Engineering Commons^™

Emergency Landing And Guidance System, Joseph Alarid

Master's Theses

Every year there are thousands of aviation accidents along with hundreds of human deaths that happen around the world. While the data is sparse, it is well documented that many of these happen from emergency landings gone awry. While pilots can generally make great landings in clear daytime conditions, they are significantly handicapped when it comes to landing at night or amongst poor visibility conditions.

Due to the nature of this problem and some of the large scale advances in software technology we propose a solution that provides a significant improvement from the status quo. Using transfer learning on neural …

Demystifying Artificial Intelligence Based Digital Twins In Manufacturing- A Bibliometric Analysis Of Trends And Techniques, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Anup Kumar M. Bongale, Pooja Kamat

Library Philosophy and Practice (e-journal)

Nowadays, data is considered as a new life force for operations of physical systems in various domains such as manufacturing, healthcare, transportations, etc. However, the hugely generated data, which mirrors the working essence of the product life cycle, is still underutilised. Digital Twin (DT), a collective representation of active and passive captured data, is a virtual counterpart of the physical resources that could help prevent effective preventive maintenance in any applied domain. Currently, lots of research is going on about the applicability of digital twin in smart IOT based manufacturing industry 4.0 environment. Still, it lacks a formal study, which …

A Bibliometric Survey Of Fashion Analysis Using Artificial Intelligence, Seema Wazarkar, Shruti Patil, Satish Kumar

Library Philosophy and Practice (e-journal)

In the 21^st century, clothing fashion has become an inevitable part of every individual human as it is considered a way to express their personality to the outside world. Currently the traditional fashion business models are experiencing a paradigm shift from being an experience-based business strategy implementation to a data driven intelligent business improvisation. Artificial Intelligence is acting as a catalyst to achieve the infusion of data intelligence into the fashion industry which aims at fostering all the business brackets such as supply chain management, trend analysis, fashion recommendation, sales forecasting, digitized shopping experience etc. The field of “Fashion …

A Bibliometric Survey On Cognitive Document Processing, Dipali Baviskar, Swati Ahirrao, Ketan Kotecha

Library Philosophy and Practice (e-journal)

Heterogenous and voluminous unstructured data is produced from various sources like emails, social media tweets, reviews, videos, audio, images, PDFs, scanned documents, etc. Organizations need to store this wide range of unstructured data for more and longer periods so that they can examine information all the more profoundly to make a better decision and extracting useful insights. Manual processing of such unstructured data is always a challenging, time-consuming, and expensive task for any organization. Automating unstructured document processing using Optical Character Recognition (OCR) and Robotics Process Automation (RPA), seems to have limitations, as those techniques are driven by rules or …

Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy

Faculty Scholarship

AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. The data science community has to work on collecting and aggregating such data in a common and widely available format, so that any AI researcher can easily look up the applicable limit measurements for their latest project. AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. Data science community has to work on collecting and …

A Bibliometric Survey On The Diagnosis Of Plant Leaf Diseases Using Artificial Intelligence, Rutuja Rajendra Patil, Sumit Kumar Dr

Library Philosophy and Practice (e-journal)

Due to uncertain environmental conditions such as untimely rainfall, hailstorms, draught, fog the agriculture sector faces huge loss in crop yield. One of the biggest reason is plant leaf diseases. Therefore the need arises to diagnose the plant leaf diseases beforehand so that the diseases could be avoided and crop yield loss could be minimized. The paper represents the bibliometric study of plant leaf disease diagnosis using Artificial Intelligence. The study focuses on 472 scientific documents such as journals, articles, book chapters publicized in various journals. These documents are extracted from Scopus database after querying it with keywords related to …

Ontological Boundaries Between Humans And Computers And The Implications For Human-Machine Communication, Andrea L. Guzman

Human-Machine Communication

In human-machine communication, people interact with a communication partner that is of a different ontological nature from themselves. This study examines how people conceptualize ontological differences between humans and computers and the implications of these differences for human-machine communication. Findings based on data from qualitative interviews with 73 U.S. adults regarding disembodied artificial intelligence (AI) technologies (voice-based AI assistants, automated-writing software) show that people differentiate between humans and computers based on origin of being, degree of autonomy, status as tool/tool-user, level of intelligence, emotional capabilities, and inherent flaws. In addition, these ontological boundaries are becoming increasingly blurred as technologies emulate …

Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola

Articles

This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on …

Implementation Of Uhf-Rfid Technology In An Academic Library Of Pakistan; A Case Study, Attya Shahid Ms, Naveed Sehar

Library Philosophy and Practice (e-journal)

There are numerous libraries in Pakistan that cannot afford RFID technology because of the limited budget and resources and confronted book theft, low security, and delay services. This paper base an experiment that how libraries can adopt this technology effectively and productively with a lower budget and higher outcomes. The FAST-National University of Computer and Emerging Sciences Library Karachi campuses is the principal library in Pakistan which has adopted UHF-RFID technology with the integration of ILS insignia; SIP II compliance that jointly works with library integrated system and numerous activities can be made through this. An exploratory study conducted in …

Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth

Publications

During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a …

Bibliometric Analysis Of Bearing Fault Detection Using Artificial Intelligence, Pooja Kamat, Rekha Sugandhi Dr.

Library Philosophy and Practice (e-journal)

The new industrial revolution called Industry 4.0 is proliferating at its peak. The time is no longer away when the human race is going to witness a huge paradigm shift. Intelligent machines empowered by Artificial Intelligence (AI)will take over the presence of human workers in the industrial manufacturing sector with the target of achieving 100% automation. With the emergence of cut-throat price competition in the product market, it has become equally important to manufacture goods at minimal costs and with the highest quality. Predicting the decrease in machinery efficiency at an earlier stage to accomplish this objective helps to reduce …