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Articles 62521 - 62550 of 198162

Full-Text Articles in Engineering

Risk - A Multi-Layered Approach, Peter S. Neff Jan 2020

Risk - A Multi-Layered Approach, Peter S. Neff

International Journal of Aviation, Aeronautics, and Aerospace

This article discusses the relationship between the mandates to achieve increased operational safety and the application of risk management strategies. That commercial airlines must operate at the highest level of safety is mandated by statute. FAA regulation, 14 CFR part 5, outlines the FAA response to the requirements of ICAO Annex 19, Safety Management, by establishing requirements for certificate holders to develop a Safety Management System with 4 components: (a) Safety Policy; (b) Safety Risk Management; (c) Safety Assurance; and (d) Safety Promotion. Safety is a tangible and intangible element foundational to the successful commercial airline sector. A structured multi-layered …

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A Review Of Dji’S Mavic Pro Precision Landing Accuracy, Cody Yoakum, Joseph Cerreta Jan 2020

A Review Of Dji’S Mavic Pro Precision Landing Accuracy, Cody Yoakum, Joseph Cerreta

International Journal of Aviation, Aeronautics, and Aerospace

Precision landing has the potential to increase the accuracy of autonomous landings. Unique applications require specific landing performance; for example, wireless charging loses efficiency with a misalignment of 100mm. Unfortunately, there is no publicly available information for the DJI Mavic Pro’s landing specifications. This research investigated the ability of a Mavic Pro to land at a specified point accurately. The purpose of this research is to determine if precision landings are more accurate than non-precision autonomous landings and if the Mavic Pro is capable of applications such as wireless charging when using precision landings. A total of 128 (64 precision …

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Simulation Analysis Of The Effects Of Performance-Based Navigation On Fuel And Block Time Efficiency, Shlok Misra Jan 2020

Simulation Analysis Of The Effects Of Performance-Based Navigation On Fuel And Block Time Efficiency, Shlok Misra

International Journal of Aviation, Aeronautics, and Aerospace

The commercial aviation industry has been grown steadily in the past decade in terms of the number of flights operated and passengers traveled. The Federal Aviation Administration has introduced several technologies and initiatives under the NextGen Program. Performance-Based Navigation (PBN) is one such technology that is aimed at improving the efficiency of the National Airspace System which will improve system capacity and reduce delays. The airlines operate with restrained resources and investments into reducing fuel costs and flight times will directly or indirectly impact profit margins. PBN procedures and routes can help airlines reduce block times as flights will be …

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Efficiency Analysis Of A Congested Brazilian Airport Applying Slots Optimization Control: Congonhas Airport Case, Mariana Franco B. Mendes, Rafael Roco De Araujo, Ana Paula Beck Da Silva Etges, Massoud Bazargan Jan 2020

Efficiency Analysis Of A Congested Brazilian Airport Applying Slots Optimization Control: Congonhas Airport Case, Mariana Franco B. Mendes, Rafael Roco De Araujo, Ana Paula Beck Da Silva Etges, Massoud Bazargan

International Journal of Aviation, Aeronautics, and Aerospace

The current slot allocation mechanism in Brazil, based on the International Air Transport Association (IATA) rules, and its supplementary local regulation The National Civil Aviation Agency (ANAC), displays a few issues and limitations (e.g. slot misuse, allocation inefficiencies). Such issues are particularly present in the case of busy airports that works near their maximum capacity for major parts of the day. This inefficiency problem is generated because of the complexity of slot allocation added to the limited decision support available for the Brazilian system. This study focuses on the implementation of an optimal slot model, based on IATA regulations with …

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Significance Of Incorporating Weather Technology Training For Ga Pilots To Curb Fatalities, Rajee Olaganathan Dr, Richard G. Ham Dr. Jan 2020

Significance Of Incorporating Weather Technology Training For Ga Pilots To Curb Fatalities, Rajee Olaganathan Dr, Richard G. Ham Dr.

International Journal of Aviation, Aeronautics, and Aerospace

Weather is considered to be the main threat to aviation safety from the early 1900s. Despite advanced technologies available at present, the weather still poses a risk to the ever-growing aviation industry. This research gives an overview of weather-related accidents with special reference to Part 91 operation in the United States from 1982 and 2017 based on the NTSB database. The analysis shows that 14 CFR Part 91 operations experienced more accidents than Part 121 operations, and weather was a cause or a contributing factor in 35 % of fatal general aviation accidents. The study also identified the main weather …

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Analyzing The Threats Of The Failure Of Visual Awareness During A Visual Approach For Transport Category Aircraft, Shlok Misra Jan 2020

Analyzing The Threats Of The Failure Of Visual Awareness During A Visual Approach For Transport Category Aircraft, Shlok Misra

International Journal of Aviation, Aeronautics, and Aerospace

The purpose of this study was to evaluate the risk posed by the failure of visual awareness during visual approaches for transport category aircraft. Visual awareness is critical while conducting visual approaches and it is important to study the factors that can limit the capabilities of human beings to maintain visual awareness. Visual approaches expose pilots to multiple and critical visual stimuli that require strong visual awareness for safe operations. The study conducted a detailed analysis of the Flight Safety Foundation accident database to study the reported incidents during visual approaches from 1998-2018. The effect of human factors was studied …

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Mini Unmanned Aerial Systems (Uav) - A Review Of The Parameters For Classification Of A Mini Uav., Ramesh Ps, Muruga Lal Jeyan Jan 2020

Mini Unmanned Aerial Systems (Uav) - A Review Of The Parameters For Classification Of A Mini Uav., Ramesh Ps, Muruga Lal Jeyan

International Journal of Aviation, Aeronautics, and Aerospace

In the recent years, Mini Unmanned Aerial Vehicle (UAV) has generated a lot of interest both in military and civilian applications. Contemporary innovations have seen the entry of Mini UAV into a wide range of hitherto fore unexplored domains. Advancement in computer systems, miniaturisation of electronics, artificial intelligence and composite materials is propelling the development of Mini UAV. Mini UAV is a class of UAV within the large family of unmanned systems categorised by a set of parameters. However, there are glaring inconsistencies and lack of uniformity in specifying the parameters which define a Mini UAV. The paper explores the …

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Aviation Safety Regulations Versus Cns/Atm Systems And Functionalities, Adeyinka Olumuyiwa Osunwusi Jan 2020

Aviation Safety Regulations Versus Cns/Atm Systems And Functionalities, Adeyinka Olumuyiwa Osunwusi

International Journal of Aviation, Aeronautics, and Aerospace

The safety, security, efficiency, regularity, and sustainable development of international civil aviation operations revolve around a web of well-defined legal, policy, regulatory and methodological frameworks, which prescribe, inter alia, mandatory, advisory, prescriptive or discretionary requirements in respect of interactivities within the civil aviation community. In relation to this body of legal, policy, regulatory and methodological frameworks, the Convention on International Civil Aviation (otherwise known as the Chicago Convention, 1944) clearly represents the locus classicus. The Chicago Convention, which governs the activities of Contracting States of the International Civil Aviation Organization (ICAO), incorporates 96 Articles and embodies, to date, …

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Development Of A Sensor Suite For Atmospheric Boundary Layer Measurement With A Small Multirotor Unmanned Aerial System, Kevin A. Adkins, Christopher J. Swinford, Peter D. Wambolt, Gordon Bease Jan 2020

Development Of A Sensor Suite For Atmospheric Boundary Layer Measurement With A Small Multirotor Unmanned Aerial System, Kevin A. Adkins, Christopher J. Swinford, Peter D. Wambolt, Gordon Bease

International Journal of Aviation, Aeronautics, and Aerospace

Small unmanned aerial systems (sUAS) are increasingly being used to conduct atmospheric research. Because of the dynamic nature and inhomogeneity of the atmospheric boundary layer (ABL), the ability of instrumented sUAS to make on-demand 3-dimensional high-resolution spatial measurements of atmospheric parameters makes them particularly suited to ABL investigations. Both fixed-wing and multirotor sUAS have been used for ABL investigations. Most investigations to date have included in-situ measurement of thermodynamic quantities such as temperature, pressure and humidity. When wind has been measured, a variety of strategies have been used. Two of the most popular techniques have been deducing wind from inertial …

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Factors Influencing The Emergence Of Suborbital Space Tourism, Brian T. Musselman, Steven Hampton Jan 2020

Factors Influencing The Emergence Of Suborbital Space Tourism, Brian T. Musselman, Steven Hampton

International Journal of Aviation, Aeronautics, and Aerospace

Suborbital space tourism is becoming a reality. The suborbital space industry is predicted to grow from $340 billion to $1 trillion over the next 20 years. A literature review, conducted on references from 2012 to 2019, identified five factors associated with the development and management of safe and effective suborbital space tourism. This paper summarizes the aspects of demand, ticket cost, motivation and risk, health risk, and policy, and how each influences the development and management of suborbital space toursim.

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Image Instance Segmentation: Using The Cirsy System To Identify Small Objects In Low Resolution Images, Orghomisan William Omatsone Jan 2020

Image Instance Segmentation: Using The Cirsy System To Identify Small Objects In Low Resolution Images, Orghomisan William Omatsone

Dissertations

The CIRSY system (or Chick Instance Recognition System) is am image processing system developed as part of this research to detect images of chicks in highly-populated images that uses the leading algorithm in instance segmentation tasks, called the Mask R-CNN. It extends on the Faster R-CNN framework used in object detection tasks, and this extension adds a branch to predict the mask of an object along with the bounding box prediction. Mask R-CNN has proven to be effective ininstance segmentation and object de-tection tasks after outperforming all existing models on evaluation of the Microsoft Common Objects in Context (MS COCO) …

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Machine Learning Assisted Gait Analysis For The Determination Of Handedness In Able-Bodied People, Hugh Gallagher Jan 2020

Machine Learning Assisted Gait Analysis For The Determination Of Handedness In Able-Bodied People, Hugh Gallagher

Dissertations

This study has investigated the potential application of machine learning for video analysis, with a view to creating a system which can determine a person’s hand laterality (handedness) from the way that they walk (their gait). To this end, the convolutional neural network model VGG16 underwent transfer learning in order to classify videos under two ‘activities’: “walking left-handed” and “walking right-handed”. This saw varying degrees of success across five transfer learning trained models: Everything – the entire dataset; FiftyFifty – the dataset with enough right-handed samples removed to produce a set with parity between activities; Female – only the female …

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An Examination Of The Smote And Other Smote-Based Techniques That Use Synthetic Data To Oversample The Minority Class In The Context Of Credit-Card Fraud Classification, Eduardo Parkinson De Castro Jan 2020

An Examination Of The Smote And Other Smote-Based Techniques That Use Synthetic Data To Oversample The Minority Class In The Context Of Credit-Card Fraud Classification, Eduardo Parkinson De Castro

Dissertations

This research project seeks to investigate some of the different sampling techniques that generate and use synthetic data to oversample the minority class as a means of handling the imbalanced distribution between non-fraudulent (majority class) and fraudulent (minority class) classes in a credit-card fraud dataset. The purpose of the research project is to assess the effectiveness of these techniques in the context of fraud detection which is a highly imbalanced and cost-sensitive dataset. Machine learning tasks that require learning from datasets that are highly unbalanced have difficulty learning since many of the traditional learning algorithms are not designed to cope …

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Transformer Neural Networks For Automated Story Generation, Kemal Araz Jan 2020

Transformer Neural Networks For Automated Story Generation, Kemal Araz

Dissertations

Towards the last two-decade Artificial Intelligence (AI) proved its use on tasks such as image recognition, natural language processing, automated driving. As discussed in the Moore’s law the computational power increased rapidly over the few decades (Moore, 1965) and made it possible to use the techniques which were computationally expensive. These techniques include Deep Learning (DL) changed the field of AI and outperformed other models in a lot of fields some of which mentioned above. However, in natural language generation especially for creative tasks that needs the artificial intelligent models to have not only a precise understanding of the given …

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Identifying Online Sexual Predators Using Support Vector Machine, Yifan Li Jan 2020

Identifying Online Sexual Predators Using Support Vector Machine, Yifan Li

Dissertations

A two-stage classification model is built in the research for online sexual predator identification. The first stage identifies the suspicious conversations that have predator participants. The second stage identifies the predators in suspicious conversations. Support vector machines are used with word and character n-grams, combined with behavioural features of the authors to train the final classifier. The unbalanced dataset is downsampled to test the performance of re-balancing an unbalanced dataset. An age group classification model is also constructed to test the feasibility of extracting the age profile of the authors, which can be used as features for classifier training. The …

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Detection Of Pathological Hfo Using Supervised Machine Learning And Ieeg Data, Isabel L. Sicardi Rosell Jan 2020

Detection Of Pathological Hfo Using Supervised Machine Learning And Ieeg Data, Isabel L. Sicardi Rosell

Dissertations

Epilepsy is the second most common neurological disorder and it affects approxi mately 50 million people worldwide. One of the main characteristics of this disorder is the presence of recurrent seizures which tend to be controlled through medication. Nonetheless, 20% of the patients with this disorder are resistant to drug treatment meaning that they need to go through alternative procedures.

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Classification Of Animal Sound Using Convolutional Neural Network, Neha Singh Jan 2020

Classification Of Animal Sound Using Convolutional Neural Network, Neha Singh

Dissertations

Recently, labeling of acoustic events has emerged as an active topic covering a wide range of applications. High-level semantic inference can be conducted based on main audioeffects to facilitate various content-based applications for analysis, efficient recovery and content management. This paper proposes a flexible Convolutional neural network-based framework for animal audio classification. The work takes inspiration from various deep neural network developed for multimedia classification recently. The model is driven by the ideology of identifying the animal sound in the audio file by forcing the network to pay attention to core audio effect present in the audio to generate Mel-spectrogram. …

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Confusion Modelling - An Estimation By Semantic Embeddings, Praveen Mohanprasad Jan 2020

Confusion Modelling - An Estimation By Semantic Embeddings, Praveen Mohanprasad

Dissertations

Approaching the task of coherence assessment of a conversation from its negative perspective ‘confusion’ rather than coherence itself, has been attempted by very few research works. Influencing Embeddings to learn from similarity/dissimilarity measures such as distance, cosine similarity between two utterances will equip them with the semantics to differentiate a coherent and an incoherent conversation through the detection of negative entity, ‘confusion’. This research attempts to measure coherence of conversation between a human and a conversational agent by means of such semantic embeddings trained from scratch by an architecture centralising the learning from the distance between the embeddings. State of …

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Finetuning Pre-Trained Language Models For Sentiment Classification Of Covid19 Tweets, Arjun Dussa Jan 2020

Finetuning Pre-Trained Language Models For Sentiment Classification Of Covid19 Tweets, Arjun Dussa

Dissertations

It is a common practice in today’s world for the public to use different micro-blogging and social networking platforms, predominantly Twitter, to share opinions, ideas, news, and information about many things in life. Twitter is also becoming a popular channel for information sharing during pandemic outbreaks and disaster events. The world has been suffering from economic crises ever since COVID-19 cases started to increase rapidly since January 2020. The virus has killed more than 800 thousand people ever since the discovery as per the statistics from Worldometer [1] which is the authorized tracking website. So many researchers around the globe …

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Investigating Effect Of Amount Of Augmented Data On Performance Of Convolutional Neural Network For Multiclass Image Classification, Shivam Khandelwal Jan 2020

Investigating Effect Of Amount Of Augmented Data On Performance Of Convolutional Neural Network For Multiclass Image Classification, Shivam Khandelwal

Dissertations

This research project seeks to investigate the use of Image Data augmentation that generates synthetic data by adding distortions to original images, as a means of replacement to a large amount of real data used to train the Convolutional Neural Networks. The purpose of the research project is to assess the effectiveness of augmented data over the real data by comparing the performance of the model trained with various amounts of augmented training and validation data ratio. Deep learning tasks involving convolutional neural networks have difficulty in generalizing the models effectively for computer vision tasks when the training dataset is …

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Investigating The Predictability Of A Chaotic Time-Series Data Using Reservoir Computing, Deep-Learning And Machine- Learning On The Short-, Medium- And Long-Term Pricing Of Bitcoin And Ethereum., Molly Kenny Jan 2020

Investigating The Predictability Of A Chaotic Time-Series Data Using Reservoir Computing, Deep-Learning And Machine- Learning On The Short-, Medium- And Long-Term Pricing Of Bitcoin And Ethereum., Molly Kenny

Dissertations

This study will investigate the predictability of a Chaotic time-series data using Reservoir computing (Echo State Network), Deep-Learning(LSTM) and Machine- Learning(Linear, Bayesian, ElasticNetCV , Random Forest, XGBoost Regression and a machine learning Neural Network) on the short (1-day out prediction), medium (5-day out prediction) and long-term (30-day out prediction) pricing of Bitcoin and Ethereum Using a range of machine learning tools, to perform feature selection by permutation importance to select technical indicators on the individual cryptocurrencies, to ensure the datasets are the best for predictions per cryptocurrency while reducing noise within the models. The predictability of these two chaotic time-series …

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Degradation Mechanism Due To Water Ingress Effect On The Top Contact Of Cu(In,Ga)Se2 Solar Cells, Deewakar Poudel, Shankar Karki, Benjamin Belfore, Grace Rajan, Sushma Swaraj Atluri, Sina Soltanmohammad, Angus Rockett, Sylvain Marsillac Jan 2020

Degradation Mechanism Due To Water Ingress Effect On The Top Contact Of Cu(In,Ga)Se2 Solar Cells, Deewakar Poudel, Shankar Karki, Benjamin Belfore, Grace Rajan, Sushma Swaraj Atluri, Sina Soltanmohammad, Angus Rockett, Sylvain Marsillac

Electrical & Computer Engineering Faculty Publications

The impact of moisture ingress on the surface of copper indium gallium diselenide (CIGS) solar cells was studied. While industry-scale modules are encapsulated in specialized polymers and glass, over time, the glass can break and the encapsulant can degrade. During such conditions, water can potentially degrade the interior layers and decrease performance. The first layer the water will come in contact with is the transparent conductive oxide (TCO) layer. To simulate the impact of this moisture ingress, complete devices were immersed in deionized water. To identify the potential sources of degradation, a common window layer for CIGS devices—a bilayer of …

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A Blockchain Simulator For Evaluating Consensus Algorithms In Diverse Networking Environments, Peter Foytik, Sachin Shetty, Sarada Prasad Gochhayat, Eranga Herath, Deepak Tosh, Laurent Njilla Jan 2020

A Blockchain Simulator For Evaluating Consensus Algorithms In Diverse Networking Environments, Peter Foytik, Sachin Shetty, Sarada Prasad Gochhayat, Eranga Herath, Deepak Tosh, Laurent Njilla

VMASC Publications

The massive scale, heterogeneity and distributed nature of Internet-of-Things (IoT) presents challenges in realizing a practical and effective security solution. Blockchain empowered platforms and technologies have been proposed to address aspects of this challenge. In order to realize a practical Blockchain deployment for IoT, there is a need for a testing and evaluation platform to evaluate performance and security of Blockchain applications and systems. In this paper, we present a Blockchain simulator that evaluates the consensus algorithms in a realistic and configurable network environment. Though, there are several Blockchain evaluation platforms, they are either wedded to a specific consensus protocol …

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Measuring Decentrality In Blockchain Based Systems, Sarada Prasad Gochhayat, Sachin Shetty, Ravi Mukkamala, Peter Foytik, Georges A. Kamhoua, Laurent Njilla Jan 2020

Measuring Decentrality In Blockchain Based Systems, Sarada Prasad Gochhayat, Sachin Shetty, Ravi Mukkamala, Peter Foytik, Georges A. Kamhoua, Laurent Njilla

VMASC Publications

Blockchain promises to provide a distributed and decentralized means of trust among untrusted users. However, in recent years, a shift from decentrality to centrality has been observed in the most accepted Blockchain system, i.e., Bitcoin. This shift has motivated researchers to identify the cause of decentrality, quantify decentrality and analyze the impact of decentrality. In this work, we take a holistic approach to identify and quantify decentrality in Blockchain based systems. First, we identify the emergence of centrality in three layers of Blockchain based systems, namely governance layer, network layer and storage layer. Then, we quantify decentrality in these layers …

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Development Of Integrated Water Resources Planning Model For Dublin Using Weap21, Mohammed Yassin Jan 2020

Development Of Integrated Water Resources Planning Model For Dublin Using Weap21, Mohammed Yassin

Doctoral

Population growth, urbanisation, and climate change are predicted to impose huge pressure on water resource systems of many cities around the world including Dublin. Integrated water resources management is seen as a viable approach to address these challenges. This approach examines the water resources system in a more interconnected manner, focusing on reducing water demands, reducing reliance on fresh water supplies, reducing discharges into receiving water bodies, and creating water supply assets from storm water and wastewater. The role of mathematical modelling in designing an integrated water resources management plan is paramount as it provides a tool whereby performances of …

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A Framework For Sustainable Procurement Practice In The Irish Construction Industry, Duga Jamus Ewuga Jan 2020

A Framework For Sustainable Procurement Practice In The Irish Construction Industry, Duga Jamus Ewuga

Doctoral

The Architectural, Engineering and Construction (AEC) sector has been called upon to develop innovative strategies to drive sustainability. Despite the efforts and commitments made, their performance is still observed to be low, this has been linked to the low level of understanding of practitioners. Also noted was the lack of interest by firms due to the uncertainty of the benefits of committing to long term investments. Nevertheless, academic literature and reports have stated that firms nowadays utilise their procurement mechanism to drive their sustainability practice. However, there is a gap in understanding how construction firms adopt and embed sustainability in …

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Forecasting The Short-Term Value Of Wind Power For Risk-Aware Bidding Strategies In Single-Imbalance Price Electricity Markets, Gianni Goretti Jan 2020

Forecasting The Short-Term Value Of Wind Power For Risk-Aware Bidding Strategies In Single-Imbalance Price Electricity Markets, Gianni Goretti

Doctoral

The participation of wind energy in electricity markets and strategic bidding in the day-ahead market has been investigated with growing interest in recent years. However, markets adopting a single-price imbalance settlement where participants can increase their profits if they help to put the system back into balance have received very limited attention in the academic literature. In this thesis, new probabilistic models forecasting the short-term value of wind power are developed and their use in bidding in these types of markets is investigated. The proposed strategies are designed for participants who want to bid strategically in the day-ahead market to …

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In Situ Image Processing And Data Binning Strategy For Particle Engineering Applications, Toufic El Arnaout, Patrick J. Cullen Jan 2020

In Situ Image Processing And Data Binning Strategy For Particle Engineering Applications, Toufic El Arnaout, Patrick J. Cullen

Articles

Crystallization control can be improved through real-time monitoring technologies. Here, a workflow is demonstrated on rapid batch cooling crystallization of L-glutamic acid. First, in situ images were generated using video microscopy sensors and analyzed, by employing a single, rapid macro code to extract particle data descriptors. A binning procedure (over time) was performed, where every data point represented the counts of particles within a specific size or shape range per 100 images. This binning method was found more informative in tracking of the populations compared to whole image averages or individual particle datapoints. This study provides a step-by-step guide towards …

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Inspire Newsletter Spring 2020, Missouri University Of Science And Technology. Inspire - University Transportation Center Jan 2020

Inspire Newsletter Spring 2020, Missouri University Of Science And Technology. Inspire - University Transportation Center

INSPIRE Newsletters

No abstract provided.

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The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Alvitta Ottley, Adam Kern Jan 2020

The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Alvitta Ottley, Adam Kern

All Computer Science and Engineering Research

The primary purpose of information visualization is to act as a window between a user and the data. Historically, this has been accomplished via a single-agent framework: the only decision-maker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but a necessity. Before this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This paper aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …

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