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Articles 1081 - 1110 of 1378
Full-Text Articles in Computer Engineering
Resilient Control In The Presence Of Man-In-The-Middle Attacks, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli
Resilient Control In The Presence Of Man-In-The-Middle Attacks, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli
Faculty Work Comprehensive List
Cyber-physical systems, which are ubiquitous in modern critical infrastructure, oftentimes rely on sending actuation commands and sensor measurements over a network, subjecting this information to potential man-in-the-middle attacks. These attacks can take the form of denial of service attacks or integrity attacks. Previous approaches at ensuring the resiliency of the overall control system against these types of attacks have leveraged functional redundancy in the system, including resilient estimation and reconfigurable control. However, these approaches are only able to ensure resiliency up to a particular subset of the actuator commands and sensor measurements being compromised. In contrast, we introduce a resiliency …
Quantum Clustering Drives Innovations: A Bibliometric And Patentometric Analysis, Shradha Deshmukh, Preeti Mulay
Quantum Clustering Drives Innovations: A Bibliometric And Patentometric Analysis, Shradha Deshmukh, Preeti Mulay
Library Philosophy and Practice (e-journal)
The paper presents a bibliometric analysis from 2014 to 2020 of the emerging and engaging field of quantum computing called Quantum Machine Learning (QML). The study discusses the analysis results from the comprehensive high indexed databases worldwide such as Institute of Electrical and Electronics Engineers (IEEE), Scopus, Web of Science (WOS), Google Scholar and the Association for Computing Machinery (ACM). Tools like iMapbuilder, IBM and SPSS Statistics are used to provide meaningful insights and flawless representations of the extracted data. There has been little research to provide a macroscopic overview of renowned authors, subject areas, funding agencies and patent applications …
Determination Of Hydrogel Degradation By Passive Mechanical Testing, Avery Rosh-Gorsky
Determination Of Hydrogel Degradation By Passive Mechanical Testing, Avery Rosh-Gorsky
Honors Theses
This paper details a new technique to measure the mechanical properties of ETTMP PEGDA hydrogels using Hertz Contact Theory and simultaneously analyze both the model drug release and gel erosion in situ. This method involves curing a drug loaded hydrogel in a standard cuvette and placing a glass bead and phosphate buffer solution (PBS). Over time, the cross-linked network of the hydrogel breaks down, and, as a result, the ball sinks into the hydrogel. This method provides a macroscopic and inexpensive way to continuously and passively measure properties of the hydrogel as the hydrogel degrades. By plotting both the …
Reducing Attack Vulnerabilities Through Decentralized Event-Triggered Control, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli
Reducing Attack Vulnerabilities Through Decentralized Event-Triggered Control, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli
Faculty Work Comprehensive List
Decentralized control systems are widely used in a number of situations and applications. In order for these systems to function properly and achieve their desired goals, information must be propagated between agents, which requires connecting to a network. To reduce vulnerabilities to attacks that may be carried out through the network, we design an event-triggered mechanism for network connection and communication that minimizes the amount of time agents must be connected to the network, in turn decreasing communication costs. This mechanism is a function of only local information and ensures stability for the overall system in attack-free scenarios. Our approach …
Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta
Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta
Electrical and Computer Engineering Faculty Publications
Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.
On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge
On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge
Articles
We consider the consequence of breaking with a fundamental result in complex analysisby lettingi2=±1wherei=√−1is the basic unit of all imaginary numbers. An analysis of theMandelbrot set for this case shows that a demarcation between a Fractal and a Euclidean object ispossible based oni2=−1andi2= +1, respectively. Further, we consider the transient behaviourassociated with the two cases to produce a range of non-standard sets in which a Fractal geometricstructure is transformed into a Euclidean object. In the case of the Mandelbrot set, the Euclideanobject is a square whose properties are investigate. Coupled with the associated Julia sets and othercomplex plane mappings, this …
การพยากรณ์ปริมาณและความเข้มข้นสารฟลอกคูแลต์ในกระบวนการพักใสสำหรับอุตสาหกรรมการผลิตน้ำตาลจากอ้อย, สิงหดิศร์ จันทรักษ์
การพยากรณ์ปริมาณและความเข้มข้นสารฟลอกคูแลต์ในกระบวนการพักใสสำหรับอุตสาหกรรมการผลิตน้ำตาลจากอ้อย, สิงหดิศร์ จันทรักษ์
Chulalongkorn University Theses and Dissertations (Chula ETD)
กระบวนการพักใสเป็นกระบวนการที่สำคัญในกระบวนการผลิตน้ำตาล ซึ่งกระบวนการมีการทำงานเพื่อแยกระหว่างตะกอนกับน้ำอ้อยออกจากกันโดยใช้สารฟลอกคูแลนต์ โดยในการใส่ปริมาณและความเข้มข้นสารฟลอกคูแลนต์ลงไปในน้ำอ้อยทำให้ส่งผลกระทบโดยตรงต่อความเร็วการตกตะกอนและค่าความขุ่นของน้ำอ้อย วิทยานิพนธ์เล่มนี้เสนอวิธีการพยากรณ์ปริมาณและความเข้มข้นสารฟลอกคูแลต์ในกระบวนการพักใสสำหรับอุตสาหกรรมการผลิตน้ำตาลจากอ้อย โดยใช้โครงข่ายประสาทเทียมแบบวนซ้ำชนิดพิเศษ Long Short-Term Memory โดยข้อมูลที่นำมาใช้เป็นข้อมูลขาเข้าสำหรับการสร้างโมเดลได้แก่ ปริมาณอ้อยสด, ปริมาณอ้อยเผา, ความขุ่นของน้ำอ้อย และปริมาณน้ำฝน และข้อมูลขาออกได้แก่ ปริมาณและความเข้มข้นของสารฟลอกคูแลนต์ ทั้งนี้ข้อมูลที่ได้นำมาจากโรงงานผลิตน้ำตาลแห่งหนึ่งในประเทศไทย ผลการทดลองแสดงให้เห็นถึงประสิทธิภาพของโมเดลที่ได้นำเสนอ LSTM โดยการเปรียบเทียบกับโมเดลอื่นๆ ได้แก่ Autoregressive Integrated Moving Average (ARIMA), Recurrent Neural Network (RNN) และ Gated Recurrent Unit (GRU) โดยใช้ตัวแปร RMSE และ MAPE เป็นตัววัดประสิทธิภาพของโมเดล พบว่าโมเดลที่นำเสนอมีประสิทธิภาพที่สุดในการพยากรณ์ปริมาณและความเข้มข้นของสารฟลอกคูแลนต์
การจำแนกปัญหาของเทคโนโลยีฐานข้อมูลในชุมชนถามตอบออนไลน์, ณัฐนัย สุวรรณชูชิต
การจำแนกปัญหาของเทคโนโลยีฐานข้อมูลในชุมชนถามตอบออนไลน์, ณัฐนัย สุวรรณชูชิต
Chulalongkorn University Theses and Dissertations (Chula ETD)
วิทยานิพนธ์นี้นำเสนอแนวทางการสร้างเครื่องมือการทำงานอัตโนมัติเพื่อจำแนกคำถามบนเว็บไซต์สแต็กโอเวอร์โฟลว์ โดยเฉพาะที่เกี่ยวกับชนิดของผลิตภัณฑ์ฐานข้อมูล ซึ่งถือเป็นข้อมูลที่มีค่าสำหรับเจ้าของผลิตภัณฑ์ฐานข้อมูลในการนำไปปรับปรุงผลิตภัณฑ์ หมวดหมู่ของคำถามกำหนดไว้เป็นสองระดับได้แก่ ระดับปัญหา และ ปัญหาย่อย โดยที่ระดับปัญหาประกอบด้วย การพัฒนา การติดตั้ง และ การปรับปรุงประสิทธิภาพ ในขณะที่ ปัญหาย่อย ประกอบด้วย การออกแบบ ข้อจำกัด และการอภิปรายปัญหา ด้วยการรวมทั้งสองระดับเข้าด้วยกัน คำถามจะถูกจำแนกออกเป็นเก้าหมวดของปัญหา-ปัญหาย่อย การประมวลผลภาษาธรรมชาติและการจำแนกข้อความถูกนำมาใช้ โดยใช้อัลกอริทึมการเรียนรู้ของเครื่องที่หลากหลาย โมเดลการจำแนกประเภทที่มีประสิทธิภาพดีที่สุดจะถูกนำมาใช้ในเว็บแอปพลิเคชัน เพื่อจำแนกแต่ละคำถามโดยใช้แท็กปัญหา-ปัญหาย่อย นอกจากนี้คำถามที่ถูกจำแนกออกตามหมวดแล้ว สามารถนำมาวิเคราะห์เพิ่มเติมโดยใช้อัลกอริทึมการสร้างแบบจำลองหัวข้อ เพื่อให้ทราบว่าคำถามในแต่ละหมวดนั้นกล่าวถึงหัวข้อใดบ้าง ซึ่งจะเป็นข้อมูลเพิ่มเติมให้กับเจ้าของผลิตภัณฑ์ฐานข้อมูลในการทำความเข้าใจถึงปัญหาของผลิตภัณฑ์เพื่อจะได้ทำการปรับปรุงต่อไป
Topological Biclustering Artmap, Raghu Yelugam
Topological Biclustering Artmap, Raghu Yelugam
Masters Theses
”Detection of gene mutations is central for assessing genetic factors affecting disease predisposition, genetic causes of a particular disease, and gene-targeted treatment. DNA microarray methods are widely used to detect mutations by contrasting the expression levels of thousands of genes together under varying experimental conditions. The experimental conditions could be diseased cell states compared with the normal cell states. Biclustering, a robust exploratory data analysis tool, can be applied to microarray data to detect subsets of genes that co-express highly only for a subset of experimental conditions. Such detection is crucial for gaining insights into gene regulatory networks, differential gene …
Visualization For Solving Non-Image Problems And Saliency Mapping, Divya Chandrika Kalla
Visualization For Solving Non-Image Problems And Saliency Mapping, Divya Chandrika Kalla
All Master's Theses
High-dimensional data play an important role in knowledge discovery and data science. Integration of visualization, visual analytics, machine learning (ML), and data mining (DM) are the key aspects of data science research for high-dimensional data. This thesis is to explore the efficiency of a new algorithm to convert non-images data into raster images by visualizing data using heatmap in the collocated paired coordinates (CPC). These images are called the CPC-R images and the algorithm that produces them is called the CPC-R algorithm. Powerful deep learning methods open an opportunity to solve non-image ML/DM problems by transforming non-image ML problems into …
Event-Driven Servers Using Asynchronous, Non-Blocking Network I/O: Performance Evaluation Of Kqueue And Epoll, Lorcan Leonard
Event-Driven Servers Using Asynchronous, Non-Blocking Network I/O: Performance Evaluation Of Kqueue And Epoll, Lorcan Leonard
Dissertations
This research project evaluates the performance of kqueue and epoll in the context of event-driven servers. The evaluation is done through benchmarking and tracing which are used to measure throughput and execution time respectively. The experiment is repeated for both a virtualised and native server environment. The results from the experiment are statistically analysed and compared. These results show significant differences between kqueue and epoll, and a profound impact of virtualisation as a variable.
A Comparison Of Instructional Efficiency Models In Third Level Education, Murali Rajendran
A Comparison Of Instructional Efficiency Models In Third Level Education, Murali Rajendran
Dissertations
This study investigates the validity and sensitivity of a novel model of instructional efficiency: the parabolic model. The novel model is compared against state-of-the-art models present in instructional design today; Likelihood model, Deviational model and Multidimensional model. This models is based on the assumption that optimal mental workload and high performance leads to high efficiency, while other models assume that low mental workload and high performance leads to high efficiency. The investigation makes use of two instructional design conditions: a direct instructions approach to learning and its extension with a collaborative activity. A control group received the former instructional design …
Dachash: A Dynamic, Cache-Aware And Concurrent Hash Table On Gpus, Hao Zhou
Dachash: A Dynamic, Cache-Aware And Concurrent Hash Table On Gpus, Hao Zhou
Electronic Theses and Dissertations
GPU acceleration of hash tables in high-volume transaction applications such as computational geometry and bio-informatics are emerging. Recently, several hash table designs have been proposed on GPUs, but our analysis shows that they still do not adequately factor in several important aspects of a GPU’s execution environment, leaving large room forfurther optimization.
Deep Learning Approach On Symptom Questionnaire And Abdominal Radiography For Diagnosis Of Dyssynergic Defecation, Sornsiri Poovongsaroj
Deep Learning Approach On Symptom Questionnaire And Abdominal Radiography For Diagnosis Of Dyssynergic Defecation, Sornsiri Poovongsaroj
Chulalongkorn University Theses and Dissertations (Chula ETD)
Dyssynergic defecation is one of the most common causes of chronic constipation. It is a behavioral problem in which the pelvic floor muscles are unable to coordinate with the surrounding muscles and nerves to evacuate stool. Patients are required to undergo specialized tests only available at tertiary healthcare centers for diagnosis. The aim of this thesis is to develop deep learning-based models to prescreen potential patients from primary and secondary healthcare centers for further diagnostic tests by using easily obtainable data such as symptom questionnaire and abdominal radiography. First, we developed a model which uses symptom questionnaire as an input …
Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang
Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang
Theses and Dissertations--Electrical and Computer Engineering
Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental …
Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave
Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave
Browse all Theses and Dissertations
Today there is a large market for Unmanned Aerial Systems. Although most current systems are remotely piloted by operators on the ground, increasingly, many of these systems will use some sort of automatic flight controller to help mitigate new challenges, due to their deployment at growing scale. These challenges include, but are not limited to, shortage of FAA-certified UAS pilots, transmission bandwidth and delay constraints and cyber security threats associated with wireless networking, profitability of operations constrained by energy capacity and efficiency and air dynamics planning, and etc. In order to address these rising challenges, this thesis is a part …
Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon
Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon
Browse all Theses and Dissertations
Human errors in healthcare can be fatal. Proper physical assessment of patients to avoid such errors is of paramount importance. Incorrect or insufficient assessment of the patient can cause treatment delays that may lead to negative outcomes. In this dissertation we introduce innovative technology to assist surgeons in patient assessment as well as during the training of nurses in order to enhance learning. Technological advancements have made it possible to visualize overlays of computer-generated 3D models on real-world surfaces. This technology is called augmented reality. Using Steady State Topography (SST) brain imaging to examine the brain activity of people who …
Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti
Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti
Browse all Theses and Dissertations
Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …
Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty
Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty
VMASC Publications
In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans …
Modeling The Effects Of Religious Belief And Affiliation On Prosociality, Luke Galen, Ross Gore, F. Leron Shults
Modeling The Effects Of Religious Belief And Affiliation On Prosociality, Luke Galen, Ross Gore, F. Leron Shults
VMASC Publications
To what extent do supernatural beliefs, group affiliation, and social interaction produce values and behaviors that benefit others, i.e., prosociality? Addressing this question involves multiple variables interacting within complex social networks that shape and constrain the beliefs and behaviors of individuals. We examine the relationships among some of these factors utilizing data from the World Values Survey to inform the construction of an Agent-Based Model. The latter was able to identify the conditions under which - and the mechanisms by which - the prosociality of simulated agents was increased or decreased within an "artificial society" designed to reflect real world …
Vind: A Blockchain-Enabled Supply Chain Provenance Framework For Energy Delivery Systems, Eranga Bandara, Sachin Shetty, Deepak Tosh, Xueping Liang
Vind: A Blockchain-Enabled Supply Chain Provenance Framework For Energy Delivery Systems, Eranga Bandara, Sachin Shetty, Deepak Tosh, Xueping Liang
VMASC Publications
Enterprise-level energy delivery systems (EDSs) depend on different software or hardware vendors to achieve operational efficiency. Critical components of these systems are typically manufactured and integrated by overseas suppliers, which expands the attack surface to adversaries with additional opportunities to infiltrate into EDSs. Due to this reason, the risk management of the EDS supply chain is crucial to ensure that we are knowledgeable about the vulnerabilities in software and hardware components that comprise any critical part, quantifiable risk metrics to assess the severity and exploitability of the attack, and provide remediation solutions that can influence a prioritized mitigation plan. There …
Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz
Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz
VMASC Publications
Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing …
Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano
Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano
VMASC Publications
The defense shipbuilding and repair industry is a labor-intensive sector that can be characterized by low-product volumes and high investments in which a large number of shared resources, technology, suppliers, and processes asynchronously converge into large construction projects. It is mainly organized by the execution of a complex combination of sequential and overlapping stages. While entities engaged in this large-scale endeavor are often knowledgeable about their first-tier suppliers, they usually do not have insight into the lower tiers suppliers. A sizable part of any supply chain disruption is attributable to instabilities in sub-tier suppliers. This research note conceptually delineates a …
Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha
Save-T: Safety Analysis Visualization And Evaluation Tool, Yuan Zhu, Sami Demiroluk, Kaan Ozbay, Kun Xie, Hong Yang, Di Sha
Civil & Environmental Engineering Faculty Publications
Traffic crashes are one of the biggest issues which constitute a threat to lives of the motorists and disrupt operations of the transportation system. To reduce the number of crashes and alleviate their impacts, it is necessary to scrutinize the factors contributing to the risk of traffic crashes. Lately, visual analytics tools become very popular for data exploration and obtaining insights from the data. In this paper, a new web-based data visualization tool called Safety Analysis Visualization and Evaluation Tool (SAVE-T) was introduced. This tool enables users to interactively create queries and visually explore the results. By utilizing an online …
Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua
Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua
Computational Modeling & Simulation Engineering Faculty Publications
Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …
Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha
Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha
Computational Modeling & Simulation Engineering Faculty Publications
Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …
Leveraging Chemical And Computational Biology To Probe The Cellulose Synthase Complex, B. Kirtley Amos
Leveraging Chemical And Computational Biology To Probe The Cellulose Synthase Complex, B. Kirtley Amos
Theses and Dissertations--Plant and Soil Sciences
Cellular expansion in plants is a complex process driven by the constraint of internal cellular turgor pressure by an expansible cell wall. The main structural element of the cell wall is cellulose. Cellulose is vital to plant fitness and the protein complex that creates it is an excellent target for small molecule inhibition to create herbicides. In the following thesis many small molecules (SMs) from a diverse library were screened in search of new cellulose biosynthesis inhibitors (CBI). Loss of cellular expansion was the primary phenotype used to search for putative CBIs. As such, this was approached in a forward …
Covid-19 And Biocybersecurity's Increasing Role On Defending Forward, Xavier Palmer, Lucas N. Potter, Saltuk Karahan
Covid-19 And Biocybersecurity's Increasing Role On Defending Forward, Xavier Palmer, Lucas N. Potter, Saltuk Karahan
Electrical & Computer Engineering Faculty Publications
The evolving nature of warfare has been changing with cybersecurity and the use of advanced biotechnology in each aspect of the society is expanding and overlapping with the cyberworld. This intersection, which has been described as “biocybersecurity” (BCS), can become a major front of the 21st-century conflicts. There are three lines of BCS which make it a critical component of overall cybersecurity: (1) cyber operations within the area of BCS have life threatening consequences to a greater extent than other cyber operations, (2) the breach in health-related personal data is a significant tool for fatal attacks, and (3) health-related misinformation …
Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li
Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li
Engineering Management & Systems Engineering Faculty Publications
Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, image super-resolution etc. In this paper, we have used GAN models for ship deck segmentation. We have used 2D scanned raster images of ship decks provided by US Navy Military Sealift Command (MSC) to extract necessary information including ship walls, objects etc. Our segmentation results will be helpful to get vector and 3D image of a ship that can be later used for maintenance of the ship. We applied the trained models to engineering documents provided …
Schizophrenia Classification Using Resting State Eeg Functional Connectivity: Source Level Outperforms Sensor Level, Sima Azizi, Daniel B. Hier, Donald C. Wunsch
Schizophrenia Classification Using Resting State Eeg Functional Connectivity: Source Level Outperforms Sensor Level, Sima Azizi, Daniel B. Hier, Donald C. Wunsch
Chemistry Faculty Research & Creative Works
Disrupted Functional and Structural Connectivity Measures Have Been Used to Distinguish Schizophrenia Patients from Healthy Controls. Classification Methods based on Functional Connectivity Derived from EEG Signals Are Limited by the Volume Conduction Problem. Recorded Time Series at Scalp Electrodes Capture a Mixture of Common Sources Signals, Resulting in Spurious Connections. We Have Transformed Sensor Level Resting State EEG Times Series to Source Level EEG Signals Utilizing a Source Reconstruction Method. Functional Connectivity Networks Were Calculated by Computing Phase Lag Values between Brain Regions at Both the Sensor and Source Level. Brain Complex Network Analysis Was Used to Extract Features and …