Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Wright State University

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 271 - 300 of 3445

Full-Text Articles in Engineering

Nmr Metabolomics For Optimizing Cell-Free Protein Synthesis, Angela M. Campo Jan 2021

Nmr Metabolomics For Optimizing Cell-Free Protein Synthesis, Angela M. Campo

Browse all Theses and Dissertations

Cell-Free Protein Synthesis (CFPS) has been utilized by biochemists to produce a variety of chemicals and therapeutics. While CFPS has spawned research in the biochemistry and medical communities, there are still unknown issues with interlaboratory variability with the technique. This work explored the black box nature of CFPS reactions by analyzing the CFPS reactions in situ with Nuclear Magnetic Resonance (NMR) spectroscopy. Aim 1 developed the protocol for conducting NMR experiments on E. coli cell-free reactions as well as a data analysis pipeline. This was accomplished with 1H NMR, capturing metabolite changes over time. The 1D NOESY experiment proved to …

Go to article

Phase Transformation In The Aluminum/Tungsten System, Ammar Azeez Mahdi Al Yasari Jan 2021

Phase Transformation In The Aluminum/Tungsten System, Ammar Azeez Mahdi Al Yasari

Browse all Theses and Dissertations

Formation and growth mechanisms of intermetallic compounds in the aluminum/tungsten system were studied during consolidation and subsequent heat treatment. Three different processes, spark plasma sintering (SPS), laser powder bed fusion (LPBF), and metal inert gas welding (MIG) were used, and each of these processes were followed up with heat treatment at different conditions. Al12W, Al5W and Al4W are the three intermetallics that are stable in the system in room temperature, and they were expected to form at the interface between tungsten and aluminum at different temperature ranges. Contrary to expectations, the Al5W phase was not observed during this study and …

Go to article

Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree Jan 2021

Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree

Browse all Theses and Dissertations

In almost every field, there is a need for strong interpersonal skills. This is especially true in fields such as medicine, psychology, and education. For instance, healthcare providers need to show understanding and compassion for LGBTQ+ and BIPOC (Black, Indigenous, and People of Color), or individuals with unique developmental or mental health needs. Improving interpersonal skills often requires first-person experience with expert evaluation and guidance to achieve proficiency. However, due to limited availability of assessment capabilities, professional standardized patients and instructional experts, students and professionals currently have inadequate opportunities for expert-guided training sessions. Therefore, this research aims to demonstrate leveraging …

Go to article

Performance Of A Dual Plane Airfoil Model With Varying Gap, Stagger, And Decalage Using Pressure Measurements And Particle Image Velocimetry, Salome Kenneth Nunes Jan 2021

Performance Of A Dual Plane Airfoil Model With Varying Gap, Stagger, And Decalage Using Pressure Measurements And Particle Image Velocimetry, Salome Kenneth Nunes

Browse all Theses and Dissertations

The dual-plane airfoil has been adopted in the design of aircraft wings, wind turbine blades, and propellers. The purpose of this research is to investigate the most important design parameters of a dual-plane airfoil model for the best aerodynamic performance, such as gap, stagger, and decalage. The dual-plane airfoil model was designed using the S826 profile. A mechanical mechanism with electrical actuator control is particularly designed to alter the gap and stagger smoothly, as well as the angle of attack (AOA) for each airfoil. It results in a gap range of 1.38c to 2.17c, a stagger range of -0.75c to …

Go to article

A Deep Understanding Of Structural And Functional Behavior Of Tabular And Graphical Modules In Technical Documents, Michail Alexiou Jan 2021

A Deep Understanding Of Structural And Functional Behavior Of Tabular And Graphical Modules In Technical Documents, Michail Alexiou

Browse all Theses and Dissertations

The rapid increase of published research papers in recent years has escalated the need for automated ways to process and understand them. The successful recognition of the information that is contained in technical documents, depends on the understanding of the document’s individual modalities. These modalities include tables, graphics, diagrams and etc. as defined in Bourbakis’ pioneering work. However, the depth of understanding is correlated to the efficiency of detection and recognition. In this work, a novel methodology is proposed for automatic processing of and understanding of tables and graphics images in technical document. Previous attempts on tables and graphics understanding …

Go to article

Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs Jan 2021

Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs

Browse all Theses and Dissertations

There is a continual push to make Artificial Intelligence (AI) as human-like as possible; however, this is a difficult task because of its inability to learn beyond its current comprehension. Analogical reasoning (AR) has been proposed as one method to achieve this goal. Current literature lacks a technical comparison on psychologically-inspired and natural-language-processing-produced AR algorithms with consistent metrics on multiple-choice word-based analogy problems. Assessment is based on “correctness” and “goodness” metrics. There is not a one-size-fits-all algorithm for all textual problems. As contribution in visual AR, a convolutional neural network (CNN) is integrated with the AR vector space model, Global …

Go to article

Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad Jan 2021

Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad

Browse all Theses and Dissertations

The amount of cloud cover present in the sky is a significant factor when determining the solar radiation impinging on a solar panel. The optimum tilt required to achieve maximum energy impingement on a surface is also influenced by the amount of cloud cover. This work presents a method for determining the optimum tilt angle for a fixed solar panel when a set amount of cloud cover is present in the sky. Fixed tilt angles that have the most incident solar energy over the course of a year as a function of cloud cover, latitude, and azimuthal angle orientation are …

Go to article

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti Jan 2021

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) …

Go to article

Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani Jan 2021

Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani

Browse all Theses and Dissertations

People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …

Go to article

Complex Interactions Between Multiple Goal Operations In Agent Goal Management, Sravya Kondrakunta Jan 2021

Complex Interactions Between Multiple Goal Operations In Agent Goal Management, Sravya Kondrakunta

Browse all Theses and Dissertations

A significant issue in cognitive systems research is to make an agent formulate and manage its own goals. Some cognitive scientists have implemented several goal operations to support this issue, but no one has implemented more than a couple of goal operations within a single agent. One of the reasons for this limitation is the lack of knowledge about how various goals operations interact with one another. This thesis addresses this knowledge gap by implementing multiple-goal operations, including goal formulation, goal change, goal selection, and designing an algorithm to manage any positive or negative interaction between them. These are integrated …

Go to article

A Deep Understanding Of Structural And Functional Behavior Of Tabular And Graphical Modules In Technical Documents, Michail Alexiou Jan 2021

A Deep Understanding Of Structural And Functional Behavior Of Tabular And Graphical Modules In Technical Documents, Michail Alexiou

Browse all Theses and Dissertations

The rapid increase of published research papers in recent years has escalated the need for automated ways to process and understand them. The successful recognition of the information that is contained in technical documents, depends on the understanding of the document’s individual modalities. These modalities include tables, graphics, diagrams and etc. as defined in Bourbakis’ pioneering work. However, the depth of understanding is correlated to the efficiency of detection and recognition. In this work, a novel methodology is proposed for automatic processing of and understanding of tables and graphics images in technical document. Previous attempts on tables and graphics understanding …

Go to article

Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs Jan 2021

Application Of Analogical Reasoning For Use In Visual Knowledge Extraction, Kara Lian Combs

Browse all Theses and Dissertations

There is a continual push to make Artificial Intelligence (AI) as human-like as possible; however, this is a difficult task because of its inability to learn beyond its current comprehension. Analogical reasoning (AR) has been proposed as one method to achieve this goal. Current literature lacks a technical comparison on psychologically-inspired and natural-language-processing-produced AR algorithms with consistent metrics on multiple-choice word-based analogy problems. Assessment is based on “correctness” and “goodness” metrics. There is not a one-size-fits-all algorithm for all textual problems. As contribution in visual AR, a convolutional neural network (CNN) is integrated with the AR vector space model, Global …

Go to article

Complex Interactions Between Multiple Goal Operations In Agent Goal Management, Sravya Kondrakunta Jan 2021

Complex Interactions Between Multiple Goal Operations In Agent Goal Management, Sravya Kondrakunta

Browse all Theses and Dissertations

A significant issue in cognitive systems research is to make an agent formulate and manage its own goals. Some cognitive scientists have implemented several goal operations to support this issue, but no one has implemented more than a couple of goal operations within a single agent. One of the reasons for this limitation is the lack of knowledge about how various goals operations interact with one another. This thesis addresses this knowledge gap by implementing multiple-goal operations, including goal formulation, goal change, goal selection, and designing an algorithm to manage any positive or negative interaction between them. These are integrated …

Go to article

Adaptive Two-Stage Edge-Centric Architecture For Deeply-Learned Embedded Real-Time Target Classification In Aerospace Sense-And-Avoidance Applications, Nicholas A. Speranza Jan 2021

Adaptive Two-Stage Edge-Centric Architecture For Deeply-Learned Embedded Real-Time Target Classification In Aerospace Sense-And-Avoidance Applications, Nicholas A. Speranza

Browse all Theses and Dissertations

With the growing number of Unmanned Aircraft Systems, current network-centric architectures present limitations in meeting real-time and time-critical requirements. Current methods utilizing centralized off-platform processing have inherent energy inefficiencies, scalability challenges, performance concerns, and cyber vulnerabilities. In this dissertation, an adaptive, two-stage, energy-efficient, edge-centric architecture is proposed to address these limitations. A novel, edge-centric Sense-and-Avoidance architecture framework is presented, and a corresponding prototype is developed using commercial hardware to validate the proposed architecture. Instead of a network-centric approach, processing is distributed at the logical edge of the sensors, and organized as Detection and Classification Subsystems. Classical machine vision algorithms are …

Go to article

Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan Jan 2021

Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan

Browse all Theses and Dissertations

Renewable and clean energy has been the driving force behind the booming storage industry. The need for producing energy from clean and quickly replenishable energy sources has never been as high as it is now. However, renewable energy only supplies a little over a quarter of the world’s electricity needs and much less of the world’s total energy requirements. One reason is the intermittent nature of renewable energy. Inexpensive and convenient storage technologies are required to solve this issue. It is believed that batteries offer the most viable solution to conquer the problem of renewable energy intermittency. To aid the …

Go to article

An Analysis Of C/C++ Datasets For Machine Learning-Assisted Software Vulnerability Detection, Daniel Grahn, Junjie Zhang Jan 2021

An Analysis Of C/C++ Datasets For Machine Learning-Assisted Software Vulnerability Detection, Daniel Grahn, Junjie Zhang

Computer Science and Engineering Faculty Publications

As machine learning-assisted vulnerability detection research matures, it is critical to understand the datasets being used by existing papers. In this paper, we explore 7 C/C++ datasets and evaluate their suitability for machine learning-assisted vulnerability detection. We also present a new dataset, named Wild C, containing over 10.3 million individual opensource C/C++ files – a sufficiently large sample to be reasonably considered representative of typical C/C++ code. To facilitate comparison, we tokenize all of the datasets and perform the analysis at this level. We make three primary contributions. First, while all the datasets differ from our Wild C dataset, some …

Go to article

Recommending Collaborations Using Link Prediction, Nikhil Chennupati Jan 2021

Recommending Collaborations Using Link Prediction, Nikhil Chennupati

Browse all Theses and Dissertations

Link prediction in the domain of scientific collaborative networks refers to exploring and determining whether a connection between two entities in an academic network may emerge in the future. This study aims to analyze the relevance of academic collaborations and identify the factors that drive co-author relationships in a heterogeneous bibliographic network. Using topological, semantic, and graph representation learning techniques, we measure the authors' similarities w.r.t their structural and publication data to identify the reasons that promote co-authorships. Experimental results show that the proposed approach successfully infer the co-author links by identifying authors with similar research interests. Such a system …

Go to article

Augmented Reality Headset Facilitates Exposure For Surgical Stabilization Of Rib Fractures, T. Sensing, Pratik Parikh, Claire Hardman, Thomas Wischgoll, Sadan Suneesh Menon Jan 2021

Augmented Reality Headset Facilitates Exposure For Surgical Stabilization Of Rib Fractures, T. Sensing, Pratik Parikh, Claire Hardman, Thomas Wischgoll, Sadan Suneesh Menon

Computer Science and Engineering Faculty Publications

Recent advances in augmented reality (AR) technology have made it more accessible, portable, and powerful. AR headsets differentiate themselves from virtual reality in that they allow the wearer an unobstructed view of the “real world” but with an image superimposed upon it. The technology has many potential applications in medicine, including surgical planning, simulation, and medical education. The aim of this project was to provide proof of concept that using an AR headset during surgical stabilization of rib fractures (SSRF) is feasible. We theorized that the use of AR could allow for more precise localization of fractures, allowing for smaller …

Go to article

Low Frequency Oscillations Of Hemodynamic Parameters As A Novel Diagnostic Measure For Traumatic Brain Injury, Andrea Gomez Carrillo Jan 2021

Low Frequency Oscillations Of Hemodynamic Parameters As A Novel Diagnostic Measure For Traumatic Brain Injury, Andrea Gomez Carrillo

Browse all Theses and Dissertations

There is a need to improve methods of monitoring patients with traumatic brain injury (TBI) in hospital settings. Current monitoring techniques and diagnosis methods are expensive, invasive, do not provide continuous measures, expose the patient to radiation, are ambiguous in the information they provide, and/or cannot be implemented at the bedside. These techniques measure imperative markers of brain function including intracranial pressure (ICP), cerebral blood flow (CBF), and oxygenation in the brain, among others. Hospitals not only require a practical method for real-time monitoring of patients at the bedside, but also meaningful metrics that characterize TBIs, since the variety of …

Go to article

Hardware Security And Side Channel Power Analysis For 16x16 Booth Multiplier In 65nm Cmos Technology, Kanchan Vissamsetty Jan 2021

Hardware Security And Side Channel Power Analysis For 16x16 Booth Multiplier In 65nm Cmos Technology, Kanchan Vissamsetty

Browse all Theses and Dissertations

As feature size is scaling down, dynamic power consumption reduces but static power consumption increases. Due to the increase of static power, leakage currents as a source, the information can be exploited successfully as a side-channel to recover the secrets of the cryptographic implementations. An attacker who has access to the hardware fabrication can insert a Trojan to the design to steal or alter information. In this thesis, a post-fab static voltage variation/detection technique is developed to detect the potential fabrication process Trojan insertion. The technique is, dividing the designed circuit into N equal segments, where each segment would have …

Go to article

Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura Jan 2021

Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura

Browse all Theses and Dissertations

Classification is an important branch of machine learning that impacts many areas of modern life. Many classification algorithms (classifiers for short) have been developed. They have highly different levels of sophistication and classification accuracy. Classification problems often have highly different levels of hardness and complexity. Practitioners of classification modeling need better understanding of those algorithms in order to select the optimal algorithm for given classification problems. Researchers of classification need new insight on how given classifiers are weak and how they can be improved by correcting their classification errors. This dissertation introduces new tools and concepts to analyze classifier weakness …

Go to article

Ab Initio Methylammonium Orientation And Monolayer Effects In Hybrid Perovskite Solar Cells, Jacob M. Artz Jan 2021

Ab Initio Methylammonium Orientation And Monolayer Effects In Hybrid Perovskite Solar Cells, Jacob M. Artz

Browse all Theses and Dissertations

Methylammonium lead triiodide (MAPbI3) has garnered attention due to their high solar cell efficiencies and low cost to manufacture, but commercialization is not yet possible owing to poor environmental stability. Thus, researchers seek ways which optimize the performance of the MAPbI3 solar cell by modifying the architecture and through interfacial engineering of the charge transport layers. Difficulties in understanding these devices arise from ion migration, charge separation and recombination, and metastable, thermally active precessions of the methylammonium (MA) moiety in the lead iodide framework. In this work, focus is given to the perovskite and an adsorbed monolayer, 2,3,4,5,6-pentafluorothiophenol (C6F5SH), which …

Go to article

Altered Skeletal Muscle Excitation-Contraction Coupling In The R6/2 Transgenic Mouse Model For Huntington's Disease, Daniel R. Miranda Jan 2021

Altered Skeletal Muscle Excitation-Contraction Coupling In The R6/2 Transgenic Mouse Model For Huntington's Disease, Daniel R. Miranda

Browse all Theses and Dissertations

Huntington’s disease (HD) has classically been categorized as a neurodegenerative disorder. However, the expression of the disease-causing mutated huntingtin gene in skeletal muscle may contribute to the symptoms of HD, namely those that involve involuntary muscle contraction. In the R6/2 transgenic mouse model of HD, we previously observed ion channel defects that could contribute to involuntary muscle contraction. Here, in R6/2 muscle we investigated the consequence of these ion channel defects on action potentials (APs), the first step in excitation-contraction (EC) coupling. We found that the ion channel defects were associated with depolarizing the baseline membrane potential during AP trains. …

Go to article

Pain Intensity Assessment In Sickle Cell Disease Patients Using Vital Signs During Hospital Visits, Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Arvind Subramaniam, Daniel M. Abrams, Gary K. Nave, Nirmish Shah Jan 2021

Pain Intensity Assessment In Sickle Cell Disease Patients Using Vital Signs During Hospital Visits, Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Arvind Subramaniam, Daniel M. Abrams, Gary K. Nave, Nirmish Shah

Computer Science and Engineering Faculty Publications

Pain in sickle cell disease (SCD) is often associated with increased morbidity, mortality, and high healthcare costs. The standard method for predicting the absence, presence, and intensity of pain has long been self-report. However, medical providers struggle to manage patients based on subjective pain reports correctly and pain medications often lead to further difficulties in patient communication as they may cause sedation and sleepiness. Recent studies have shown that objective physiological measures can predict subjective self-reported pain scores for inpatient visits using machine learning (ML) techniques. In this study, we evaluate the generalizability of ML techniques to data collected from …

Go to article

Als-Induced Excitability Changes In Individual Motorneurons And The Spinal Motorneuron Network In Sod1-G93a Mice At Symptom Onset, Christiana S.I. Draper Jan 2021

Als-Induced Excitability Changes In Individual Motorneurons And The Spinal Motorneuron Network In Sod1-G93a Mice At Symptom Onset, Christiana S.I. Draper

Browse all Theses and Dissertations

Amyotrophic lateral sclerosis (ALS) is the most common motorneuron (MN) disease in adulthood. ALS is hallmarked by the progressive loss of MNs in the brain, brainstem, and spinal cord. Many hypotheses to explain the pathogenesis of ALS have been explored, but the exact mechanisms underlying the development of this disease remain unknown. However, abnormalities in MN excitability and glutamate excitotoxicity are the most widely studied. For decades, researchers have examined MN excitability in ALS, but the current literature is inconsistent, showing evidence of hyperexcitability, hypoexcitability, or no change in excitability of MNs in ALS. Many of these studies also focus …

Go to article

The Theory And Design Of Class E Power Amplifiers For Impulse Excitation In Nuclear Magnetic Resonance, Owen D. Riemer Jan 2021

The Theory And Design Of Class E Power Amplifiers For Impulse Excitation In Nuclear Magnetic Resonance, Owen D. Riemer

Browse all Theses and Dissertations

A new method for analyzing the effectiveness of NMR impulse power amplifiers was developed using a classical linear systems approach to NMR. The method demonstrates a way to compare NMR power amplifiers and outputs. Thermodynamic calculations and the harmonic content of NMR amplifiers is presented to provide a complete description of the NMR power amplifier design problem. A design procedure for class E NMR power amplifiers with a pi-impedance matching network is outlined for matching the amplifier to the transmitter coil. The thesis concludes with the presentation of a 53 MHz power amplifier developed with the procedure. The complete amplifier …

Go to article

Multi-Label Classification On Locally-Linear Data: Application To Chemical Toxicity Prediction, Xiu Huan Yap Jan 2021

Multi-Label Classification On Locally-Linear Data: Application To Chemical Toxicity Prediction, Xiu Huan Yap

Browse all Theses and Dissertations

Computational models may assist in identification and prioritization of large chemical libraries. Recent experimental and data curation efforts, such as from the Tox21 consortium, have contributed towards toxicological datasets of increasing numbers of chemicals and toxicity endpoints, creating a golden opportunity for the exploration of multi-label learning and deep learning approaches in this thesis. Multi-label classification (MLC) methods may improve model predictivity by accounting for label dependence. However, current measures of label dependence, such as correlation coefficient, are inappropriate for datasets with extreme class imbalance, often seen in toxicological datasets. In this thesis, we propose a novel label dependence measure …

Go to article

Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave Jan 2021

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 …

Go to article

Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon Jan 2021

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 …

Go to article

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti Jan 2021

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) …

Go to article

First Prev Next Last