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Full-Text Articles in Engineering

Analysis Of Recent Trends In Continuous Sign Language Recognition Using Nlp, Vijayshri Nitin Khedkar, Sonali Kothari Dr, Aarohi Prasad, Arunima Mishra, Varun Saha, Vinay Kumar Mar 2021

Analysis Of Recent Trends In Continuous Sign Language Recognition Using Nlp, Vijayshri Nitin Khedkar, Sonali Kothari Dr, Aarohi Prasad, Arunima Mishra, Varun Saha, Vinay Kumar

Library Philosophy and Practice (e-journal)

Oralism is an ideology and practice that advocates communication that is based solely on speech. This practice is encouraged from a pretty early age in our country. As a consequence, the hard of hearing are constantly forced to negotiate with schools, colleges, organisations, workspaces, and families that don’t acknowledge the need and preference for sign language over oral languages. This results in inconsideration of an entire community for admissions, jobs and general social position. We aim to close that communication gap a little and take a step towards fighting the stigma associated with Sign Language. The aim is to provide …


A Bibliometric Analysis Of Plant Disease Classification With Artificial Intelligence Based On Scopus And Wos, Shivali Amit Wagle, Harikrishnan R Feb 2021

A Bibliometric Analysis Of Plant Disease Classification With Artificial Intelligence Based On Scopus And Wos, Shivali Amit Wagle, Harikrishnan R

Library Philosophy and Practice (e-journal)

The maneuver of Artificial Intelligence (AI) techniques in the field of agriculture help in the classification of diseases. Early prediction of the disease benefits in taking relevant management steps. This is an important step towards controlling the disease growth that will yield good quality products to fulfill the global food demand. The main objective of this paper is to study the extent of research work done in this area of plant disease classification. The paper discusses the bibliometric analysis of plant disease classification with AI in Scopus and Web of Science core collection (WOS) database in analyzing the research by …


Time Series Data Analysis Using Machine Learning-(Ml) Approach, Mvv Prasad Kantipudi Dr., Pradeep Kumar N.S Dr., S.Sreenath Kashyap Dr., Ss Anusha Vemuri Ms Jan 2021

Time Series Data Analysis Using Machine Learning-(Ml) Approach, Mvv Prasad Kantipudi Dr., Pradeep Kumar N.S Dr., S.Sreenath Kashyap Dr., Ss Anusha Vemuri Ms

Library Philosophy and Practice (e-journal)

Healthcare benefits related to continuous monitoring of human movement and physical activity can potentially reduce the risk of accidents associated with elderly living alone at home. Based on the literature review, it is found that many studies focus on human activity recognition and are still active towards achieving practical solutions to support the elderly care system. The proposed system has introduced a joint approach of machine learning and signal processing technology for the recognition of human's physical movements using signal data generated by accelerometer sensors. The framework adopts the concept of DSP to select very descriptive feature sets and uses …


Bibliometric Of Feature Selection Using Optimization Techniques In Healthcare Using Scopus And Web Of Science Databases, Rahul Joshi, Harita Gadikta, Saneeka Kharat, Soumi Mandal, Kalyani Kadam, Anupkumar M. Bongale Dr., Siddhant Pandit Jan 2021

Bibliometric Of Feature Selection Using Optimization Techniques In Healthcare Using Scopus And Web Of Science Databases, Rahul Joshi, Harita Gadikta, Saneeka Kharat, Soumi Mandal, Kalyani Kadam, Anupkumar M. Bongale Dr., Siddhant Pandit

Library Philosophy and Practice (e-journal)

Feature selection technique is an important step in the prediction and classification process, primarily in data mining related aspects or related to medical field. Feature selection is immersive with the errand of choosing a subset of applicable features that could be utilized in developing a prototype. Medical datasets are huge in size; hence some effective optimization techniques are required to produce accurate results. Optimization algorithms are a critical function in medical data mining particularly in identifying diseases since it offers excellent effectiveness in minimum computational expense and time. The classification algorithms also produce superior outcomes when an objective function is …


A Bibliometric Analysis Of The Tea Quality Evaluation Using Artificial Intelligence, Amruta Bajirao Patil Research Scholar, Mrinal Rahul Bachute Ph.D Guide And Associate Professor Jan 2021

A Bibliometric Analysis Of The Tea Quality Evaluation Using Artificial Intelligence, Amruta Bajirao Patil Research Scholar, Mrinal Rahul Bachute Ph.D Guide And Associate Professor

Library Philosophy and Practice (e-journal)

ABSTRACT: In this study, we have carried the bibliometric review of the “Tea quality evaluation using artificial intelligence”. Only the Scopus database is under consideration for this analysis. To coat all possible research approaches here we have generated the valid search queries which excludes irrelevant literature. The result analysis shows overall 602 useful papers are available on the tea quality evaluation out of which 12 papers are specifically on artificial taste perception of tea. This survey illustrates the emerging trend of quality evaluation and assurance (QEA) in tea industry and its importance. As the production of tea is huge, storage …


Bert For Question Answering On Bioasq, Eric R. Fu, Rikel Djoko, Maysam Mansor, Robert Slater Jan 2021

Bert For Question Answering On Bioasq, Eric R. Fu, Rikel Djoko, Maysam Mansor, Robert Slater

SMU Data Science Review

Machine reading comprehension and question answering are topics of considerable focus in the field of Natural Language Processing (NLP). In recent years, language models like Bidirectional Encoder Representations from Transformers (BERT) [3] have been very successful in language related tasks like question answering. The difficulty of the question answering task lies in developing accurate representations of language and being able to produce answers for questions. In this study, the focus is to investigate how to train and fine tune a BERT model to improve its performance on BioASQ, a challenge on large scale biomedical question answering. Our most accurate BERT …


Annual Report 2020-2021, Depaul University College Of Computing And Digital Media Jan 2021

Annual Report 2020-2021, Depaul University College Of Computing And Digital Media

CDM Annual Reports

LETTER FROM THE DEAN

As I write this letter during the beginning of the 2021–22 academic year, we have started to welcome the majority of our students to campus— many for the very first time, and some for the first time in a year and a half. It has been wonderful to be together, in-person, again. Four quarters of learning and working remotely was challenging, to be sure, but I have been consistently amazed by the resilience, innovation, and hard work of our students, faculty, and staff, even in the most difficult of circumstances. This annual report, covering the 2020–21 …


Evaluación Analítica De Parámetros No Considerados En La Formulación De Resistencia Nominal De Conectores Tipo Espigo, José David Ovalle Fernández, William Oswaldo Ramírez Patiño Jan 2021

Evaluación Analítica De Parámetros No Considerados En La Formulación De Resistencia Nominal De Conectores Tipo Espigo, José David Ovalle Fernández, William Oswaldo Ramírez Patiño

Ingeniería Civil

Existe una gran variedad de sistemas estructurales, cada uno con características específicas para el soporte de cargas verticales y horizontales. Uno de ellos, el sistema compuesto, el cual es desarrollado buscando ventajas como: la optimización del uso de los materiales combinando ambos en una unidad estructural, el uso de mayores luces entre columnas; la posibilidad de reutilización de la estructura; reducción de los costos de construcción debido a la disminución de tiempos en obra; de tamaño de columnas y cimentación; además, del aumento de protección contra el fuego y corrosión.

Con la aplicación de tecnologías como la soldadura, fue posible …


Detecting Interlocutor Confusion In Situated Human-Avatar Dialogue: A Pilot Study, Na Li, John D. Kelleher, Robert J. Ross Jan 2021

Detecting Interlocutor Confusion In Situated Human-Avatar Dialogue: A Pilot Study, Na Li, John D. Kelleher, Robert J. Ross

Conference papers

In order to enhance levels of engagement with conversational systems, our long term research goal seeks to monitor the confusion state of a user and adapt dialogue policies in response to such user confusion states. To this end, in this paper, we present our initial research centred on a user-avatar dialogue scenario that we have developed to study the manifestation of confusion and in the long term its mitigation. We present a new definition of confusion that is particularly tailored to the requirements of intelligent conversational system development for task-oriented dialogue. We also present the details of our Wizard-of-Oz based …


Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis Jan 2021

Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis

Williams Honors College, Honors Research Projects

Concussion in sports is a prevalent medical issue. It can be difficult for medical professionals to diagnose concussions. With the fast pace nature of many sports, and the damaging effects of concussions, it is important that any concussion risks are assessed immediately. There is a growing trend of wearable technology that collects data such as steps and provides the wearer with in-depth information regarding their performance. The Smart Headband project created a wearable that can record impact data and provide the wearer with a detailed analysis on their risk of sustaining a concussion. The Smart Headband uses accelerometers and gyroscopes …


The Youplanner, Taylor Burgess Jan 2021

The Youplanner, Taylor Burgess

Williams Honors College, Honors Research Projects

Staying organized can be difficult. A four tier web application was created to help in the endeavor. Utilizing software engineering practices, an online notepad was created where users can add, update, and delete notes. The application was a full stack application. For the backend, MySQL was the language and phpMyAdmin was the server. For the front end, PHP and Bootstrap 5.1 was used.


Touching Light: A Framework For The Facilitation Of Music-Making In Mixed Reality, Ian Thomas Riley Jan 2021

Touching Light: A Framework For The Facilitation Of Music-Making In Mixed Reality, Ian Thomas Riley

Graduate Theses, Dissertations, and Problem Reports

Drawing upon the historical development of analog and digital technologies alongside the proliferation of computer-assisted performance practices, this research seeks to develop a framework for integrating Mixed Reality applications to live musical performance, specifically through the creation of a Microsoft HoloLens 2 Mixed Reality application in order to facilitate a live performance of an original musical composition for percussion and real-time Mixed Reality environment. Mixed Reality enables a performer to interact with virtual (holograms, VSTs, etc.) and physical (vibraphone, tuned drums, microphones, etc.) objects simultaneously. Tandem to the development of the conceptual framework was the composition of an original score …


Determination Of Hydrogel Degradation By Passive Mechanical Testing, Avery Rosh-Gorsky Jan 2021

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 …


Integrating The First Person View And The Third Person View Using A Connected Vr-Mr System For Pilot Training, Chang-Geun Oh, Kwanghee Lee, Myunghoon Oh Jan 2021

Integrating The First Person View And The Third Person View Using A Connected Vr-Mr System For Pilot Training, Chang-Geun Oh, Kwanghee Lee, Myunghoon Oh

Journal of Aviation/Aerospace Education & Research

Virtual reality (VR)-based flight simulator provides pilots the enhanced reality from the first-person view. Mixed reality (MR) technology generates effective 3D graphics. The users who wear the MR headset can walk around the 3D graphics to see all its 360 degrees of vertical and horizontal aspects maintaining the consciousness of real space. A VR flight simulator and an MR application were connected to create the capability of both first-person view and third-person view for a comprehensive pilot training system. This system provided users the capability to monitor the aircraft progress along the planned path from the third-person view as well …


Self && Self, Shuang Cai Jan 2021

Self && Self, Shuang Cai

Senior Projects Spring 2021

Seldom before the COVID-19 pandemic have so many people simultaneously had their lifestyle drastically changed in the same way. The forced physical isolation is, ironically, a communal experience. The sickening quarantine left everyone nothing but time to confront and reconnect with themselves. Another inevitable result of corporal isolation is the predominant awakening awareness of digital existences and connections. Evoking the shared sensitivity and delicacy, studying the tectonic activity of the digital world, the project documents the endured contemplation in the upcoming resurgence.


Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar Jan 2021

Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the …


Quantum Clustering Drives Innovations: A Bibliometric And Patentometric Analysis, Shradha Deshmukh, Preeti Mulay Jan 2021

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 …


Deep Learning Architectures For Heterogeneous Face Recognition, Seyed Mehdi Iranmanesh Jan 2021

Deep Learning Architectures For Heterogeneous Face Recognition, Seyed Mehdi Iranmanesh

Graduate Theses, Dissertations, and Problem Reports

Face recognition has been one of the most challenging areas of research in biometrics and computer vision. Many face recognition algorithms are designed to address illumination and pose problems for visible face images. In recent years, there has been significant amount of research in Heterogeneous Face Recognition (HFR). The large modality gap between faces captured in different spectrum as well as lack of training data makes heterogeneous face recognition (HFR) quite a challenging problem. In this work, we present different deep learning frameworks to address the problem of matching non-visible face photos against a gallery of visible faces.

Algorithms for …


Hr Process Automation: A Bibliometric Analysis, Shubham Mishra, Monica Kunte, Netra Neelam, Sanjay Bhattacharya, Preeti Mulay Jan 2021

Hr Process Automation: A Bibliometric Analysis, Shubham Mishra, Monica Kunte, Netra Neelam, Sanjay Bhattacharya, Preeti Mulay

Library Philosophy and Practice (e-journal)

Automation is interpreted as the replacement of manual operations by electronics and computer-controlled systems. Human resource management is an indispensable part of every firm be it the space of retail, healthcare, education or any other sector. Activities such as hiring new workers, training, or making sure that local labour laws are obeyed with HR processes and are a crucial part of every organisation. HR has typically been believed of as an extremely manual department procedure. Employees are accustomed to doing this manually and getting the job done themselves. But everything around the HR processes are changing rapidly. HR Automation is …


Predictive Maintenance Of Bearing Machinery Using Simulation- A Bibliometric Study, Karan Gulati Mr., Keshav Basandrai Mr., Shubham Tiwari Mr., Pooja Kamat Prof., Satish Kumar Dr. Jan 2021

Predictive Maintenance Of Bearing Machinery Using Simulation- A Bibliometric Study, Karan Gulati Mr., Keshav Basandrai Mr., Shubham Tiwari Mr., Pooja Kamat Prof., Satish Kumar Dr.

Library Philosophy and Practice (e-journal)

Modelling is a way of constructing a virtual representation of software and hardware that involves a real-world device. We will discover the behaviour of the system if the software elements of this model are guided by mathematical relationships. For testing conditions that may be difficult to replicate with hardware prototypes alone, modelling and simulation are particularly useful, especially in the early phase of the design process when hardware might not be available. Model-based approach in MATLAB-Simulink can be useful for predictive maintenance of machines as it can reduce unplanned downtimes and maintenance costs when industrial equipment breaks. Through this bibliometric …


Increasing The Reliability Of Software Systems On Small Satellites Using Software-Based Simulation Of The Embedded System, Matthew D. Grubb Jan 2021

Increasing The Reliability Of Software Systems On Small Satellites Using Software-Based Simulation Of The Embedded System, Matthew D. Grubb

Graduate Theses, Dissertations, and Problem Reports

The utility of Small Satellites (SmallSats) for technology demonstrations and scientific research has been proven over the past few decades by governments, universities, and private companies. While the research and technology demonstration objectives that can be provided by these SmallSats are becoming similar to larger spacecraft, their reliability still falls behind. This is in part due to the reduced cost of SmallSat missions in comparison to large spacecraft, which requires cheaper components, rapid development schedules, and accepted risk. In these missions, the importance of the flight software is often overlooked, and the software is rushed through development and not fully …


A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi Jan 2021

A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi

Graduate Theses, Dissertations, and Problem Reports

Long non coding Ribonucleic Acids (lncRNAs) can be localized to different cellular components, such as the nucleus, exosome, cytoplasm, ribosome, etc. Their biological functions can be influenced by the region of the cell they are located. Many of these lncRNAs are associated with different challenging diseases. Thus, it is crucial to study their subcellular localization. However, compared to the vast number of lncRNAs, only relatively few have annotations in terms of their subcellular localization. Conventional computational methods use q-mer profiles from lncRNA sequences and then train machine learning models, such as support vector machines and logistic regression with the profiles. …


Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon Jan 2021

Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon

Graduate Theses, Dissertations, and Problem Reports

With the rise of Connected-and-Automated-Vehicle (CAV) technologies on roadways, transportation networks have become increasingly connected through Vehicle-to-Everything (V2X) systems. With access to the additional data from V2X, modern cruise control systems like Adaptive Cruise Control (ACC) are further improved upon to develop systems like Cooperative ACC (CACC) which reduces traffic congestion and increases driver safety and energy efficiency. With that increased connectivity, previously closed vehicle systems are now vulnerable to new security threats which pose new technical challenges. Significant research has been done to strengthen the network against external threats such as denial-of-service attacks (DoS) or passive eavesdropping attacks using …


Iot Malicious Traffic Classification Using Machine Learning, Michael Austin Jan 2021

Iot Malicious Traffic Classification Using Machine Learning, Michael Austin

Graduate Theses, Dissertations, and Problem Reports

Although desktops and laptops have historically composed the bulk of botnet nodes, Internet of Things (IoT) devices have become more recent targets. Lightbulbs, outdoor cameras, watches, and many other small items are connected to WiFi and each other; and few have well-developed security or hardening. Research on botnets typically leverages honeypots, PCAPs, and network traffic analysis tools to develop detection models. The research questions addressed in this Problem Report are: (1) What machine learning algorithm performs the best in a binary classification task for a representative dataset of malicious and benign IoT traffic; and (2) What features have the most …


Intrusion Detection For Industrial Control Systems, Kurt Lamon Jan 2021

Intrusion Detection For Industrial Control Systems, Kurt Lamon

EWU Masters Thesis Collection

Industrial Control Systems (ICS) are rapidly shifting from closed local networks, to remotely accessible networks. This shift has created a need for strong cybersecurity anomaly and intrusion detection for these systems; however, due to the complexity and diversity of ICSs, well defined and reliable anomaly and intrusion detection systems are still being developed. Machine learning approaches for anomaly and intrusion detection on the network level may provide general protection that can be applied to any ICS. This paper explores two machine learning applications for classifying the attack label of the UNSW-NB15 dataset. The UNSW-NB15 is a benchmark dataset that was …


Visualization For Solving Non-Image Problems And Saliency Mapping, Divya Chandrika Kalla Jan 2021

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 …


Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel Dec 2020

Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel

Theses

The scalability and power efficiency of the conventional CMOS technology is steadily coming to a halt due to increasing problems and challenges in fabrication technology. Many non-volatile memory devices have emerged recently to meet the scaling challenges. Memory devices such as RRAMs or ReRAM (Resistive Random-Access Memory) have proved to be a promising candidate for analog in memory computing applications related to inference and learning in artificial intelligence. A RRAM cell has a MIM (Metal insulator metal) structure that exhibits reversible resistive switching on application of positive or negative voltage. But detailed studies on the power consumption, repeatability and retention …


Recent Advances And Machine Learning Techniques On Sickle Cell Disease, Noorh H. Alharbi, Rana O. Bameer, Shahad S. Geddan, Hajar M. Alharbi Dec 2020

Recent Advances And Machine Learning Techniques On Sickle Cell Disease, Noorh H. Alharbi, Rana O. Bameer, Shahad S. Geddan, Hajar M. Alharbi

Future Computing and Informatics Journal

Sickle cell disease is a severe hereditary disease caused by an abnormality of the red blood cells. The current therapeutic decision-making process applied to sickle cell disease includes monitoring a patient’s symptoms and complications and then adjusting the treatment accordingly. This process is time-consuming, which might result in serious consequences for patients’ lives and could lead to irreversible disease complications. Artificial intelligence, specifically machine learning, is a powerful technique that has been used to support medical decisions. This paper aims to review the recently developed machine learning models designed to interpret medical data regarding sickle cell disease. To propose an …


Models And Methods Of Designing Human-Machine Interaction-Oriented Interfaces, Ozod Radjabov, Shakhrillo Bobokulov, Behruz Boboqulov, Hojiyev Sunatullo Dec 2020

Models And Methods Of Designing Human-Machine Interaction-Oriented Interfaces, Ozod Radjabov, Shakhrillo Bobokulov, Behruz Boboqulov, Hojiyev Sunatullo

Bulletin of TUIT: Management and Communication Technologies

Formalization approaches of user interface design (UID) in conjunction with model driven techniques aim to improve the usability in terms of conformity to standards or style guides and to leverage code generation of interactive software systems, so that various UI platforms for web, desktop or mobile Applications are supported. Because large parts of the UI are described platform independent instead of platform dependent implementations, re-usability of the UI concept is also improved. However, UI formalization requires the usage of a formal UI description language and a higher level of abstractness compared to concrete UI code. These languages need to be …


Use Of Image Processing Algorithms For Mine Originating Waste Grain Size Determination, Sebastian Iwaszenko Dec 2020

Use Of Image Processing Algorithms For Mine Originating Waste Grain Size Determination, Sebastian Iwaszenko

Journal of Sustainable Mining

The utilization of mineral wastes from the mining industry is one of most challenging phases in the raw materials life cycle. In many countries, there are piles of mineral waste materials that date back to the previous century. There is also a constant stream of accompanying mineral matter excavated during everyday mine operation. This stream of waste matter is particularly notable for deep coal mining. Grain size composition of waste mineral matter is one of most important characteristics of coal originating waste material. This paper presents the use of image analysis for the determination of grain size composition of mineral …