Performance Analysis Of Whale Optimization Based Data Clustering, Ahamed Shafeeq B M, Zahid Ahmed Ansari, Shyam Karanth

Future Computing and Informatics Journal

Data clustering is the method of gathering of data points so that the more similar points will be in the same group. It is a key role in exploratory data mining and a popular technique used in many fields to analyze statistical data. Quality clusters are the key requirement of the cluster analysis result. There will be tradeoffs between the speed of the clustering algorithm and the quality of clusters it produces. Both the quality and speed criteria must be considered for the state-of-the-art clustering algorithm for applications. The Bio-inspired technique has ensured that the process is not trapped in …

Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan

Future Computing and Informatics Journal

In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …

A Literature Review For Contributing Mining Approaches For Business Process Reengineering, Noha Ahmed Bayomy Nab, Ayman E. Khedr Aek, Laila A. Abd-Elmegid Laa, Amira M. Idrees Ami

Future Computing and Informatics Journal

Due to the changing dynamics of the business environment, organizations need to redesign or reengineer their business processes in order to provide services with the lowest cost and shortest response time while increasing quality. Thence, Business Process Re-engineering (BPR) provides a roadmap to achieve operational goals that leads to enhance flexibility and productivity, cost reduction, and quality of service/product. In this paper, we propose a literature review for the different proposed models for Business Process Reengineering. The models specify where the breakdowns occur in BPR implementation, justifies why such breakdowns occur, and propose techniques to prevent their occurrence again. The …

A Bibliometric Perspective Survey Of Iot Controlled Ai Based Swarm Robots, Rhea Sawant, Ariz Shaikh, Chetna Singh, Aman Aggarwal, Shivali Amit Wagle, Harikrishnan R, Priti Shahane

Library Philosophy and Practice (e-journal)

Robotics is the ­new-age domain of technology that deals with bringing a collaboration of all disciplines of sciences and engineering to create a mechanical machine that may or may not work entirely independently but definitely focuses on making human lives much easier. It has repeatedly shown its ability to change lives at home and in the industry. As the field of robotics research grows and reaches new worlds, the military is one area where advances can have a significant impact, and the government is aware of this. Military technology has come a long way from the days where soldiers had …

Neural Network With Nlp, Harshita Sharma, Tinkle Jain

School of Professional Studies

This thesis is about neural networks and how their algorithmic systems work. Neural networks are well-suited to aiding people with complex challenges in real-world situations. Thesis topics include nonlinear and complicated interactions between inputs and outputs, as well as making inferences, discovering hidden links, patterns, and predictions, and modeling highly volatile data and variations to forecast uncommon events. Neural networks have the potential to help people make better decisions. NLP is a technique for analyzing, interpreting, and comprehending large amounts of text. We can no longer evaluate the text using traditional approaches due to the massive volumes of text data …

Machine Learning-Based Recognition On Crowdsourced Food Images, Aditya Kulkarni

Honors Scholar Theses

With nearly a third of the world’s population suffering from food-induced chronic diseases such as obesity, the role of food in community health is required now more than ever. While current research underscores food proximity and density, there is a dearth in regard to its nutrition and quality. However, recent research in geospatial data collection and analysis as well as intelligent deep learning will help us study this further.

Employing the efficiency and interconnection of computer vision and geospatial technology, we want to study whether healthy food in the community is attainable. Specifically, with the help of deep learning in …

Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks, Spencer Nelson

Graduate Theses and Dissertations

Artificial intelligence (AI) has experienced a tremendous surge in recent years, resulting in high demand for a wide array of implementations of algorithms in the field. With the rise of Internet-of-Things devices, the need for artificial intelligence algorithms implemented in hardware with tight design restrictions has become even more prevalent. In terms of low power and area, ASIC implementations have the best case. However, these implementations suffer from high non-recurring engineering costs, long time-to-market, and a complete lack of flexibility, which significantly hurts their appeal in an environment where time-to-market is so critical. The time-to-market gap can be shortened through …

Wearables And Wearable Data In Tele-Health Applications, Jack Mazza

Honors Theses

With the sudden emergence of Covid-19, Tele-Health has been forced into the forefront of healthcare. With no human contact, regular in-person doctor or clinic visits could not be made. Unfortunately, there is a gap in patient data for healthcare professionals when making diagnoses remotely. Fortunately, many users are constantly collecting some primary health data through wearables that have become commonplace in users' homes. Tapping into this unused data could provide healthcare professionals with a better picture of patients' health remotely. In this thesis, I will determine whether this wearable data can be a viable addition to Tele-Health applications, providing additional …

Non-Volatile Memory Adaptation In Asynchronous Microcontroller For Low Leakage Power And Fast Turn-On Time, Jean Pierre Thierry Habimana

Graduate Theses and Dissertations

This dissertation presents an MSP430 microcontroller implementation using Multi-Threshold NULL Convention Logic (MTNCL) methodology combined with an asynchronous non-volatile magnetic random-access-memory (RAM) to achieve low leakage power and fast turn-on. This asynchronous non-volatile RAM is designed with a Spin-Transfer Torque (STT) memory device model and CMOS transistors in a 65 nm technology. A self-timed Quasi-Delay-Insensitive 1 KB STT RAM is designed with an MTNCL interface and handshaking protocol. A replica methodology is implemented to handle write operation completion detection for long state-switching delays of the STT memory device. The MTNCL MSP430 core is integrated with the STT RAM to create …

Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and shaped …

Owsnet: Towards Real-Time Offensive Words Spotting Network For Consumer Iot Devices, Bharath Sudharsan, Sweta Malik, Peter Corcoran, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Publications

Every modern household owns at least a dozen of IoT devices like smart speakers, video doorbells, smartwatches, where most of them are equipped with a Keyword spotting(KWS) system-based digital voice assistant like Alexa. The state-of-the-art KWS systems require a large number of operations, higher computation, memory resources to show top performance. In this paper, in contrast to existing resource-demanding KWS systems, we propose a light-weight temporal convolution based KWS system named OWSNet, that can comfortably execute on a variety of IoT devices around us and can accurately spot multiple keywords in real-time without disturbing the device's routine functionalities.

When OWSNet …

Cognitive Digital Twins For Smart Manufacturing, Muhammad Intizar Ali, Pankesh Patel, John G. Breslin, Ramy Harik, Amit Sheth

Publications

Smart manufacturing or Industry 4.0, a trend initiated a decade ago, aims to revolutionize traditional manufacturing using technology-driven approaches. Modern digital technologies such as the Industrial Internet of Things (IIoT), Big Data Analytics, Augmented/Virtual Reality, and Artificial Intelligence (AI) are the key enablers of new smart manufacturing approaches. The digital twin is an emerging concept whereby a digital replica can be built of any physical object. Digital twins are becoming mainstream; many organizations have started to rely on digital twins to monitor, analyze, and simulate physical assets and processes. The current use of digital twins for smart manufacturing is largely …

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 …

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 …

Lecture 00: Opening Remarks: 46th Spring Lecture Series, Tulin Kaman

Mathematical Sciences Spring Lecture Series

Opening remarks for the 46th Annual Mathematical Sciences Spring Lecture Series at the University of Arkansas, Fayetteville.

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 …

Heterogeneous Resources Cost-Aware Geo-Distributed Data Analytics, Minmin Zhang

UNO Student Research and Creative Activity Fair

Many popular cloud service providers deploy tens of data centers (DCs) around the world to reduce user-perceived latency for better user experiences, in which a large amount of data is generated and stored in a geo-distributed manner. Geo-distributed Data Analytics (GDA) has gained great popularity in meeting the growing demand to mine meaningful and timely knowledge from such highly dispersed data. Since GDA systems require a large data migration between DCs via a wide area network (WAN), many existing works invested significant effort to optimize data transfer strategies to efficiently use limited WAN by considering the network pricing policies on …

Bibliometric Survey For Stock Market Prediction Using Sentimental Analysis And Lstm, Pooja Bagane, Nimit Mehta Mr, Parth Kakde Mr, Nisarg Bramhbhatt Mr, Ishansh Sahni Mr, Sirbi Kotrappa Dr

Library Philosophy and Practice (e-journal)

Creating an overview of the flow fundamentals of the global market trading and sublimation of equities into a superimposed system of economic agendas. Furthermore this leads to dynamic overlapping with the current technological advancements to create a platform for information exchange and inculcations. This created a new field of access points where we could enhance and analyse the data available and create an interface to predict the rise and fall trends involved with the stock market. These help create a sense of control and format over the public personification over the economic impacts and use social media and involve discrete …

Welcome To The Journal Of Electronic Theses And Dissertations (J-Etd), Edward A. Fox

The Journal of Electronic Theses and Dissertations

On behalf of the Networked Digital Library of Theses and Dissertations (NDLTD; see our website with multiple aliases: ndltd.org, theses.org, dissertations.org), I welcome you to the first volume of J-ETD. Now is the time to broadly share through an archival journal some of the most interesting discussions related to the global movement around ETDs. We hope you will find this journal to be of interest, and will spread the word that it is globally accessible as an open access archival forum empowering graduate student researchers and universities to broadly contribute to scholarship, knowledge, education, and understanding. We hope you and …

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 …