Non-Linear Dimensionality Reduction Using Auto-Encoder For Optimized Malaria Infected Blood Cell Classifier, Aayush Dhakal

Honors Theses

Neural Networks have been widely used in the problem of Medical Image Analysis. However, when dealing with large images, deep networks easily exhaust computer resources, which in turn hinders training. This paper shows the efficacy of using Auto-Encoders as a dimensionality reduction tool to increase the efficiency of a Malaria Infected Blood Cell Image classifier. We show that using an autoencoder, we can reduce the dimensionality of large blood cell images effectively such that the features in the new space retain all the essential information from the original input. Then we show that the new features obtained from the autoencoder …

Machine Learning Meets Internet Of Things: From Theory To Practice, Bharath Sudharsan, Pankesh Patel

Publications

Standalone execution of problem-solving Artificial Intelligence (AI) on IoT devices produces a higher level of autonomy and privacy. This is because the sensitive user data collected by the devices need not be transmitted to the cloud for inference. The chipsets used to design IoT devices are resource-constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing complex problem-solving AI (usually an ML model) on IoT devices. Since there is a high potential for building intelligent IoT devices, in this tutorial, we teach researchers and developers; (i) How to …

Recent Trends In Cloud Computing And Edge Computing, Sonali Deshpande, Nilima Kulkarni

Library Philosophy and Practice (e-journal)

Background: This study aims to analyze the work done in domain of cloud computing and edge computing using artificial intelligence from 2015 to 2021. Recent research shows the bibliometric methods are useful for such kind of analysis. Thus in this paper analysis is carried out using the bibliometric methods.

Methods: different articles on edge computing and edge intelligence were retrieved using one of the most popular database- Scopus. The research articles are considered between 2015 to 2021. Scopus analyzer is used for getting some analysis results such as documents by year, source, country and so on. VOSviewer Version 1.6.16 is …

Second Version On A Centralized Approach To Reducing Burnouts In The It Industry Using Work Pattern Monitoring Using Artificial Intelligence Using Mongodb Atlas And Python, Sasibhushan Rao Chanthati

Harrisburg University Other Works

Industry burnout is interlinked with cultural, individual, physical, or emotional exhaustion, and social factors, the resolution of which requires the technology-driven trends in the workplace and the technologies such as work pattern monitoring and Artificial Intelligence that can deal with large amounts of data. Industries face a gigantic problem i.e., employee burnout which can charge a firm loss in numerous hours and thousands of dollars every year. The more advanced companies use work pattern monitoring using Artificial Intelligence to make their employees work more professionally. In this research my attempts to understand the development and leadership, on the effects of …

Coding Club, Nicole Livingston, Madalyn Meyer

Honors Program: Expanded Learning Clubs

Lesson plans for an about 12-week club designed to introduce middle schoolers to coding using Scratch. By the end of the club, every student will have made a game they can share with the class and have learned basic coding and game creation tools. Students can also miss classes or join late and still be able to join and enjoy the club with a different focus lesson every week.

How The Power Of Machine – Machine Learning, Data Science And Nlp Can Be Used To Prevent Spoofing And Reduce Financial Risks, Sasibhushan Rao Chanthati

Harrisburg University Other Works

This paper discusses the potential of machine learning, data science, and natural language processing (NLP) in mitigating the incidence of spoofing and financial risks hinged on cyber threats. Another one is spoofing; it is the act of impersonating legitimate entities to gain unauthorized information and it is indeed a threat to the public and companies to some extent. The research introduces two primary methodologies to combat spoofing: an email filtering system using a machine learning algorithm and an encryption and decryption system using a Caesar Cipher and Python programming language. It distinguishes between approved domains and unapproved domains by using …

On-Device Deep Learning Inference For System-On-Chip (Soc) Architectures, Tom Springer, Elia Eiroa-Lledo, Elizabeth Stevens, Erik Linstead

Engineering Faculty Articles and Research

As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for target architectures at the “edge” that are resource-constrained. The realization of machine learning, and deep learning, is being driven by the availability of specialized hardware, such as system-on-chip solutions, which provide some alleviation of constraints. Equally important, however, are the operating systems that run on this hardware, and specifically the ability to leverage commercial real-time operating systems which, unlike general purpose operating systems such as Linux, can …

Analysis Of Recent Trends In Malware Attacks On Android Phone: A Survey Using Scopus Database, Sonali Kothari Tidke, Vijayshri Khedkar

Library Philosophy and Practice (e-journal)

In past few years, smartphone use has shifted from professional access to personal need. Smartphone has now become an essential requirement to perform day to day activities. This has made smartphones unsecured and vulnerable to cyber threats and malware attacks. This study is also focused on finding intersection between malware attacks and Android OS considering Android as the most widely used mobile OS. A comprehensive search is conducted on Scopus Database for peer-reviewed articles. The study is carried out on bibliometric data of the considered articles to generate a highly useful concept map.

Review And Analysis Of Failure Detection And Prevention Techniques In It Infrastructure Monitoring, Deepali Arun Bhanage, Ambika Vishal Pawar, K Kotecha

Library Philosophy and Practice (e-journal)

Maintaining the health of IT infrastructure components for improved reliability and availability is a research and innovation topic for many years. Identification and handling of failures are crucial and challenging due to the complexity of IT infrastructure. System logs are the primary source of information to diagnose and fix failures.

In this work, we address three essential research dimensions about failures, such as the need for failure handling in IT infrastructure, understanding the contribution of system-generated log in failure detection and reactive & proactive approaches used to deal with failure situations.

This study performs a comprehensive analysis of existing literature …

Towards A Blockchain Assisted Patient Owned System For Electronic Health Records, Tomilayo Fatokun, Avishek Nag, Sachin Sharma

Articles

Security and privacy of patients’ data is a major concern in the healthcare industry. In this paper, we propose a system that activates robust security and privacy of patients’ medical records as well as enables interoperability and data exchange between the different healthcare providers. The work proposes the shift from patient’s electronic health records being managed and controlled by the healthcare industry to a patient-centric application where patients are in control of their data. The aim of this research is to build an Electronic Healthcare Record (EHR) system that is layered on the Ethereum blockchain platform and smart contract in …

Pomegranate: Procedural 3d Tree Creation Via User-Defined L-Systems, Jeremy Berchtold

Computer Science and Software Engineering

Pomegranate creates procedural 3D trees based on a user-specified template. The template supports randomness and allows users to generate an entire forest of unique trees from a single template. The output trees are a single closed mesh without intersecting geometry (with the exception of leaves). Additionally, the output contains a skeletal rig used for animating the trees. Pomegranate produces textured trees that can use either a realistic or stylized look, as well as supporting different mesh densities for games or film. Since this project uses a procedural workflow, artists can quickly create and make edits to their trees. This increase …

Accelerating Point Set Registration For Automated Aerial Refueling, Ryan M. Raettig

Theses and Dissertations

The goal of AAR is to control the tanker boom to safely refuel a receiving aircraft with no input or aid from the boom operator. To achieve this, the pose of the receiver relative to the tanker must be known. Point set registration is a fundamental issue used to estimate the relative pose of an object in an environment. However, it's likely a computational bottleneck of a vision processing pipeline. In addition, the matching of each sensed point with a closest truth point, nearest neighbor matching, is the most costly portion of the point set registration process. For this reason, …

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

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

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

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

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

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

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 …

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 …

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

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 …

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 …

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

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.

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 …

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 …

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 …

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 (ETD)

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 …

Deep Learning Architectures For Heterogeneous Face Recognition, Seyed Mehdi Iranmanesh

Graduate Theses, Dissertations, and Problem Reports (ETD)

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 …