeking work or accessing health care. In this research, we seek to increase access to public transportation by introducing a virtual pre-travel training system that enables people with disabilities to get familiar with a public transportation venue prior to arriving at the venue. Using this system, users establish a mental map of the target environment prior to their arrival to the …


Efficient Scaling Of A Web Proxy Cluster, Hao Zhang Oct 2017

Efficient Scaling Of A Web Proxy Cluster, Hao Zhang

Masters Theses

With the continuing growth in network traffic and increasing diversity in web content, web caching, together with various network functions (NFs), has been introduced to enhance security, optimize network performance, and save expenses. In a large enterprise network with more than tens of thousands of users, a single proxy server is not enough to handle a large number of requests and turns to group processing. When multiple web cache proxies are working as a cluster, they talk with each other and share cached objects by using internet cache protocol (ICP). This leads to poor scalability.

This thesis describes the development …


Query On Knowledge Graphs With Hierarchical Relationships, Kaihua Liu Oct 2017

Query On Knowledge Graphs With Hierarchical Relationships, Kaihua Liu

Masters Theses

The dramatic popularity of graph database has resulted in a growing interest in graph queries. Two major topics are included in graph queries. One is based on structural relationship to find meaningful results, such as subgraph pattern match and shortest-path query. The other one focuses on semantic-based query to find question answering from knowledge bases. However, most of these queries take knowledge graphs as flat forms and use only normal relationship to mine these graphs, which may lead to mistakes in the query results. In this thesis, we find hierarchical relationship in the knowledge on their semantic relations and make …


Virtualization Of Closed-Loop Sensor Networks, Priyanka Dattatri Kedalagudde Jul 2017

Virtualization Of Closed-Loop Sensor Networks, Priyanka Dattatri Kedalagudde

Masters Theses

The existing closed-loop sensor networks are based on architectures that are designed and implemented for one specific application and require dedicated sensing and computational resources. This prevents the sharing of these networks. In this work, we propose an architecture of virtualization to allow sharing of closed-loop sensor networks. We also propose a scheduling approach that will manage requests from competing applications and evaluate their impact on system utilization against utilization achieved by more traditional, dedicated sensor networks. These algorithms are evaluated through trace-driven simulations, where the trace data is taken from CASA’s closed-loop weather radar sensor network. Results from this …


Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan Mar 2017

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …


Image Processing And Understanding Based On Graph Similarity Testing: Algorithm Design And Software Development, Jieqi Kang Mar 2017

Image Processing And Understanding Based On Graph Similarity Testing: Algorithm Design And Software Development, Jieqi Kang

Doctoral Dissertations

Image processing and understanding is a key task in the human visual system. Among all related topics, content based image retrieval and classification is the most typical and important problem. Successful image retrieval/classification models require an effective fundamental step of image representation and feature extraction. While traditional methods are not capable of capturing all structural information on the image, using graph to represent the image is not only biologically plausible but also has certain advantages. Graphs have been widely used in image related applications. Traditional graph-based image analysis models include pixel-based graph-cut techniques for image segmentation, low-level and high-level image …


Spotlight: An Information Service For The Cloud, Xue Ouyang Jul 2016

Spotlight: An Information Service For The Cloud, Xue Ouyang

Masters Theses

Infrastructure-as-a-Service cloud platforms are incredibly complex: they rent hundreds of different types of servers across multiple geographical regions under a wide range of contract types that offer varying tradeoffs between risk and cost. Unfortunately, the internal dynamics of cloud platforms are opaque in several dimensions. For example, while the risk of servers not being available when requested is critical in optimizing these risk-cost tradeoffs, it is not typically made visible to users. Thus, inspired by prior work on Internet bandwidth probing, we propose actively probing cloud platforms to explicitly learn such information, where each "probe'' is a request for a …


Indoor And Outdoor Real Time Information Collection In Disaster Scenario, Dongyi Yang Nov 2015

Indoor And Outdoor Real Time Information Collection In Disaster Scenario, Dongyi Yang

Masters Theses

A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario.

The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along …


Application Of Techniques For Map Estimation To Distributed Constraint Optimization Problem, Yoonheui Kim Nov 2015

Application Of Techniques For Map Estimation To Distributed Constraint Optimization Problem, Yoonheui Kim

Doctoral Dissertations

The problem of efficiently finding near-optimal decisions in multi-agent systems has become increasingly important because of the growing number of multi-agent applications with large numbers of agents operating in real-world environments. In these systems, agents are often subject to tight resource constraints and agents have only local views. When agents have non-global constraints, each of which is independent, the problem can be formalized as a distributed constraint optimization problem (DCOP). The DCOP is closely associated with the problem of inference on graphical models. Many approaches from inference literature have been adopted to solve DCOPs. We focus on the Max-Sum algorithm …


On Applications Of Relational Data, Samamon Khemmarat Nov 2015

On Applications Of Relational Data, Samamon Khemmarat

Doctoral Dissertations

With the advances of technology and the popularity of the Internet, a large amount of data is being generated and collected. Much of these data is relational data, which describe how people and things, or entities, are related to one another. For example, data from sale transactions on e-commerce websites tell us which customers buy or view which products. Analyzing the known relationships from relational data can help us to discover knowledge that can benefit businesses, organizations, and our lives. For instance, learning the products that are commonly bought together allows businesses to recommend products to customers and increase their …


Physically Equivalent Intelligent Systems For Reasoning Under Uncertainty At Nanoscale, Santosh Khasanvis Nov 2015

Physically Equivalent Intelligent Systems For Reasoning Under Uncertainty At Nanoscale, Santosh Khasanvis

Doctoral Dissertations

Machines today lack the inherent ability to reason and make decisions, or operate in the presence of uncertainty. Machine-learning methods such as Bayesian Networks (BNs) are widely acknowledged for their ability to uncover relationships and generate causal models for complex interactions. However, their massive computational requirement, when implemented on conventional computers, hinders their usefulness in many critical problem areas e.g., genetic basis of diseases, macro finance, text classification, environment monitoring, etc. We propose a new non-von Neumann technology framework purposefully architected across all layers for solving these problems efficiently through physical equivalence, enabled by emerging nanotechnology. The architecture builds …


Function Verification Of Combinational Arithmetic Circuits, Duo Liu Jul 2015

Function Verification Of Combinational Arithmetic Circuits, Duo Liu

Masters Theses

Hardware design verification is the most challenging part in overall hardware design process. It is because design size and complexity are growing very fast while the requirement for performance is ever higher. Conventional simulation-based verification method cannot keep up with the rapid increase in the design size, since it is impossible to exhaustively test all input vectors of a complex design. An important part of hardware verification is combinational arithmetic circuit verification. It draws a lot of attention because flattening the design into bit-level, known as the bit-blasting problem, hinders the efficiency of many current formal techniques. The goal of …


Integrating Non-Topical Aspects Into Information Retrieval, Elif Aktolga Aug 2014

Integrating Non-Topical Aspects Into Information Retrieval, Elif Aktolga

Doctoral Dissertations

When users investigate a topic, they are often interested in results that are not just relevant, but also strongly opinionated or covering a range of times. To get such results, users are forced to formulate ambiguous, complex, or longer queries. Commonly this becomes a burden, since users need to issue several queries with reformulations if initial search results are not completely satisfactory. In this thesis, we focus on those two non-topical dimensions: opinionatedness and time. We develop measures for quantifying them in documents and incorporate them into search results. For improving search results with respect to non-topical dimensions, we use …


Scheduling Heuristics For Maximizing The Output Quality Of Iris Task Graphs In Multiprocessor Environment With Time And Energy Bounds, Rajeswaran Chockalingapuram Ravindran Jan 2012

Scheduling Heuristics For Maximizing The Output Quality Of Iris Task Graphs In Multiprocessor Environment With Time And Energy Bounds, Rajeswaran Chockalingapuram Ravindran

Masters Theses 1911 - February 2014

Embedded real time applications are often subject to time and energy constraints. Real time applications are usually characterized by logically separable set of tasks with precedence constraints. The computational effort behind each of the task in the system is responsible for a physical functionality of the embedded system. In this work we mainly define theoretical models for relating the quality of the physical func- tionality to the computational load of the tasks and develop optimization problems to maximize the quality of the system subject to various constraints like time and energy. Specifically, the novelties in this work are three fold. …


Leveraging Multi-Radio Communication For Mobile Wireless Sensor Networks, Jeremy J. Gummeson Jan 2011

Leveraging Multi-Radio Communication For Mobile Wireless Sensor Networks, Jeremy J. Gummeson

Masters Theses 1911 - February 2014

An important challenge in mobile sensor networks is to enable energy-efficient communication over a diversity of distances while being robust to wireless effects caused by node mobility. In this thesis, we argue that the pairing of two complementary radios with heterogeneous range characteristics enables greater range and interference diversity at lower energy cost than a single radio. We make three contributions towards the design of such multi-radio mobile sensor systems. First, we present the design of a novel reinforcement learning-based link layer algorithm that continually learns channel characteristics and dynamically decides when to switch between radios. Second, we describe a …


Evaluating A New Mac For Current And Next Generation Rfid, Serge Zhilyaev Jan 2010

Evaluating A New Mac For Current And Next Generation Rfid, Serge Zhilyaev

Masters Theses 1911 - February 2014

We evaluate SQUASH, a new MAC for RFID, in hardware and software. A smaller hardware design for SQUASH is proposed which also reduces latency. Area and latency in hardware are reduced further with a new variant we call permuted SQUASH. We explore SQUASH on embedded microprocessors and propose a method to choose the optimal partial product ordering to reduce latency.


Implementation Of Data Path Credentials For High-Performance Capabilities-Based Networks, Kamlesh T. Vasudevan Jan 2009

Implementation Of Data Path Credentials For High-Performance Capabilities-Based Networks, Kamlesh T. Vasudevan

Masters Theses 1911 - February 2014

Capabilities-based networks present a fundamental shift in the security design of network architectures. Instead of permitting the transmission of packets from any source to any destination, routers deny forwarding by default. For a successful transmission, packets need to positively identify themselves and their permissions to the router. A major challenge for a high performance implementation of such a network is an efficient design of the credentials that are carried in the packet and the verification procedure on the router. A network protocol that implements data path credentials based on Bloom filters is presented in this thesis. Our prototype implementation shows …